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Appl. Sci., Volume 13, Issue 17 (September-1 2023) – 509 articles

Cover Story (view full-size image): This study proposes a full integration method for the double capacitances and inductance–series (LCCL-S)-compensated inductive power transfer (IPT) of electric vehicles (EVs). The transmitter and receiver coils adopt the unipolar coil, and the compensation inductor is designed as an extended DD coil. Specifically, the use of an extended DD coil enhances the misalignment tolerance of the EVs. When the IPT system is in the misaligned state, a primary transfer path for magnetic flux is established between the transmitter and receiver coils, and a secondary transfer path is established between the extended DD coil and receiver coil. The distance between the two unipolar coils of the extended DD coil is optimized to maximize the magnetic flux on the secondary transfer path, thereby increasing the total power of the system misaligned state. View this paper
 
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14 pages, 2131 KiB  
Article
Hide45: A Method for Optimal Payload Data Hiding in Base45 Encoded Strings
by Marco Botta, Davide Cavagnino and Alessandro Druetto
Appl. Sci. 2023, 13(17), 9993; https://doi.org/10.3390/app13179993 - 4 Sep 2023
Viewed by 1272
Abstract
Base45 encodes pairs of octets using 3 characters from an alphabet of 45 printable symbols. Previous works showed the ability to hide payload data into encoded strings by exploiting the unused configurations of the Base45 encoding. In this paper, we present Hide45, an [...] Read more.
Base45 encodes pairs of octets using 3 characters from an alphabet of 45 printable symbols. Previous works showed the ability to hide payload data into encoded strings by exploiting the unused configurations of the Base45 encoding. In this paper, we present Hide45, an algorithm for hiding data into Base45 encoded strings that optimizes the embedding capacity, according to the frequency distribution of the input data. Experimental tests show that an optimal assignment of bit configurations to the most frequent pairs of octets allows to reach a payload capacity very close to the theoretical capacity of the method, improving over a baseline assignment by up to 53%. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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<p>Mapping <math display="inline"><semantics> <mi>μ</mi> </semantics></math> between binary strings of length <span class="html-italic">n</span> and sequences of <span class="html-italic">t</span> symbols from an alphabet <math display="inline"><semantics> <mi mathvariant="bold-italic">A</mi> </semantics></math>.</p>
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<p>Mapping <math display="inline"><semantics> <mi>η</mi> </semantics></math> between the unused sequences of <math display="inline"><semantics> <mi mathvariant="script">S</mi> </semantics></math> and a subset of the sequences of <math display="inline"><semantics> <mi mathvariant="script">W</mi> </semantics></math>; note that <math display="inline"><semantics> <mrow> <mi mathvariant="script">W</mi> <mo>⊂</mo> <mi mathvariant="script">S</mi> <mo>,</mo> <mi mathvariant="script">E</mi> <mo>⊆</mo> <mi mathvariant="script">W</mi> <mo>,</mo> <mi mathvariant="script">S</mi> <mo>=</mo> <mi mathvariant="script">D</mi> <mo>∪</mo> <mi mathvariant="script">W</mi> <mo>,</mo> <mi mathvariant="script">D</mi> <mo>∩</mo> <mi mathvariant="script">W</mi> <mo>=</mo> <mo>⌀</mo> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi mathvariant="bold">card</mi> <mfenced open="(" close=")"> <mi mathvariant="script">D</mi> </mfenced> <mo>=</mo> <mi mathvariant="bold">card</mi> <mfenced open="(" close=")"> <mi mathvariant="script">E</mi> </mfenced> </mrow> </semantics></math> .</p>
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<p>Cumulative distributions of all octet pairs sorted in decreasing order of frequency.</p>
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<p>Cumulative distributions of the most frequent 128 octet pairs (zoom on the leftmost area of graph in <a href="#applsci-13-09993-f003" class="html-fig">Figure 3</a>) sorted in decreasing order of frequency.</p>
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22 pages, 1549 KiB  
Review
X-ray Diffraction Data Analysis by Machine Learning Methods—A Review
by Vasile-Adrian Surdu and Romuald Győrgy
Appl. Sci. 2023, 13(17), 9992; https://doi.org/10.3390/app13179992 - 4 Sep 2023
Cited by 28 | Viewed by 14819
Abstract
X-ray diffraction (XRD) is a proven, powerful technique for determining the phase composition, structure, and microstructural features of crystalline materials. The use of machine learning (ML) techniques applied to crystalline materials research has increased significantly over the last decade. This review presents a [...] Read more.
X-ray diffraction (XRD) is a proven, powerful technique for determining the phase composition, structure, and microstructural features of crystalline materials. The use of machine learning (ML) techniques applied to crystalline materials research has increased significantly over the last decade. This review presents a survey of the scientific literature on applications of ML to XRD data analysis. Publications suitable for inclusion in this review were identified using the “machine learning X-ray diffraction” search term, keeping only English-language publications in which ML was employed to analyze XRD data specifically. The selected publications covered a wide range of applications, including XRD classification and phase identification, lattice and quantitative phase analyses, and detection of defects and substituents, as well as microstructural material characterization. Current trends in the field suggest that future efforts pertaining to the application of ML techniques to XRD data analysis will address shortcomings of ML approaches related to data quality and availability, interpretability of the results and model generalizability and robustness. Additionally, future research will likely incorporate more domain knowledge and physical constraints, integrate with quantum physical methods, and apply techniques like real-time data analysis and high-throughput screening to accelerate the discovery of tailored novel materials. Full article
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<p>Number of publications about machine learning, according to Web of Science: (<b>a</b>) yearly publication counts; (<b>b</b>) classification by research area.</p>
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<p>Machine learning algorithms used in X-ray diffraction data analysis.</p>
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20 pages, 8953 KiB  
Article
Evaluation of Thermodynamic and Chemical Kinetic Models for Hypersonic and High-Temperature Flow Simulation
by Wei Zhao, Xinglian Yang, Jingying Wang, Yongkang Zheng and Yue Zhou
Appl. Sci. 2023, 13(17), 9991; https://doi.org/10.3390/app13179991 - 4 Sep 2023
Cited by 2 | Viewed by 2310
Abstract
Significant thermochemical nonequilibrium effects always exist in the flow field around hypersonic vehicle at extreme flight condition. Previous studies have proposed various thermodynamic and chemical kinetic models to describe the thermochemical nonequilibrium processes in hypersonic and high-temperature flow. However, different selections from such [...] Read more.
Significant thermochemical nonequilibrium effects always exist in the flow field around hypersonic vehicle at extreme flight condition. Previous studies have proposed various thermodynamic and chemical kinetic models to describe the thermochemical nonequilibrium processes in hypersonic and high-temperature flow. However, different selections from such models might lead to remarkable variations in computational burden and prediction accuracy, which is still a matter of being unclear. In the present study, different commonly studied models for calculating the thermochemical nonequilibrium are systematically evaluated. The 5-, 7- and 11-species chemical kinetic models of Dunn-Kang, Gupta and Park together with the one- and two-temperature models are employed respectively to simulate the hypersonic flows over a standard cylinder with the radius of 1 m by HyFLOW, which is a commercial software based on the numerical solution of Navier-Stokes equations. Three flight conditions of FIRE Ⅱ classical flight trajectory are employed in the study. It shows that the differences between the results of the Dunn-Kang, Gupta and Park chemical kinetic models with the same number of species are small, but the Gupta model predicts the most conservative values of the wall heat flux. When only the order of magnitude and distribution trends of the pressure and wall heat flux are concerned, the one-temperature model combined with 5-species chemical reaction model can be used for a rapid prediction. While the accurate flow solution is required, the two-temperature model conjugated with Gupta 11-species model is recommended, especially at the conditions of extremely high altitude and Mach number. Full article
(This article belongs to the Special Issue Advances in Hypersonic Flows)
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<p>Grid for Cylindrical Flow Field.</p>
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<p>Temperature distribution around the flow field considering Gupta model under different conditions.</p>
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<p>Temperature distribution around the flow field considering Gupta model under different conditions.</p>
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<p>Temperature distribution along the stagnation line under different conditions.</p>
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<p>Temperature distribution along the stagnation line under different conditions.</p>
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<p>Pressure distribution along the stagnation line under different conditions.</p>
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<p>Pressure distribution along the stagnation line under different conditions.</p>
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<p>Number density of atom nitrogen along the stagnation line for one temperature model with different chemical kinetic model.</p>
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<p>Number density of atom nitrogen along the stagnation line for one temperature model with different chemical kinetic model.</p>
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<p>Number density of electron along the stagnation line for two temperature model with different chemical kinetic model.</p>
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<p>Number density of electron along the stagnation line for two temperature model with different chemical kinetic model.</p>
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<p>Wall heat fluxes for three cases calculated by different models.</p>
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<p>Wall heat fluxes for three cases calculated by different models.</p>
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<p>Wall pressure distribution predicted by different models for the three cases.</p>
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22 pages, 8838 KiB  
Article
Fatigue Assessment of Cable-Girder Anchorage Zone in a Low Ambient Temperature Environment Based on Extended Finite Element Method
by Huating Chen, Yifan Zhuo, Yubo Jiao and Weigang Bao
Appl. Sci. 2023, 13(17), 9990; https://doi.org/10.3390/app13179990 - 4 Sep 2023
Cited by 2 | Viewed by 1290
Abstract
The fatigue safety of cable-girder anchorage structures in cable-stayed bridges under long-term service has attracted much attention. For bridges located in seasonally cold regions, the effect of low-temperature environments should be considered when evaluating fatigue performance. Using the Heilongjiang Bridge in China as [...] Read more.
The fatigue safety of cable-girder anchorage structures in cable-stayed bridges under long-term service has attracted much attention. For bridges located in seasonally cold regions, the effect of low-temperature environments should be considered when evaluating fatigue performance. Using the Heilongjiang Bridge in China as a case study, a room-temperature fatigue test with a numerical simulation that considers the low-temperature effect on both load effect and fatigue resistance was proposed. A fatigue test with increased testing load amplitude was performed on a 1:3.75 ratio specimen. After 3.2 million loading cycles and using an acoustic emission technique, no fatigue crack was observed in the anchorage structure. The extended finite element method was then adopted to analyze the anchorage zone’s fatigue crack initiation position and propagation path. Finally, based on the fatigue characteristics of bridge steel, the fatigue resistance to the crack propagation of the vulnerable area was evaluated under three different service conditions. The results show that the fatigue performance of the anchorage zone at low temperatures is sufficient. Moreover, this paper provides a more widely applicable and cost-effective approach for the fatigue evaluation of steel bridges. Full article
(This article belongs to the Special Issue Bridge Structural Analysis)
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<p>Bridge elevation layout (only one-quarter of the bridge structure shown due to symmetry, dimensions in m).</p>
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<p>Typical cross section of the bridge (dimensions in mm).</p>
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<p>Anchor box type cable-girder anchorage structure.</p>
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<p>Design of fatigue test specimen.</p>
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<p>Fatigue test setup.</p>
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<p>Schematic diagram of strain gauge position: (<b>a</b>) Support plates; (<b>b</b>) Girder outer web; (<b>c</b>) Girder inner web.</p>
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<p>Acoustic emission instrument and sensors.</p>
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<p>Illustration of nodal enhancement and crack coordinates: (<b>a</b>) Nodal enhancement due to a crack; (<b>b</b>) Normal and tangential coordinates of a crack.</p>
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<p>Load-strain diagram from static load test: (<b>a</b>) Measuring point W<sub>2</sub>; (<b>b</b>) Measuring point W<sub>9</sub>; (<b>c</b>) Measuring point W<sub>5</sub>; (<b>d</b>) Measuring point W<sub>12</sub>.</p>
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<p>Load-strain diagram from static load test: (<b>a</b>) Measuring point W<sub>2</sub>; (<b>b</b>) Measuring point W<sub>9</sub>; (<b>c</b>) Measuring point W<sub>5</sub>; (<b>d</b>) Measuring point W<sub>12</sub>.</p>
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<p>Stress time history during fatigue verification test: (<b>a</b>) Girder inner web; (<b>b</b>) Girder outer web.</p>
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<p>Variation of monitored energy data during fatigue test: (<b>a</b>) Percentage of energy greater than 500 PJ; (<b>b</b>) Cumulative energy value.</p>
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<p>Crack evolution of test specimen.</p>
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<p>Stress distribution of inner web.</p>
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<p>Crack propagation path of the test specimen: (<b>a</b>) Location of fatigue crack initiation; (<b>b</b>) Crack growth under different analysis stages.</p>
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<p>Simulation of crack propagation path in bridge segment: (<b>a</b>) Location of fatigue crack initiation; (<b>b</b>) Crack growth under different analysis stages.</p>
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<p>Simulation of crack propagation path in bridge segment: (<b>a</b>) Location of fatigue crack initiation; (<b>b</b>) Crack growth under different analysis stages.</p>
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<p>Crack location and propagation boundary.</p>
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<p>Sensitivity analysis of initial crack size and critical crack size: (<b>a</b>) Influence of initial crack size; (<b>b</b>) Influence of critical crack size.</p>
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18 pages, 3131 KiB  
Article
An Alternative Audio-Tactile Method of Presenting Structural Information Contained in Mathematical Drawings Adapted to the Needs of the Blind
by Michał Maćkowski, Mateusz Kawulok, Piotr Brzoza, Marceli Janczy and Dominik Spinczyk
Appl. Sci. 2023, 13(17), 9989; https://doi.org/10.3390/app13179989 - 4 Sep 2023
Cited by 2 | Viewed by 1714
Abstract
Alternative methods of presenting the information contained in mathematical images, which are adapted to the needs of blind people, are significant challenges in modern education. This article presents an alternative multimodal method that substitutes the sense of sight with the sense of touch [...] Read more.
Alternative methods of presenting the information contained in mathematical images, which are adapted to the needs of blind people, are significant challenges in modern education. This article presents an alternative multimodal method that substitutes the sense of sight with the sense of touch and hearing to convey graphical information. The developed method was evaluated at a center specializing in the education of the blind in Poland, on a group of 46 students aged 15–19. They solved a set of 60 high school-level problems on geometry, mathematical analysis, and various types of graphs. We assessed the mechanisms introduced for the sense of touch and hearing, as well as the overall impression of the users. The system usability scale and the NASA task load index tests were used in the evaluation. The results obtained indicate an overall increase in user satisfaction and usefulness of the proposed approach and a reduction in the workload during exercise solving. The results also show a significant impact of the proposed navigation modes on the average time to reach objects in the drawing. Therefore, the presented method could significantly contribute to the development of systems supporting multimodal education for people with blindness. Full article
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<p>Diagram of the stages of the developed methodology.</p>
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<p>The proposed solution involves substituting the visual channel by combining the sense of touch and hearing.</p>
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<p>An example of a completeness map (the circle inscribed in a triangle). The navigation mode is necessary to navigate to the missing elements.</p>
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<p>Example of using navigation modes for a bar chart figure, (<b>a</b>) before adaptation, (<b>b</b>) after adaptation and using navigation modes.</p>
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<p>The real use of the system during tests by a blind student. On the left, the student puts the tactile image on the tablet screen (on the left). On the right, the student uses the application and can listen to alternative descriptions by performing the tap gesture on the tablet screen (under the fingers the student feels the tactile elements in the drawing).</p>
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<p>Example exercise/tap maps: (1) raw mode, (2) gesture mode, (3) long press gesture, and (4) information completeness mode.</p>
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22 pages, 8920 KiB  
Article
Performance Comparison of Traction Synchronous Motors with Ferrite Magnets for a Subway Train: Reluctance versus Homopolar Variants
by Vladimir Dmitrievskii, Vadim Kazakbaev and Vladimir Prakht
Appl. Sci. 2023, 13(17), 9988; https://doi.org/10.3390/app13179988 - 4 Sep 2023
Cited by 3 | Viewed by 1824
Abstract
Due to the high cost and the predicted shortage of rare earth elements in the near future, the task of developing energy-efficient electric machines without rare earth magnets is of great importance. This article presents a comparative analysis of optimized designs of a [...] Read more.
Due to the high cost and the predicted shortage of rare earth elements in the near future, the task of developing energy-efficient electric machines without rare earth magnets is of great importance. This article presents a comparative analysis of optimized designs of a ferrite-assisted synchronous reluctance machine (FaSynRM) and a ferrite-assisted synchronous homopolar machine (FaSHM) in a 370-kW subway train drive. The objectives of optimizing these traction machines are to reduce their losses, maximum armature current, and torque ripple. The optimization considers the characteristics of the machines in the subway train moving cycle. The problem of the risk of irreversible demagnetization of ferrites in the FaSynRM and FaSHM is also considered. To reduce the computational burden, the Nelder-Mead method is used for the optimization. It is shown that the FaSHM demonstrates better field weakening capability, which can reduce the maximum current, power, and cost of the inverter power modules. At the same time, the FaSynRM requires less permanent magnet mass for the same torque density and is more resistant to irreversible demagnetization, which can reduce costs and improve the reliability of the electric machine. Full article
(This article belongs to the Topic Advanced Electrical Machines and Drives Technologies)
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<p>Dynamic speed (green line) and torque (blue line) profiles of the subway train’s traction motor.</p>
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<p>Demanded speed-torque characteristic of the subway train drive. The numbers 0–5 indicate the numbers of operating points of the electric machine, taken into account in the optimization process.</p>
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<p>Motor design representation. Red arrows mark the directions of magnetization of the permanent magnets. (<b>a</b>) Ferrite-assisted synchronous reluctance motor (FaSynRM), 2-Pole area, red, blue and green colors indicate the different phases of the armature winding; (<b>b</b>) Ferrite-assisted synchronous homopolar motor (FaSHM), 1/4 cross-section and stator armature winding layout; (<b>c</b>) 3D cutout view of FaSHM with 1/2 stator cutout and unobstructed rotor.</p>
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<p>Layout of the three-phase inverter with a DC breaker designed to supply the excitation winding; letters A, B, and C represent the armature winding phases.</p>
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<p>Objective function calculation block diagram.</p>
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<p>FaSHM parameters. (<b>a</b>) Stator, the red arrow marks the direction of magnetization of the permanent magnet.; (<b>b</b>) Armature winding; (<b>c</b>) Rotor; (<b>d</b>) Axial plane.</p>
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<p>FaSHM optimization progress.</p>
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<p>The cross-section of the optimized designs of the FaSHM and the plot of flux density magnitudes at operating point 4; saturation areas (&gt;2 T) are shown with white. (<b>a</b>) Design optimized in [<a href="#B14-applsci-13-09988" class="html-bibr">14</a>]; (<b>b</b>) New FaSHM design.</p>
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<p>Operating point 4 demagnetizing force (kOe) in the FaSHM permanent magnet zone. Field stronger than −2.5 kOe is not shown (white color is used) (<b>a</b>) Design optimized in [<a href="#B14-applsci-13-09988" class="html-bibr">14</a>]; (<b>b</b>) New FaSHM design.</p>
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<p>FaSHM calculated waveforms. (<b>a</b>) Torque ripple at operating point 1; (<b>b</b>) Torque ripple at operating point 4; (<b>c</b>) Line-to-line back EMF at operating point 3 (maximum EMF amplitude); (<b>d</b>) Line-to-line back EMF at coasting (operating point 0); (<b>e</b>) Cogging torque.</p>
Full article ">Figure 10 Cont.
<p>FaSHM calculated waveforms. (<b>a</b>) Torque ripple at operating point 1; (<b>b</b>) Torque ripple at operating point 4; (<b>c</b>) Line-to-line back EMF at operating point 3 (maximum EMF amplitude); (<b>d</b>) Line-to-line back EMF at coasting (operating point 0); (<b>e</b>) Cogging torque.</p>
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<p>Geometric parameters of the FaSynRM. (<b>a</b>) Stator slot; (<b>b</b>) Rotor flux barrier, red arrows mark the direction of magnetization of the permanent magnets. Areas occupied by ferrite magnets are marked in yellow.</p>
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<p>FaSynRM optimization progress.</p>
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<p>FaSynRM cross-section before optimization, with a plot of flux density modulus at saturation limit (&gt;2 T) highlighted in white. (<b>a</b>) Operating point 1; (<b>b</b>) Operating point 2; (<b>c</b>) Operating point 3; (<b>d</b>) Operating point 4; (<b>e</b>) Operating point 5.</p>
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<p>FaSynRM cross-section after optimization, with a plot of flux density modulus at saturation limit (&gt;2 T) highlighted in white. (<b>a</b>) Operating point 1; (<b>b</b>) Operating point 2; (<b>c</b>) Operating point 3; (<b>d</b>) Operating point 4; (<b>e</b>) Operating point.</p>
Full article ">Figure 14 Cont.
<p>FaSynRM cross-section after optimization, with a plot of flux density modulus at saturation limit (&gt;2 T) highlighted in white. (<b>a</b>) Operating point 1; (<b>b</b>) Operating point 2; (<b>c</b>) Operating point 3; (<b>d</b>) Operating point 4; (<b>e</b>) Operating point.</p>
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<p>The demagnetizing field in the area of permanent magnets of the PMaSynRM rotor. Areas with the strongest demagnetization (&lt;−2 kOe) are highlighted in white. (<b>a</b>) Before optimization; (<b>b</b>) After optimization.</p>
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<p>FaSynRM calculated waveforms. (<b>a</b>) Torque ripple at operating point 1; (<b>b</b>) Torque ripple at operating point 4; (<b>c</b>) Line-to-line back EMF at operating point 2 (maximum EMF amplitude); (<b>d</b>) Line-to-line back EMF at coasting (operating point 0); (<b>e</b>) Cogging torque.</p>
Full article ">Figure 16 Cont.
<p>FaSynRM calculated waveforms. (<b>a</b>) Torque ripple at operating point 1; (<b>b</b>) Torque ripple at operating point 4; (<b>c</b>) Line-to-line back EMF at operating point 2 (maximum EMF amplitude); (<b>d</b>) Line-to-line back EMF at coasting (operating point 0); (<b>e</b>) Cogging torque.</p>
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19 pages, 21026 KiB  
Article
Detection of Wheat Yellow Rust Disease Severity Based on Improved GhostNetV2
by Zhihui Li, Xin Fang, Tong Zhen and Yuhua Zhu
Appl. Sci. 2023, 13(17), 9987; https://doi.org/10.3390/app13179987 - 4 Sep 2023
Cited by 13 | Viewed by 2388
Abstract
Wheat production safety is facing serious challenges because wheat yellow rust is a worldwide disease. Wheat yellow rust may have no obvious external manifestations in the early stage, and it is difficult to detect whether it is infected, but in the middle and [...] Read more.
Wheat production safety is facing serious challenges because wheat yellow rust is a worldwide disease. Wheat yellow rust may have no obvious external manifestations in the early stage, and it is difficult to detect whether it is infected, but in the middle and late stages of onset, the symptoms of the disease are obvious, though the severity is difficult to distinguish. A traditional deep learning network model has a large number of parameters, a large amount of calculation, a long time for model training, and high resource consumption, making it difficult to transplant to mobile and edge terminals. To address the above issues, this study proposes an optimized GhostNetV2 approach. First, to increase communication between groups, a channel rearrangement operation is performed on the output of the Ghost module. Then, the first five G-bneck layers of the source model GhostNetV2 are replaced with Fused-MBConv to accelerate model training. Finally, to further improve the model’s identification of diseases, the source attention mechanism SE is replaced by ECA. After experimental comparison, the improved algorithm shortens the training time by 37.49%, and the accuracy rate reaches 95.44%, which is 2.24% higher than the GhostNetV2 algorithm. The detection accuracy and speed have major improvements compared with other lightweight model algorithms. Full article
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<p>The severity of wheat yellow rust.</p>
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<p>Image enhancement. (<b>a</b>) Original image; (<b>b</b>) enhanced image.</p>
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<p>Feature Map.</p>
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<p>Vanilla Convolution.</p>
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<p>The Ghost module.</p>
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<p>The information flow of DFC attention.</p>
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<p>The GhostNet bottleneck map. (<b>a</b>) GhostNet bottleneck; (<b>b</b>) GhostNetV2 bottleneck and DFC.</p>
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<p>The CS-Ghost Module.</p>
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<p>Structure of MBConv and Fused-MBConv.</p>
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<p>ECA structure diagram.</p>
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<p>Accuracy in training.</p>
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<p>Heat map of four experiments.</p>
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<p>Feature map. (<b>a</b>) Improved model Block1 features; (<b>b</b>) improved model Block2 features; (<b>c</b>) original model block features.</p>
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<p>Confusion Matrix.</p>
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<p>Six model training results. (<b>a</b>) Accuracy curve; (<b>b</b>) loss curve.</p>
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<p>Six model training results. (<b>a</b>) Accuracy curve; (<b>b</b>) loss curve.</p>
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16 pages, 3362 KiB  
Article
Scan to BIM Mapping Process Description for Building Representation in 3D GIS
by Taewook Kang
Appl. Sci. 2023, 13(17), 9986; https://doi.org/10.3390/app13179986 - 4 Sep 2023
Cited by 7 | Viewed by 2550
Abstract
This paper introduces a novel approach for mapping process description with Scan data to Building Information Modeling (BIM) in a 3D Geographic Information System (GIS). The methodology focuses on automatically generating building mass and facade information on the GIS platform using Point Cloud [...] Read more.
This paper introduces a novel approach for mapping process description with Scan data to Building Information Modeling (BIM) in a 3D Geographic Information System (GIS). The methodology focuses on automatically generating building mass and facade information on the GIS platform using Point Cloud Data (PCD) of Airborne Laser Scanning (ALS). Advanced scanning techniques capture detailed geometry from the physical site and generate high-resolution point clouds, which are processed to create 3D models for GIS integration. The critical contribution of this research lies in a scalable Scan to BIM mapping process, which can be used for generating building footprints and masses, including attributes, on 3D GIS. The resulting integrated BIM–GIS dataset provides an accurate building mass, facade information, facility asset management, and architectural design and facilitates improved decision-making in urban planning based on enhanced visualization, analysis, and simulation. This study suggests a flexible Scan to BIM mapping process description based on use cases, including algorisms. Through prototype development, a case study demonstrates the effectiveness of the process approach, the automatic generation of BIM on a 3D GIS platform, and reducing the manual efforts. The proposed method automatically creates DEM, SHP, GeoJSON, IFC, and coordinate system information from scan data and can effectively map building objects in 3D GIS. Full article
(This article belongs to the Section Civil Engineering)
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<p>Research method.</p>
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<p>The building mapping process from the ALS dataset in 3D GIS.</p>
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<p>Use cases diagram for SBMD.</p>
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<p>Process framework architecture (UML. * = multiple).</p>
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<p>Building roof height calculation method (dashed green = footprint, yellow = offset polygon, and red dot = z-value sampling point).</p>
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<p>Results of the SBMD execution.</p>
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<p>Building information list generated by SBMD.</p>
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<p>Manual operation time analysis for footprint generation in the Scan dataset (<span class="html-italic">x</span>-axis = vertex input count about each building footprint’s polygon, <span class="html-italic">y</span>-axis = second).</p>
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43 pages, 8806 KiB  
Article
A Study on the Design and Control of the Overhead Hoist Railway-Based Transportation System
by Thuy Duy Truong, Xuan Tuan Nguyen, Tuan Anh Vu, Nguyen Huu Loc Khuu, Quoc Dien Le, Tran Thanh Cong Vu, Hoa Binh Tran and Tuong Quan Vo
Appl. Sci. 2023, 13(17), 9985; https://doi.org/10.3390/app13179985 - 4 Sep 2023
Cited by 2 | Viewed by 2794
Abstract
Overhead hoist transportation systems (OHTS) have been the subject of worldwide research and development in recent years. The majority of these systems are utilized in semi-automated or fully automated factories. This article proposes a new solution for OTHS based on the concept of [...] Read more.
Overhead hoist transportation systems (OHTS) have been the subject of worldwide research and development in recent years. The majority of these systems are utilized in semi-automated or fully automated factories. This article proposes a new solution for OTHS based on the concept of the modulation of mobile units that can move on a railway structure from one point to another. The OHTS mentioned in this article is a group of shuttles that can operate independently but which also have the ability to cooperate together to complete the desired tasks. By using the space below the ceiling, this system can operate without affecting the original design of the factories. There are many potential fields of application for picking-up and delivering, such as the medical field, the food and beverage fields, automotive and electrical appliances, etc. Moreover, by applying Dijkstra’s algorithm in the controller design, the transportation speed among the stations in the whole system can be improved. The real prototype of the whole system, including three shuttles, is also manufactured to explore and assess the design and operation of the proposed system and its controller. Full article
(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics)
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<p>The mechanism design of the shuttle.</p>
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<p>Design of the main elements of the rails module.</p>
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<p>The schematic diagram of the system.</p>
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<p>The principle diagram of the shuttle.</p>
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<p>The real shuttle base for experiment.</p>
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<p>An experimental station and elevator.</p>
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<p>The transmission and reception diagram for the system’s electrical signals.</p>
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<p>The position of the shuttle at the time 0 s.</p>
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<p>The position of the shuttle at the time 5 s.</p>
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<p>The position of the shuttle at the time 45 s.</p>
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<p>Algorithm flowchart of the whole system.</p>
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<p>Two shuttles will cause jam situation when traveling as marked direction.</p>
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<p>Illustration of the position of three shuttles.</p>
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<p>The shortest route to complete the tasks of each Shuttle (I, II, and III).</p>
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<p>Station 4 in the route of Shuttle III.</p>
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<p>Shuttle A wants to return to the old route but shuttles B and C are standing in front of the station.</p>
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<p>The flow chart for “Find the direction for each shuttles”.</p>
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<p>The sytems at the time <math display="inline"><semantics> <msub> <mi>t</mi> <mn>0</mn> </msub> </semantics></math>.</p>
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<p>The “stuck” happens at “O” position if Shuttle 5 is directed to move in a counter-clockwise direction.</p>
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<p>A new mission appears while the shuttles are doing their job at the time <math display="inline"><semantics> <msub> <mi>t</mi> <mn>0</mn> </msub> </semantics></math>.</p>
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<p>The mission was completed on time.</p>
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<p>Case 1—The system has just started to operate.</p>
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<p>Case 1—The system has just started to operate.</p>
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<p>Case 2—The shuttle doing its job must make another shuttle run away.</p>
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<p>Case 2—The shuttle doing its job must make another shuttle run away.</p>
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<p>Case 3—There is more than one shuttle operating to carry out the mission.</p>
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<p>Case 3—There is more than one shuttle operating to carry out the mission.</p>
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<p>Case 4—The low priority shuttle should find a station to avoid a high priority.</p>
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<p>The new mission is added from Station 1 to Station 3.</p>
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<p>The system chooses Shuttle 1 for the mission.</p>
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<p>The Shuttle 1 is running to Station 1 to get the goods.</p>
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<p>Shuttle 1 is going into Station 1 to get the goods.</p>
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<p>The shuttle is loading the goods.</p>
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<p>The shuttle returns to the route.</p>
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<p>Shuttle 1 runs into Elevator 2.</p>
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<p>Elevator 2 goes upstairs with Shuttle 1.</p>
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<p>Shuttle 1 goes upstairs successfully.</p>
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<p>Shuttle 1 continues running.</p>
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<p>Elevator 1 goes up to take Shuttle 1.</p>
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<p>Shuttle 1 goes into Elevator 1 to go down.</p>
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<p>Elevator 1 brings Shuttle 1 go down.</p>
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<p>Shuttle 1 successfully goes down.</p>
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<p>System orders Shuttle 2 to run with Shuttle 1.</p>
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<p>Shuttle 2 runs with Shuttle 1.</p>
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<p>Shuttle 2 keeps running.</p>
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<p>Shuttle 1 goes into Station 3.</p>
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<p>After unloading, Shuttle 1 returns to the route.</p>
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<p>The new mission is added.</p>
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<p>Shuttle 1 goes to Station 2 to acquire the goods.</p>
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<p>Station 2 receives Shuttle 1.</p>
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<p>Shuttle 1 returns to the route for delivering.</p>
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<p>Shuttle 1 begins running to Station 3 for delivering.</p>
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<p>Shuttle 3 is forced to run by Shuttle 1.</p>
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<p>Shuttle 2 is forced to run by the Shuttle 1 group.</p>
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<p>Shuttle 1 gets into Station 3.</p>
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<p>The mission from Station 2 to Station 3 is added.</p>
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<p>Shuttle 1 is chosen for the first mission.</p>
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<p>The second mission is added.</p>
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<p>The system selects the shuttle for second mission.</p>
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<p>Shuttle 1 and Shuttle 2 are loading.</p>
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<p>Shuttle 1 is coming to Station 3.</p>
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<p>The decision of system after Shuttle 2 has returned the route.</p>
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<p>Shuttle 2 exists the path of Shuttle 1.</p>
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<p>Shuttle 2 runs after waiting for Shuttle 1 to enter Station 3.</p>
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<p>Shuttle 2 arrives in the unloading station.</p>
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11 pages, 1186 KiB  
Article
Characterization of Chemical Composition and Antioxidant Activity of Eucalyptus globulus Leaves under Different Extraction Conditions
by Jae Yeon Park, Ju Yeon Kim, Yun Gon Son, Seong Doo Kang, Sang Won Lee, Kwang Dong Kim and Jeong Yoon Kim
Appl. Sci. 2023, 13(17), 9984; https://doi.org/10.3390/app13179984 - 4 Sep 2023
Cited by 9 | Viewed by 2844
Abstract
Eucalyptus globulus leaves contain various types of phenolic metabolites related to their antioxidant effects such as acids, catechin, flavonoids, and others. To optimize its antioxidative phenolic contents, E. globulus was extracted under various solvent conditions using 0, 10, 30, 50, 70, 90, and [...] Read more.
Eucalyptus globulus leaves contain various types of phenolic metabolites related to their antioxidant effects such as acids, catechin, flavonoids, and others. To optimize its antioxidative phenolic contents, E. globulus was extracted under various solvent conditions using 0, 10, 30, 50, 70, 90, and 100% ethanol. The 50% ethanol extract possessed the highest content of total phenolics with 497.7 mg GAE (gallic acid equivalent)/g extract. In contrast, the highest content of total flavonoids was evaluated in the 100% ethanol extract, having 169.3 mg QE (quercetin equivalent)/g extract. The antioxidant activity of various extraction conditions was assessed against the radical scavenging effect of DPPH (SC50 = 188.2~5841.7 μg/mL) and ABTS (SC50 = 14.2~171.3 μg/mL). The major chemical composition of E. globulus leaves was identified as including salicylic acid β-D-glucuronide (1), chlorogenic acid (2), epicatechin (3), 2″-O-galloylhyperin (4), isoquercitrin (5), isorhapontin (6), quercitrin (7), and quercetin-3-O-glucuronide (8) using LC-Q-TOF/MS analysis. Among them, the identified metabolites were clarified and their contents in the extracts were calculated via quantitative analysis using HPLC at 254 nm. The flavonoids (4, 5, 7, and 8) were determined to have an influence on the TPC, TFC, and antioxidant activity of E. globulus leaves. The results suggested that optimizing the extraction conditions can result in appropriate chemical composition and antioxidant activity. Full article
(This article belongs to the Section Chemical and Molecular Sciences)
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<p>Correlations between TPC, TFC, and radical scavenging effects of different conditions of <span class="html-italic">E. globulus</span> leaf extracts. (<b>a</b>) DPPH-ABTS, (<b>b</b>) TPC-TFC, (<b>c</b>) TPC-DPPH, (<b>d</b>) TFC-DPPH, (<b>e</b>) TPC-ABTS, and (<b>f</b>) TFC-ABTS.</p>
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<p>LC-Q-TOF/MS analysis of representative <span class="html-italic">E. globulus</span> leaf extracts. (<b>a</b>) Base peak chromatogram (BPC) of <span class="html-italic">E. globulus</span> leaf extracts using 30% ethanol. (<b>b</b>–<b>i</b>) Mass gram of individual peaks 1–8. Peak 1, salicylic acid β-D-O-glucuronide (<b>1</b>); Peak 2, chlorogenic acid (<b>2</b>); Peak 3, epicatechin (<b>3</b>); Peak 4, 2″-O-galloylhyperin (<b>4</b>); Peak 5, isoquercitrin (<b>5</b>); Peak 6, isorhapontin (<b>6</b>); Peak 7, quercitrin (<b>7</b>); Peak 8, quercetin-3-O-glucuronide (<b>8</b>).</p>
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<p>HPLC chromatogram of <span class="html-italic">E. globulus</span> leaves under different extract conditions using 0%, 10%, 30%, 50%, 70%, 90%, and 100% ethanol.</p>
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24 pages, 1472 KiB  
Article
Engineering Supply Chain Transportation Indexes through Big Data Analytics and Deep Learning
by Damianos P. Sakas, Nikolaos T. Giannakopoulos, Marina C. Terzi and Nikos Kanellos
Appl. Sci. 2023, 13(17), 9983; https://doi.org/10.3390/app13179983 - 4 Sep 2023
Cited by 6 | Viewed by 2004
Abstract
Deep learning has experienced an increased demand for its capabilities to categorize and optimize operations and provide higher-accuracy information. For this purpose, the implication of deep learning procedures has been described as a vital tool for the optimization of supply chain firms’ transportation [...] Read more.
Deep learning has experienced an increased demand for its capabilities to categorize and optimize operations and provide higher-accuracy information. For this purpose, the implication of deep learning procedures has been described as a vital tool for the optimization of supply chain firms’ transportation operations, among others. Concerning the indexes of transportation operations of supply chain firms, it has been found that the contribution of big data analytics could be crucial to their optimization. Due to big data analytics’ variety and availability, supply chain firms should investigate their impact on their key transportation indexes in their effort to comprehend the variation of the referred indexes. The authors proceeded with the gathering of the required big data analytics from the most established supply chain firms’ websites, based on their (ROPA), revenue growth, and inventory turn values, and performed correlation and linear regression analyses to extract valuable insights for the next stages of the research. Then, these insights, in the form of statistical coefficients, were inserted into the development of a Hybrid Model (Agent-Based and System Dynamics modeling), with the application of the feedforward neural network (FNN) method for the estimation of specific agents’ behavioral analytical metrics, to produce accurate simulations of the selected key performance transportation indexes of supply chain firms. An increase in the number of website visitors to supply chain firms leads to a 60% enhancement of their key transportation performance indexes, mostly related to transportation expenditure. Moreover, it has been found that increased supply chain firms’ website visibility tends to decrease all of the selected transportation performance indexes (TPIs) by an average amount of 87.7%. The implications of the research outcomes highlight the role of increased website visibility and search engine ranking as a cost-efficient means for reducing specific transportation costs (Freight Expenditure, Inferred Rates, and Truckload Line Haul), thus achieving enhanced operational efficiency and transportation capacity. Full article
(This article belongs to the Special Issue Deep Learning in Supply Chain and Logistics)
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<p>Conceptual Framework.</p>
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<p>The system architecture of the simulation model.</p>
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<p>Deployment of a supply chain analytics Hybrid Model.</p>
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<p>Supply chain transportation indexes simulation procedure with 100 (<b>a</b>) and 1000 (<b>b</b>) agents in 360 days.</p>
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<p>Supply chain transportation index simulation procedure with 10,000 (<b>a</b>) and 100,000 (<b>b</b>) agents in 360 days.</p>
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30 pages, 1714 KiB  
Review
Exploring the Potential of Sensing for Breast Cancer Detection
by Nure Alam Chowdhury, Lulu Wang, Linxia Gu and Mehmet Kaya
Appl. Sci. 2023, 13(17), 9982; https://doi.org/10.3390/app13179982 - 4 Sep 2023
Cited by 6 | Viewed by 2534
Abstract
Breast cancer is a generalized global problem. Biomarkers are the active substances that have been considered as the signature of the existence and evolution of cancer. Early screening of different biomarkers associated with breast cancer can help doctors to design a treatment plan. [...] Read more.
Breast cancer is a generalized global problem. Biomarkers are the active substances that have been considered as the signature of the existence and evolution of cancer. Early screening of different biomarkers associated with breast cancer can help doctors to design a treatment plan. However, each screening technique for breast cancer has some limitations. In most cases, a single technique can detect a single biomarker at a specific time. In this study, we address different types of biomarkers associated with breast cancer. This review article presents a detailed picture of different techniques and each technique’s associated mechanism, sensitivity, limit of detection, and linear range for breast cancer detection at early stages. The limitations of existing approaches require researchers to modify and develop new methods to identify cancer biomarkers at early stages. Full article
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<p>Distribution of antennas around the breast phantom (<b>left</b> panel) and detection of the tumor by considering backscattered signals (<b>right</b> panel) [<a href="#B64-applsci-13-09982" class="html-bibr">64</a>].</p>
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<p>SPR experimental setup [<a href="#B94-applsci-13-09982" class="html-bibr">94</a>].</p>
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<p>Detection of target microRNA-21 using SERS [<a href="#B102-applsci-13-09982" class="html-bibr">102</a>].</p>
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<p>Experimental setup of flow cytometry [<a href="#B121-applsci-13-09982" class="html-bibr">121</a>].</p>
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<p>Different steps of molecularly imprinted polymer preparation [<a href="#B132-applsci-13-09982" class="html-bibr">132</a>].</p>
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17 pages, 8037 KiB  
Article
Geo-Environment Suitability Evaluation for Urban Construction in Rongcheng District of Xiong’an New Area, China
by Hongwei Liu and Bo Han
Appl. Sci. 2023, 13(17), 9981; https://doi.org/10.3390/app13179981 - 4 Sep 2023
Cited by 1 | Viewed by 1427
Abstract
Xiong’an New Area is a national event and a project planned for a millennium of China. Its high-quality construction is of great significance to easing the noncapital functions of Beijing and the coordinated development of the Beijing-Tianjin-Hebei region. As an emerging city, the [...] Read more.
Xiong’an New Area is a national event and a project planned for a millennium of China. Its high-quality construction is of great significance to easing the noncapital functions of Beijing and the coordinated development of the Beijing-Tianjin-Hebei region. As an emerging city, the development and construction of Xiong’an New Area is bound to be restricted by geological and resource conditions. Therefore, geo-environment suitability analysis is the necessary basis of urban development and construction. Geo-environment suitability analysis of urban construction is a complex process that requires various geological indicator information, and relevant expertise to analyze their relevance. This paper focuses on the analytic hierarchy process (AHP) for the assessment of geo-environment suitability for urban construction in Rongcheng district, which is a Start Construction Region in Xiong’an New Area. Multiple factors, including the characteristic value of bearing capacity of foundation soil, land subsidence rate, geological faults, ground fissures, potential liquefied sands, quality of groundwater chemistry, quality of soil chemistry, chemical corrosion of concrete by groundwater, chemical corrosion of steel by groundwater, and enrichment of deep groundwater and geothermal resource, were used for the suitability assessments. From the evaluation achievements, the high and very high suitable lands for urban construction, with an acreage percentage of 89.2%, were located in most parts of the study area. Meanwhile, for another 9.1% of the land, the impacts of geological faults, land subsidence, and potential liquefied sands needed to be noted preferentially for urban construction. Full article
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<p>The study area of the Rongcheng district in Xiong’an New Area, China.</p>
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<p>Comprehensive evaluation frame of geo-environment suitability.</p>
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<p>Spatial distributions of characteristic values of bearing capacity of foundation soils at different depths.</p>
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<p>Spatial distributions of characteristic values of bearing capacity of foundation soils at different depths.</p>
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<p>Spatial distributions of characteristic values of bearing capacity of foundation soils at different depths.</p>
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<p>Zonal distributions of land subsidence rate.</p>
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<p>Distributions of geological faults.</p>
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<p>Distributions of ground fissures and potential liquefied sands.</p>
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<p>Quality distribution of groundwater chemistry samples.</p>
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<p>Zonal distributions of chemical corrosion of steel by groundwater.</p>
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<p>Zonal distributions of enrichment of deep groundwater.</p>
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<p>Distributions of geothermal gradient.</p>
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<p>Zonal distributions of geo-environment suitability for urban construction.</p>
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22 pages, 2352 KiB  
Article
Study on the Optimization of Pile Length of Micropiles in Soil Landslides
by Hui Cheng, Guochen Sui, Guanglu Wang, Junfeng Deng, Huan Wei, Rui Xu, Youshan He and Wei Yang
Appl. Sci. 2023, 13(17), 9980; https://doi.org/10.3390/app13179980 - 4 Sep 2023
Cited by 2 | Viewed by 1551
Abstract
This study summarizes the engineering design and calculation methods of micropiles and proposes a pile length optimization model based on numerical simulation software. Based on the proposed micropile calculation method and optimization method, a specific analysis of a project example was carried out, [...] Read more.
This study summarizes the engineering design and calculation methods of micropiles and proposes a pile length optimization model based on numerical simulation software. Based on the proposed micropile calculation method and optimization method, a specific analysis of a project example was carried out, and a series of calculations, such as micropile design calculation and pile length optimization for the project, was completed. The results show that the miniature pile length optimization model based on numerical simulation finite difference method improves the previous method by automating the optimization process through fast modeling, automatic creation of optimization commands, and output and analysis of optimization results, and realizes the optimization of pile length using numerical simulation, which improves the efficiency of the optimization of the pile length under the premise of guaranteeing accuracy, and achieves the unity of both efficiency and accuracy. The feasibility of this optimization process is proved by engineering examples. The engineering practicability of the micropile design calculation method and optimization method proposed in this study is proved through practice. It provides a reference value for the initial fast and flexible management of small landslides. Full article
(This article belongs to the Section Civil Engineering)
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<p>Micropile diameter and deformation coefficient curve. (<b>a</b>) The ”m-m” method. (<b>b</b>) The “m-k” method.</p>
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<p>Schematic diagram of the computational model. (<b>a</b>) Micropile and landslide action model. (<b>b</b>) Landslide thrust distribution model. (<b>c</b>) A monopile calculation model.</p>
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<p>Finite difference method calculation diagram. (<b>a</b>) Calculation diagram of elastic pile. (<b>b</b>) Ground to Sliding Surface Calculations. (<b>c</b>) Slip surface to pile base calculation.</p>
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<p>Optimization Flowchart.</p>
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<p>Flowchart of the optimization algorithm for micropile length.</p>
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<p>Schematic diagram of plane modeling and coordinate adaptation.</p>
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<p>Design calculation results.</p>
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<p>Optimization calculation model.</p>
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<p>Calculation results of bending moment at optimal pile length.</p>
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<p>Calculation of shear force at optimum pile length.</p>
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15 pages, 4222 KiB  
Article
Development of an Application That Implements a Brain–Computer Interface to an Upper-Limb Motor Assistance Robot to Facilitate Active Exercise in Patients: A Feasibility Study
by Tadashi Yamamoto and Toyohiro Hamaguchi
Appl. Sci. 2023, 13(17), 9979; https://doi.org/10.3390/app13179979 - 4 Sep 2023
Cited by 1 | Viewed by 1562
Abstract
In this study, we aimed to evaluate the effectiveness of a brain robot in rehabilitation that combines motor imagery (MI), robotic motor assistance, and electrical stimulation. Thirteen in-patients with severe post-stroke hemiplegia underwent electroencephalography (EEG), measured according to the international 10–20 method, during [...] Read more.
In this study, we aimed to evaluate the effectiveness of a brain robot in rehabilitation that combines motor imagery (MI), robotic motor assistance, and electrical stimulation. Thirteen in-patients with severe post-stroke hemiplegia underwent electroencephalography (EEG), measured according to the international 10–20 method, during MI. The dicephalus robotic system (DiC) was activated by detecting event-related desynchronization (ERD) using the Markov switching model (MSM) and relative power (RP) from the EEG of the motor cortex (C3 and C4). The reaction times (the time between ERD detection and DiC activation) of the MSM and RP were compared using Wilcoxon’s signed rank sum test. ERD was detected in all 13 and 12 patients with the MSM and RP, respectively. The DiC reaction time for the ERD detection process was significantly shorter for the MSM (13.02 ± 0.16 s) than for the RP (19.95 ± 7.45 s) (W = 9, p = 0.0037). The results of this study suggest that ERD responses can be detected in the motor cortex during MI in patients with severe upper-extremity paralysis; the MSM is more effective than the RP in detecting ERD when the EEG signal is used as a switch to activate the robot, and the reaction time to detect the signal is shorter. Full article
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<p>Diagram of the research overview. (<b>A</b>) Recording of EEG signals while the patient performs motor imagery. (<b>B</b>) Detection of ERD from the EEG using a classifier of the MSM and RP. (<b>C</b>) Measurement of reaction time, which is from the start of the EEG to when the arm starts to move. EEG, electroencephalogram; ERD, event-related desynchronization; MSM, Markov switching model; RP, relative power.</p>
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<p>Images used for the motion image. (<b>A</b>) An image shown 1 s before the start of MI. The patient was instructed not to perform MI during this phase. (<b>B</b>) After 1 s, the patient was shown a movie of a hand reaching out from a red card to a white card. The patient was instructed to imagine that he/she was stretching his/her hand in accordance with the motion picture. They were cautioned not to move their body. (<b>C</b>) After 4 s, the image was switched to a still image of the gazing point. MI, motion imagery.</p>
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<p>Electroencephalogram recording protocol.</p>
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<p>Procedure for recording EEG to control the DiC.</p>
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<p>Flow chart regarding participant selection.</p>
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<p>EEG data of patient 6: lesion, right radial coronary infarction; FMA-UE score, 8 points; MMSE score, 30 points; age, 77 years. The patient passed 109 days from the onset of stroke. ERD, downward convex waveform surrounded by red lines; ERS, upward convex waveform surrounded by blue lines.</p>
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<p>Comparison of the reaction time from ERD detection to DiC activation for the MSM and RP. The vertical axis indicates reaction time; MSM, n = 12; RP, n = 10; * W = 12, <span class="html-italic">p</span> &lt; 0.0017, by Wilcoxon’s signed rank sum test.</p>
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<p>Correlation between the reaction time from event-related desynchronization (ERD) detection to DiC activation and subjective quality of motor imagery (MI) in the MSM and relative power (RP). The vertical axis shows the response time, and the horizontal axis shows the quality score regarding MI based on the visual analog scale (VAS). (<b>Left</b>) MSM, r = −0.110, <span class="html-italic">p</span> = 0.779, n = 9. (<b>Right</b>) RP, r = 0.280, <span class="html-italic">p</span> = 0.503, n = 10.</p>
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18 pages, 4090 KiB  
Article
Deep Learning- and IoT-Based Framework for Rock-Fall Early Warning
by Mohammed Abaker, Hatim Dafaalla, Taiseer Abdalla Elfadil Eisa, Heba Abdelgader, Ahmed Mohammed, Mohammed Burhanur, Aiman Hasabelrsoul, Mohammed Ibrahim Alfakey and Mohammed Abdelghader Morsi
Appl. Sci. 2023, 13(17), 9978; https://doi.org/10.3390/app13179978 - 4 Sep 2023
Cited by 3 | Viewed by 1702
Abstract
In recent years, several strategies have been introduced to enhance early warning systems and lower the risk of rock-falls. In this regard, this paper introduces a deep learning- and IoT-based framework for rock-fall early warning, devoted to reducing rock-fall risk with high accuracy. [...] Read more.
In recent years, several strategies have been introduced to enhance early warning systems and lower the risk of rock-falls. In this regard, this paper introduces a deep learning- and IoT-based framework for rock-fall early warning, devoted to reducing rock-fall risk with high accuracy. In this framework, the prediction accuracy was augmented by eliminating the uncertainties and confusion plaguing the prediction model. In order to achieve augmented prediction accuracy, this framework fused prediction model-based deep learning with a detection model-based Internet of Things. This study utilized parameters, namely, overall prediction performance measures based on a confusion matrix, to assess the performance of the framework in addition to its ability to reduce the risk. The result indicates an increase in prediction model accuracy from 86% to 98.8%. In addition, the framework reduced the risk probability from 1.51 × 10−3 to 8.57 × 10−9. Our findings demonstrate the high prediction accuracy of the framework, which also offers a reliable decision-making mechanism for providing early warning and reducing the potential hazards of rock falls. Full article
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<p>Rock-fall early warning framework.</p>
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<p>Rock-fall detection model.</p>
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<p>Deep learning model design.</p>
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<p>The neuron’s main parts.</p>
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<p>Union of non-mutually exclusive probabilities process.</p>
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<p>The mean squared error (MSE) curve.</p>
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<p>The ROC curve for the validation dataset).</p>
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<p>The rock-fall risk probability.</p>
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<p>ALARP threshold triangle.</p>
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<p>Rock-fall risk reduction.</p>
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11 pages, 2071 KiB  
Article
Feasibility of a Patient-Specific Bolus Using the Life-Casting Method for Radiation Therapy
by Jeongho Kim, Jeehoon Park, Beomjun Park, Byungdo Park and Tae-Gyu Kim
Appl. Sci. 2023, 13(17), 9977; https://doi.org/10.3390/app13179977 - 4 Sep 2023
Cited by 1 | Viewed by 3306
Abstract
Radiation therapy for treating shallow tumors is challenging, necessitating the use of boluses. This study introduces the first application of the life-casting method to fabricate patient-specific bolus molds from gypsum sheets, comparing them with commercial boluses. Our developed boluses reduced the air gap [...] Read more.
Radiation therapy for treating shallow tumors is challenging, necessitating the use of boluses. This study introduces the first application of the life-casting method to fabricate patient-specific bolus molds from gypsum sheets, comparing them with commercial boluses. Our developed boluses reduced the air gap between the skin and bolus by 77.62% compared to that of commercial boluses. In vivo dosimetry using the patient-specific bolus demonstrated better results compared to using a commercial bolus. When using the commercial bolus, the mean %Diff and max %Diff were 1.10 ± 0.61%, respectively, and 2.00% for three-dimensional conformal radiation therapy (3D-CRT) and 7.19 ± 1.90% and 10.14% for volumetric modulated arc therapy (VMAT), respectively. Contrastingly, our developed bolus demonstrated more accurate dose delivery with a mean %Diff and max %Diff of 0.82 ± 0.61% and 1.69% for 3D-CRT and 3.42 ± 1.01% and 5.03% for VMAT, respectively. Furthermore, the standard deviation between the measurements was more than 50% lower when using a patient-specific bolus than when using a commercial bolus. These results show that our bolus reduces air gaps, improves the accuracy of bolus positioning, and enhances the precision of dose delivery compared with the performance of commercial boluses. Therefore, the developed bolus is expected to be valuable in clinical applications. Full article
(This article belongs to the Special Issue Medical Physics: Latest Advances and Prospects)
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<p>Fabrication procedure for a patient-specific bolus using the life-casting (LC) method.</p>
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<p>In-house phantom with (<b>a</b>) patient-specific bolus and (<b>b</b>) SuperFlab bolus.</p>
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<p>Optically stimulated luminescent dosimetry (OSLD) measurement points for in vivo dosimetry.</p>
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<p>Axial and sagittal views of the phantom’s computed tomography (CT) image using the patient-specific bolus and the SuperFlab bolus.</p>
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<p>Dose-volume histogram (DVH) of (<b>a</b>) three-dimensional conformal radiation therapy (3D-CRT) plans and (<b>b</b>) volumetric modulated arc therapy (VMAT) plans with the patient-specific bolus and the SuperFlab bolus.</p>
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19 pages, 5312 KiB  
Article
Analysis of the Impact of Small Group Behavior on Cruise Ship Emergency Evacuation
by Xuetao Zhang, Huajun Zhang, Shuqi Wang, Zhicheng Xiao and Wanying Zhang
Appl. Sci. 2023, 13(17), 9976; https://doi.org/10.3390/app13179976 - 4 Sep 2023
Cited by 1 | Viewed by 1707
Abstract
The effectiveness of a cruise ship’s emergency evacuation is greatly influenced by the way people interact; this paper uses the social force model to simulate two different evacuation scenarios considering the impact of small groups. It uses an agent to simulate the behavior [...] Read more.
The effectiveness of a cruise ship’s emergency evacuation is greatly influenced by the way people interact; this paper uses the social force model to simulate two different evacuation scenarios considering the impact of small groups. It uses an agent to simulate the behavior of a single occupant, and leverages the social force model to quantify the effect of group behavior on the group members. According to the influence of the group on the members, this paper corrects the expected speed of the members to determine the speed of crowd evacuation. It uses the SAFEGUARD cruise ship as the evacuation platform to simulate the process of evacuating the passengers to the boarding station and assembly station, respectively, and calculates the evacuation time, congestion area, and congestion duration of passengers under the action of groups. The simulation results of the two scenarios show that the group effect increases the average evacuation time by 15.29% and 21.79%, and increases the average detour distance by 24.54% and 17.89%, respectively. Full article
(This article belongs to the Topic Ship Dynamics, Stability and Safety)
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<p>Two ways of evacuating passengers.</p>
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<p>Cruise ship layout on three levels: (<b>a</b>) Cruise ship interior layout on level 1; (<b>b</b>) Cruise ship interior layout on level 2; (<b>c</b>) Cruise ship interior layout on level 3.</p>
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<p>Cruise ship layout on three levels: (<b>a</b>) Cruise ship interior layout on level 1; (<b>b</b>) Cruise ship interior layout on level 2; (<b>c</b>) Cruise ship interior layout on level 3.</p>
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<p>Age profile of global cruise ship occupants, 2016–2018.</p>
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<p>Flowchart for personnel emergency evacuation simulation.</p>
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<p>Frequency distribution of evacuation time without groups.</p>
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<p>The personnel thermal distribution map of congested areas during cruise ship evacuation.</p>
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<p>The variation in crowd density with time in congested areas without groups.</p>
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<p>Frequency distribution of evacuation time with groups.</p>
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<p>Variation in congestion density with time in the congested area with group.</p>
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<p>Variation in evacuation parameters with and without groups effect.</p>
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<p>The rate of change in sustained congestion time under the effect of more no clusters.</p>
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<p>Detour distance with and without groups.</p>
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17 pages, 11696 KiB  
Article
A Finite Element Analysis of a Tooth-Supported 3D-Printed Surgical Guide without Metallic Sleeves for Dental Implant Insertion
by Ionut Gabriel Ghionea, Oana Elena Burlacu Vatamanu, Ana Maria Cristescu, Mihai David, Izabela Cristina Stancu, Cristian Butnarasu and Corina Marilena Cristache
Appl. Sci. 2023, 13(17), 9975; https://doi.org/10.3390/app13179975 - 4 Sep 2023
Cited by 3 | Viewed by 2441
Abstract
Static guided surgery for dental implant insertion is a well-documented procedure requiring the manufacturing of a custom-made surgical guide, either teeth-supported, mucosal-supported, bone-supported, or mixed (teeth-mucosal-supported), depending on the clinical situation. The guidance of the surgical drills during implant bed preparation could be [...] Read more.
Static guided surgery for dental implant insertion is a well-documented procedure requiring the manufacturing of a custom-made surgical guide, either teeth-supported, mucosal-supported, bone-supported, or mixed (teeth-mucosal-supported), depending on the clinical situation. The guidance of the surgical drills during implant bed preparation could be undertaken using a sequence of different diameters of metal drill sleeves or, with the sleeves incorporated in the surgical guide, shank-modified drills, both clinically accepted and used with good results. Despite the great number of advantages associated with the use of guided surgery, one of the major risks is guide fracture during drilling for implant bed preparation. Therefore, the aim of the present study was to evaluate the surgical guides without metal sleeves and to simulate, with the aid of Finite Element Analysis (FEA), the use of such dentally supported guides for implant insertion. The FEA is performed in CATIA v5 software after defining the surgical guide mesh material and bone properties. A maximum stress of 6.92 MPa appeared on the guide at the special built-in window meant to allow cooling during drilling, and the maximum value of the guide displacement during drilling simulation was 0.002 mm. Taking into consideration the limits of the current research, the designed tooth-supported surgical guide can withstand the forces occurring during the surgery, even in denser bone, without the risk of fracture. Full article
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<p>Surgical guide design in R2Gate™ software, version 2.0: (<b>a</b>) DICOM files from CBCT and .stl files of the patient’s corresponding dental arch impression are imported in the software, and a three-point matching is performed; (<b>b</b>) a second 3D manual matching of CBCT with the digital model is undertaken; (<b>c</b>) design of the digital wax-up; (<b>d</b>) for dental implant insertion in the mandible, one extra step, alveolar nerve tracing, is required; (<b>e</b>) selecting the adequate implant and 3D positioning panning according to the final prosthetic restoration and the existing width and height of the bone; (<b>f</b>) when planning is performed and approved, the R2Gate corresponding drill core is selected and the window is positioned on the buccal side; (<b>g</b>) the planned implant position is exported as .rws file.</p>
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<p>Surgical guide design in R2Gate™ software, version 2.0: (<b>a</b>) DICOM files from CBCT and .stl files of the patient’s corresponding dental arch impression are imported in the software, and a three-point matching is performed; (<b>b</b>) a second 3D manual matching of CBCT with the digital model is undertaken; (<b>c</b>) design of the digital wax-up; (<b>d</b>) for dental implant insertion in the mandible, one extra step, alveolar nerve tracing, is required; (<b>e</b>) selecting the adequate implant and 3D positioning panning according to the final prosthetic restoration and the existing width and height of the bone; (<b>f</b>) when planning is performed and approved, the R2Gate corresponding drill core is selected and the window is positioned on the buccal side; (<b>g</b>) the planned implant position is exported as .rws file.</p>
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<p>Guide design in R2Ware software, version 1.1.40201: (<b>a</b>) the .rws file of the planning im–plant insertion is imported in the software; (<b>b</b>) the undercuts are removed and the limits of the sur–gical guide are traced using the option “draw boundary”; (<b>c</b>) the thickness of the guide is set at 3 mm (default) and the offset at 0.05 mm, and three inspecting windows are designed to check the perfect fit on the neighboring teeth; (<b>d</b>) the surgical guide is 3D printed in clear, transparent E-Guide Resin, postprocessed, and its fit is checked on the 3D printed model of the patient’s dental arch.</p>
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<p>Initial mesh surface of the guide from the .stl file while it is offset to create a new surface/model in order to be recognized by the CATIA v5 program.</p>
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<p>Joining the surface elements while simplifying the resulted surface and checking for tangency and connexity issues.</p>
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<p>Applying restraints and loads to the solid 3D model of the guide.</p>
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<p>Representative digital images suggestive of flapless implant bed preparation and insertion with the aid of the surgical guide, without metallic sleeves: (<b>a</b>) the guide is placed over the remaining natural teeth (tooth-supported guide type); (<b>b</b>) an initial drill is needed to initial the path in the cortical bone; (<b>c</b>) the implant osteotomy has to be prepared using the guide stop drills in a successive order based on drill diameter and length; (<b>d</b>) guided dental implant insertion.</p>
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<p>Results of the finite element analysis: (<b>a</b>) location and values of the maximum stress; (<b>b</b>) displacements of the guide and their maximum value; (<b>c</b>,<b>d</b>) propagation of the displacements show–ing the most critical areas.</p>
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29 pages, 2541 KiB  
Article
Optimization of the Production Management of an Upholstery Manufacturing Process Using Lean Tools: A Case Study
by Eva Santos, Tânia M. Lima and Pedro D. Gaspar
Appl. Sci. 2023, 13(17), 9974; https://doi.org/10.3390/app13179974 - 4 Sep 2023
Cited by 8 | Viewed by 5006
Abstract
This study aims to address the challenge of implementing Lean philosophy in Small and Medium Enterprises (SMEs) and fill the research gap regarding Lean application in vehicle seat upholstery maintenance/repairing processes. The Lean tools applied in a case study of an upholstery industry [...] Read more.
This study aims to address the challenge of implementing Lean philosophy in Small and Medium Enterprises (SMEs) and fill the research gap regarding Lean application in vehicle seat upholstery maintenance/repairing processes. The Lean tools applied in a case study of an upholstery industry of vehicle seats were as follows: Value Stream Mapping, Spaghetti Diagram, Gemba, 5S, Standardized Work, Kaizen, Kanban, and Poka-Yoke tools. A Decision Support Method using Excel Microsoft 365 was developed for improved stock control. A GUT Matrix was formulated to prioritize improvement opportunities, aiding prompt decision-making. This systematic approach enabled the company to address critical areas requiring swift attention. The results of Lean tools implementation led to a process waste minimization around 47%, and the process Lead Time decreased by approximately 26%, resulting in a 33% production increase. Thus, the Lean tools integration leads to substantial waste reduction, shorter process time, and increased production. The Decision Support Method enabled the company to efficiently monitor and manage its stock levels, thereby enhancing inventory management practices. This case study outlines the successful optimization of an upholstery production process in an SME by effectively applying Lean tools, highlighting its feasibility and benefits. Full article
(This article belongs to the Section Mechanical Engineering)
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<p>Proposed label.</p>
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<p>Weekly control interface.</p>
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<p>New project interface.</p>
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<p>Creation of a new project interface.</p>
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<p>Current State Spaghetti Diagram.</p>
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<p>Future State Spaghetti Diagram.</p>
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<p>Kanban.</p>
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<p>Poka-Yoke.</p>
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<p>Map of the storage areas of the different categories.</p>
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<p>Checklist for the 5S concerning the workstation shelves.</p>
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23 pages, 11482 KiB  
Article
Modeling of RC Moment Frame Retrofit with Mortar Walls Reinforced with Steel Wire Mesh
by Melisa Herrera, Diego Sosa, Sigifredo Díaz and Jessica Thangjitham
Appl. Sci. 2023, 13(17), 9973; https://doi.org/10.3390/app13179973 - 4 Sep 2023
Cited by 2 | Viewed by 1242
Abstract
Current construction codes require detailed analyses for structural retrofitting, which must consider performance during seismic events. Therefore, the computational models used to evaluate existing infrastructure require nonlinear structural analysis and damage estimates. For structural retrofitting, nonlinear computational modeling must represent the connectivity between [...] Read more.
Current construction codes require detailed analyses for structural retrofitting, which must consider performance during seismic events. Therefore, the computational models used to evaluate existing infrastructure require nonlinear structural analysis and damage estimates. For structural retrofitting, nonlinear computational modeling must represent the connectivity between existing and new elements. This study proposes recommendations on structural modeling based on fiber elements to represent reinforced concrete (RC) moment frames retrofitted with mortar walls reinforced with steel wire mesh. For this purpose, capacity curves of moment frames retrofitted with mortar walls were calculated by hand with the Bernoulli–Euler beam theory, moment–curvature analyses, and a plastic hinge model. Then, these capacity curves were used to calibrate the connectivity and constraint conditions in fiber models between the existing frame and the new wall required to capture the performance of the retrofitted structure. The study found that, for a single wall connected with top and bottom frame border elements, the capacity curves from fiber models underestimate stiffness, maximum strength, and residual strength. These estimation issues are reduced by including intermediate connectivity nodes between the top and bottom frame where rigid link constraints connect the existing frame with the new wall. Full article
(This article belongs to the Special Issue Advanced Technologies in Seismic Design, Assessment and Retrofitting)
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<p>Retrofit of moment frame with mortar wall.</p>
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<p>Transverse section geometry.</p>
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<p>Steel constitutive models.</p>
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<p>Concrete and mortar constitutive models.</p>
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<p>Strain distribution.</p>
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<p>Internal forces for elastic range.</p>
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<p>Internal forces for elastic range.</p>
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<p>Internal forces for plastic range.</p>
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<p>Curvature distribution idealization.</p>
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<p>Experimental test construction details [<a href="#B18-applsci-13-09973" class="html-bibr">18</a>]. (<b>a</b>) Wire mesh connected by steel rods to border columns. (<b>b</b>) Wire mesh covered with mortar.</p>
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<p>Experimental specimen detailing.</p>
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<p>Gauss–Lobatto integration sections.</p>
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<p>Cross-section discretization pattern.</p>
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<p>Discretization 1 connectivity.</p>
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<p>Wall discretization methods.</p>
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<p>Moment–curvature diagram.</p>
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<p>Benchmark capacity curves.</p>
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<p>Shear deformation influence in capacity curves.</p>
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<p>Flexural vs. shear displacement contribution.</p>
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<p>Infill panel masonry contribution in benchmark capacity curves.</p>
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<p>Masonry stress contribution for yielding and serviceability limit states.</p>
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<p>Benchmark and experimental capacity curves comparison.</p>
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<p>Capacity curves for each <math display="inline"><semantics> <mrow> <mi mathvariant="normal">H</mi> <mo>/</mo> <mi mathvariant="normal">L</mi> <mi mathvariant="normal">w</mi> </mrow> </semantics></math>.</p>
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<p>Capacity curves for each <math display="inline"><semantics> <mrow> <mi mathvariant="normal">H</mi> <mo>/</mo> <mi mathvariant="normal">L</mi> <mi mathvariant="normal">w</mi> </mrow> </semantics></math>.</p>
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2 pages, 161 KiB  
Editorial
Aditive Manufacturing in Maxillofacial Prosthodontics
by Corina Marilena Cristache
Appl. Sci. 2023, 13(17), 9972; https://doi.org/10.3390/app13179972 - 4 Sep 2023
Viewed by 920
Abstract
Additive manufacturing (AM) or additive layer manufacturing (ALM), defined by the International Organization for Standardization and American Society of Testing and Materials (ISO/ASTM 52900) as the “process of joining materials to make parts from 3D model data, usually layer upon layer, as opposed [...] Read more.
Additive manufacturing (AM) or additive layer manufacturing (ALM), defined by the International Organization for Standardization and American Society of Testing and Materials (ISO/ASTM 52900) as the “process of joining materials to make parts from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing and formative manufacturing methodologies” [...] Full article
22 pages, 10544 KiB  
Article
Evaluation of the Possibilities Validation of Interval Velocity Models Using Non-Seismic Data and Its Impact on Geological Interpretation of PreSDM Results
by Michał Stefaniuk, Adam Cygal, Tomasz Maćkowski, Michał Martuś, Piotr Hadro, Krzysztof Pieniądz and Anna Maria Wachowicz-Pyzik
Appl. Sci. 2023, 13(17), 9971; https://doi.org/10.3390/app13179971 - 4 Sep 2023
Viewed by 1051
Abstract
The paper presents the problem of generation and validation of Velocity Interval Depth (VID) models with the application of non-seismic geophysical and geological data. The study area is a part of the Carpathian Foredeep located close to its contact with the Carpathian Overthrust. [...] Read more.
The paper presents the problem of generation and validation of Velocity Interval Depth (VID) models with the application of non-seismic geophysical and geological data. The study area is a part of the Carpathian Foredeep located close to its contact with the Carpathian Overthrust. In this area of complicated geological structure, hydrocarbon deposits have been successfully explored for decades with seismic methods and drilling. The research applied the Simultaneous Joint Inversion (SJI) of independent geophysical data, which is a modern methodology of geophysical data processing, that is still under development. Such an attempt was necessary due to the lack of a sufficiently dense grid of wells in the study area, in which seismic velocities would be correctly recorded. Such data would be then applied for the generation of relevant VID models, which in turn, could be used to perform the Prestack Depth Migration (PreSDM) procedures. The application of procedures taking advantage of independent geophysical and geological data enabled researchers to control the generation process of the spatial VID model in the areas without wells. The analyses aimed to verify the correctness of VID model evaluation and its influence on the quality of seismic imaging in the area of the Carpathian Overthrust. Precisely, the influence was tested of such non-standard generation procedure of seismic velocity fields, not only on the PreSDM results but also on the geological interpretation of both the Rączyna and the Jodłówka gas deposits. The latter aspect of the presented results seems to be crucial to the effectiveness of petroleum exploration in the transition zone between the Carpathian Orogen and the Carpathian Foredeep. Full article
(This article belongs to the Collection Advances in Theoretical and Applied Geophysics)
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<p>The location of the analyzed seismic profiles against the background of the results from 2D/3D seismic image interpretation [<a href="#B7-applsci-13-09971" class="html-bibr">7</a>,<a href="#B24-applsci-13-09971" class="html-bibr">24</a>]. The main drilling wells, which were used in the evaluation process, are marked on the map by black dots. The geological spatial data, used for map construction, were freely provided in the SHP format by the State Geological Institute-PIB.</p>
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<p>The location of the analyzed seismic profiles against the background of the results from 2D/3D seismic image interpretation [<a href="#B7-applsci-13-09971" class="html-bibr">7</a>,<a href="#B24-applsci-13-09971" class="html-bibr">24</a>]. The main drilling wells, which were used in the evaluation process, are marked on the map by black dots. The geological spatial data, used for map construction, were freely provided in the SHP format by the State Geological Institute-PIB.</p>
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<p>Visualization of the Rączyna and Jodłówka gas fields ([<a href="#B27-applsci-13-09971" class="html-bibr">27</a>] modified). (<b>A</b>)—Interpretation along the seismic section 16A-2-91K (Drohobyczka—Skopów fragment, POGC seismic works). (<b>B</b>)—Interpretation along seismic section XL-100 (Jodłówka 3D, POGC seismic works). More explanation in the text. (<b>C</b>)—Stratigraphy profile for R-4 well (Source: <a href="https://otworywiertnicze.pgi.gov.pl" target="_blank">https://otworywiertnicze.pgi.gov.pl</a>; downloading date: 1 August 2023).</p>
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<p>Validation workflow of Parametric Velocity Model (PVM).</p>
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<p>Scheme of application of SJI procedure for PVM model validation. Scheme has been based on published instructions [<a href="#B10-applsci-13-09971" class="html-bibr">10</a>,<a href="#B30-applsci-13-09971" class="html-bibr">30</a>,<a href="#B31-applsci-13-09971" class="html-bibr">31</a>]. The testing loop is presented as tool for VID models improving and their verification.</p>
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<p>The Bouguer anomalies compared with the regional anomalies extracted for the described seismic traverse. (<b>A</b>) Comparison of regional anomalies calculated as differences between the Bouguer anomalies and the corresponding residual trends. (<b>B</b>) Comparison of residual anomalies calculated as differences between the Bouguer anomalies and the corresponding regional trends. The black rectangle represents the Rączyna deposit area where PreDSM migration tests were performed. Other explanations: I—Zone of Carpathian gravity depression, II—Zone of Carpathian Overthrust (Area of Interest (AoI), III—Zone of shallowing of crystalline basement (boundary of Carpathian Foredeep).</p>
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<p>The construction of Parametric Velocity Model (PVM)—visualization. A—3D structural grid; B—Cross-sections through the 3D PVM in the context of the structural grid.</p>
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<p>Comparison of seismic wave velocity models: (<b>A</b>)—raw P-wave velocity model, (<b>B</b>)—result of refraction tomography for near and far offsets, (<b>C</b>)—result of simultaneous inversion of refraction and gravity data.</p>
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<p>Comparison of modeled gravity responses with respect to the observed residual values (Option-1) adopted for gravity inversion. Modeled effects for SJI (Simultaneous Joint Inversion), Single Gravity Inversion (SGI), and the raw model based on parametric modeling (PVM) were compared. The analysis was presented in a regional context, and the area subjected to PreSDM migration was marked with a black square.</p>
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<p>Verification of the correctness of the velocity field correction was conducted at wells D-4 and R-8.</p>
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<p>Results of PreSDM migration. (<b>A</b>)—Seismic sections after PreSDM calculated using the raw velocity model PVM. (<b>B</b>)—Seismic sections after PreSDM calculated using the velocity model obtained from refraction tomography for near and far offsets. (<b>C</b>)—Seismic sections after PreSDM calculated using the velocity model obtained from SJI of refraction and gravity data. The same PreSDM workflow was applied to all versions, with only the velocity model being changed. The projections of the nearest wells D-4 and R-8 were overlaid on the seismic sections.</p>
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<p>Parts of the results of PreSDM depth migration are as follows: (<b>A</b>)—Seismic sum of the components after PreSDM calculated using the raw velocity model PVM. (<b>B</b>)—Seismic sum of the components after PreSDM calculated using the velocity model resulting from wide-offset refractory tomography. (<b>C</b>)—Seismic sum of the components after PreSDM calculated using the velocity model resulting from simultaneous inversion of refractory and gravimetric data. The same PreSDM workflow was applied to all versions, with only the velocity model being changed. The seismic sums are overlaid with projections of the nearest D-4 and R-8 wells, as well as elements of detailed interpretation.</p>
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<p>A comparison of example CDP gathers from the Carpathian thrust area. The “1st iteration” collection presents seismic data from <a href="#applsci-13-09971-f009" class="html-fig">Figure 9</a> and <a href="#applsci-13-09971-f010" class="html-fig">Figure 10</a>, while the “Update” collection presents generated seismic data from <a href="#applsci-13-09971-f012" class="html-fig">Figure 12</a>.</p>
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<p>The result of PreSDM after the “Update” based on the VID model derived from SJI. The seismic section includes a simplified interpretation and a legend. A detailed description is provided in the text.</p>
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12 pages, 4788 KiB  
Article
A Lightweight Knowledge-Distillation-Based Model for the Detection and Classification of Impacted Mandibular Third Molars
by Yujie Lei, Xiang Chen, Yunlong Wang, Rong Tang and Baoping Zhang
Appl. Sci. 2023, 13(17), 9970; https://doi.org/10.3390/app13179970 - 4 Sep 2023
Cited by 3 | Viewed by 1931
Abstract
The extraction of impacted third molars is one of the most common dental operations. When the impacted third molar is extracted, the operation plan is generally different because of the different impacted positions of the tooth. Therefore, judging the impacted type of the [...] Read more.
The extraction of impacted third molars is one of the most common dental operations. When the impacted third molar is extracted, the operation plan is generally different because of the different impacted positions of the tooth. Therefore, judging the impacted type of the third molar is the basis of the third molar extraction operation. At present, oral health professionals usually analyze panoramic radiographs to determine the types of impacted third molars, but the diagnosis is easily affected by oral health professionals’ subjective consciousnesses. Computer vision technology can help doctors analyze medical images faster and more accurately, so it is very desirable to use computer vision to detect and classify the impacted third molars. Based on the panoramic radiographs of the School of Stomatology, Lanzhou University, this paper establishes an object detection dataset containing six types of impacted third molars. On the basis of this dataset, the lightweight third molar impacted detection and classification model is studied in this paper. This study introduces the method of knowledge distillation on the basis of YOLOv5s and uses YOLOv5x as the teacher’s model to guide YOLOv5s, which not only ensures the light weight of the model but also improves the accuracy of the model. Finally, the YOLOv5s-x model is obtained. The experimental results show that the introduction of knowledge distillation effectively improves the accuracy of the model while ensuring its light weight, the mAP of YOLOv5s-x is increased by 2.9% compared with the original model, and the amount of parameters and calculations is also reduced to a certain extent. Compared with mainstream object detection networks, including YOLOv8, YOLOv5s-x also has certain advantages, which can provide oral health professionals with better impacted third molar detection and classification services. Full article
(This article belongs to the Special Issue Artificial Intelligence Applied to Dentistry)
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<p>Example images of the dataset.</p>
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<p>Winter’s classification.</p>
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<p>Six impacted category images. (<b>a</b>) Vertical position, numbered 0; (<b>b</b>) Mesioangular position, numbered 1; (<b>c</b>) Horizontal position, numbered 2; (<b>d</b>) Distoangular position, numbered 3; (<b>e</b>) Other, numbered 4; (<b>f</b>) Buccolingual position, numbered 5.</p>
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<p>Label example diagram.</p>
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<p>Example diagram of data enhancement.</p>
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<p>YOLOv5 structure diagram [<a href="#B27-applsci-13-09970" class="html-bibr">27</a>].</p>
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<p>Comparison chart of detection effect. (<b>A</b>–<b>D</b>): prediction results of YOLOv5s; (<b>E</b>–<b>H</b>): Prediction results of YOLOv5s-x.</p>
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<p>Graph of the relationship between mAP and other indicators. (<b>a</b>) Diagram between mAP and parameters; (<b>b</b>) diagram of the relationship between mAP and GFLOPs; (<b>c</b>) diagram of the relationship between mAP and model size.</p>
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16 pages, 4012 KiB  
Article
Sea Drift Trajectory Prediction Based on Quantum Convolutional Long Short-Term Memory Model
by Siyao Yan, Jing Zhang, Mosharaf Md Parvej and Tianchi Zhang
Appl. Sci. 2023, 13(17), 9969; https://doi.org/10.3390/app13179969 - 4 Sep 2023
Cited by 4 | Viewed by 1918
Abstract
This paper proposes a novel Sea Drift Trajectory Prediction method based on the Quantum Convolutional Long Short-Term Memory (QCNN-LSTM) model. Accurately predicting sea drift trajectories is a challenging task, as they are influenced by various complex factors, such as ocean currents, wind speed, [...] Read more.
This paper proposes a novel Sea Drift Trajectory Prediction method based on the Quantum Convolutional Long Short-Term Memory (QCNN-LSTM) model. Accurately predicting sea drift trajectories is a challenging task, as they are influenced by various complex factors, such as ocean currents, wind speed, and wave morphology. Therefore, in a complex marine environment, there is a need for more applicable and computationally advanced prediction methods. Our approach combines quantized convolutional neural networks with Long Short-Term Memory networks, utilizing two different input types of prediction to enhance the network’s applicability. By incorporating quantization techniques, we improve the computational power and accuracy of the trajectory prediction. We evaluate our method using sea drift datasets and AUV drift trajectory datasets, comparing it with other commonly used traditional methods. The experimental results demonstrate significant improvements in accuracy and robustness achieved by our proposed Quantum Convolutional Long Short-Term Memory model. Regardless of the input mode employed, the accuracy consistently surpasses 98%. In conclusion, our research provides a new approach for sea drift trajectory prediction, enhancing prediction accuracy and providing valuable insights for marine environmental management and related decision-making. Future research can further explore and optimize this model to have a greater impact on marine prediction and applications. Full article
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<p>A high-level abstract overview of the computational steps involved in the end-to-end pipeline for inference.</p>
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<p>Visualization of the Hadamard gate on the Bloch sphere, acting on the input state.</p>
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<p>A densely angular coded quantum circuit representing some data points of discrete data input QCNN-LSTM.</p>
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<p>Dense angle-coded quantum circuits representing the input data points of the time-window QCNN-LSTM model.</p>
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<p>QCNN-LSTM model structure.</p>
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<p>Performance of CNN model.</p>
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<p>Performance of CNN-LSTM mode.</p>
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<p>Performance of QCNN model.</p>
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<p>Performance of QCNN-LSTM model.</p>
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<p>Prediction Results of Ocean Current Data.</p>
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<p>Prediction Results of AUV Data.</p>
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14 pages, 5437 KiB  
Article
A Study on the Roof-Cutting and Pressure Releasing Technology of Roof Blasting
by Xiaowu Huang, Jian Guo, Yusong Miao, Xianqi Xie, Yujin Li, Hailiang Wang and Feifei Huang
Appl. Sci. 2023, 13(17), 9968; https://doi.org/10.3390/app13179968 - 4 Sep 2023
Cited by 4 | Viewed by 1126
Abstract
The surrounding rock during a coal mine excavation is prone to significant engineering disasters such as considerable deformation and rock bursts. Pressure release can improve the stress field of a deep rock mass and prevent the occurrence of dangers such as roadway collapse [...] Read more.
The surrounding rock during a coal mine excavation is prone to significant engineering disasters such as considerable deformation and rock bursts. Pressure release can improve the stress field of a deep rock mass and prevent the occurrence of dangers such as roadway collapse and coal and gas outbursts. This paper uses the ANSYS 19.0/LS-DYNA finite element software to simulate the crush area and fracture zone of a detonation charge with different diameters under in situ stress. The stability of the surrounding rock was analyzed based on the impact stress and velocity, and was verified by field tests. The research results show that the blasting load primarily affects the damaged area near the borehole, while the in situ stress affects far-field crack propagation. The crack propagates in the direction of high surrounding rock pressure. When the uncoupling index is 1.5, the impact pressure of a 60 mm diameter cartridge is eight times that of a 20 mm diameter cartridge. The impact speed can reach two times that of the 20 mm diameter cartridge. The high-energy event at the roof is transferred to the front of the working face, the distribution is no longer concentrated, and a better pressure-relief blasting effect is achieved. The research results can help guide the prevention and control measures of rock bursts and other mining disasters. Full article
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<p>Schematic diagram of crush zone and stress state of rock blasting.</p>
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<p>Schematic diagram of the calculation model.</p>
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<p>Stress nephograms of different diameters of charge at <span class="html-italic">t</span> = 1.0 ms.</p>
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<p>The variation law of the rock damage zone with the diameter of the charge.</p>
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<p>Impact pressure curve at the monitoring point.</p>
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<p>Layout of monitoring points for borehole interstice.</p>
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<p>Borehole clearance pressure and velocity curves. (<b>a</b>) Pressure curve, (<b>b</b>) Velocity curve.</p>
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<p>Borehole parameters.</p>
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<p>On-site charges to borehole.</p>
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<p>Coal seam stress receiver layout.</p>
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<p>The relationship between the daily average stress changes of the stress gauges at different positions near the borehole.</p>
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<p>Energy distribution law of micro-seismic events.</p>
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<p>Variation of energy events.</p>
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20 pages, 2949 KiB  
Article
Improving Dimensionality Reduction Projections for Data Visualization
by Bardia Rafieian, Pedro Hermosilla and Pere-Pau Vázquez
Appl. Sci. 2023, 13(17), 9967; https://doi.org/10.3390/app13179967 - 4 Sep 2023
Cited by 3 | Viewed by 4560
Abstract
In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim of preserving significant properties from the original data. Many dimensionality [...] Read more.
In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim of preserving significant properties from the original data. Many dimensionality reduction algorithms exist, and nonlinear approaches such as the t-SNE (t-Distributed Stochastic Neighbor Embedding) and UMAP (Uniform Manifold Approximation and Projection) have gained popularity in the field of information visualization. In this paper, we introduce a simple yet powerful manipulation for vector datasets that modifies their values based on weight frequencies. This technique significantly improves the results of the dimensionality reduction algorithms across various scenarios. To demonstrate the efficacy of our methodology, we conduct an analysis on a collection of well-known labeled datasets. The results demonstrate improved clustering performance when attempting to classify the data in the reduced space. Our proposal presents a comprehensive and adaptable approach to enhance the outcomes of dimensionality reduction for visual data exploration. Full article
(This article belongs to the Special Issue AI Applied to Data Visualization)
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<p>Dimensionality reduction of the spheres’ dataset using the different DR algorithms. Note that one of the classes, identified with the pink color, tends to overlap with the other clusters in the different cases. Our modifications effectively disentangle a substantial portion of the data points, resulting in a clearer and improved data visualization.</p>
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<p>Comparing other clustering algorithms for the PaCMAP DR algorithm. The results are equivalent to the ones obtained with SVM.</p>
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<p>Evaluation of trimap clustering using KNN, DT, MLP, and XGBoost. As in the previous case, the results are analogous to the ones obtained with SVM.</p>
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<p>Results obtained with the additional clustering algorithms for tSNE.</p>
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<p>Analysis of the UMAP DR data. The additional clustering algorithms also work similarly to the SVM.</p>
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<p>Dimensionality reduction of the USPS dataset utilizing different DR algorithms. The PaCMAP (<b>a</b>) exhibits good results with the original data. Applying our vector modification (<b>b</b>), although numerically inferior to the original, the clusters are not substantially changed. For the tSNE (<b>c</b>), the modified version may give poorer results due to the fragmentation of some of the clusters that can be seen in (<b>d</b>). trimap DR (<b>e</b>) is less effective than PaCMAP or UMAP at cluster separation. Our algorithm output (<b>f</b>) appears visually akin to the original version (<b>e</b>). Finally, UMAP (<b>g</b>) yields results similar to PaCMAP, with well-concentrated clusters and only minor instances of collision or overlap. In this case, the data modification in (<b>h</b>) causes slight proximity changes in a couple of clusters.</p>
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<p>Dimensionality reduction of the USPS dataset utilizing different DR algorithms. The PaCMAP (<b>a</b>) exhibits good results with the original data. Applying our vector modification (<b>b</b>), although numerically inferior to the original, the clusters are not substantially changed. For the tSNE (<b>c</b>), the modified version may give poorer results due to the fragmentation of some of the clusters that can be seen in (<b>d</b>). trimap DR (<b>e</b>) is less effective than PaCMAP or UMAP at cluster separation. Our algorithm output (<b>f</b>) appears visually akin to the original version (<b>e</b>). Finally, UMAP (<b>g</b>) yields results similar to PaCMAP, with well-concentrated clusters and only minor instances of collision or overlap. In this case, the data modification in (<b>h</b>) causes slight proximity changes in a couple of clusters.</p>
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<p>The Coil20 dataset demonstrates enhanced clustering accuracy across all DR algorithms following our modification, except for the tSNE algorithm. This dataset contains 20 classes. Observe that the overall distribution of clusters improves after our modification (second and last column).</p>
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<p>The documents dataset indicated clear improvements in all the DR algorithms. Please note that the modified versions generated projections with a better separation between clusters.</p>
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<p>This document set was not as clearly separated by any of the DR techniques. With our modification, the trimap demonstrated superior performance in achieving cluster separation. The other techniques also improved, but the clustering separations were not obvious.</p>
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27 pages, 15031 KiB  
Article
Active Support System for the Correction of a 4m SiC Primary Mirror Based on the Bending Mode
by Zhiyuan Yu, Xiaoxia Wu and Fuguo Wang
Appl. Sci. 2023, 13(17), 9966; https://doi.org/10.3390/app13179966 - 4 Sep 2023
Cited by 1 | Viewed by 1363
Abstract
Active optics is a key technology in ground-based large-aperture telescopes. The active correction of the surface shape of the primary mirror is used to reduce the surface shape error and improve the imaging quality. At present, the structure of the active optics support [...] Read more.
Active optics is a key technology in ground-based large-aperture telescopes. The active correction of the surface shape of the primary mirror is used to reduce the surface shape error and improve the imaging quality. At present, the structure of the active optics support system is not standardized. Therefore, to ensure the imaging quality of a telescope using a 4m SiC (silicon carbide) primary mirror, this article designed an active support system for the primary mirror and comprehensively evaluated the performance of the system. The system used pneumatic actuators to correct the surface shape of the primary mirror and a six-hardpoint positioning mechanism to correct the pose of the primary mirror. A method for compensating for the force on the hardpoints that causes protrusions and dents on the primary mirror surface was proposed, which effectively improved the accuracy of the primary mirror surface. The bending-mode method was used to determine the correction force. To achieve better results in the surface shape correction based on the bending mode, the relationship between the order of the bending modes used in the correction and the correction effect was studied, enabling the system to achieve a higher surface shape accuracy with a smaller correction force. Finally, the performance of the system was evaluated under various conditions, such as under gravity, thermal load, and wind load. The results indicated that the system had good correction effects on the deformation of the primary mirror under various operating conditions and could meet the requirements of optical design for surface accuracy. In conclusion, this study not only verified the application of active optics technology based on the bending mode in large-aperture SiC mirrors, but also improved on the relevant theoretical research on active optics. Full article
(This article belongs to the Section Optics and Lasers)
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<p>Structural schematic of the active support system for a 4m SiC primary mirror.</p>
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<p>Layout and numbering of pneumatic surface control actuators and hardpoints.</p>
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<p>Finite element model of the active support system for the 4m SiC primary mirror.</p>
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<p>Influence function <b><span class="html-italic">A</span></b><span class="html-italic"><sub>i</sub></span> and equilibrium force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>Ai</sub></span> of some pneumatic actuators. (<b>a</b>) Influence function <b><span class="html-italic">A</span></b><sub>1</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A1</sub>; (<b>b</b>) Influence function <b><span class="html-italic">A</span></b><sub>5</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A5</sub>; (<b>c</b>) Influence function <b><span class="html-italic">A</span></b><sub>7</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A7</sub>; (<b>d</b>) Influence function <b><span class="html-italic">A</span></b><sub>16</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A16</sub>; (<b>e</b>) Influence function <b><span class="html-italic">A</span></b><sub>19</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A19</sub>; (<b>f</b>) Influence function <b><span class="html-italic">A</span></b><sub>28</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A28</sub>; (<b>g</b>) Influence function <b><span class="html-italic">A</span></b><sub>31</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A31</sub>; (<b>h</b>) Influence function <b><span class="html-italic">A</span></b><sub>50</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A50</sub>.</p>
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<p>Influence function <b><span class="html-italic">A</span></b><span class="html-italic"><sub>i</sub></span> and equilibrium force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>Ai</sub></span> of some pneumatic actuators. (<b>a</b>) Influence function <b><span class="html-italic">A</span></b><sub>1</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A1</sub>; (<b>b</b>) Influence function <b><span class="html-italic">A</span></b><sub>5</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A5</sub>; (<b>c</b>) Influence function <b><span class="html-italic">A</span></b><sub>7</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A7</sub>; (<b>d</b>) Influence function <b><span class="html-italic">A</span></b><sub>16</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A16</sub>; (<b>e</b>) Influence function <b><span class="html-italic">A</span></b><sub>19</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A19</sub>; (<b>f</b>) Influence function <b><span class="html-italic">A</span></b><sub>28</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A28</sub>; (<b>g</b>) Influence function <b><span class="html-italic">A</span></b><sub>31</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A31</sub>; (<b>h</b>) Influence function <b><span class="html-italic">A</span></b><sub>50</sub> and equilibrium force <b><span class="html-italic">F</span></b><sub>A50</sub>.</p>
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<p>Theoretical values of partial bending mode <b><span class="html-italic">B</span></b><span class="html-italic"><sub>i</sub></span> of the 4m SiC primary mirror and corresponding bending-mode forces <b><span class="html-italic">F</span></b><span class="html-italic"><sub>Bi</sub></span>. (<b>a</b>) Bending mode <b><span class="html-italic">B</span></b><sub>1</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>1</sub>; (<b>b</b>) Bending mode <b><span class="html-italic">B</span></b><sub>3</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>3</sub>; (<b>c</b>) Bending mode <b><span class="html-italic">B</span></b><sub>5</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>5</sub>; (<b>d</b>) Bending mode <b><span class="html-italic">B</span></b><sub>7</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>7</sub>; (<b>e</b>) Bending mode <b><span class="html-italic">B</span></b><sub>9</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>9</sub>; (<b>f</b>) Bending mode <b><span class="html-italic">B</span></b><sub>11</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>11</sub>; (<b>g</b>) Bending mode <b><span class="html-italic">B</span></b><sub>13</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>13</sub>; (<b>h</b>) Bending mode <b><span class="html-italic">B</span></b><sub>15</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>15</sub>; (<b>i</b>) Bending mode <b><span class="html-italic">B</span></b><sub>17</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>17</sub>; (<b>j</b>) Bending mode <b><span class="html-italic">B</span></b><sub>19</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>19</sub>.</p>
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<p>Theoretical values of partial bending mode <b><span class="html-italic">B</span></b><span class="html-italic"><sub>i</sub></span> of the 4m SiC primary mirror and corresponding bending-mode forces <b><span class="html-italic">F</span></b><span class="html-italic"><sub>Bi</sub></span>. (<b>a</b>) Bending mode <b><span class="html-italic">B</span></b><sub>1</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>1</sub>; (<b>b</b>) Bending mode <b><span class="html-italic">B</span></b><sub>3</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>3</sub>; (<b>c</b>) Bending mode <b><span class="html-italic">B</span></b><sub>5</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>5</sub>; (<b>d</b>) Bending mode <b><span class="html-italic">B</span></b><sub>7</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>7</sub>; (<b>e</b>) Bending mode <b><span class="html-italic">B</span></b><sub>9</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>9</sub>; (<b>f</b>) Bending mode <b><span class="html-italic">B</span></b><sub>11</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>11</sub>; (<b>g</b>) Bending mode <b><span class="html-italic">B</span></b><sub>13</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>13</sub>; (<b>h</b>) Bending mode <b><span class="html-italic">B</span></b><sub>15</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>15</sub>; (<b>i</b>) Bending mode <b><span class="html-italic">B</span></b><sub>17</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>17</sub>; (<b>j</b>) Bending mode <b><span class="html-italic">B</span></b><sub>19</sub> and bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>B</sub></span><sub>19</sub>.</p>
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<p>Relationship between the amplitude of bending-mode force <b><span class="html-italic">F</span></b><span class="html-italic"><sub>Bi</sub></span> and the order <span class="html-italic">i</span> of the bending mode.</p>
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<p>Structural diagram of the six-hardpoint positioning mechanism. (<b>a</b>) Mechanism in the initial pose; (<b>b</b>) mechanism in the state after pose adjustment.</p>
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<p>Deformation diagram of the mirror cell. (<b>a</b>) Elevation angle of 45°; (<b>b</b>) Elevation angle of 90°.</p>
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<p>Relationship between the pose error of the primary mirror and elevation angle.</p>
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<p>Adjustment amount of hardpoint length required to correct the primary mirror pose error.</p>
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<p>Primary mirror surface defects caused by force on hardpoints (external conditions: gravity; elevation angle: 15°; order of the bending modes: 40; the rms after surface correction: 53.9 nm).</p>
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<p>Actual values of partial bending mode <b><span class="html-italic">B</span></b><span class="html-italic"><sub>i</sub></span> of the 4m SiC primary mirror. (<b>a</b>) Actual values of <b><span class="html-italic">B</span></b><sub>1</sub>; (<b>b</b>) Actual values of <b><span class="html-italic">B</span></b><sub>3</sub>; (<b>c</b>) Actual values of <b><span class="html-italic">B</span></b><sub>5</sub>; (<b>d</b>) Actual values of <b><span class="html-italic">B</span></b><sub>7</sub>; (<b>e</b>) Actual values of <b><span class="html-italic">B</span></b><sub>9</sub>; (<b>f</b>) Actual values of <b><span class="html-italic">B</span></b><sub>11</sub>; (<b>g</b>) Actual values of <b><span class="html-italic">B</span></b><sub>13</sub>; (<b>h</b>) Actual values of <b><span class="html-italic">B</span></b><sub>15</sub>; (<b>i</b>) Actual values of <b><span class="html-italic">B</span></b><sub>17</sub>; (<b>j</b>) Actual values of <b><span class="html-italic">B</span></b><sub>19</sub>.</p>
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<p>Schematic diagram of the deformation of the 4m SiC primary mirror surface due to gravity. (<b>a</b>) Elevation angle of 90°; (<b>b</b>) Elevation angle of 45°; (<b>c</b>) Elevation angle of 0°.</p>
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<p>Correction of gravity deformation of the primary mirror using the first 40 orders of bending modes at an elevation angle of 45°. (<b>a</b>) Surface shape correction result (force on hardpoint not compensated); (<b>b</b>) Surface shape before correction (force on hardpoint compensated); (<b>c</b>) Surface shape correction result (force on hardpoint compensated).</p>
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<p>Results of correcting gravity deformation of the primary mirror using different orders of bending modes. (<b>a</b>) Results at elevation angle of 90°; (<b>b</b>) Results at elevation angle of 45°; (<b>c</b>) Results at elevation angle of 0°.</p>
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<p>Results of correcting the gravity deformation of the primary mirror using the first 30 orders of bending modes. (<b>a</b>) Elevation angle of 90°; (<b>b</b>) Elevation angle of 45°; (<b>c</b>) Elevation angle of 0°.</p>
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<p>Zernike distributions of surface before and after correction (elevation angle of 90°).</p>
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<p>Three temperature fields corresponding to three types of temperature differences. (<b>a</b>) Temperature field of 0.2 °C axial temperature difference; (<b>b</b>) Temperature field of 0.2 °C radial temperature difference; (<b>c</b>) Temperature field of 0.2 °C transverse temperature difference.</p>
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<p>The 4m SiC primary mirror surface shape caused by three types of temperature differences. (<b>a</b>) Axial temperature difference of 0.2 °C; (<b>b</b>) Radial temperature difference of 0.2 °C; (<b>c</b>) Transverse temperature difference of 0.2 °C.</p>
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<p>Results of correcting the thermal load deformation of the primary mirror using the first 30 orders of bending modes. (<b>a</b>) Axial temperature difference of 0.2 °C; (<b>b</b>) Radial temperature difference of 0.2 °C; (<b>c</b>) Transverse temperature difference of 0.2 °C.</p>
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<p>Zernike distributions of surface before and after correction (axial temperature difference of 0.2 °C).</p>
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<p>Results of correcting the thermal load deformation of 4m SiC primary mirror with the first 30 orders of bending modes.</p>
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<p>Schematic diagram of the 4m SiC primary mirror under wind load.</p>
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<p>Schematic diagram of the deformation of the 4m SiC primary mirror surface due to static wind load. (<b>a</b>) <span class="html-italic">θ</span> = 0°; (<b>b</b>) <span class="html-italic">θ</span> = 30°; (<b>c</b>) <span class="html-italic">θ</span> = 60°.</p>
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<p>Correction results for the deformation of the primary mirror under static wind load using the first 30 orders of bending modes. (<b>a</b>) <span class="html-italic">θ</span> = 0°; (<b>b</b>) <span class="html-italic">θ</span> = 30°; (<b>c</b>) <span class="html-italic">θ</span> = 60°.</p>
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<p>Zernike distributions of surface before and after correction (<span class="html-italic">θ</span> = 0°).</p>
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19 pages, 2508 KiB  
Article
Forecasting of NOx Emissions of Diesel LHD Vehicles in Underground Mines—An ANN-Based Regression Approach
by Aleksandra Banasiewicz, Forougholsadat Moosavi, Michalina Kotyla, Paweł Śliwiński, Pavlo Krot, Jacek Wodecki and Radosław Zimroz
Appl. Sci. 2023, 13(17), 9965; https://doi.org/10.3390/app13179965 - 4 Sep 2023
Cited by 3 | Viewed by 1728
Abstract
An approach based on an artificial neural network (ANN) for the prediction of NOx emissions from underground load–haul–dumping (LHD) vehicles powered by diesel engines is proposed. A Feed-Forward Neural Network, the Multi-Layer Perceptron (MLP), is used to establish a nonlinear relationship between input [...] Read more.
An approach based on an artificial neural network (ANN) for the prediction of NOx emissions from underground load–haul–dumping (LHD) vehicles powered by diesel engines is proposed. A Feed-Forward Neural Network, the Multi-Layer Perceptron (MLP), is used to establish a nonlinear relationship between input and output layers. The predicted values of NOx emissions have less than 15% error compared to the real values measured by the LHD onboard monitoring system by the standard sensor. This is considered quite good efficiency for dynamic behaviour prediction of extremely complex systems. The achieved accuracy of NOx prediction allows the application of the ANN-based “soft sensor” in environmental impact estimation and ventilation system demand planning, which depends on the number of working LHDs in the underground mine. The proposed solution to model NOx concentrations from mining machines will help to provide a better understanding of the atmosphere of the working environment and will also contribute to improving the safety of underground crews. Full article
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<p>LKP-1701: the LHD vehicle (KGHM ZANAM) [<a href="#B63-applsci-13-09965" class="html-bibr">63</a>].</p>
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<p>The DEUTZ TCD 12.0 V6 diesel engine with its SCR system [<a href="#B64-applsci-13-09965" class="html-bibr">64</a>].</p>
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<p>The power and torque functions of diesel engine DEUTZ TCD 12.0 V6 [<a href="#B64-applsci-13-09965" class="html-bibr">64</a>].</p>
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<p>The structure of a Multi-Layer Perceptron (MLP) network.</p>
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<p>The time series of recorded signals: NOx emission ENGNOX (ppm); engine rotations ENGRPM (rpm); and engine acceleration ENGTPS (%).</p>
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<p>The time series of recorded signals: NOx emission ENGNOX (ppm); intake air pressure INTAKEP (kPa); selected gear (−4…0…4); and hydraulic oil pressure HYDOILP (MPa).</p>
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<p>The correlation of LHD operational parameters.</p>
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<p>Training data.</p>
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<p>Validation data.</p>
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<p>Test data.</p>
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<p>All data with outliers.</p>
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<p>Training data.</p>
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<p>Validation data.</p>
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<p>Test data.</p>
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<p>All data.</p>
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<p>Cumulative NOx emissions: original measured data and predicted (<b>a</b>); error of MLP prediction (<b>b</b>).</p>
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16 pages, 3175 KiB  
Article
Transimpedance Amplifier for Noise Measurements in Low-Resistance IR Photodetectors
by Krzysztof Achtenberg, Graziella Scandurra, Janusz Mikołajczyk, Carmine Ciofi and Zbigniew Bielecki
Appl. Sci. 2023, 13(17), 9964; https://doi.org/10.3390/app13179964 - 4 Sep 2023
Cited by 4 | Viewed by 2562
Abstract
This paper presents the design and testing of an ultra-low-noise transimpedance amplifier (TIA) for low-frequency noise measurements on low-impedance (below 1 kΩ) devices, such as advanced IR photodetectors. When dealing with low-impedance devices, the main source of background noise in transimpedance amplifiers comes [...] Read more.
This paper presents the design and testing of an ultra-low-noise transimpedance amplifier (TIA) for low-frequency noise measurements on low-impedance (below 1 kΩ) devices, such as advanced IR photodetectors. When dealing with low-impedance devices, the main source of background noise in transimpedance amplifiers comes from the equivalent input voltage noise of the operational amplifier, which is used in a shunt–shunt configuration to obtain a transimpedance stage. In our design, we employ a hybrid operational amplifier in which an input front end based on ultra-low-noise discrete JFET devices is used to minimize this noise contribution. When using IF3602 JFETs for the input stage, the equivalent voltage noise of the hybrid operational amplifier can be as low as 4 nV/√Hz, 2 nV/√Hz, and 0.9 nV/√Hz at 1 Hz, 10 Hz, and 1 kHz, respectively. When testing the current noise of an ideal 1 kΩ resistor, these values correspond to a current noise contribution of the same order as or below that of the thermal noise of the resistor. Therefore, in cases in which the current flicker noise is dominant, i.e., much higher than the thermal noise, the noise contribution from the transimpedance amplifier can be neglected in most cases of interest. Test measurements on advanced low-impedance photodetectors are also reported to demonstrate the effectiveness of our proposed approach for directly measuring low-frequency current noise in biased low-impedance electronic devices. Full article
(This article belongs to the Special Issue Latest Research on Electronic Noise)
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<p>Current noise measurement system.</p>
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<p>Proposed TIA amplifier. The component types and their values are listed in <a href="#applsci-13-09964-t001" class="html-table">Table 1</a>.</p>
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<p>Simplified equivalent circuit for noise calculation.</p>
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<p>Test results when using resistances at room temperature as DUTs. Tests were performed on 100 Ω and 1 kΩ resistances using two different values for the feedback resistance <span class="html-italic">R<sub>R</sub></span>. The continuous black lines represent the expected noise, that is, the thermal current noise generated when using the resistances as DUTs.</p>
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<p>The architecture of the investigated InAsSb-based barrier IR detector. Reprinted with permission from Ref. [<a href="#B25-applsci-13-09964" class="html-bibr">25</a>]. 2023, SPIE.</p>
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<p>Current–voltage (I-V) characteristics of the tested photodiode at different temperatures.</p>
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<p>The determined differential resistance of the photodiode at a temperature of 280 K.</p>
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<p>Current noise measurement results at different bias levels.</p>
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<p>Current noise at 10 Hz vs. bias current. The I-V characteristics of the device at 280 K from <a href="#applsci-13-09964-f005" class="html-fig">Figure 5</a> are reported in the inset.</p>
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