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Appl. Sci., Volume 11, Issue 8 (April-2 2021) – 431 articles

Cover Story (view full-size image): We successfully demonstrated conversion of the indirect band gap nature of bilayer MoS2 to a direct band gap nature and enhanced the photoluminescence (PL) intensity of bilayer MoS2 dramatically. The procedure combines UV irradiation with superacid molecular treatment on bilayer MoS2. The process dramatically enhances the PL intensity of bilayer MoS2 by a factor of 700×. The monolayer-like top layer is generated and physically separated from the substrate by the intermediate bottom MoS2 layer. This situation is preferable for achieving a strong PL intensity. View this paper
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17 pages, 2606 KiB  
Article
A DMAIC Integrated Fuzzy FMEA Model: A Case Study in the Automotive Industry
by Radu Godina, Beatriz Gomes Rolis Silva and Pedro Espadinha-Cruz
Appl. Sci. 2021, 11(8), 3726; https://doi.org/10.3390/app11083726 - 20 Apr 2021
Cited by 26 | Viewed by 5023
Abstract
The growing competitiveness in the automotive industry and the strict standards to which it is subject, require high quality standards. For this, quality tools such as the failure mode and effects analysis (FMEA) are applied to quantify the risk of potential failure modes. [...] Read more.
The growing competitiveness in the automotive industry and the strict standards to which it is subject, require high quality standards. For this, quality tools such as the failure mode and effects analysis (FMEA) are applied to quantify the risk of potential failure modes. However, for qualitative defects with subjectivity and associated uncertainty, and the lack of specialized technicians, it revealed the inefficiency of the visual inspection process, as well as the limitations of the FMEA that is applied to it. The fuzzy set theory allows dealing with the uncertainty and subjectivity of linguistic terms and, together with the expert systems, allows modeling of the knowledge involved in tasks that require human expertise. In response to the limitations of FMEA, a fuzzy FMEA system was proposed. Integrated in the design, measure, analyze, improve and control (DMAIC) cycle, the proposed system allows the representation of expert knowledge and improves the analysis of subjective failures, hardly detected by visual inspection, compared to FMEA. The fuzzy FMEA system was tested in a real case study at an industrial manufacturing unit. The identified potential failure modes were analyzed and a fuzzy risk priority number (RPN) resulted, which was compared with the classic RPN. The main results revealed several differences between both. The main differences between fuzzy FMEA and classical FMEA come from the non-linear relationship between the variables and in the attribution of an RPN classification that assigns linguistic terms to the results, thus allowing a strengthening of the decision-making regarding the mitigation actions of the most “important” failure modes. Full article
(This article belongs to the Section Applied Industrial Technologies)
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<p>Fuzzy inference system (adapted from [<a href="#B10-applsci-11-03726" class="html-bibr">10</a>]).</p> Full article ">Figure 2
<p>Fuzzy FMEA system integration in DMAIC cycle.</p> Full article ">Figure 3
<p>Partial view of the inference rules in MATLAB 2017.</p> Full article ">Figure 4
<p>Partial view of the inference process in MATLAB 2017.</p> Full article ">Figure 5
<p>Process schematic of injection coil 1 production line. The representation by colors are as follows: all the machines on the production line, the plastic injection machines, where the plastic components that make up the part (orange), the assembly stations (Mtg), winding, casting, and final testing are molded (blue) and the visual inspection stations, where the operator inspects the parts or lots at the exit of the critical machines (green).</p> Full article ">Figure 6
<p>An example of the rule viewer for failure mode “Conical winding”.</p> Full article ">
16 pages, 65872 KiB  
Article
Implementation of Pavement Defect Detection System on Edge Computing Platform
by Yu-Chen Lin, Wen-Hui Chen and Cheng-Hsuan Kuo
Appl. Sci. 2021, 11(8), 3725; https://doi.org/10.3390/app11083725 - 20 Apr 2021
Cited by 15 | Viewed by 3634
Abstract
Road surfaces in Taiwan, as well as other developed countries, often experience structural failures, such as patches, bumps, longitudinal and lateral cracking, and potholes, which cause discomfort and pose direct safety risks to motorists. To minimize damage to vehicles from pavement defects or [...] Read more.
Road surfaces in Taiwan, as well as other developed countries, often experience structural failures, such as patches, bumps, longitudinal and lateral cracking, and potholes, which cause discomfort and pose direct safety risks to motorists. To minimize damage to vehicles from pavement defects or provide the corresponding comfortable ride promotion strategy later, in this study, we developed a pavement defect detection system using a deep learning perception scheme for implementation on Xilinx Edge AI platforms. To increase the detection distance and accuracy of pavement defects, two cameras with different fields of view, at 70∘ and 30∘, respectively, were used to capture the front views of a car, and then the YOLOv3 (you only look once, version 3) model was employed to recognize the pavement defects, such as potholes, cracks, manhole covers, patches, and bumps. In addition, to promote continuous pavement defect recognition rate, a tracking-via-detection strategy was employed, which first detects pavement defects in each frame and then associates them to different frames using the Kalman filter method. Thus, the average detection accuracy of the pothole category could reach 71%, and the miss rate was about 29%. To confirm the effectiveness of the proposed detection strategy, experiments were conducted on an established Taiwan pavement defect image dataset (TPDID), which is the first dataset for Taiwan pavement defects. Moreover, different AI methods were used to detect the pavement defects for quantitative comparative analysis. Finally, a field-programmable gate-array-based edge computing platform was used as an embedded system to implement the proposed YOLOv3-based pavement defect detection system; the execution speed reached 27.8 FPS while maintaining the accuracy of the original system model. Full article
(This article belongs to the Special Issue Deep Learning for Signal Processing Applications)
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<p>YOLOv3-based model for pavement defect detection.</p> Full article ">Figure 2
<p>Tracking-via-detection framework.</p> Full article ">Figure 3
<p>Model compression strategy and verification flowchart.</p> Full article ">Figure 4
<p>Improvement effect of model compression ratio.</p> Full article ">Figure 5
<p>Implementation of embedded system for YOLOv3-based pavement defect detection systems. (<b>a</b>) Xilinx ZCU104 platform; (<b>b</b>) Nvidia TX2 platform; (<b>c</b>) quantitative performance comparison.</p> Full article ">Figure 6
<p>Taiwan pavement defect image database (TPDID).</p> Full article ">Figure 7
<p>Pavement defect detection results by two lenses with different viewing angles. (<b>a</b>) Detection results at time step t; (<b>b</b>) Detection and tracking results at time step <span class="html-italic">t</span> + <span class="html-italic">j</span>.</p> Full article ">Figure 8
<p>Loss function and mAP for our proposed pavement defect detection system.</p> Full article ">Figure 9
<p>Average precision and miss rate for 6 pavement defect categories. (<b>a</b>) Average detection accuracy of each category; (<b>b</b>) Miss rate of each category.</p> Full article ">Figure 10
<p>Pothole recognition results in low-illumination night environment.</p> Full article ">Figure 11
<p>Pothole recognition results under severe conditions from the Pacific Northwest highway dataset.</p> Full article ">Figure 12
<p>Pavement defect detection results using different deep learning models. (<b>a</b>) YOLOv4; (<b>b</b>) YOLO-mobilenet; (<b>c</b>) TF-YOLO; (<b>d</b>) RetinaNet.</p> Full article ">Figure 13
<p>Quantitative comparison of mAP and FPS for different deep learning models.</p> Full article ">Figure 14
<p>Comparison of miss rate for different deep learning models.</p> Full article ">Figure 15
<p>Quantitative comparison of AP of pothole category for each model in different distance intervals. (<b>a</b>) Relationship between the pixel differences to actual road distance; (<b>b</b>) AP evaluation results for each model in different distance intervals.</p> Full article ">Figure 15 Cont.
<p>Quantitative comparison of AP of pothole category for each model in different distance intervals. (<b>a</b>) Relationship between the pixel differences to actual road distance; (<b>b</b>) AP evaluation results for each model in different distance intervals.</p> Full article ">
11 pages, 2954 KiB  
Article
Conventional and Enzyme-Assisted Extraction of Rosemary Leaves (Rosmarinus officinalis L.): Toward a Greener Approach to High Added-Value Extracts
by Antonella Rozaria Nefeli Pontillo, Lydia Papakosta-Tsigkri, Theopisti Lymperopoulou, Diomi Mamma, Dimitris Kekos and Anastasia Detsi
Appl. Sci. 2021, 11(8), 3724; https://doi.org/10.3390/app11083724 - 20 Apr 2021
Cited by 24 | Viewed by 4522
Abstract
The effect of different extraction methods of rosemary leaves on the total phenolic content (TPC), and the antioxidant activity of the extracts was herein investigated. Firstly, the solid-liquid conventional extraction (CEM) and microwave-assisted extraction (MAE) were implemented in an effort to identify the [...] Read more.
The effect of different extraction methods of rosemary leaves on the total phenolic content (TPC), and the antioxidant activity of the extracts was herein investigated. Firstly, the solid-liquid conventional extraction (CEM) and microwave-assisted extraction (MAE) were implemented in an effort to identify the effect of the solvent and of microwave irradiation on the extract quality. The extract obtained from CEM at room temperature, using ethanol/water 95:5 v/v, showed the highest antioxidant activity (IC50 = 12.1 μg/mL). MAE using ethanol/water 50:50 v/v provided an extract with TPC and DPPH radical scavenging ability in a significantly shorter extraction time (1 h for MAE and 24 h for CEM). Enzyme-assisted extraction (EAE) using five commercial enzyme formulations was implemented, and the kinetic equation was calculated. Finally, the effect of EAE as a pretreatment method to CEM was examined. Pretreatment of the plant material with pectinolytic enzymes for 1 h prior to a 24 h CEM with 50% hydroethanolic solvent was found to be the optimum conditions for the extraction of rosemary leaves, providing an extract with higher DPPH radical scavenging ability (IC50 14.3 ± 0.8 μg/mL) and TPC (15.2 ± 0.3 mgGAE/grosemary) than the corresponding extract without the enzyme pretreatment. Full article
(This article belongs to the Special Issue Recent Advances in the Development and Application of Green Extraction Techniques)
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<p>Effect of enzymatic extraction time on TPC. Symbols: (●) Alcalase 2.4L FG, (◯) Cellic CTec2, (▲) Viscozyme L, (△) Cellic HTec2, (▼) Bioprep 3000L. Dashed lines are the non-linear fitting curves (Equation (2)).</p> Full article ">Figure 2
<p>TPC (mgGAE/g rosemary) values for a 24 h enzyme-assisted extraction in water using (●) 2.5% or (◯) 5.0% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) of Bioprep 3000L.</p> Full article ">Figure 3
<p>The effect of extraction time on the TPC (mg<sub>GAE</sub>/g<sub>rosemary</sub>) (●).</p> Full article ">Figure 4
<p>Effect of extraction time on TPC during (◯) conventional extraction (50% <span class="html-italic">v</span>/<span class="html-italic">v</span> ethanol) and (●) ΕAΕ + CEM. Dashed lines are the non-linear fitting curves (Equation (2)).</p> Full article ">
10 pages, 4148 KiB  
Article
Testing of Natural Sorbents for the Assessment of Heavy Metal Ions’ Adsorption
by Vera Yurak, Rafail Apakashev, Alexey Dushin, Albert Usmanov, Maxim Lebzin and Alexander Malyshev
Appl. Sci. 2021, 11(8), 3723; https://doi.org/10.3390/app11083723 - 20 Apr 2021
Cited by 17 | Viewed by 2624
Abstract
Nowadays, the sorption-oriented approach is on the agenda in the remediation practices of lands contaminated with heavy metals. The current growing quantity of research accounts for different sorbents. However, there is still a lack of studies utilizing the economic criteria. Therefore, to ensure [...] Read more.
Nowadays, the sorption-oriented approach is on the agenda in the remediation practices of lands contaminated with heavy metals. The current growing quantity of research accounts for different sorbents. However, there is still a lack of studies utilizing the economic criteria. Therefore, to ensure a wide application of opportunities, one of the necessary requirements is their economic efficiency in use. By utilizing these criteria, this manuscript researches the generally accepted natural sorbents for the assessment of heavy metal ions’ adsorption, such as peat, diatomite, vermiculite and their mixtures in different proportions and physical shapes. The methodological base of the study consists of the volumetric (titrimetric) method, X-ray fluorescence spectrometry and atomic absorption spectrometry. Experimental tests show a certain decline in the efficiency of heavy metal ions’ adsorption from aqueous salt solutes as follows: granular peat–diatomite > large-fraction vermiculite > medium-fraction vermiculite > non-granular peat–diatomite > diatomite. Full article
(This article belongs to the Special Issue Environmental Restoration of Metal-Contaminated Soils)
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<p>Efficiency of the sorbents (A) in relation to the grade of heavy metal ion extraction from the model solutions.</p> Full article ">Figure 2
<p>The total value of the degree of extraction of heavy metal ions (A) by various sorbents.</p> Full article ">Figure 3
<p>The surface of the peat–diatomite granular sorbent (Altami MET 1 optical microscope (Altami Ltd, Russia; it has been sourced from St. Petersburg, Russia); magnification ×40).</p> Full article ">Figure 4
<p>The surface of diatomite (SNE 4500M microscope).</p> Full article ">Figure 5
<p>The surface of vermiculite (SNE 4500M microscope).</p> Full article ">
14 pages, 635 KiB  
Article
CF-CNN: Coarse-to-Fine Convolutional Neural Network
by Jinho Park, Heegwang Kim and Joonki Paik
Appl. Sci. 2021, 11(8), 3722; https://doi.org/10.3390/app11083722 - 20 Apr 2021
Cited by 6 | Viewed by 3737
Abstract
In this paper, we present a coarse-to-fine convolutional neural network (CF-CNN) for learning multilabel classes. The basis of the proposed CF-CNN is a disjoint grouping method that first creates a class group with hierarchical association, and then assigns a new label to a [...] Read more.
In this paper, we present a coarse-to-fine convolutional neural network (CF-CNN) for learning multilabel classes. The basis of the proposed CF-CNN is a disjoint grouping method that first creates a class group with hierarchical association, and then assigns a new label to a class belonging to each group so that each class acquires multiple labels. CF-CNN consists of one main network and two subnetworks. Each subnetwork performs coarse prediction using the group labels created by the disjoint grouping method. The main network includes a refine convolution layer and performs fine prediction to fuse the feature maps acquired from the subnetwork. The generated class set in the upper level has the same classification boundary to that in the lower level. Since the classes belonging to the upper level label are classified with a higher priority, parameter optimization becomes easier. In experimental results, the proposed method is applied to various classification tasks to show a higher classification accuracy by up to 3% with a much smaller number of parameters without modification of the baseline model. Full article
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology Ⅲ)
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<p>Network structure and hierarchical structure label illustrations. (<b>a</b>) SplitNet [<a href="#B22-applsci-11-03722" class="html-bibr">22</a>], (<b>b</b>) HD-CNN [<a href="#B19-applsci-11-03722" class="html-bibr">19</a>], (<b>c</b>) B-CNN [<a href="#B20-applsci-11-03722" class="html-bibr">20</a>], (<b>d</b>) our CF-CNN, and (<b>e</b>) hierarchical structure label.</p> Full article ">Figure 2
<p>Comparison with the CIFAR-100 dataset.</p> Full article ">Figure 3
<p>Effect of group balance regularization. The bar graph shows group assignment results for different values of <math display="inline"><semantics> <msub> <mi>λ</mi> <mi>B</mi> </msub> </semantics></math> with <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>4</mn> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Result of the hierarchical structure label generation on the CIFAR-10 dataset.</p> Full article ">
11 pages, 831 KiB  
Article
Effectiveness of Shock Wave Therapy versus Intra-Articular Corticosteroid Injection in Diabetic Frozen Shoulder Patients’ Management: Randomized Controlled Trial
by Ahmed Ebrahim Elerian, David Rodriguez-Sanz, Abdelaziz Abdelaziz Elsherif, Hend Adel Dorgham, Dina Mohamed Ali Al-Hamaky, Mahmoud S. El Fakharany and Mahmoud Ewidea
Appl. Sci. 2021, 11(8), 3721; https://doi.org/10.3390/app11083721 - 20 Apr 2021
Cited by 7 | Viewed by 5790
Abstract
Frozen shoulder is a major musculoskeletal illness in diabetic patients. This study aimed to compare the effectiveness of shock wave and corticosteroid injection in the management of diabetic frozen shoulder patients. Fifty subjects with diabetic frozen shoulder were divided randomly into group A [...] Read more.
Frozen shoulder is a major musculoskeletal illness in diabetic patients. This study aimed to compare the effectiveness of shock wave and corticosteroid injection in the management of diabetic frozen shoulder patients. Fifty subjects with diabetic frozen shoulder were divided randomly into group A (the intra-articular corticosteroid injection group) and group B that received 12 sessions of shock wave therapy, while each patient in both groups received the traditional physiotherapy program. The level of pain and disability, the range of motion, as well as the glucose triad were evaluated before patient assignment to each group, during the study and at the end of the study. Compared to the pretreatment evaluations there were significant improvements of shoulder pain and disability and in shoulder flexion and abduction range of motion in both groups (p < 0.05). The shock wave group revealed a more significant improvement the intra-articular corticosteroid injection group, where p was 0.001 for shoulder pain and disability and shoulder flexion and abduction. Regarding the effect of both interventions on the glucose triad, there were significant improvements in glucose control with group B, where p was 0.001. Shock waves provide a more effective and safer treatment modality for diabetic frozen shoulder treatment than corticosteroid intra-articular injection. Full article
(This article belongs to the Special Issue Physical Therapy and Health)
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<p>Flow chart of the study.</p> Full article ">
16 pages, 543 KiB  
Article
Adversarial Optimization-Based Knowledge Transfer of Layer-Wise Dense Flow for Image Classification
by Doyeob Yeo, Min-Suk Kim and Ji-Hoon Bae
Appl. Sci. 2021, 11(8), 3720; https://doi.org/10.3390/app11083720 - 20 Apr 2021
Cited by 2 | Viewed by 2182
Abstract
A deep-learning technology for knowledge transfer is necessary to advance and optimize efficient knowledge distillation. Here, we aim to develop a new adversarial optimization-based knowledge transfer method involved with a layer-wise dense flow that is distilled from a pre-trained deep neural network (DNN). [...] Read more.
A deep-learning technology for knowledge transfer is necessary to advance and optimize efficient knowledge distillation. Here, we aim to develop a new adversarial optimization-based knowledge transfer method involved with a layer-wise dense flow that is distilled from a pre-trained deep neural network (DNN). Knowledge distillation transferred to another target DNN based on adversarial loss functions has multiple flow-based knowledge items that are densely extracted by overlapping them from a pre-trained DNN to enhance the existing knowledge. We propose a semi-supervised learning-based knowledge transfer with multiple items of dense flow-based knowledge extracted from the pre-trained DNN. The proposed loss function would comprise a supervised cross-entropy loss for a typical classification, an adversarial training loss for the target DNN and discriminators, and Euclidean distance-based loss in terms of dense flow. For both pre-trained and target DNNs considered in this study, we adopt a residual network (ResNet) architecture. We propose methods of (1) the adversarial-based knowledge optimization, (2) the extended and flow-based knowledge transfer scheme, and (3) the combined layer-wise dense flow in an adversarial network. The results show that it provides higher accuracy performance in the improved target ResNet compared to the prior knowledge transfer methods. Full article
(This article belongs to the Special Issue Artificial Intelligence and Control Technology for Unmanned Transport Systems)
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<p>Adversarial-based knowledge transfer framework architecture.</p> Full article ">Figure 2
<p>Adversarial concurrent knowledge transfer structure using the layer-wise dense flow. In this figure, <math display="inline"><semantics> <msubsup> <mi>G</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> <mi>R</mi> </msubsup> </semantics></math>, <math display="inline"><semantics> <msubsup> <mi>G</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> <mi>T</mi> </msubsup> </semantics></math>, and <math display="inline"><semantics> <msub> <mi>D</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </semantics></math> refer to the FSP matrix of pre-trained ResNet, the FSP matrix of target ResNet, and the discriminator, respectively. Only the variables in the dotted box marked “Trainable Variables” are used for training.</p> Full article ">Figure 3
<p>Distributions of FSP matrices for the 32-layer pre-trained, 8-layer target, and original 8-layer ResNets without knowledge. In this figure, the blue, red, and yellow points denote the mean and variables of the FSP matrices for the pre-trained, target, and original ResNets, respectively.</p> Full article ">
15 pages, 3684 KiB  
Article
A Technique of Recursive Reliability-Based Missing Data Imputation for Collaborative Filtering
by Sun-Young Ihm, Shin-Eun Lee, Young-Ho Park, Aziz Nasridinov, Miyeon Kim and So-Hyun Park
Appl. Sci. 2021, 11(8), 3719; https://doi.org/10.3390/app11083719 - 20 Apr 2021
Cited by 5 | Viewed by 2419
Abstract
Collaborative filtering (CF) is a recommendation technique that analyzes the behavior of various users and recommends the items preferred by users with similar preferences. However, CF methods suffer from poor recommendation accuracy when the user preference data used in the recommendation process is [...] Read more.
Collaborative filtering (CF) is a recommendation technique that analyzes the behavior of various users and recommends the items preferred by users with similar preferences. However, CF methods suffer from poor recommendation accuracy when the user preference data used in the recommendation process is sparse. Data imputation can alleviate the data sparsity problem by substituting a virtual part of the missing user preferences. In this paper, we propose a k-recursive reliability-based imputation (k-RRI) that first selects data with high reliability and then recursively imputes data with additional selection while gradually lowering the reliability criterion. We also propose a new similarity measure that weights common interests and indifferences between users and items. The proposed method can overcome disregarding the importance of missing data and resolve the problem of poor data imputation of existing methods. The experimental results demonstrate that the proposed approach significantly improves recommendation accuracy compared to those resulting from the state-of-the-art methods while demanding less computational complexity. Full article
(This article belongs to the Collection The Development and Application of Fuzzy Logic)
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<p>An example of user similarity matrix of k-RRI.</p> Full article ">Figure 2
<p>An example of item similarity matrix of k-RRI.</p> Full article ">Figure 3
<p>An example of missing data imputation of k-RRI.</p> Full article ">Figure 4
<p>An example of missing data imputation of k-RRI (step 2).</p> Full article ">Figure 5
<p>An example of missing data imputation of k-RRI (step 3).</p> Full article ">Figure 6
<p>The prediction accuracy of missing data imputation algorithms.</p> Full article ">Figure 7
<p>The prediction accuracy of k-RRI as number of k values varies.</p> Full article ">
16 pages, 3492 KiB  
Article
Sustained Antibacterial Effect and Wear Behavior of Quaternary Ammonium Contact-Killing Dental Polymers after One-Year of Hydrolytic Degradation
by Abdulrahman A. Balhaddad, Lamia S. Mokeem, Michael D. Weir, Huakun Xu and Mary Anne S. Melo
Appl. Sci. 2021, 11(8), 3718; https://doi.org/10.3390/app11083718 - 20 Apr 2021
Cited by 7 | Viewed by 3028
Abstract
This study intended to investigate the long-term antibacterial effect, mechanical performance, and surface topography of new anticaries dental composites. While most artificial aging studies of dental resins lasted for 30–90 days, this study prolonged the water-aging to one year to be more clinically [...] Read more.
This study intended to investigate the long-term antibacterial effect, mechanical performance, and surface topography of new anticaries dental composites. While most artificial aging studies of dental resins lasted for 30–90 days, this study prolonged the water-aging to one year to be more clinically relevant. The base resin was loaded with dimethylaminohexadecyl methacrylate (DMAHDM) at 3 or 5 wt.% and nano-sized amorphous calcium phosphate (NACP) at 20 wt.%. Composites were subjected to one-year water storage and wear. Following water aging, samples were evaluated for flexural strength, elastic modulus, and microbiological assays. Biofilm plate counting method, metabolic assay, colorimetric quantification of lactic acid, and Baclight bacterial viability assay were measured after one year. Topography changes (ΔRa, ΔRq, ΔRv, ΔRt) were examined after wear and observed by scanning electron microscopy. Biofilm assays and topography changes data were analyzed via one-way ANOVA and Tukey’s tests. Mechanical properties and normalized data were verified using a t-test. The flexural strength values for the formulations that contained 5% DMAHDM-20% NACP, 3% DMAHDM, and 5% DMAHDM were reduced significantly (p < 0.05) in relation to the baseline but the values were still above the ISO standards. No significant differences were observed between the groups concerning the topography changes, except for the ΔRt, where there was a significant increase in the 5% DMAHDM-20% NACP group. All the groups demonstrated robust biofilm-inhibition, with slightly reduced antibacterial properties following water aging. The aged samples reduced the total microorganisms, total streptococci, and mutans streptococci by 1.5 to 3-log, compared to the experimental control. The new formulations containing DMAHDM and NACP were able to sustain the antibacterial performance after one-year of aging. Mechanical properties and surface topography were slightly affected over time. Full article
(This article belongs to the Special Issue 10th Anniversary of Applied Sciences: Invited Papers in Applied Dentistry Section)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Flowchart of the experimental design proposed in this study. Different antibacterial formulations were designed. Following the aging, the mechanical properties were assessed via flexural strength, elastic modulus, and measurements of the topography changes following simulated wear. The antibacterial activity was analyzed by biofilm plate counting method, metabolic assay, colorimetric quantification of lactic acid, and Baclight <sup>®</sup> bacterial viability assay.</p> Full article ">Figure 2
<p>(<b>A</b>) The flexural strength values (mean ± SD; n = 6) of different composite formulations at baseline and after aging. (<b>B</b>) The elastic modulus values (mean ± SD; n = 6) in different composite formulations after aging and at baseline. * Asterisks indicate significant differences compared to baseline values before aging.</p> Full article ">Figure 3
<p>Colony-forming unit (CFU) counts of the (<b>A</b>) total microorganisms, (<b>B</b>) total streptococci, and (<b>C</b>) <span class="html-italic">mutans streptococci</span> on the composite surface (mean ± SD; n = 9). Different letters indicate significant differences between groups (<span class="html-italic">p</span> &lt; 0.05). The difference in the log reduction between the baseline and aged samples concerning the (<b>D</b>) total microorganisms, (<b>E</b>) total streptococci, and (<b>F</b>) <span class="html-italic">mutans streptococci</span> is illustrated. * Asterisks indicate significant differences compared to baseline values before aging. (EC = experimental control; 3D = 3% DMAHDM; 5D = 5% DMAHDM; 3DN = 3% DMAHDM-20% NACP; 5DN = 5% DMAHDM-20% NACP).</p> Full article ">Figure 4
<p>(<b>A</b>) The metabolic activities and (<b>C</b>) lactic acid production of the biofilms grown over the baseline and aged samples (mean ± SD; n = 9). Different letters indicate significant differences between groups (<span class="html-italic">p</span> &lt; 0.05). The normalized data of the (<b>B</b>) metabolic activities and (<b>D</b>) lactic acid reduction in percentage. * Asterisks indicate significant differences compared to baseline values before aging. (EC = experimental control; 3D = 3% DMAHDM; 5D = 5% DMAHDM; 3DN = 3% DMAHDM-20% NACP; 5DN = 5% DMAHDM-20% NACP).</p> Full article ">Figure 5
<p>The live/dead images for the biofilms formed over the composites’ surface (n = 3). (<b>A</b>) A schematic drawing showing the accumulation of the biofilm over the composite surface. Live bacteria were stained green, and compromised bacteria were stained red. The higher amount of viable microorganisms was associated with the experimental control group (<b>B</b>), followed by the 3% and 5% DMAHDM (<b>C</b>,<b>D</b>). The minimum load of viable bacteria was observed over the DMAHDM-NACP groups (<b>E</b>,<b>F</b>).</p> Full article ">Figure 6
<p>Scanning electron microscopy showing the topography changes on the composites’ surfaces following the simulated wear at ×100, ×500, and ×1000 magnification.</p> Full article ">
40 pages, 2621 KiB  
Review
Selenium-Containing Polysaccharides—Structural Diversity, Biosynthesis, Chemical Modifications and Biological Activity
by Sandra Górska, Anna Maksymiuk and Jadwiga Turło
Appl. Sci. 2021, 11(8), 3717; https://doi.org/10.3390/app11083717 - 20 Apr 2021
Cited by 27 | Viewed by 5898
Abstract
Selenosugars are a group of sugar derivatives of great structural diversity (e.g., molar masses, selenium oxidation state, and selenium binding), obtained as a result of biosynthesis, chemical modification of natural compounds, or chemical synthesis. Seleno-monosaccharides and disaccharides are known to be non-toxic products [...] Read more.
Selenosugars are a group of sugar derivatives of great structural diversity (e.g., molar masses, selenium oxidation state, and selenium binding), obtained as a result of biosynthesis, chemical modification of natural compounds, or chemical synthesis. Seleno-monosaccharides and disaccharides are known to be non-toxic products of the natural metabolism of selenium compounds in mammals. In the case of the selenium-containing polysaccharides of natural origin, their formation is also postulated as a form of detoxification of excess selenium in microorganisms, mushroom, and plants. The valency of selenium in selenium-containing polysaccharides can be: 0 (encapsulated nano-selenium), IV (selenites of polysaccharides), or II (selenoglycosides or selenium built into the sugar ring to replace oxygen). The great interest in Se-polysaccharides results from the expected synergy between selenium and polysaccharides. Several plant- and mushroom-derived polysaccharides are potent macromolecules with antitumor, immunomodulatory, antioxidant, and other biological properties. Selenium, a trace element of fundamental importance to human health, has been shown to possess several analogous functions. The mechanism by which selenium exerts anticancer and immunomodulatory activity differs from that of polysaccharide fractions, but a similar pharmacological effect suggests a possible synergy of these two agents. Various functions of Se-polysaccharides have been explored, including antitumor, immune-enhancement, antioxidant, antidiabetic, anti-inflammatory, hepatoprotective, and neuroprotective activities. Due to being non-toxic or much less toxic than inorganic selenium compounds, Se-polysaccharides are potential dietary supplements that could be used, e.g., in chemoprevention. Full article
(This article belongs to the Special Issue Polysaccharides: From Extraction to Applications)
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<p>Structures of the trahydroselenophene (<b>a</b>), selenane (<b>b</b>), and some derivates: 1,4-anhydro-4-seleno-hexofuranose (1,4-anhydro-4-seleno-D-talitol) (<b>c</b>) and 1,5-anhydro-5-seleno-hexopyranose (1,5-anhydro-5-seleno-D-mannitol) (<b>d</b>).</p> Full article ">Figure 2
<p>Se-alkyl-selenoglucoside in protected (<b>a</b>) and deprotected (<b>b</b>) form.</p> Full article ">Figure 3
<p>The application of selenoglycosides in polysaccharide synthesis. Bz—benzoyl group: C<sub>6</sub>H<sub>5</sub>C(O)-; Ac—acetyl group: CH<sub>3</sub>C(O)-.</p> Full article ">Figure 4
<p>An example of a structure of the protected selenodisaccharide (Gal<span class="html-italic">p</span>α(1→4)Gal<span class="html-italic">p</span>) synthesized by Nanami et al. [<a href="#B239-applsci-11-03717" class="html-bibr">239</a>]. SE-2-(trimethylsilyl)ethyl-group, Tf-trifluoromethanesulfonyl-(triflyl-) group.</p> Full article ">Figure 5
<p>Three selenoglycosides detected as urinary selenium metabolites within the required to low-toxic range: (<b>a</b>) 1β-methylseleno-<span class="html-italic">N</span>-acetyl-D-galactosamine, (<b>b</b>) 1β-methylseleno-D-galactosamine, and (<b>c</b>) 1β-methylseleno-<span class="html-italic">N</span>-acetyl-D-glucosamine.</p> Full article ">Figure 6
<p>Hepatic metabolite A.</p> Full article ">Figure 7
<p>Examples of the alkylselenide structures derived from pyranose (<b>a</b>) and furanose (<b>b</b>), synthesized by Vargas et. al. [<a href="#B242-applsci-11-03717" class="html-bibr">242</a>].</p> Full article ">Figure 8
<p>Formation of the selenious acid ester of carbohydrate.</p> Full article ">Figure 9
<p>The hypothetical local structures around Se in Se-polysaccharide [<a href="#B39-applsci-11-03717" class="html-bibr">39</a>]: (<b>a</b>) 1,3-Se-β-D-glycosidic bond in glucan chain, (<b>b</b>) 1,4-Se-α-D-glycosidic bond in mannan chain, and (<b>c</b>) Se in glucopyranose ring.</p> Full article ">Figure 10
<p>Theoretical structure of the polyglucopyranose with three hydroxyl groups per monomer acylated by selenious acid (DS = 3).</p> Full article ">Figure 11
<p>The proposed linear (<b>a</b>) and cyclic (<b>b</b>) structures of selenodextran (according to Huang et al. [<a href="#B345-applsci-11-03717" class="html-bibr">345</a>]).</p> Full article ">
16 pages, 4181 KiB  
Article
Research on O-ring Dimension Measurement Algorithm Based on Cubic Spline Interpolation
by Hu Haibing, Xipeng Zheng, Jiajie Yin and Yueyan Wang
Appl. Sci. 2021, 11(8), 3716; https://doi.org/10.3390/app11083716 - 20 Apr 2021
Cited by 9 | Viewed by 2431
Abstract
Current O-ring dimension measurement algorithms based on machine vision are mainly whole-pixel level algorithms, which have the disadvantage of a low measurement accuracy. In order to improve the stability and accuracy of O-ring dimension measurement, a sub-pixel edge detection algorithm based on cubic [...] Read more.
Current O-ring dimension measurement algorithms based on machine vision are mainly whole-pixel level algorithms, which have the disadvantage of a low measurement accuracy. In order to improve the stability and accuracy of O-ring dimension measurement, a sub-pixel edge detection algorithm based on cubic spline interpolation is proposed for O-ring dimension measurement. After image pre-processing of the O-ring graphics, the whole-pixel-level O-ring edges are obtained by using a noise-resistant mathematical morphology method, and then the sub-pixel edge contours are obtained using a sub-pixel edge detection algorithm based on cubic spline interpolation. Finally, the edge curve is fitted with the least squares method to obtain its inner and outer diameter as well as the size of the wire diameter. The experimental data show that the algorithm has a mean square error of 4.8 μm for the outer diameter and 0.18 μm for the wire diameter. The outer diameter error is kept within ±100 μm and the wire diameter error can be kept within ±15 μm. Compared with the whole pixel algorithm, the measurement accuracy has been greatly improved. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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<p>Physical structure of image acquisition system.</p> Full article ">Figure 2
<p>Schematic diagram of four-direction structural elements. (<b>a</b>) the unit matrix; (<b>b</b>) the matrix with 0 except the second column as 1; (<b>c</b>) the matrix with 0 except the second row as 1; (<b>d</b>) the sub-diagonal matrix as 1 and the rest as 0.</p> Full article ">Figure 3
<p>Comparison of noise-resistant mathematical morphological edge detection algorithm and whole-pixel edge detection algorithm. (<b>a</b>) Original image; (<b>b</b>) noise-resistant mathematical morphology edge detection results; (<b>c</b>) the Sobel operator edge detection result; (<b>d</b>) plot of the edge detection results of the Canny operator.</p> Full article ">Figure 4
<p>Schematic diagram of gradient direction.</p> Full article ">Figure 5
<p>Algorithm flow.</p> Full article ">Figure 6
<p>Grayscale values of pixels in each gradient direction.</p> Full article ">Figure 7
<p>Image of a triple spline interpolation function and its first-order and second-order derivatives.</p> Full article ">Figure 8
<p>O-ring sub-pixel edge point.</p> Full article ">Figure 9
<p>O-ring inner and outer circle fitting diagram. (<b>a</b>) Fitting of the O-ring outer diameter circle; (<b>b</b>) fitting of inner diameter circle of the O-ring.</p> Full article ">Figure 10
<p>Images of the 17-mm standard gauge block.</p> Full article ">Figure 11
<p>Graph of measurement results. (<b>a</b>) Comparison of outside diameter measurement values; (<b>b</b>) comparison of wire diameter measurement values.</p> Full article ">Figure 12
<p>Error analysis chart. (<b>a</b>) Comparison chart of outside diameter measurement error; (<b>b</b>) comparison chart of wire diameter measurement error.</p> Full article ">
16 pages, 16032 KiB  
Article
Detoxified Spent Pot Lining from Aluminum Production as (Alumino-)Silicate Source for Composite Cement and AutoClaved Aerated Concrete
by Arne Peys, Mateja Košir, Ruben Snellings, Ana Mladenovič and Liesbeth Horckmans
Appl. Sci. 2021, 11(8), 3715; https://doi.org/10.3390/app11083715 - 20 Apr 2021
Cited by 7 | Viewed by 3645
Abstract
New sources of supplementary cementitious materials (SCMs) are needed to meet the future demand. A potential new source of SCM is spent pot lining, a residue from aluminum production. The present work showed that the refined aluminosilicate part of spent pot lining (SPL) [...] Read more.
New sources of supplementary cementitious materials (SCMs) are needed to meet the future demand. A potential new source of SCM is spent pot lining, a residue from aluminum production. The present work showed that the refined aluminosilicate part of spent pot lining (SPL) has a moderate chemical reactivity in a cementitious system measured in the R3 calorimetry test, comparable to commercially used coal fly ash. The reaction of SPL led to the consumption of Ca(OH)2 in a cement paste beyond 7 days after mixing. At 28 and 90 days a significant contribution to strength development was therefore observed, reaching a relative strength, which is similar to composite cements with coal fly ash. At early age a retardation of the cement hydration is caused by the SPL, which should most likely be associated with the presence of trace amounts of NH3. The spent pot lining is also investigated as silica source for autoclaved aerated concrete blocks. The replacement of quartz by spent pot lining did not show an adverse effect on the strength-density relation of the lightweight blocks up to 50 wt% quartz substitution. Overall, spent pot lining can be used in small replacement volumes (30 wt%) as SCM or as replacement of quartz (50 wt%) in autoclaved aerated concrete blocks. Full article
(This article belongs to the Special Issue Eco-Performance of Alternative Binder Systems)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>X-ray diffractogram of the spent pot lining aluminosilicates.</p> Full article ">Figure 2
<p>Backscattered electron images obtained from electron microscopy on embedded polished powder of the spent pot lining aluminosilicates. Phases that could be recognized are indicated: Am = amorphous, Qtz = quartz, He = hematite. Image (<b>a</b>) and (<b>b</b>) are two example images from the same sample.</p> Full article ">Figure 3
<p>Elemental maps of the major elements in spent pot lining aluminosilicates obtained from energy dispersive X-ray spectroscopy measurements: (<b>a</b>) Si, (<b>b</b>) Al, (<b>c</b>) Na and (<b>d</b>) Fe. Note that these measurements were performed on image (<b>b</b>) in <a href="#applsci-11-03715-f002" class="html-fig">Figure 2</a>.</p> Full article ">Figure 4
<p>R3 heat release of the spent pot lining aluminosilicates determined using isothermal calorimetry compared to class F coal fly ashes as reference. Data for coal fly ashes was obtained from Snellings et al. [<a href="#B32-applsci-11-03715" class="html-bibr">32</a>].</p> Full article ">Figure 5
<p>Heat flow (<b>a</b>) and cumulative heat (<b>b</b>) during isothermal calorimetry measurements. A measurement using 30 wt% spent pot lining aluminosilicates (70 wt% CEM I) is compared to references composed of 100% CEM I and 70 wt% CEM I with 30 wt% fine quartz filler.</p> Full article ">Figure 6
<p>X-ray diffractogram of the hydrated pastes including 30 wt% of spent pot lining aluminosilicates. The hydrates are indicated and other peaks result from unreacted SPL.</p> Full article ">Figure 7
<p>Detailed image of the Portlandite peak in the X-ray diffractograms of hydrated pastes including 30 wt% of quartz filler and 30 wt% of spent pot lining aluminosilicates at (<b>a</b>) 7 and (<b>b</b>) 28 days.</p> Full article ">Figure 8
<p>Pore volume distribution (<b>a</b>) and total porosity (<b>b</b>) obtained from mercury intrusion porosimetry measurements. A measurement using 30 wt% SPL 2nd cut (70 wt% CEM I) is compared to a reference composed of 70 wt% CEM I with 30 wt% fine quartz filler.</p> Full article ">Figure 9
<p>Compressive strength evolution of mortars using several replacement levels of spent pot lining aluminosilicates (SPL) as supplementary cementitious material (<b>a</b>). The influence of the addition of limestone (L) to mixtures with 30 wt% of SPL is shown in (<b>b</b>).</p> Full article ">Figure 10
<p>Compressive strength evolution of mortars with 30 wt% spent pot lining aluminosilicates (SPL) as supplementary cementitious material, including 90 days strength (<b>a</b>). The relative strength is calculated and compared to the replacement level (<b>b</b>). The replacement level is represented by a dotted line as a visual aid (in green for 30 wt% replacement—70% strength and in red for 30 + 15 wt% replacement—55% strength).</p> Full article ">Figure 11
<p>Density of the AAC blocks using several replacement levels of quartz for SPL aluminosilicates after drying at 40 °C.</p> Full article ">Figure 12
<p>Compressive strength of the AAC blocks using several replacement levels of quartz for SPL aluminosilicates.</p> Full article ">Figure 13
<p>Strength-density relation of the AAC blocks compared to the density classes defined in EN 771-4 and to data from references.</p> Full article ">
20 pages, 8790 KiB  
Article
Straight Gait Research of a Small Electric Hexapod Robot
by Feng Zhang, Shidong Zhang, Qian Wang, Yujie Yang and Bo Jin
Appl. Sci. 2021, 11(8), 3714; https://doi.org/10.3390/app11083714 - 20 Apr 2021
Cited by 8 | Viewed by 2508
Abstract
Gait is an important research content of hexapod robots. To better improve the motion performance of hexapod robots, many researchers have adopted some high-cost sensors or complex gait control algorithms. This paper studies the straight gait of a small electric hexapod robot with [...] Read more.
Gait is an important research content of hexapod robots. To better improve the motion performance of hexapod robots, many researchers have adopted some high-cost sensors or complex gait control algorithms. This paper studies the straight gait of a small electric hexapod robot with a low cost, which can be used in daily life. The strategy of “increasing duty factor” is put forward in the gait planning, which aims to reduce foot sliding and attitude fluctuation in robot motion. The straight gaits of the robot include tripod gait, quadrangular gait, and pentagonal gait, which can be described conveniently by discretization and a time sequence diagram. In order to facilitate the user to control the robot to achieve all kinds of motion, an online gait transformation algorithm based on the adjustment of foot positions is proposed. In addition, according to the feedback of the actual attitude information, a yaw angle correction algorithm based on kinematics analysis and PD controller is designed to reduce the motion error of the robot. The experiments show that the designed gait planning scheme and control algorithm are effective, and the robot can achieve the expected motion. The RMSE of the row, pitch, and yaw angle was reduced by 35%, 25%, and 12%, respectively, using the “increasing duty factor” strategy, and the yaw angle was limited in the range −3°~3° using the yaw angle correction algorithm. Finally, the comparison with related works and the limitations are discussed. Full article
(This article belongs to the Section Robotics and Automation)
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<p>Picture of HexWalker II.</p> Full article ">Figure 2
<p>Main contents of the motion control algorithm.</p> Full article ">Figure 3
<p>D–H coordinate frames of HexWalker II.</p> Full article ">Figure 4
<p>Foot trajectory relative to {<span class="html-italic">O<sub>iB</sub></span>}: (<b>a</b>) Position variations in the X and Z directions; (<b>b</b>) Foot trajectory in the XZ plane.</p> Full article ">Figure 5
<p>Time sequence diagram of the robot walking forward in tripod gait: (<b>a</b>) The general tripod gait; (<b>b</b>) The tripod gait with “increasing duty factor”; (<b>c</b>) The quadrangular gait with “increasing duty factor”; (<b>d</b>) The pentagonal gait with “increasing duty factor”.</p> Full article ">Figure 6
<p>Discretization of foot positions on the ground.</p> Full article ">Figure 7
<p>Walking forward using tripod gait.</p> Full article ">Figure 8
<p>Flow chart of gait transformation.</p> Full article ">Figure 9
<p>Kinematic model of yaw angle correction in straight gait.</p> Full article ">Figure 10
<p>Flow chart of hexapod robot yaw angle correction algorithm.</p> Full article ">Figure 11
<p>Controller design of hexapod robot yaw angle correction algorithm.</p> Full article ">Figure 12
<p>The experiment of HexWalker II walking forward using tripod gait: (<b>a</b>) Leg 2, leg 3, and leg 6 are swinging; (<b>b</b>) Leg 1, leg 4, and leg 5 are swinging; (<b>c</b>) Leg 2, leg 3, and leg 6 are swinging.</p> Full article ">Figure 13
<p>Comparison between the ideal foot trajectory and the actual foot trajectory of leg 1 in tripod gait.</p> Full article ">Figure 14
<p>Attitude variations in tripod gait (no correction).</p> Full article ">Figure 15
<p>Comparison of ideal foot trajectory in Y direction of leg 1 with and without correction.</p> Full article ">Figure 16
<p>Attitude variations in tripod gait (with correction).</p> Full article ">Figure 17
<p>Attitude variations in tripod gait (without the strategy of “increasing duty factor”).</p> Full article ">Figure 18
<p>Comparison between the ideal foot trajectory and the actual foot trajectory of leg 1~3 in the experiment of gait transformation.</p> Full article ">Figure 19
<p>Attitude variations in the experiment of gait transformation.</p> Full article ">
17 pages, 4009 KiB  
Article
Verification and Optimization of an Ultra-Low Volume (ULV) Sprayer Used for the Inactivation of Indoor Total Bacteria
by Yun-Hee Choi, Da-An Huh, Ju-Yeon Lee, Ji Yoon Choi and Kyong Whan Moon
Appl. Sci. 2021, 11(8), 3713; https://doi.org/10.3390/app11083713 - 20 Apr 2021
Cited by 5 | Viewed by 2655
Abstract
Physical and chemical cleaning for the removal of indoor microorganisms, which can cause allergic reactions and respiratory diseases, is labor-intensive and time-consuming. An ultra-low volume (ULV) sprayer, a newly introduced device to inactivate pathogenic microorganisms, allows the disinfectant particles to reach hard-to-reach spaces [...] Read more.
Physical and chemical cleaning for the removal of indoor microorganisms, which can cause allergic reactions and respiratory diseases, is labor-intensive and time-consuming. An ultra-low volume (ULV) sprayer, a newly introduced device to inactivate pathogenic microorganisms, allows the disinfectant particles to reach hard-to-reach spaces indoors and is more cost-effective than the existing methods. However, few studies have been conducted to verify the efficiency of the ULV sprayer. Here, we verified the disinfection efficiency of the ULV sprayer for inactivating total bacteria present on indoor surfaces, considering the factors affecting bacteria inactivation, and presented the optimal ULV sprayer usage conditions to achieve the highest disinfection efficiency depending on room size. The total bacteria removal efficiency was high (range: 0.56–2.46 log10 reductions), including hard-to-reach spaces. A response surface model was developed to identify the individual and interactive effects of the disinfectant concentration, spray amount, and room size on total bacteria disinfection efficiency. These three variables had interactive effects on the total bacteria disinfection efficiency. The experimental data were fitted to a second-order polynomial model, with high coefficients of determination (R2) for all models (R2 > 0.82). The optimum conditions were a spray amount of 3.08–6.40 L in 160 m3, 3.78–7.22 L in 230 m3, and 5.68–8 L in 300 m3 surface area when using dilution rates of 100 times. These conditions predicted a bacterial disinfection efficiency of >1.10 log10 reductions (92%) on all surfaces. Our results clearly indicate that the ULV sprayer effectively inactivates total bacteria present on indoor surfaces. Full article
(This article belongs to the Section Environmental Sciences)
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<p>The ULV sprayer DH-FOG30′s picture and specification.</p> Full article ">Figure 2
<p>Flow-chart of the experiments.</p> Full article ">Figure 3
<p>Schematic diagram of locations where total bacteria was seeded in the classroom.</p> Full article ">Figure 4
<p>Variation of three different sizes of PM fractions after spraying with ULV sprayer: (<b>a</b>) variation of PM<sub>10</sub>, PM<sub>2.5</sub>, and PM<sub>1.0</sub> after dispensing using a ULV sprayer when the spray amount was 2 L in 230 m<sup>3</sup>, (<b>b</b>) variation of PM<sub>10</sub>, PM<sub>2.5</sub>, and PM<sub>1.0</sub> after dispensing using a ULV sprayer when the spray amount was 5 L in 230 m<sup>3</sup>, and (<b>c</b>) variation of PM<sub>10</sub>, PM<sub>2.5</sub>, and PM<sub>1.0</sub> after dispensing using a ULV sprayer when the spray amount was 8 L in 230 m<sup>3</sup>.</p> Full article ">Figure 5
<p>Disinfection efficiency (log<sub>10</sub> units) of total bacteria on indoor surfaces by locations and time after spraying.</p> Full article ">Figure 6
<p>Response surface plots presenting the interaction effects of three variables on the average total bacteria disinfection efficiency: (<b>a</b>) surface plot showing the effect of disinfectant concentration and spray amount on the average disinfection efficiency, (<b>b</b>) surface plot showing the effect of disinfectant concentration and room size on the average disinfection efficiency, and (<b>c</b>) surface plot showing the effect of spray amount and room size on the average disinfection efficiency.</p> Full article ">Figure 7
<p>Overlay plot of the disinfectant concentration and spray amount on the disinfection efficiency at each point when the room size is 160 m<sup>3</sup>.</p> Full article ">Figure 8
<p>Overlay plot of the disinfectant concentration and spray amount on the disinfection efficiency at each point when the room size is 230 m<sup>3</sup>.</p> Full article ">Figure 9
<p>Overlay plot of the disinfectant concentration and spray amount on the disinfection efficiency at each point when the room size is 300 m<sup>3</sup>.</p> Full article ">
18 pages, 1610 KiB  
Review
Haptic-Enabled Hand Rehabilitation in Stroke Patients: A Scoping Review
by Mohamed-Amine Choukou, Sophia Mbabaali, Jasem Bani Hani and Carol Cooke
Appl. Sci. 2021, 11(8), 3712; https://doi.org/10.3390/app11083712 - 20 Apr 2021
Cited by 13 | Viewed by 6073
Abstract
There is a plethora of technology-assisted interventions for hand therapy, however, less is known about the effectiveness of these interventions. This scoping review aims to explore studies about technology-assisted interventions targeting hand rehabilitation to identify the most effective interventions. It is expected that [...] Read more.
There is a plethora of technology-assisted interventions for hand therapy, however, less is known about the effectiveness of these interventions. This scoping review aims to explore studies about technology-assisted interventions targeting hand rehabilitation to identify the most effective interventions. It is expected that multifaceted interventions targeting hand rehabilitation are more efficient therapeutic approaches than mono-interventions. The scoping review will aim to map the existing haptic-enabled interventions for upper limb rehabilitation and investigates their effects on motor and functional recovery in patients with stroke. The methodology used in this review is based on the Arksey and O’Malley framework, which includes the following stages: identifying the research question, identifying relevant studies, study selection, charting the data, and collating, summarizing, and reporting the results. Results show that using three or four different technologies was more positive than using two technologies (one technology + haptics). In particular, when standardized as a percentage of outcomes, the combination of three technologies showed better results than the combination of haptics with one technology or with three other technologies. To conclude, this study portrayed haptic-enabled rehabilitation approaches that could help therapists decide which technology-enabled hand therapy approach is best suited to their needs. Those seeking to undertake research and development anticipate further opportunities to develop haptic-enabled hand telerehabilitation platforms. Full article
(This article belongs to the Special Issue Advances in Technological Rehabilitation)
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<p>Study selection process [<a href="#B50-applsci-11-03712" class="html-bibr">50</a>].</p> Full article ">Figure 2
<p>Frequency of publication per year.</p> Full article ">Figure 3
<p>(<b>a</b>–<b>d</b>) Characteristics of the interventions reported in the included articles.</p> Full article ">Figure 4
<p>Combinations of hand rehabilitation technologies.</p> Full article ">Figure 5
<p>Outcomes according to number of technologies involved.</p> Full article ">Figure 6
<p>Outcomes classified according to intervention modality and the ICF framework components and domain according to intervention modality.</p> Full article ">
20 pages, 21295 KiB  
Article
Time Travel to the Past of Bosnia and Herzegovina through Virtual and Augmented Reality
by Selma Rizvić, Dušanka Bošković, Vensada Okanović, Ivona Ivković Kihić, Irfan Prazina and Bojan Mijatović
Appl. Sci. 2021, 11(8), 3711; https://doi.org/10.3390/app11083711 - 20 Apr 2021
Cited by 10 | Viewed by 4677
Abstract
Bosnia and Herzegovina (BH) has a very picturesque past. Founded in 11th century, it has always been a crossroads of faiths and civilizations. Extended Reality (XR) technologies can finally take us to time travel into this history, enable us to experience past events [...] Read more.
Bosnia and Herzegovina (BH) has a very picturesque past. Founded in 11th century, it has always been a crossroads of faiths and civilizations. Extended Reality (XR) technologies can finally take us to time travel into this history, enable us to experience past events and meet historical characters. In this paper, we overview the latest applications we developed that use Virtual Reality (VR) video, Virtual and Augmented Reality (AR) for interactive digital storytelling about BH history. “Nine dissidents” is the first BH VR documentary, tackling a still tricky subject of dissidents in the Socialist Yugoslavia, artists and writers falsely accused, persecuted and still forbidden. “Virtual Museum of Old Crafts” aims to present and preserve crafts intangible heritage through Virtual Reality. “Battle on Neretva VR” is recreating a famous WWII battle offering the users to experience it and meet comrade Tito, the commander of the Yugoslav Liberation Army. “Sarajevo 5D” shows the cultural monuments from Sarajevo that do not exist anymore in physical form using Augmented Reality. Through user experience studies, we measure the user immersion and edutainment of these applications and show the potential of XR for the presentation and preservation of cultural heritage. Full article
(This article belongs to the Special Issue Extended Reality: From Theory to Applications)
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<p>Nine dissidents project workflow.</p> Full article ">Figure 2
<p>Nine dissidents—gameplay video screen shot.</p> Full article ">Figure 3
<p>Old Crafts Virtual Museum application structure.</p> Full article ">Figure 4
<p>Old crafts Virtual Museum production workflow.</p> Full article ">Figure 5
<p>Posters for craftsmens’ windows.</p> Full article ">Figure 6
<p>Battle on Neretva application structure.</p> Full article ">Figure 7
<p>Battle on Neretva application workflow.</p> Full article ">Figure 8
<p>Tašlihan AR model.</p> Full article ">Figure 9
<p>The map with AR trackers—Sarajevo5D project.</p> Full article ">Figure 10
<p>Sarajevo 5D application structure.</p> Full article ">Figure 11
<p>Sarajevo5D application workflow.</p> Full article ">Figure 12
<p>Word cloud illustrating the frequency of words used to describe feelings after viewing the VR movie “Nine Dissidents”.</p> Full article ">Figure 13
<p>Distribution of responses across each item Constructs: Effort Expectancy (EE): Easy of Use.</p> Full article ">Figure 14
<p>Distribution of responses across each item Constructs: Performance Expectancy (PE): Edutainment and Immersion.</p> Full article ">
22 pages, 3289 KiB  
Article
Intelligent Scheduling with Reinforcement Learning
by Bruno Cunha, Ana Madureira, Benjamim Fonseca and João Matos
Appl. Sci. 2021, 11(8), 3710; https://doi.org/10.3390/app11083710 - 20 Apr 2021
Cited by 15 | Viewed by 5692
Abstract
In this paper, we present and discuss an innovative approach to solve Job Shop scheduling problems based on machine learning techniques. Traditionally, when choosing how to solve Job Shop scheduling problems, there are two main options: either use an efficient heuristic that provides [...] Read more.
In this paper, we present and discuss an innovative approach to solve Job Shop scheduling problems based on machine learning techniques. Traditionally, when choosing how to solve Job Shop scheduling problems, there are two main options: either use an efficient heuristic that provides a solution quickly, or use classic optimization approaches (e.g., metaheuristics) that take more time but will output better solutions, closer to their optimal value. In this work, we aim to create a novel architecture that incorporates reinforcement learning into scheduling systems in order to improve their overall performance and overcome the limitations that current approaches present. It is also intended to investigate the development of a learning environment for reinforcement learning agents to be able to solve the Job Shop scheduling problem. The reported experimental results and the conducted statistical analysis conclude about the benefits of using an intelligent agent created with reinforcement learning techniques. The main contribution of this work is proving that reinforcement learning has the potential to become the standard method whenever a solution is necessary quickly, since it solves any problem in very few seconds with high quality, approximate to the optimal methods. Full article
(This article belongs to the Collection Machine Learning in Computer Engineering Applications)
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<p>Representation of a <span class="html-italic">Job Shop</span> scheduling problem (based on Beirão proposal [<a href="#B15-applsci-11-03710" class="html-bibr">15</a>]).</p> Full article ">Figure 2
<p>Diagram illustrating the principal activities of each phase.</p> Full article ">Figure 3
<p>Diagram of the developed system (adapted from our previous proposal [<a href="#B50-applsci-11-03710" class="html-bibr">50</a>]).</p> Full article ">Figure 4
<p>Boxplot of the runtime, in seconds (scientific notation), of algorithms: LPT, SPT, CUN, Peng and Zhang.</p> Full article ">Figure 5
<p>Runtime, in seconds (scientific notation), for each problem (TAI1-TAI50).</p> Full article ">Figure 6
<p>Makespan for <span class="html-italic">LPT</span>, <span class="html-italic">SPT</span>, <span class="html-italic">CUN</span> and the optimal value for each instance.</p> Full article ">Figure 7
<p>Boxplot of the normalized makespan of the three methods.</p> Full article ">
27 pages, 7363 KiB  
Article
Towards Flexible Distribution Systems: Future Adaptive Management Schemes
by Hannu Laaksonen, Hosna Khajeh, Chethan Parthasarathy, Miadreza Shafie-khah and Nikos Hatziargyriou
Appl. Sci. 2021, 11(8), 3709; https://doi.org/10.3390/app11083709 - 20 Apr 2021
Cited by 22 | Viewed by 5158
Abstract
During the ongoing evolution of energy systems toward increasingly flexible, resilient, and digitalized distribution systems, many issues need to be developed. In general, a holistic multi-level systemic view is required on the future enabling technologies, control and management methods, operation and planning principles, [...] Read more.
During the ongoing evolution of energy systems toward increasingly flexible, resilient, and digitalized distribution systems, many issues need to be developed. In general, a holistic multi-level systemic view is required on the future enabling technologies, control and management methods, operation and planning principles, regulation as well as market and business models. Increasing integration of intermittent renewable generation and electric vehicles, as well as industry electrification during the evolution, requires a huge amount of flexibility services at multiple time scales and from different voltage levels, resources, and sectors. Active use of distribution network-connected flexible energy resources for flexibility services provision through new marketplaces will also be needed. Therefore, increased collaboration between system operators in operation and planning of the future power system will also become essential during the evolution. In addition, use of integrated cyber-secure, resilient, cost-efficient, and advanced communication technologies and solutions will be of key importance. This paper describes a potential three-stage evolution path toward fully flexible, resilient, and digitalized electricity distribution networks. A special focus of this paper is the evolution and development of adaptive control and management methods as well as compatible collaborative market schemes that can enable the improved provision of flexibility services by distribution network-connected flexible energy resources for local (distribution system operator) and system-wide (transmission system operator) needs. Full article
(This article belongs to the Special Issue Future Distribution Network Solutions)
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<p>Power system readiness level, PSRL evolution that requires simultaneous development and readiness of (i) technology/solutions, (ii) customer, (iii) regulation, and (iv) market and business models.</p> Full article ">Figure 2
<p>Future flexible and digitalized electricity distribution system.</p> Full article ">Figure 3
<p>Future adaptive control and management methods to increase flexibility availability for provision of services (see <a href="#applsci-11-03709-t001" class="html-table">Table 1</a>, <a href="#applsci-11-03709-t002" class="html-table">Table 2</a>, <a href="#applsci-11-03709-t003" class="html-table">Table 3</a>, <a href="#applsci-11-03709-t004" class="html-table">Table 4</a> and <a href="#applsci-11-03709-t005" class="html-table">Table 5</a>).</p> Full article ">Figure 4
<p>Real-time adaptive DER unit <span class="html-italic">QU</span>-droop-based on OLTC set value, OLTC setting value, location, and participation to rapid voltage control with (<b>a</b>) constants A and B [<a href="#B81-applsci-11-03709" class="html-bibr">81</a>] or (<b>b</b>) constant k (see <a href="#applsci-11-03709-t003" class="html-table">Table 3</a> and <a href="#applsci-11-03709-t004" class="html-table">Table 4</a>).</p> Full article ">Figure 5
<p>Real-time adaptive DER unit <span class="html-italic">QU</span>-droop based on OLTC set value, OLTC setting value, location, and participation on rapid voltage control, as well as participation on <span class="html-italic">PQ</span> flow management (see <a href="#applsci-11-03709-f004" class="html-fig">Figure 4</a> and <a href="#applsci-11-03709-t003" class="html-table">Table 3</a> and <a href="#applsci-11-03709-t004" class="html-table">Table 4</a>).</p> Full article ">Figure 6
<p>(<b>a</b>) Frequency adaptive DER unit <span class="html-italic">PU</span>-droop for a BESS during smaller and larger under and over-frequency situations and (<b>b</b>) Real-time smooth-frequency adaptive <span class="html-italic">PU</span>-droop without specific frequency and voltage limits for activation, e.g., for BESS unit [<a href="#B79-applsci-11-03709" class="html-bibr">79</a>] (see <a href="#applsci-11-03709-t003" class="html-table">Table 3</a> and <a href="#applsci-11-03709-t004" class="html-table">Table 4</a>).</p> Full article ">Figure 7
<p>Real-time HV/MV substation <span class="html-italic">PQ</span> flow-dependent OLTC setting value (kV) with Sundom Smart Grid <span class="html-italic">PQ</span> flow limits (see <a href="#applsci-11-03709-t005" class="html-table">Table 5</a> and <a href="#applsci-11-03709-f003" class="html-fig">Figure 3</a>).</p> Full article ">Figure 8
<p>DSO network-connected DER participation on the provision of TSO frequency control services at evolution stage 2 through different markets also considering the location and type of DER as well as possible DSO network congestions (see <a href="#applsci-11-03709-t001" class="html-table">Table 1</a>, <a href="#applsci-11-03709-t002" class="html-table">Table 2</a>, <a href="#applsci-11-03709-t003" class="html-table">Table 3</a>, <a href="#applsci-11-03709-t004" class="html-table">Table 4</a> and <a href="#applsci-11-03709-t005" class="html-table">Table 5</a> and <a href="#applsci-11-03709-f003" class="html-fig">Figure 3</a>).</p> Full article ">
17 pages, 5096 KiB  
Article
Characteristics of Warm Mix Asphalt Incorporating Coarse Steel Slag Aggregates
by Adham Mohammed Alnadish, Mohamad Yusri Aman, Herda Yati Binti Katman and Mohd Rasdan Ibrahim
Appl. Sci. 2021, 11(8), 3708; https://doi.org/10.3390/app11083708 - 20 Apr 2021
Cited by 7 | Viewed by 2785
Abstract
The major goal of sustainable practices is to preserve raw resources through the utilization of waste materials as an alternative to natural resources. Decreasing the temperature required to produce asphalt mixes contributes to environmental sustainability by reducing energy consumption and toxic emissions. In [...] Read more.
The major goal of sustainable practices is to preserve raw resources through the utilization of waste materials as an alternative to natural resources. Decreasing the temperature required to produce asphalt mixes contributes to environmental sustainability by reducing energy consumption and toxic emissions. In this study, warm mix asphalt incorporating coarse steel slag aggregates was investigated. Warm mix asphalt was produced at different temperatures lower than the control asphalt mixes (hot mix asphalt) by 10, 20, and 30 °C. The performances of the control and warm mix asphalt were assessed through laboratory tests examining stiffness modulus, dynamic creep, and moisture sensitivity. Furthermore, a response surface methodology (RSM) was conducted by means of DESIGN EXPERT 11 to develop prediction models for the performance of warm mix asphalt. The findings of this study illustrate that producing warm mix asphalt at a temperature 10 °C lower than that of hot mix asphalt exhibited the best results, compared to the other mixes. Additionally, the warm mix asphalt produced at 30 °C lower than the hot mix asphalt exhibited comparable performance to the hot mix asphalt. However, as the production temperature increases, the performance of the warm mix asphalt improves. Full article
(This article belongs to the Special Issue Advances in Asphalt Pavement Technologies and Practices)
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<p>LEADCAP additive.</p> Full article ">Figure 2
<p>Laboratory tests: (<b>a</b>) stiffness modulus (<b>b</b>) dynamic creep; (<b>c</b>) Indirect tensile strength.</p> Full article ">Figure 3
<p>Stiffness modulus and the standard error bars of the mixes at 25 °C.</p> Full article ">Figure 4
<p>Stiffness modulus and the standard error bars of the mixes at 40 °C.</p> Full article ">Figure 5
<p>Accumulated strain and the standard error bars of the asphalt mixtures.</p> Full article ">Figure 6
<p>Indirect tensile strength and the standard error bars of the asphalt mixes.</p> Full article ">Figure 7
<p>Tensile strength ratio and the standard error bars of the mixes.</p> Full article ">Figure 8
<p>Plot of normality of 2FI model.</p> Full article ">Figure 9
<p>Plot of actual versus predicted values of the 2FI model.</p> Full article ">Figure 10
<p>Plot of the interaction between the factors and the response of the 2FI model.</p> Full article ">Figure 11
<p>Plot of the normal probability of the linear model.</p> Full article ">Figure 12
<p>Plot of the externally residuals versus predicted values of the linear model.</p> Full article ">Figure 13
<p>Plot of the externally residuals versus run number of the linear model.</p> Full article ">Figure 14
<p>Plot of the actual versus predicted values of the linear model.</p> Full article ">Figure 15
<p>Plot of the interaction between the factors and the response of the linear model.</p> Full article ">
15 pages, 1872 KiB  
Article
The Impact of Additive Manufacturing on the Flexibility of a Manufacturing Supply Chain
by Ageel Abdulaziz Alogla, Martin Baumers, Christopher Tuck and Waiel Elmadih
Appl. Sci. 2021, 11(8), 3707; https://doi.org/10.3390/app11083707 - 20 Apr 2021
Cited by 27 | Viewed by 4651
Abstract
There is an increasing need for supply chains that can rapidly respond to fluctuating demands and can provide customised products. This supply chain design requires the development of flexibility as a critical capability. To this end, firms are considering Additive Manufacturing (AM) as [...] Read more.
There is an increasing need for supply chains that can rapidly respond to fluctuating demands and can provide customised products. This supply chain design requires the development of flexibility as a critical capability. To this end, firms are considering Additive Manufacturing (AM) as one strategic option that could enable such a capability. This paper develops a conceptual model that maps AM characteristics relevant to flexibility against key market disruption scenarios. Following the development of this model, a case study is undertaken to indicate the impact of adopting AM on supply chain flexibility from four major flexibility-related aspects: volume, mix, delivery, and new product introduction. An inter-process comparison is implemented in this case study using data collected from a manufacturing company that produces pipe fittings using Injection Moulding (IM). The supply chain employing IM in this case study shows greater volume and delivery flexibility levels (i.e., 65.68% and 92.8% for IM compared to 58.70% and 75.35% for AM, respectively) while the AM supply chain shows greater mix and new product introduction flexibility, indicated by the lower changeover time and cost of new product introduction to the system (i.e., 0.33 h and €0 for AM compared to 4.91 h and €30,000 for IM, respectively). This work will allow decision-makers to take timely decisions by providing useful information on the effect of AM adoption on supply chain flexibility in different sudden disruption scenarios such as demand uncertainty, demand variability, lead-time compression and product variety. Full article
(This article belongs to the Special Issue Smart Manufacturing Systems for Industry 5.0: Challenges and Opportunities)
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<p>The link between external market requirements, external flexibility and internal flexibility (inspired by Reichhart and Holweg [<a href="#B26-applsci-11-03707" class="html-bibr">26</a>]).</p> Full article ">Figure 2
<p>A conceptual model that maps AM characteristics relevant to supply chain flexibility against key market scenarios faced by managers.</p> Full article ">Figure 3
<p>The historical demand of the Pipe Tee joint fitting ¾” for 48 months.</p> Full article ">Figure 4
<p>CAD drawing of the part selected for the case study: Pipe tee joint ¾’’ (dimensions in mm).</p> Full article ">Figure 5
<p>Flowchart of the current supply chain configuration of the pipe tee joint manufacturing company.</p> Full article ">Figure 6
<p>Flowchart of the supply chain configuration with AM only.</p> Full article ">Figure 7
<p>Relationship between volume flexibility and unit cost of the studied part for (<b>A</b>) IM and (<b>B</b>) AM.</p> Full article ">Figure 8
<p>The relationship between the external flexibility capabilities, manufacturing technology and demand volume level.</p> Full article ">
25 pages, 12595 KiB  
Article
Prediction of Non-Uniform Distorted Flows, Effects on Transonic Compressor Using CFD, Regression Analysis and Artificial Neural Networks
by Muhammad Umer Sohail, Hossein Raza Hamdani, Asad Islam, Khalid Parvez, Abdul Munem Khan, Usman Allauddin, Muhammad Khurram and Hassan Elahi
Appl. Sci. 2021, 11(8), 3706; https://doi.org/10.3390/app11083706 - 20 Apr 2021
Cited by 11 | Viewed by 2842
Abstract
Non-uniform inlet flows frequently occur in aircrafts and result in chronological distortions of total temperature and total pressure at the engine inlet. Distorted inlet flow operation of the axial compressor deteriorates aerodynamic performance, which reduces the stall margin and increases blade stress levels, [...] Read more.
Non-uniform inlet flows frequently occur in aircrafts and result in chronological distortions of total temperature and total pressure at the engine inlet. Distorted inlet flow operation of the axial compressor deteriorates aerodynamic performance, which reduces the stall margin and increases blade stress levels, which in turn causes compressor failure. Deep learning is an efficient approach to predict catastrophic compressor failure, and its stability for better performance at minimum computational cost and time. The current research focuses on the development of a transonic compressor instability prediction tool for the comprehensive modeling of axial compressor dynamics. A novel predictive approach founded by an extensive CFD-based dataset for supervised learning has been implemented to predict compressor performance and behavior at different ambient temperatures and flow conditions. Artificial Neural Network-based results accurately predict compressor performance parameters by minimizing the Root Mean Square Error (RMSE) loss function. Computational results show that, as compared to the tip radial pressure distortion, hub radial pressure distortion has improved the stability range of the compressor. Furthermore, the combined effect of pressure distortion with the bulk flow has a qualitative and deteriorator effect on the compressor. Full article
(This article belongs to the Section Aerospace Science and Engineering)
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<p>Hexahedral grid mesh of a single blade for rotor-67 [<a href="#B13-applsci-11-03706" class="html-bibr">13</a>].</p> Full article ">Figure 2
<p>Black box for compressor input and output variables.</p> Full article ">Figure 3
<p>(<b>a</b>) Pressure ratio vs. normalized mass flow rate, and (<b>b</b>) isentropic efficiency vs. normalized mass flow rate.</p> Full article ">Figure 4
<p>Computational and experimental span-wise profiles of (<b>a</b>) total pressure ratio and (<b>b</b>) total temperature ratio at the peak efficiency condition.</p> Full article ">Figure 5
<p>Characteristic map of (<b>a</b>) hub radial pressure distortion with variable ambient temperature, (<b>b</b>) tip radial pressure distortion with variable ambient temperature, (<b>c</b>) bulk flow with the variable RPM, (<b>d</b>) the combined effects of hub radial pressure distortion with the co-swirl flow, (<b>e</b>) the combined effects of hub radial pressure distortion with the counter swirl flow, (<b>f</b>) tip radial pressure distortion with the co-swirl flow, and (<b>g</b>) tip radial pressure distortion with the counter swirl flow.</p> Full article ">Figure 5 Cont.
<p>Characteristic map of (<b>a</b>) hub radial pressure distortion with variable ambient temperature, (<b>b</b>) tip radial pressure distortion with variable ambient temperature, (<b>c</b>) bulk flow with the variable RPM, (<b>d</b>) the combined effects of hub radial pressure distortion with the co-swirl flow, (<b>e</b>) the combined effects of hub radial pressure distortion with the counter swirl flow, (<b>f</b>) tip radial pressure distortion with the co-swirl flow, and (<b>g</b>) tip radial pressure distortion with the counter swirl flow.</p> Full article ">Figure 6
<p>Loss function of the Neural Network model during train and test phase.</p> Full article ">Figure 7
<p>Testing dataset unity plots for (<b>a</b>) mass flow rate, (<b>b</b>) pressure ratio, (<b>c</b>) temperature ratio, and (<b>d</b>) isentropic efficiency.</p> Full article ">Figure 8
<p>Regression models for mass flow rate (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM Medium, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Matern, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 8 Cont.
<p>Regression models for mass flow rate (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM Medium, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Matern, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 9
<p>Regression models for pressure ratio (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM Medium, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Matern, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 9 Cont.
<p>Regression models for pressure ratio (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM Medium, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Matern, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 10
<p>Regression models for temperature ratio (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM Medium, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Exponential, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 10 Cont.
<p>Regression models for temperature ratio (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM Medium, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Exponential, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 11
<p>Regression models for isentropic efficiency (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM fine, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Matern, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 11 Cont.
<p>Regression models for isentropic efficiency (<b>a</b>) Ensembled Bagged Tree, (<b>b</b>) Tree Fine, (<b>c</b>) SVM fine, (<b>d</b>) Stepwise Linear, (<b>e</b>) GPR Matern, and (<b>f</b>) GPR Rational Quadratic.</p> Full article ">Figure 12
<p>Best Response Regression Models (<b>a</b>) Exponential GPR for mass flow rate, (<b>b</b>) GPR Matern for pressure ratio, (<b>c</b>) GPR Matern for temperature ratio, and (<b>d</b>) GPR Exponential for isentropic efficiency.</p> Full article ">Figure 13
<p>RMSE comparison (<b>a</b>) Linear RMSE, (<b>b</b>) GPR’s RMSE, (<b>c</b>) Tree’s RMSE, and (<b>d</b>) SVM’s RMSE.</p> Full article ">Figure 13 Cont.
<p>RMSE comparison (<b>a</b>) Linear RMSE, (<b>b</b>) GPR’s RMSE, (<b>c</b>) Tree’s RMSE, and (<b>d</b>) SVM’s RMSE.</p> Full article ">
17 pages, 3592 KiB  
Article
Prediction of Peak Particle Velocity Caused by Blasting through the Combinations of Boosted-CHAID and SVM Models with Various Kernels
by Jie Zeng, Panayiotis C. Roussis, Ahmed Salih Mohammed, Chrysanthos Maraveas, Seyed Alireza Fatemi, Danial Jahed Armaghani and Panagiotis G. Asteris
Appl. Sci. 2021, 11(8), 3705; https://doi.org/10.3390/app11083705 - 20 Apr 2021
Cited by 34 | Viewed by 3283
Abstract
This research examines the feasibility of hybridizing boosted Chi-Squared Automatic Interaction Detection (CHAID) with different kernels of support vector machine (SVM) techniques for the prediction of the peak particle velocity (PPV) induced by quarry blasting. To achieve this objective, a boosting-CHAID technique was [...] Read more.
This research examines the feasibility of hybridizing boosted Chi-Squared Automatic Interaction Detection (CHAID) with different kernels of support vector machine (SVM) techniques for the prediction of the peak particle velocity (PPV) induced by quarry blasting. To achieve this objective, a boosting-CHAID technique was applied to a big experimental database comprising six input variables. The technique identified four input parameters (distance from blast-face, stemming length, powder factor, and maximum charge per delay) as the most significant parameters affecting the prediction accuracy and utilized them to propose the SVM models with various kernels. The kernel types used in this study include radial basis function, polynomial, sigmoid, and linear. Several criteria, including mean absolute error (MAE), correlation coefficient (R), and gains, were calculated to evaluate the developed models’ accuracy and applicability. In addition, a simple ranking system was used to evaluate the models’ performance systematically. The performance of the R and MAE index of the radial basis function kernel of SVM in training and testing phases, respectively, confirm the high capability of this SVM kernel in predicting PPV values. This study successfully demonstrates that a combination of boosting-CHAID and SVM models can identify and predict with a high level of accuracy the most effective parameters affecting PPV values. Full article
(This article belongs to the Collection Heuristic Algorithms in Engineering and Applied Sciences)
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<p>A systematic flowchart of this study.</p> Full article ">Figure 2
<p>Representation of SVM.</p> Full article ">Figure 3
<p>SVM arrangement for regression.</p> Full article ">Figure 4
<p>Kernels’ formula.</p> Full article ">Figure 5
<p>Location information of the quarry sites.</p> Full article ">Figure 6
<p>Measured PPV values and their frequency distribution.</p> Full article ">Figure 7
<p>Predicted PPV values of the SVM models with different Kernels.</p> Full article ">Figure 8
<p>Gain chart of the proposed models.</p> Full article ">Figure 9
<p>Input variable importance for the analysis of PPV.</p> Full article ">
19 pages, 7638 KiB  
Article
FEM-CFD Simulation and Experimental Study of Compound Parabolic Concentrator (CPC) Solar Collectors with and without Fins for Residential Applications
by Javier E. Barrón-Díaz, Emmanuel A. Flores-Johnson, Danny G. Chan-Colli, J. Francisco Koh-Dzul, Ali Bassam, Luis D. Patiño-Lopez and Jose G. Carrillo
Appl. Sci. 2021, 11(8), 3704; https://doi.org/10.3390/app11083704 - 20 Apr 2021
Cited by 5 | Viewed by 3122
Abstract
Compound parabolic concentrator (CPC) solar collectors are widely used for solar energy systems in industry; however, CPC collectors for residential applications have not been fully investigated. In this work, the thermal performance of non-tracking, small-size and low-cost CPC collectors with an absorber with [...] Read more.
Compound parabolic concentrator (CPC) solar collectors are widely used for solar energy systems in industry; however, CPC collectors for residential applications have not been fully investigated. In this work, the thermal performance of non-tracking, small-size and low-cost CPC collectors with an absorber with and without segmented fins was studied experimentally and by means of a proposed numerical methodology that included ray tracing simulation and a coupled heat transfer finite element method (FEM)-computational fluid dynamics (CFD) simulation, which was validated with experimental data. The experimental results showed that the CPC with a finned absorber has better thermal performance than that of the CPC with absorber without fins, which was attributed to the increase in thermal energy on the absorber surface. The numerical results showed that ray tracing simulation can be used to estimate the heat flux on the absorber surface and the FEM-CFD simulation can be used to estimate the heat transfer from the absorber to the water running through the pipe along with its temperature. The numerical results showed that mass flow rate is an important parameter for the design of the CPC collectors. The numerical methodology developed in this work was capable of describing the thermal performance of the CPC collectors and can be used for the modeling of the thermal behavior of other CPCs solar systems. Full article
(This article belongs to the Special Issue Recent Progress in Solar Thermal Technologies and Applications)
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Graphical abstract
Full article ">Figure 1
<p>(<b>a</b>) Cross-section of CPC solar collector; (<b>b</b>) side view of CPC solar collector; (<b>c</b>) image of the CPC solar collector systems; (<b>d</b>) image of CPC with an absorber without fins; (<b>e</b>) image of the CPC with an absorber with segmented fins.</p> Full article ">Figure 2
<p>Tubular absorber with segmented fins.</p> Full article ">Figure 3
<p>Schematic of the numerical methodology: (<b>a</b>) ray tracing analysis in Tonatiuh; (<b>b</b>) data processing in MATLAB; (<b>c</b>) coupled FEM-CFD thermal analysis in Abaqus.</p> Full article ">Figure 4
<p>(<b>a</b>) CPC collector with an absorber without fins; (<b>b</b>) CPC collector with an absorber with segmented fins; (<b>c</b>) CPC collector with an absorber with continuous fins; (<b>d</b>) ray tracing simulation of CPC collector with segmented fins; (<b>e</b>) close-up view.</p> Full article ">Figure 5
<p>Photons striking the CPC absorber at a given time: (<b>a</b>) absorber without fins; (<b>b</b>) absorber with segmented fins; (<b>c</b>) absorber with continuous fins. Heat flux in each individual area of the CPC absorber: (<b>d</b>) absorber without fins; (<b>e</b>) absorber with segmented fins; (<b>f</b>) absorber with continuous fins.</p> Full article ">Figure 6
<p>(<b>a</b>) Mesh of FEM and CFD models; (<b>b</b>) thermal loading on the absorber surface; (<b>c</b>) mesh and boundary conditions of the CFD model of the water.</p> Full article ">Figure 7
<p>Mesh of CPC absorber models: (<b>a</b>) CPC absorber without fins; (<b>b</b>) CPC absorber with segmented fins; (<b>c</b>) CPC absorber with continuous fins.</p> Full article ">Figure 8
<p>Experimental measurements of the inlet, outlet and absorber temperatures in the CPC collectors, ambient temperature and global solar radiation on 1 March 2020: (<b>a</b>) absorber without fins; (<b>b</b>) absorber with segmented fins.</p> Full article ">Figure 9
<p>Temperature difference Δ<span class="html-italic">T</span> and thermal efficiency <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mi>t</mi> </msub> </mrow> </semantics></math> for the CPC collectors with absorber without fins and with segmented fins on 1 March 2020.</p> Full article ">Figure 10
<p>Thermal efficiency <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mi>t</mi> </msub> </mrow> </semantics></math> for the CPC collectors with absorber without fins and with segmented fins on 1 March 2020.</p> Full article ">Figure 11
<p>(<b>a</b>) Comparison between experimental and predicted outlet temperatures for both CPC with absorber without fins and with absorber with segmented fins on 1 March 2020; (<b>b</b>) predicted outlet temperatures for CPCs with absorbers without fins, with segmented fins and with continuous fins using either mapped heat flux load or homogenous heat flux load.</p> Full article ">Figure 12
<p>Contour plot of the temperatures of the CPC absorber and cross section at the outlet at 12 p.m. (noon) on 1 March 2020: CPC absorber without fins (<b>a</b>,<b>b</b>); CPC absorber with segmented fins (<b>c</b>,<b>d</b>); CPC absorber with continuous fins (<b>e</b>,<b>f</b>).</p> Full article ">Figure 13
<p>Predicted temperature difference Δ<span class="html-italic">T</span> and power on the absorber surface for the different CPC collectors (left image) and image of the incident angle of the solar rays impacting the CPC at noon for illustration purposes (right image): (<b>a</b>,<b>b</b>) on late winter (1 March 2020) with a constant inlet temperature of 27 °C and inlet velocity of 0.0076 m/s; (<b>c</b>,<b>d</b>) on early winter (15 January 2021) with a constant inlet temperature of 23 °C and an inlet velocity of 0.0076 m/s; (<b>e</b>,<b>f</b>) on summer (9 July 2020) with a constant inlet temperature of 34 °C and an inlet velocity of 0.0076 m/s.</p> Full article ">Figure 14
<p>Longitudinal and transverse <span class="html-italic">IAM</span> as a function of the incidence angle <math display="inline"><semantics> <mi>θ</mi> </semantics></math> for the different CPC absorbers.</p> Full article ">Figure 15
<p>(<b>a</b>) Predicted maximum temperature difference Δ<span class="html-italic">T</span> versus mass flow rate and (<b>b</b>) predicted thermal efficiency <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mi>t</mi> </msub> </mrow> </semantics></math> versus mass flow rate <math display="inline"><semantics> <mover accent="true"> <mi>m</mi> <mo>˙</mo> </mover> </semantics></math>, on 1 March 2020, with a constant inlet temperature of 27 °C for the different CPC absorbers.</p> Full article ">
31 pages, 3505 KiB  
Article
Path Planning Based on Obstacle-Dependent Gaussian Model Predictive Control for Autonomous Driving
by Dong-Sung Pae, Geon-Hee Kim, Tae-Koo Kang and Myo-Taeg Lim
Appl. Sci. 2021, 11(8), 3703; https://doi.org/10.3390/app11083703 - 20 Apr 2021
Cited by 18 | Viewed by 4222
Abstract
Path planning research plays a vital role in terms of safety and comfort in autonomous driving systems. This paper focuses on safe driving and comfort riding through path planning in autonomous driving applications and proposes autonomous driving path planning through an optimal controller [...] Read more.
Path planning research plays a vital role in terms of safety and comfort in autonomous driving systems. This paper focuses on safe driving and comfort riding through path planning in autonomous driving applications and proposes autonomous driving path planning through an optimal controller integrating obstacle-dependent Gaussian (ODG) and model prediction control (MPC). The ODG algorithm integrates the information from the sensors and calculates the risk factors in the driving environment. The MPC function finds vehicle control signals close to the objective function under limited conditions, such as the structural shape of the vehicle and road driving conditions. The proposed method provides safe control and minimizes vehicle shaking due to the tendency to respond to avoid obstacles quickly. We conducted an experiment using mobile robots, similar to an actual vehicle, to verify the proposed algorithm performance. The experimental results show that the average safety metric is 72.34%, a higher ISO-2631 comport score than others, while the average processing time is approximately 14.2 ms/frame. Full article
(This article belongs to the Special Issue Artificial Intelligence and Control Technology for Unmanned Transport Systems)
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<p>Autonomous driving environment.</p> Full article ">Figure 2
<p>Illustration with vehicle and obstacles of the laser range finder (LRF) sensor.</p> Full article ">Figure 3
<p>Sensor data and threshold distance.</p> Full article ">Figure 4
<p>Enlarging the angle occupied by obstacles.</p> Full article ">Figure 5
<p>Result of obstacle-dependent Gaussian (ODG) potential field (PF).</p> Full article ">Figure 6
<p>Generalized model predictive control architecture.</p> Full article ">Figure 7
<p>Obstacle-dependent Gaussian model prediction control architecture.</p> Full article ">Figure 8
<p>Vehicle bicycle model for path planning.</p> Full article ">Figure 9
<p>Obstacle-dependent Gaussian concept (<math display="inline"><semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msup> <mi>σ</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math>).</p> Full article ">Figure 10
<p>Obstacle-dependent Gaussian (ODG) for solid and dotted lines.</p> Full article ">Figure 11
<p>Line obstacle-dependent Gaussian (ODG) with model prediction control (MPC) longitudinal position.</p> Full article ">Figure 12
<p>Vehicle obstacle-dependent Gaussian (ODG) with model prediction control longitudinal position.</p> Full article ">Figure 13
<p>Total obstacle-dependent Gaussian (ODG) with model prediction control longitudinal position.</p> Full article ">Figure 14
<p>Safety (<math display="inline"><semantics> <mrow> <mi>S</mi> <mi>T</mi> </mrow> </semantics></math>) metric.</p> Full article ">Figure 15
<p>Experimental environment.</p> Full article ">Figure 16
<p>Mobile Robots 1 and 2 on experimental platforms.</p> Full article ">Figure 17
<p>Scenario map.</p> Full article ">Figure 18
<p>Results of the path for Scenario 1.</p> Full article ">Figure 19
<p>Results of the path from Scenario 2 for a static obstacle.</p> Full article ">Figure 20
<p>Results of the acceleration from Scenario 2 for a static obstacle.</p> Full article ">Figure 21
<p>Results of the obstacle distance from Scenario 2 for a static obstacle.</p> Full article ">Figure 22
<p>Results of the path from Scenario 2 for a dynamic obstacle.</p> Full article ">Figure 23
<p>Results of the acceleration from Scenario 2 for a dynamic obstacle.</p> Full article ">Figure 24
<p>Results of the obstacle distance from Scenario 2 for a dynamic obstacle.</p> Full article ">Figure 25
<p>Results of the path from Scenario 3 for two static obstacles.</p> Full article ">Figure 26
<p>Results of the acceleration from Scenario 3 for two static obstacles.</p> Full article ">Figure 27
<p>Results of the obstacle distance from Scenario 3 for static Obstacle 1.</p> Full article ">Figure 28
<p>Results of the obstacle distance from Scenario 3 for static Obstacle 2.</p> Full article ">Figure 29
<p>Results of the path from Scenario 3 for one dynamic obstacle and one static obstacle.</p> Full article ">Figure 30
<p>Results of the acceleration from Scenario 3 for one dynamic obstacle and one static obstacle.</p> Full article ">Figure 31
<p>Results of the obstacle distance from Scenario 3 for a dynamic obstacle.</p> Full article ">Figure 32
<p>Results of the obstacle distance from Scenario 3 for a static obstacle.</p> Full article ">
10 pages, 3635 KiB  
Article
Pulpal Response to the Combined Use of Mineral Trioxide Aggregate and Iloprost for Direct Pulp Capping
by AlAnoud Almeshari, Rita Khounganian, Wael Mahdi, Fahd Aljarbou, Shilpa Bhandi and Sara Alsubait
Appl. Sci. 2021, 11(8), 3702; https://doi.org/10.3390/app11083702 - 20 Apr 2021
Cited by 2 | Viewed by 2672
Abstract
Purpose: The present study aims to assess the combined effects of mineral trioxide aggregate (MTA) and iloprost when used as a pulp capping material on pulpal inflammation and tertiary dentin formation compared with MTA and iloprost alone in rat molar teeth. Methods: Eighty [...] Read more.
Purpose: The present study aims to assess the combined effects of mineral trioxide aggregate (MTA) and iloprost when used as a pulp capping material on pulpal inflammation and tertiary dentin formation compared with MTA and iloprost alone in rat molar teeth. Methods: Eighty maxillary first molar rat teeth were exposed and capped with iloprost solution, MTA, or MTA mixed with iloprost (MTA-iloprost). The cavities were then filled with resin-modified glass ionomer. The cavity was restored with glass ionomer without the use of pulp capping agent in the control group. The rats were sacrificed after one and four weeks. Block sections of the molar specimens were prepared and subjected to hematoxylin and eosin staining for evaluation. Statistical analysis was done using the Kruskal–Wallis test, followed by Dunnett’s test. Results: At week one, the control group showed significantly more severe pulpal inflammatory reactions than the iloprost (p = 0.00), MTA (p = 0.04), and MTA-iloprost (p = 0.00) groups. Hard tissue formation was commonly found in the iloprost, MTA, and MTA-iloprost groups. After four weeks, pulpal tissue degeneration was observed in the control group. Complete hard tissue barriers were found in 50%, 72.7%, and 77.8% of the specimens in iloprost, MTA, and MTA-iloprost groups, respectively, with no significant differences among the experimental groups. The dentinal tubule patterns were mostly regular in the MTA-iloprost group and irregular in the iloprost and MTA groups. Conclusions: The application of iloprost, MTA, and MTA-iloprost as a pulp capping material resulted in similar pulpal responses in the mechanically exposed pulp of rat molars. Therefore, mixing MTA with iloprost might not be clinically significant. Full article
(This article belongs to the Special Issue Innovative Techniques in Endodontics)
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<p>Histologic features of maxillary first molars subjected to pulp exposure and restored with glass ionomer without the use of pulp capping agent at week one. Representative photomicrographs showing (<b>A</b>) diffuse inflammation and (<b>B</b>) degenerated pulp with granulation tissue filling the exposure area. H&amp;E stain ×200 magnification. Arrows indicate the exposure area.</p> Full article ">Figure 2
<p>Histologic features of maxillary first molars capped with (<b>A</b>,<b>B</b>) iloprost, (<b>C</b>,<b>D</b>) MTA, and (<b>E</b>,<b>F</b>) MTA-iloprost at one week. Higher magnification showing dilated and engorged blood vessels in (<b>B</b>) iloprost and (<b>F</b>) MTA-iloprost specimens. H&amp;E stain ×200 and ×400 magnification. Arrows indicate tertiary dentin.</p> Full article ">Figure 3
<p>Histologic features of maxillary first molars subjected to pulp exposure and restored with glass ionomer without the use of pulp capping agent at week four. Representative photomicrographs showing (<b>A</b>) pulpal degeneration and (<b>B</b>) calcified bridge formation. H&amp;E ×200 magnification.</p> Full article ">Figure 4
<p>Histologic features of maxillary first molars subjected to pulp exposure and capped with (<b>A</b>) iloprost, (<b>B</b>) MTA, and (<b>C</b>) MTA-iloprost at week four. H&amp;E stain ×200 magnification. The star indicates tertiary dentin.</p> Full article ">
16 pages, 4328 KiB  
Article
Measurement of Temperature and H2O Concentration in Premixed CH4/Air Flame Using Two Partially Overlapped H2O Absorption Signals in the Near Infrared Region
by Sunghyun So, Nakwon Jeong, Aran Song, Jungho Hwang, Daehae Kim and Changyeop Lee
Appl. Sci. 2021, 11(8), 3701; https://doi.org/10.3390/app11083701 - 20 Apr 2021
Cited by 8 | Viewed by 2624
Abstract
It is important to monitor the temperature and H2O concentration in a large combustion environment in order to improve combustion (and thermal) efficiency and reduce harmful combustion emissions. However, it is difficult to simultaneously measure both internal temperature and gas concentration [...] Read more.
It is important to monitor the temperature and H2O concentration in a large combustion environment in order to improve combustion (and thermal) efficiency and reduce harmful combustion emissions. However, it is difficult to simultaneously measure both internal temperature and gas concentration in a large combustion system because of the harsh environment with rapid flow. In regard, tunable diode laser absorption spectroscopy, which has the advantages of non-intrusive, high-speed response, and in situ measurement, is highly attractive for measuring the concentration of a specific gas species in the combustion environment. In this study, two partially overlapped H2O absorption signals were used in the tunable diode laser absorption spectroscopy (TDLAS) to measure the temperature and H2O concentration in a premixed CH4/air flame due to the wide selection of wavelengths with high temperature sensitivity and advantages where high frequency modulation can be applied. The wavelength regions of the two partially overlapped H2O absorptions were 1.3492 and 1.34927 μm. The measured signals separated the multi-peak Voigt fitting. As a result, the temperature measured by TDLAS based on multi-peak Voigt fitting in the premixed CH4/air flame was the highest at 1385.80 K for an equivalence ratio of 1.00. It also showed a similarity to those tendencies to the temperature measured by the corrected R-type T/C. In addition, the H2O concentrations measured by TDLAS based on the total integrated absorbance area for various equivalent ratios were consistent with those calculated by the chemical equilibrium simulation. Additionally, the H2O concentration measured at an equivalence ratio of 1.15 was the highest at 18.92%. Full article
(This article belongs to the Special Issue Diode Laser Spectroscopy – Robust Sensing for Environmental and Industrial Applications)
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<p>(<b>a</b>) Linestrengths of H<sub>2</sub>O and combustion products within 1.3490-1.3495 µm at 296 K, (<b>b</b>) 1073.15 K, (<b>c</b>) 1473.15 K, and (<b>d</b>) 1773.15 K from the HITRAN2012 database.</p> Full article ">Figure 2
<p>(<b>a</b>) Calculated temperature sensitivity of the linestrength ratio at the temperature range 550–1800 K, and (<b>b</b>) calculated linestrength ratios for the two selected absorption lines at 300–1800 K.</p> Full article ">Figure 3
<p>Schematic diagram of the measurement system applied to an electric furnace.</p> Full article ">Figure 4
<p>Schematic diagram of the measurement system applied to a metal fiber burner.</p> Full article ">Figure 5
<p>(<b>a</b>) Two partially overlapped H<sub>2</sub>O absorption signals measured at 1073.15 K, (<b>b</b>) 1273.15 K, and (<b>c</b>) 1573.15 K in the electric furnace.</p> Full article ">Figure 6
<p>Measured temperature profile using thermocouple at 1473.15 K in the electric furnace.</p> Full article ">Figure 7
<p>Comparison of reconstruction method using half absorbance and multi-peak Voigt fitting method presented for analysis of the two partially overlapped H<sub>2</sub>O absorption signal.</p> Full article ">Figure 8
<p>(<b>a</b>) Multi-peak Voigt fitting for measured data at 1073.15 K, and (<b>b</b>) comparison of the experimentally obtained temperature using TDLAS with measured temperature using T/C in the electric furnace.</p> Full article ">Figure 9
<p>Reconstruction method using half absorbance for measured data at (<b>a</b>) 1073.15 K and (<b>b</b>) 1473.15 K.</p> Full article ">Figure 10
<p>Two partially overlapped H<sub>2</sub>O absorption signals (<b>a</b>) for measuring temperature, and (<b>b</b>) for measuring H<sub>2</sub>O concentration under an equivalence ratio of 1.00.</p> Full article ">Figure 11
<p>(<b>a</b>) Comparison of measured temperature using TDLAS and thermocouple, and (<b>b</b>) analysis of the H<sub>2</sub>O concentration using Chemkin and TDLAS according to various equivalence ratios in a combustion environment.</p> Full article ">
8 pages, 626 KiB  
Article
Odor Emissions Factors for Bitumen-Related Production Sites
by Enrico Davoli, Giancarlo Bianchi, Anna Bonura, Marzio Invernizzi and Selena Sironi
Appl. Sci. 2021, 11(8), 3700; https://doi.org/10.3390/app11083700 - 20 Apr 2021
Cited by 1 | Viewed by 2306
Abstract
Bitumen-related production sites are facing increasing difficulties with nearby residents due to odor emissions. This parameter is still not regulated for these plants and little is known about the emissions that these plants have put into the atmosphere with the technologies available today. [...] Read more.
Bitumen-related production sites are facing increasing difficulties with nearby residents due to odor emissions. This parameter is still not regulated for these plants and little is known about the emissions that these plants have put into the atmosphere with the technologies available today. In this study, emission data from 47 Italian production plants were collected and analyzed to assess which values could describe the current situation in Italy. The results of the analysis showed that emissions are very variable, with odor concentration values between 200 to 37,000 ouE/m3, but data have a normal distribution. The mean value of the stack odor concentration was found to be 2424 ouE/m3. It was also possible to calculate emission factors of the plants, such as odor emission rate (OER), which represents the quantity of odor emitted per unit of time, and is expressed in odor units per second (ouE∙s−1) and odor emission factor (OEF) per ton of product, expressed in ouE/t. The values obtained were 7.1 × 104 ouE/s and 1.4 × 106 ouE/t. respectively. These data could provide a starting point for the definition of shared values among various stakeholders for the definition of regional guidelines for the emissions of these plants, in order to adjust available technologies towards emission parameters that are protective of the surrounding environment. Full article
(This article belongs to the Special Issue New Frontiers in the Assessment, Monitoring and Control of Environmental Odors)
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<p>OEF data for bitumen-related production sites on a logarithmic scale.</p> Full article ">Figure 2
<p>QQplot of the logarithm-transformed OEF data. As mentioned in text, due to the nature of odor concentration measurements, the statistical calculations are based on the log-transformed data.</p> Full article ">
16 pages, 4366 KiB  
Article
Non-Deterministic Methods and Surrogates in the Design of Rockfill Dams
by Rajeev Das and Azzedine Soulaimani
Appl. Sci. 2021, 11(8), 3699; https://doi.org/10.3390/app11083699 - 20 Apr 2021
Cited by 7 | Viewed by 2388
Abstract
The parameters of the constitutive models used in the design of rockfill dams are associated with a high degree of uncertainty. This occurs because rockfill dams are comprised of numerous zones, each with different soil materials, and it is not feasible to extract [...] Read more.
The parameters of the constitutive models used in the design of rockfill dams are associated with a high degree of uncertainty. This occurs because rockfill dams are comprised of numerous zones, each with different soil materials, and it is not feasible to extract materials from such structures to accurately ascertain their behavior or their respective parameters. The general approach involves laboratory tests using small material samples or empirical data from the literature. However, such measures lack an accurate representation of the actual scenario, resulting in uncertainties. This limits the suitability of the model in the design process. Inverse analysis provides an option to better understand dam behavior. This procedure involves the use of real monitored data, such as deformations and stresses, from the dam structure via installed instruments. Fundamentally, it is a non-destructive approach that considers optimization methods and actual performance data to determine the values of the parameters by minimizing the differences between simulated and observed results. This paper considers data from an actual rockfill dam and proposes a surrogate assisted non-deterministic framework for its inverse analysis. A suitable error/objective function that measures the differences between the actual and simulated displacement values is defined first. Non-deterministic algorithms are used as the optimization technique, as they can avoid local optima and are more robust when compared to the conventional deterministic methods. Three such approaches, the genetic algorithm, differential evolution, and particle swarm optimization are evaluated to identify the best strategy in solving problems of this nature. A surrogate model in the form of a polynomial regression is studied and recommended in place of the actual numerical model of the dam to reduce computation cost. Finally, this paper presents the relevant dam parameters estimated by the analysis and provides insights into the performance of the three procedures to solve the inverse problem. Full article
(This article belongs to the Section Civil Engineering)
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<p>2D cross-section model of the Romaine-2 dam in Plaxis. Different zones of the dam are highlighted by letters. The vertical inclinometer INV1 is found in section PM560.</p> Full article ">Figure 2
<p>Measurements recorded by INV01 prior to the start of impoundment, denoted by the dotted line. These denote horizontal movements; a negative value indicates upstream movement.</p> Full article ">Figure 3
<p>Flow diagrams of the algorithms considered. (<b>a</b>) GA, (<b>b</b>) PSO, and (<b>c</b>) DE represent the different steps associated with each of the three non-deterministic algorithms.</p> Full article ">Figure 4
<p>Pseudocode of genetic algorithm considered.</p> Full article ">Figure 5
<p>Pseudocode of particle swarm optimization algorithm.</p> Full article ">Figure 6
<p>Pseudocode of differential evolution algorithm.</p> Full article ">Figure 7
<p>The cycle associated with the surrogate-assisted non-deterministic approach.</p> Full article ">Figure 8
<p>Steps involved in generating a surrogate model of a rockfill dam. Thirty two evenly distributed locations along the inclinometer were considered for the analysis. A set of five parameters was used to generate the 300 input points. These inputs were used to create the regression models for the 32 locations using the Sckit-learn package and the actual displacement values at these locations.</p> Full article ">Figure 9
<p>Displacements at different sections of the dam along INV01. Specific weight, shear modulus, and Poisson coefficient were considered to plot the results. Surface plot representation at different elevations here provide an insight into the nature of the optimization problem at hand.</p> Full article ">Figure 10
<p>Convergences observed in the analysis using three different algorithms: the GA, DE, and the PSO.</p> Full article ">Figure 11
<p>Measurements recorded at INV01 by the inclinometer are denoted by the dotted line. The solid line represents the simulated displacement using the optimal parameter values obtained with DE.</p> Full article ">Figure A1
<p>Sample points generated by the Sobol LDS approach for zone P. Units: Cohesion—kN/m<sup>2</sup>; Sp. Material Weight—kN/m<sup>3</sup>; Friction angle—Degree; Shear modulus—kN/m<sup>2</sup>.</p> Full article ">
14 pages, 18230 KiB  
Article
Chaotic Communication System with Symmetry-Based Modulation
by Timur Karimov, Vyacheslav Rybin, Georgii Kolev, Ekaterina Rodionova and Denis Butusov
Appl. Sci. 2021, 11(8), 3698; https://doi.org/10.3390/app11083698 - 20 Apr 2021
Cited by 33 | Viewed by 3285
Abstract
Communication systems based on chaotic synchronization are gaining interest in the area of secure and covert data transmission. In this paper, a novel digital communication technique based on a coherent chaotic data transmission approach is proposed. In general, this technique resembles the well-known [...] Read more.
Communication systems based on chaotic synchronization are gaining interest in the area of secure and covert data transmission. In this paper, a novel digital communication technique based on a coherent chaotic data transmission approach is proposed. In general, this technique resembles the well-known approach based on the modulation of nonlinearity parameters. The key idea of this study is to modulate a signal by varying not the system parameter but the symmetry coefficient in discrete chaotic models obtained by the special numerical integration method. For this purpose, the self-adjoint semi-implicit integration method of order 2 is used to obtain discrete master and slave models of the considered chaotic oscillator. The experimental results explicitly show that, like during parameter modulation, transmitting and receiving oscillators may completely synchronize only if the symmetry coefficients are equal in both systems. The architecture of the communication system based on the proposed modulation is presented. The practical applicability of the approach is confirmed by transmitting a test binary sequence between the transmitter and receiver models and preliminary benchmarking of the obtained communication system. Since the symmetry coefficient modulation does not significantly impact the chaotic behavior of the transmitting digital system, its better suitability for covert messaging was experimentally confirmed by comparing it with the parameter modulation technique. Full article
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<p>One integration step of the semi-implicit method with variable symmetry.</p> Full article ">Figure 2
<p>Block-diagram of the peer-to-peer SCM communication system with alphabet of <span class="html-italic">n</span> symbols.</p> Full article ">Figure 3
<p>Block-diagram of one-to-many SCM communication system suitable for asynchronous binary coding with <span class="html-italic">n</span> receivers.</p> Full article ">Figure 4
<p>The dependence between average (<b>a</b>) and maximum (<b>b</b>) synchronization time and the symmetry and synchronization coefficients.</p> Full article ">Figure 5
<p>Normalized synchronization errors at receiver systems during a symbol transmission associated with value <math display="inline"><semantics> <msub> <mi>S</mi> <mn>1</mn> </msub> </semantics></math> at the transmitter.</p> Full article ">Figure 6
<p>The behavior of synchronization errors at the receiver during transmission of message “10101100”.</p> Full article ">Figure 7
<p>Dependence of synchronization time from the threshold synchronization error <math display="inline"><semantics> <mrow> <mo>Δ</mo> <mi>x</mi> </mrow> </semantics></math>.</p> Full article ">Figure 8
<p>Bifurcation diagrams for Rössler system simulated with <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math> s.</p> Full article ">Figure 9
<p>Spectrum diagrams for Rössler system simulated with <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math> s.</p> Full article ">Figure 10
<p>Bifurcation diagrams of the Rössler system for the symmetry coefficient variation at different numerical integration steps.</p> Full article ">Figure 11
<p>Spectrograms for message transmission using parameter modulation (<b>a</b>) and symmetry coefficient modulation (<b>b</b>). For parameter modulation, values <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>a</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>0.22</mn> </mrow> </semantics></math> were switched while values of <math display="inline"><semantics> <mrow> <mi>b</mi> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>c</mi> <mo>=</mo> <mn>5.7</mn> </mrow> </semantics></math> were constant. For SCM case, symmetry coefficients were <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>0.6</mn> </mrow> </semantics></math>, respectively.</p> Full article ">
18 pages, 3195 KiB  
Article
Framework for Social Media Analysis Based on Hashtag Research
by Ladislav Pilař, Lucie Kvasničková Stanislavská, Roman Kvasnička, Petr Bouda and Jana Pitrová
Appl. Sci. 2021, 11(8), 3697; https://doi.org/10.3390/app11083697 - 20 Apr 2021
Cited by 20 | Viewed by 6157
Abstract
Social networks have become a common part of many people’s daily lives. Users spend more and more time on these platforms and create an active and passive digital footprint through their interaction with other subjects. These data have high research potential in many [...] Read more.
Social networks have become a common part of many people’s daily lives. Users spend more and more time on these platforms and create an active and passive digital footprint through their interaction with other subjects. These data have high research potential in many fields, because understanding people’s communication on social media is essential to understanding their attitudes, experiences and behaviours. Social media analysis is a relatively new subject. There is still a need to develop methods and tools for researchers to help solve typical problems associated with this area. A researcher will be able to focus on the subject of research entirely. This article describes the Social Media Analysis based on Hashtag Research (SMAHR) framework, which uses social network analysis methods to explore social media communication through a network of hashtags. The results show that social media analysis based on hashtags provides information applicable to theoretical research and practical strategic marketing and management applications. Full article
(This article belongs to the Special Issue Social Network Analysis)
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<p>Seven phases of social media analysis based on hashtag research (SMAHR) framework process. Source: Own processing.</p> Full article ">Figure 2
<p>Transformation example of hashtags from messages to the network (case study of corporate social responsibility). Source: reference [<a href="#B14-applsci-11-03697" class="html-bibr">14</a>].</p> Full article ">Figure 3
<p>Default network visualization after import into Gephi (14,788 hashtags and 363,525 edges). Source: Own processing.</p> Full article ">Figure 4
<p>Network visualization in Gephi after modularity calculation without application of algorithm for layout visualization (14,788 hashtags and 363,525 edges). Source: Own processing.</p> Full article ">Figure 5
<p>Network hashtag layout based on the ForceAtlas 2 algorithm (1425 hashtags and 195,993 edges). Source: “Education and Business as a Key Topics at the Instagram Posts in the Area of Gamification” [<a href="#B20-applsci-11-03697" class="html-bibr">20</a>].</p> Full article ">Figure 6
<p>Basic communities of users on social networks. Adapted from: “Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters” [<a href="#B58-applsci-11-03697" class="html-bibr">58</a>].</p> Full article ">Figure 7
<p>Example of tight communities. Source: “Customer Experience with Farmers’ Markets: What Hashtags Can Reveal” [<a href="#B12-applsci-11-03697" class="html-bibr">12</a>].</p> Full article ">Figure 8
<p>Example of an Instagram message with hashtags.</p> Full article ">Figure 9
<p>Output from Google Vision—Object identification.</p> Full article ">
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