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Sensors, Volume 15, Issue 6 (June 2015) – 135 articles , Pages 12103-14829

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1176 KiB  
Article
A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization
by David Sánchez-Rodríguez, Pablo Hernández-Morera, José Ma. Quinteiro and Itziar Alonso-González
Sensors 2015, 15(6), 14809-14829; https://doi.org/10.3390/s150614809 - 23 Jun 2015
Cited by 40 | Viewed by 7028
Abstract
Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important [...] Read more.
Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have. Full article
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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<p><b>(a)</b> Multiple weighted decision trees (ensemble model); <b>(b)</b> proposed system in the test phase.</p> Full article ">
<p>Evaluation of center of mass, nearest vertices and nearest orientation methods: (<b>a</b>) location estimation error; (<b>b</b>) CDF of performance.</p> Full article ">
<p>Layout of the testbed floor at University of Mannheim. The gray dots represent the offline reference locations; the black dots represent the selected online locations; and the squares show the location of access points.</p> Full article ">
<p>Data distribution for ten locations and the AP1, AP2 and AP3 access points.</p> Full article ">
<p>Effect of the training size at each reference location on the: (<b>a</b>) performance of the proposed system; (<b>b</b>) elapsed time to build the model of multiple weighted decision trees.</p> Full article ">
<p>(<b>a</b>) Effect of the test size on the performance of the system; (<b>b</b>) effect of the training size on the elapsed time to estimate a location.</p> Full article ">
<p>Effect of the multiple decision trees: (<b>a</b>) average estimation error; (<b>b</b>) elapsed time.</p> Full article ">
<p>Evaluation of different positioning algorithms: (<b>a</b>) CDF of performance; (<b>b</b>) elapsed time to estimate a location.</p> Full article ">
1232 KiB  
Article
Design of a Thermoacoustic Sensor for Low Intensity Ultrasound Measurements Based on an Artificial Neural Network
by Jida Xing and Jie Chen
Sensors 2015, 15(6), 14788-14808; https://doi.org/10.3390/s150614788 - 23 Jun 2015
Cited by 8 | Viewed by 6936
Abstract
In therapeutic ultrasound applications, accurate ultrasound output intensities are crucial because the physiological effects of therapeutic ultrasound are very sensitive to the intensity and duration of these applications. Although radiation force balance is a benchmark technique for measuring ultrasound intensity and power, it [...] Read more.
In therapeutic ultrasound applications, accurate ultrasound output intensities are crucial because the physiological effects of therapeutic ultrasound are very sensitive to the intensity and duration of these applications. Although radiation force balance is a benchmark technique for measuring ultrasound intensity and power, it is costly, difficult to operate, and compromised by noise vibration. To overcome these limitations, the development of a low-cost, easy to operate, and vibration-resistant alternative device is necessary for rapid ultrasound intensity measurement. Therefore, we proposed and validated a novel two-layer thermoacoustic sensor using an artificial neural network technique to accurately measure low ultrasound intensities between 30 and 120 mW/cm2. The first layer of the sensor design is a cylindrical absorber made of plexiglass, followed by a second layer composed of polyurethane rubber with a high attenuation coefficient to absorb extra ultrasound energy. The sensor determined ultrasound intensities according to a temperature elevation induced by heat converted from incident acoustic energy. Compared with our previous one-layer sensor design, the new two-layer sensor enhanced the ultrasound absorption efficiency to provide more rapid and reliable measurements. Using a three-dimensional model in the K-wave toolbox, our simulation of the ultrasound propagation process demonstrated that the two-layer design is more efficient than the single layer design. We also integrated an artificial neural network algorithm to compensate for the large measurement offset. After obtaining multiple parameters of the sensor characteristics through calibration, the artificial neural network is built to correct temperature drifts and increase the reliability of our thermoacoustic measurements through iterative training about ten seconds. The performance of the artificial neural network method was validated through a series of experiments. Compared to our previous design, the new design reduced sensing time from 20 s to 12 s, and the sensor’s average error from 3.97 mW/cm2 to 1.31 mW/cm2 respectively. Full article
(This article belongs to the Special Issue Acoustic Waveguide Sensors)
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Figure 1
<p>Schematic of the standard thermoacoustic sensor and its setup.</p> Full article ">Figure 2
<p>The structure of the two-layer thermoacoustic sensor.</p> Full article ">Figure 3
<p>Pressure distribution of the generated ultrasound wave.</p> Full article ">Figure 4
<p>Ultrasound pressure distributions of the remaining waves for (<b>a</b>) the two-layer sensor after attenuation, and (<b>b</b>) the one-layer sensor after attenuation.</p> Full article ">Figure 5
<p>Thermistor curve fitting based on the quadratic model.</p> Full article ">Figure 6
<p>Curve fitting results for temperature rise data by MATLAB’s curve fitting box (60 mW/cm<sup>2</sup>).</p> Full article ">Figure 7
<p>Model of the thermoacoustic sensor compensation using a neural network. The neural network algorithm is implemented using a microcontroller.</p> Full article ">Figure 8
<p>Schematic of a three-layer artificial neural network.</p> Full article ">Figure 9
<p>Variation of mean squared error with training epochs.</p> Full article ">Figure 10
<p>The agreement between the network’s output intensity and target intensity.</p> Full article ">Figure 11
<p>Comparison between the estimated data sets and the real measurement data sets.</p> Full article ">Figure 12
<p>Ultrasound intensity error with and without network temperature compensation.</p> Full article ">Figure 13
<p>Response time of the one- and two-layer sensors with respect to measurement error percentage.</p> Full article ">Figure 14
<p>Comparison of the new sensors design measurements with that of the radiation force balance as a means to conduct a performance evaluation.</p> Full article ">
2728 KiB  
Review
Biosensing with Förster Resonance Energy Transfer Coupling between Fluorophores and Nanocarbon Allotropes
by Shaowei Ding, Allison A. Cargill, Suprem R. Das, Igor L. Medintz and Jonathan C. Claussen
Sensors 2015, 15(6), 14766-14787; https://doi.org/10.3390/s150614766 - 23 Jun 2015
Cited by 30 | Viewed by 9217
Abstract
Nanocarbon allotropes (NCAs), including zero-dimensional carbon dots (CDs), one-dimensional carbon nanotubes (CNTs) and two-dimensional graphene, exhibit exceptional material properties, such as unique electrical/thermal conductivity, biocompatibility and high quenching efficiency, that make them well suited for both electrical/electrochemical and optical sensors/biosensors alike. In particular, [...] Read more.
Nanocarbon allotropes (NCAs), including zero-dimensional carbon dots (CDs), one-dimensional carbon nanotubes (CNTs) and two-dimensional graphene, exhibit exceptional material properties, such as unique electrical/thermal conductivity, biocompatibility and high quenching efficiency, that make them well suited for both electrical/electrochemical and optical sensors/biosensors alike. In particular, these material properties have been exploited to significantly enhance the transduction of biorecognition events in fluorescence-based biosensing involving Förster resonant energy transfer (FRET). This review analyzes current advances in sensors and biosensors that utilize graphene, CNTs or CDs as the platform in optical sensors and biosensors. Widely utilized synthesis/fabrication techniques, intrinsic material properties and current research examples of such nanocarbon, FRET-based sensors/biosensors are illustrated. The future outlook and challenges for the research field are also detailed. Full article
(This article belongs to the Special Issue FRET Biosensors)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>(<b>a</b>) The fluorescence spectra of NS-co-doped fluorescent carbon nanodots (NSCDs) as treated with different concentrations of methotrexate (MTX) ranging from 0–50.0 µM; the intensity decreases as the concentration of MTX increases and FRET is inhibited. The inset shows photographs that correspond to the increasing concentrations of MTX; (<b>b</b>) The linear relationship between fluorescence and MTX concentration. Reproduced with permission from Wang <span class="html-italic">et al.</span> [<a href="#B42-sensors-15-14766" class="html-bibr">42</a>]. Copyright 2015 Biosensors and Bioelectronics, Elsevier. PL, photoluminescence.</p> Full article ">Figure 2
<p>(<b>a</b>) Scheme showing the FRET process from upconverting phosphors (UCPs) to CNPs; (<b>b</b>) interference testing shows that the fluorescent intensity increases dramatically in the presence of thrombin. Reproduced with permission from Wang, Bao, Liu and Pang [<a href="#B84-sensors-15-14766" class="html-bibr">84</a>]. Copyright 2011 American Chemical Society.</p> Full article ">Figure 3
<p>Microscopic images of the NBD nanotubes upon the addition of the fluorescence acceptor dye QSY7, which quenches NBD via FRET. Reprinted with permission from Kameta <span class="html-italic">et al.</span> [<a href="#B85-sensors-15-14766" class="html-bibr">85</a>]. Copyright 2007 American Chemical Society.</p> Full article ">Figure 4
<p>FRET causes the aptamer to bind to graphene, thus quenching the fluorescence of an attached dye. The fluorescence is recovered when quadruplex-thrombin is formed, as it has a weak affinity to graphene, thus removing the dyes from the graphene. Reproduced with permission from Chang <span class="html-italic">et al.</span> [<a href="#B88-sensors-15-14766" class="html-bibr">88</a>]. Copyright 2010 American Chemical Society.</p> Full article ">Figure 5
<p>Intensity at donor emission (max 520 nm) of DNA-D-NT. (<b>a</b>) Förster resonance energy transfer (FRET) is clearly occurring, as indicated by the two alternating peaks. This, in turn, indicates DNA hybridization on nanotube surfaces. Emission of the donor on DNA-NT decreases with additions of attachment to the acceptor, thus the alternating peaks. The addition of complement conjugated with acceptor (cDNA-A) actually increases the donor emission at higher concentrations; (<b>b</b>) No FRET between donor and acceptor appears, indicating that there is no hybridization occurring, and the donor fluorescence remains significantly lower in the presence of cDNA-A than without it. Reproduced with permission from Jeng <span class="html-italic">et al.</span> [<a href="#B57-sensors-15-14766" class="html-bibr">57</a>]. Copyright 2006, American Chemical Society.</p> Full article ">Figure 6
<p>(<b>a</b>) Scheme showing DNA analysis using three probes (P5, P6, P7) in the presence of a blue T5 target; (<b>b</b>–<b>d</b>) fluorescence spectra for multicolor detection showing corresponding wavelengths when the probe is in the presence of different targets: (b) blue T5 at 494/526 nm/nm; (c) red T6 643/666 nm/nm; and (d) orange T7 587/609 nm/nm. Reproduced with permission from He <span class="html-italic">et al.</span> [<a href="#B90-sensors-15-14766" class="html-bibr">90</a>]. Copyright 2010 Advanced Functional Materials, John Wiley and Sons.</p> Full article ">
882 KiB  
Article
First-Principles Studies of Hydrogen Adsorption at Pd-SiO2 Interfaces
by Yoshihiro Irokawa and Mamoru Usami
Sensors 2015, 15(6), 14757-14765; https://doi.org/10.3390/s150614757 - 22 Jun 2015
Cited by 8 | Viewed by 5996
Abstract
The interaction of hydrogen with Pd-SiO2 interfaces has been investigated for the first time using first-principles calculations based on density functional theory. The hydrogen-induced polarization at the Pd-SiO2 interfaces was evaluated using Pd-SiO2 interface supercells. As a result, the potential [...] Read more.
The interaction of hydrogen with Pd-SiO2 interfaces has been investigated for the first time using first-principles calculations based on density functional theory. The hydrogen-induced polarization at the Pd-SiO2 interfaces was evaluated using Pd-SiO2 interface supercells. As a result, the potential change induced by interfacial hydrogen atoms was not observed even for hydrogen concentration of ~1.3 × 1015 cm−2 at the Pd-SiO2 interface. This result implies that hydrogen does not create an electric double layer at the Pd-SiO2 interface but change the property of the SiO2 region, resulting in the hydrogen sensitivity of the devices. Full article
(This article belongs to the Section Chemical Sensors)
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Figure 1
<p>The atomic structure of the Pd-SiO<sub>2</sub> interface supercell. O, Si, H, and Pd atoms are depicted by the red, flesh color, yellow, and dull blue spheres, respectively.</p> Full article ">Figure 2
<p>The calculated density of states (DOS) of the generated SiO<sub>2</sub> structure.</p> Full article ">Figure 3
<p>The Pd-SiO<sub>2</sub> interface supercell with 24 hydrogen atoms adsorbed at both Pd-SiO<sub>2</sub> interfaces of the supercell, which corresponds to a hydrogen concentration of ~1.3 × 10<sup>15</sup> cm<sup>−2</sup> at the Pd-SiO<sub>2</sub> interface.</p> Full article ">Figure 4
<p>In-plane averaged potential along the interface normal with the two interface planes in the Pd-SiO<sub>2</sub> interface supercell before and after 24 hydrogen atom adsorption at the Pd-SiO<sub>2</sub> interfaces.</p> Full article ">Figure 5
<p>A charge-density difference plot of the Pd-SiO<sub>2</sub> interface supercell before and after 24 hydrogen atom adsorption at the Pd-SiO<sub>2</sub> interfaces. Charge accumulation/depletion regions are displayed in translucent red/green isosurface value by ± 0.1 e/Bohr<sup>3</sup>.</p> Full article ">
3413 KiB  
Article
Electrothermally-Actuated Micromirrors with Bimorph Actuators—Bending-Type and Torsion-Type
by Cheng-Hua Tsai, Chun-Wei Tsai, Hsu-Tang Chang, Shih-Hsiang Liu and Jui-Che Tsai
Sensors 2015, 15(6), 14745-14756; https://doi.org/10.3390/s150614745 - 22 Jun 2015
Cited by 17 | Viewed by 6394
Abstract
Three different electrothermally-actuated MEMS micromirrors with Cr/Au-Si bimorph actuators are proposed. The devices are fabricated with the SOIMUMPs process developed by MEMSCAP, Inc. (Durham, NC, USA). A silicon-on-insulator MEMS process has been employed for the fabrication of these micromirrors. Electrothermal actuation has achieved [...] Read more.
Three different electrothermally-actuated MEMS micromirrors with Cr/Au-Si bimorph actuators are proposed. The devices are fabricated with the SOIMUMPs process developed by MEMSCAP, Inc. (Durham, NC, USA). A silicon-on-insulator MEMS process has been employed for the fabrication of these micromirrors. Electrothermal actuation has achieved a large angular movement in the micromirrors. Application of an external electric current 0.04 A to the bending-type, restricted-torsion-type, and free-torsion-type mirrors achieved rotation angles of 1.69°, 3.28°, and 3.64°, respectively. Full article
(This article belongs to the Section Physical Sensors)
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Figure 1

Figure 1
<p>The 3-D schematic drawings of the (<b>a</b>) bending-type, (<b>b</b>) restricted-torsion-type and (<b>c</b>) free-torsion-type electrothermally-actuated micro-electro-mechanical systems (MEMS) mirrors. For simplicity, buried oxide is not shown.</p> Full article ">Figure 2
<p>Photos of the three different electrothermally-actuated MEMS mirrors: (<b>a</b>) bending-type, (<b>b</b>) restricted-torsion-type, and (<b>c</b>) free-torsion-type.</p> Full article ">Figure 3
<p>Schematic cross-section view along A–A’ of <a href="#sensors-15-14745-f002" class="html-fig">Figure 2</a>c. The structure details are depicted and the materials used are shown.</p> Full article ">Figure 4
<p>Experimental setup for measuring the rotation angle, corresponding voltage and electrical resistance of the MEMS mirror when an external electric current is applied.</p> Full article ">Figure 5
<p>Experimental results for the bending-type MEMS mirrors of different wire resistances: (<b>a</b>) optical microscope images; (<b>b</b>) rotation angles; (<b>c</b>) applied voltages; and (<b>d</b>) total resistances.</p> Full article ">Figure 6
<p>Experimental results for the restricted-torsion-type MEMS mirrors of different wire resistances: (<b>a</b>) optical microscope images; (<b>b</b>) rotation angles; (<b>c</b>) applied voltages; and (<b>d</b>) total resistances.</p> Full article ">Figure 7
<p>Experimental results for the free-torsion-type MEMS mirrors of different wire resistances: (<b>a</b>) optical microscope images; (<b>b</b>) rotation angles; (<b>c</b>) applied voltages; and (<b>d</b>) total resistances.</p> Full article ">Figure 8
<p>Schematic drawing of the experimental setup for tracing the light spot of the reflected laser beam.</p> Full article ">Figure 9
<p>Trace of the light spot on a screen of the reflected laser beam from the restricted-torsion-type mirror. In addition, the mirror postures at <span class="html-italic">i</span> = 0 A and 0.04 A are shown.</p> Full article ">
3486 KiB  
Article
A 3-Axis Miniature Magnetic Sensor Based on a Planar Fluxgate Magnetometer with an Orthogonal Fluxguide
by Chih-Cheng Lu and Jeff Huang
Sensors 2015, 15(6), 14727-14744; https://doi.org/10.3390/s150614727 - 19 Jun 2015
Cited by 37 | Viewed by 14449
Abstract
A new class of tri-axial miniature magnetometer consisting of a planar fluxgate structure with an orthogonal ferromagnetic fluxguide centrally situated over the magnetic cores is presented. The magnetic sensor possesses a cruciform ferromagnetic core placed diagonally upon the square excitation coil under which [...] Read more.
A new class of tri-axial miniature magnetometer consisting of a planar fluxgate structure with an orthogonal ferromagnetic fluxguide centrally situated over the magnetic cores is presented. The magnetic sensor possesses a cruciform ferromagnetic core placed diagonally upon the square excitation coil under which two pairs of pick-up coils for in-plane field detection are allocated. Effective principles and analysis of the magnetometer for 3-D field vectors are described and verified by numerically electromagnetic simulation for the excitation and magnetization of the ferromagnetic cores. The sensor is operated by applying the second-harmonic detection technique that can verify V-B relationship and device responsivity. Experimental characterization of the miniature fluxgate device demonstrates satisfactory spatial magnetic field detection results in terms of responsivity and noise spectrum. As a result, at an excitation frequency of 50 kHz, a maximum in-plane responsivity of 122.4 V/T appears and a maximum out-of-plane responsivity of 11.6 V/T is obtained as well. The minimum field noise spectra are found to be 0.11 nT/√Hz and 6.29 nT/√Hz, respectively, in X- and Z-axis at 1 Hz under the same excitation frequency. Compared with the previous tri-axis fluxgate devices, this planar magnetic sensor with an orthogonal fluxguide provides beneficial enhancement in both sensory functionality and manufacturing simplicity. More importantly, this novel device concept is considered highly suitable for the extension to a silicon sensor made by the current CMOS-MEMS technologies, thus emphasizing its emerging applications of field detection in portable industrial electronics. Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 1)
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Figure 1

Figure 1
<p>(<b>a</b>) Conceptual schematic of the planar fluxgate structure with an orthogonal fluxguide; (<b>b</b>) the PCB-based tri-axis fluxgate magnetometer. Note that all pick-up coils are implemented on the back side of the PCB.</p> Full article ">Figure 2
<p>Flux line diagrams illustrate the sensing principle of the planar fluxgate only with a cruciform core and the cross-section is along the longitudinal core: (<b>a</b>) in X-axis sensing direction; (<b>b</b>) in Z-axis sensing direction.</p> Full article ">Figure 3
<p>Flux line diagrams illustrate the sensing principle of the planar fluxgate with a cruciform core and an orthogonal fluxguide, and the cross-section is along the longitudinal core: (<b>a</b>) in X-axis sensing direction; (<b>b</b>) in Z-axis sensing direction.</p> Full article ">Figure 4
<p>The theoretical magnetic flux density along the magnetic core <span class="html-italic">vs.</span> the distance from the core junction with respect to various wire width.</p> Full article ">Figure 5
<p>The theoretical magnetic flux density along the longitudinal core <span class="html-italic">vs.</span> the distance from the core junction with respect to various core width.</p> Full article ">Figure 6
<p>A 3-D model of a planar excitation coils and its simulated result with a 2-mm cruciform ferromagnetic core under the excitation current of 5 A.</p> Full article ">Figure 7
<p>A 3-D modeling and simulation result of a tri-axis planar device with a 2-mm cruciform ferromagnetic core and a fluxguide (<b>left</b>); The variation of magnetic flux density along the core is also available and the magnetic fields in Z-axis is 40 A/m (<b>right</b>).</p> Full article ">Figure 8
<p>A schematic diagram of the fluxgate magnetometer setup for characterization measurement.</p> Full article ">Figure 9
<p>In-plane sensor responsivity (e.g., X-axis) <span class="html-italic">vs.</span> the excitation current at 25 kHz and 50 kHz, respectively.</p> Full article ">Figure 10
<p>The orthogonal sensor responsivity (<span class="html-italic">i.e.</span>, Z-axis) <span class="html-italic">vs.</span> the excitation current at 25 kHz and 50 kHz excitation frequencies, respectively.</p> Full article ">Figure 11
<p>Field noise spectra of the magnetometer with 2-mm core width under different excitation frequencies in X- and Z-axis: (<b>a</b>) at 25 kHz; (<b>b</b>) at 50 kHz.</p> Full article ">Figure 12
<p>Comparison of the maximum field noise spectral density results under different excitation frequencies in X- and Z-axis.</p> Full article ">Figure 13
<p>The frequency response result of the fluxgate with regard to the external field frequency.</p> Full article ">Figure 14
<p>The V-B diagram close to zero magnetism at different excitation frequencies in X-axis.</p> Full article ">Figure 15
<p>The geomagnetic measurement results of the planar fluxgate magnetometer as an electric compass under a excitation frequency of 25 kHz.</p> Full article ">Figure 16
<p>The error distribution of geomagnetic measurement for the in-plane axes with respect to the azimuth angle.</p> Full article ">
4549 KiB  
Article
Performance Analysis of Several GPS/Galileo Precise Point Positioning Models
by Akram Afifi and Ahmed El-Rabbany
Sensors 2015, 15(6), 14701-14726; https://doi.org/10.3390/s150614701 - 19 Jun 2015
Cited by 17 | Viewed by 5891
Abstract
This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference [...] Read more.
This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage of the IGS-MGEX network products to correct for the satellite differential code biases and the orbital and satellite clock errors. Natural Resources Canada’s GPSPace PPP software is modified to handle the various GPS/Galileo PPP models. A total of six data sets of GPS and Galileo observations at six IGS stations are processed to examine the performance of the various PPP models. It is shown that the traditional un-differenced GPS/Galileo PPP model, the GPS decoupled clock model, and the semi-decoupled clock GPS/Galileo PPP model improve the convergence time by about 25% in comparison with the un-differenced GPS-only model. In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model. Moreover, the BSSD GPS/Galileo PPP model improves the solution convergence time by about 50%, in comparison with the un-differenced GPS PPP model, regardless of the type of BSSD combination used. As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model. Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems)
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<p>Average 2014 IGS receiver DCB for GPS and Galileo signals.</p> Full article ">Figure 2
<p>Average IGS 2014 satellite DCB for both GPS/Galileo signals.</p> Full article ">Figure 3
<p>IGS and decoupled clock corrections 26 August 2012.</p> Full article ">Figure 3 Cont.
<p>IGS and decoupled clock corrections 26 August 2012.</p> Full article ">Figure 4
<p>IGS and decoupled clock corrections 27 August 2012.</p> Full article ">Figure 5
<p>IGS and decoupled clock corrections 5 April 2013.</p> Full article ">Figure 6
<p>Analysis stations.</p> Full article ">Figure 7
<p>Postioining results of the traditional GPS/Galileo PPP model.</p> Full article ">Figure 8
<p>Ambiguity parameters the traditional GPS/Galileo PPP model.</p> Full article ">Figure 9
<p>Positioning results of the GPS decoupled clock model.</p> Full article ">Figure 10
<p>Receiver clock errors of the GPS decoupled clock model.</p> Full article ">Figure 11
<p>Ambiguity parameters of the GPS decoupled clock model.</p> Full article ">Figure 12
<p>Positioning results of the semi-decoupled clock PPP model.</p> Full article ">Figure 13
<p>Receiver clock errors of the semi-decoupled clock GPS/Galileo PPP model.</p> Full article ">Figure 14
<p>Ambiguity parameters of the semi-decoupled clock GPS/Galileo PPP model.</p> Full article ">Figure 15
<p>Inter-system bias of the semi-decoupled clock GPS/Galileo PPP model.</p> Full article ">Figure 16
<p>Positioning results of the BSSD PPP tight combination model using (<b>a</b>) GPS reference satellite; and (<b>b</b>) Galileo reference satellite</p> Full article ">Figure 17
<p>Ambiguity parameters the BSSD PPP tight combination model using (<b>a</b>) GPS reference satellite; and (<b>b</b>) Galileo reference satellite.</p> Full article ">Figure 18
<p>Positioning results of the BSSD PPP loose combination model.</p> Full article ">Figure 19
<p>Ambiguity parameters the BSSD PPP loose combination model.</p> Full article ">Figure 20
<p>Positioning results for BSSD semi-decoupled GPS/Galileo PPP model. (<b>a</b>) GPS reference satellite; and (<b>b</b>) Galileo reference satellite.</p> Full article ">Figure 21
<p>Ambiguity parameters the semi-decoupled GPS/Galileo PPP model (<b>a</b>) GPS reference satellite; and (<b>b</b>) Galileo reference satellite.</p> Full article ">Figure 22
<p>Positioning results of the semi-decoupled per-constellation GPS/Galileo BSSD PPP model.</p> Full article ">Figure 23
<p>Ambiguity parameters the semi-decoupled per-constellation GPS/Galileo BSSD PPP model.</p> Full article ">Figure 24
<p>Summary of convergence times of all stations and analysis cases. (<b>1</b>) Un-differenced GPS model; (<b>2</b>) Un-differenced GPS/Galileo model; (<b>3</b>) Decoupled clock model using GPS observations only; (<b>4</b>) semi-decoupled clock GPS/Galileo PPP model; (<b>5</b>) BSSD model with a GPS satellite as a reference; (<b>6</b>) BSSD model with a Galileo satellite as a reference; (<b>7</b>) BSSD model with both a GPS and a Galileo satellite as reference satellites; (<b>8</b>) BSSD semi-decoupled clock GPS/Galileo model with a GPS satellite as a reference; (<b>9</b>) BSSD semi-decoupled clock GPS/Galileo model with a Galileo satellite as a reference; (<b>10</b>) BSSD semi-decoupled clock GPS/Galileo model with both a GPS and a Galileo satellite as reference satellites.</p> Full article ">Figure 25
<p>Summary of positioning standard deviations in East, North, and Up directions of all stations and analysis cases. (<b>1</b>) Un-differenced GPS model; (<b>2</b>) Un-differenced GPS/Galileo model; (<b>3</b>) Decoupled clock model using GPS observations only; (<b>4</b>) semi-decoupled clock GPS/Galileo PPP model; (<b>5</b>) BSSD model with a GPS satellite as a reference; (<b>6</b>) BSSD model with a Galileo satellite as a reference; (<b>7</b>) BSSD model with both a GPS and a Galileo satellite as reference satellites; (<b>8</b>) BSSD semi-decoupled clock GPS/Galileo model with a GPS satellite as a reference; (<b>9</b>) BSSD semi-decoupled clock GPS/Galileo model with a Galileo satellite as a reference; (<b>10</b>) BSSD semi-decoupled clock GPS/Galileo model with both a GPS and a Galileo satellite as reference satellites.</p> Full article ">Figure 25 Cont.
<p>Summary of positioning standard deviations in East, North, and Up directions of all stations and analysis cases. (<b>1</b>) Un-differenced GPS model; (<b>2</b>) Un-differenced GPS/Galileo model; (<b>3</b>) Decoupled clock model using GPS observations only; (<b>4</b>) semi-decoupled clock GPS/Galileo PPP model; (<b>5</b>) BSSD model with a GPS satellite as a reference; (<b>6</b>) BSSD model with a Galileo satellite as a reference; (<b>7</b>) BSSD model with both a GPS and a Galileo satellite as reference satellites; (<b>8</b>) BSSD semi-decoupled clock GPS/Galileo model with a GPS satellite as a reference; (<b>9</b>) BSSD semi-decoupled clock GPS/Galileo model with a Galileo satellite as a reference; (<b>10</b>) BSSD semi-decoupled clock GPS/Galileo model with both a GPS and a Galileo satellite as reference satellites.</p> Full article ">
4195 KiB  
Article
Gaze-Assisted User Intention Prediction for Initial Delay Reduction in Web Video Access
by Seungyup Lee, Juwan Yoo and Gunhee Han
Sensors 2015, 15(6), 14679-14700; https://doi.org/10.3390/s150614679 - 19 Jun 2015
Cited by 13 | Viewed by 6924
Abstract
Despite the remarkable improvement of hardware and network technology, the inevitable delay from a user’s command action to a system response is still one of the most crucial influence factors in user experiences (UXs). Especially for a web video service, an initial delay [...] Read more.
Despite the remarkable improvement of hardware and network technology, the inevitable delay from a user’s command action to a system response is still one of the most crucial influence factors in user experiences (UXs). Especially for a web video service, an initial delay from click action to video start has significant influences on the quality of experience (QoE). The initial delay of a system can be minimized by preparing execution based on predicted user’s intention prior to actual command action. The introduction of the sequential and concurrent flow of resources in human cognition and behavior can significantly improve the accuracy and preparation time for intention prediction. This paper introduces a threaded interaction model and applies it to user intention prediction for initial delay reduction in web video access. The proposed technique consists of a candidate selection module, a decision module and a preparation module that prefetches and preloads the web video data before a user’s click action. The candidate selection module selects candidates in the web page using proximity calculation around a cursor. Meanwhile, the decision module computes the possibility of actual click action based on the cursor-gaze relationship. The preparation activates the prefetching for the selected candidates when the click possibility exceeds a certain limit in the decision module. Experimental results show a 92% hit-ratio, 0.5-s initial delay on average and 1.5-s worst initial delay, which is much less than a user’s tolerable limit in web video access, demonstrating significant improvement of accuracy and advance time in intention prediction by introducing the proposed threaded interaction model. Full article
(This article belongs to the Special Issue HCI In Smart Environments)
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<p>Process flow of web access. (<b>a</b>) Typical web video access; (<b>b</b>) web video access using the proposed user intention prediction.</p> Full article ">
<p>(<b>a</b>) General framework of threaded interaction model (TIM); (<b>b</b>) proposed TIM.</p> Full article ">
<p>(<b>a</b>) A video website layout; (<b>b</b>) mouse event pattern of the video website used; (<b>c</b>) gaze event pattern of the video website used.</p> Full article ">
<p>(<b>a</b>) An example of the cursor and gaze behavior; (<b>b</b>) the proposed threaded interaction model for user intention prediction in web video access.</p> Full article ">
<p>The proposed gaze-assisted user intention prediction based on TIM.</p> Full article ">
<p>Typical target selections and decision boundary on the feature space.</p> Full article ">
<p>Test environment of the proposed gaze-assisted user intention prediction. (<b>a</b>) Framework of the implemented test system; (<b>b</b>) gaze trackers; (<b>c</b>) SmartEye Pro gaze tracking software.</p> Full article ">
<p>Relationship between hit-ratio and initial delay. (<b>a</b>) Normalized histogram of the hit-ratio; (<b>b</b>) influence of the hit-ratio.</p> Full article ">
<p>Influence of preparation time. (<b>a</b>) Normalized histogram of preparation time; (<b>b</b>) initial delay depending on preparation time (the vertical axis is drawn in binary logarithmic scale.</p> Full article ">
9536 KiB  
Article
Radar Sensing for Intelligent Vehicles in Urban Environments
by Giulio Reina, David Johnson and James Underwood
Sensors 2015, 15(6), 14661-14678; https://doi.org/10.3390/s150614661 - 19 Jun 2015
Cited by 71 | Viewed by 10052
Abstract
Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the [...] Read more.
Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the sensor frame, without the need for a separate synchronised navigation source, calibration parameters describing the location of the radar in the vehicle frame, or the geometric restrictions made in the previous main method in the field. Experimental results are presented in various urban scenarios to validate this approach, showing its potential applicability for advanced driving assistance systems and autonomous vehicle operations. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
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<p>A vehicle equipped with a millimetre-wave (MMW) radar to perform terrain analysis.</p> Full article ">
<p>Example of radar image (<b>Left</b>). Note that the forward direction of the vehicle is marked by the black line. Front view of the vehicle (<b>Right</b>), as acquired by a co-located camera.</p> Full article ">
<p>Change in the ground-echo model for increasing grazing angles, as indicated by the arrow in figure (<span class="html-italic">R</span><sub>0</sub> = 15 <span class="html-italic">m</span>, <span class="html-italic">I<sub>R</sub></span><sub><sub>0</sub></sub> = 65 <span class="html-italic">dB</span>), <span class="html-italic">θ<sub>g</sub></span> = 3−12° (<b>a</b>); Change in the footprint and range-spread as a function of <span class="html-italic">θ<sub>g</sub></span> while <span class="html-italic">R</span><sub>0</sub> is kept constant (<b>b</b>).</p> Full article ">
<p>Radar beam model for flat, horizontal ground, up view (<b>a</b>); Uphill ground in view of the radar (<b>b</b>).</p> Full article ">
<p>Radar-based ground detection in a general environment where motion plane and area under investigation do not coincide.</p> Full article ">
<p>Example of good fit (SE = 94.0 <span class="html-italic">dB</span><sup>2</sup>) (<b>a</b>), and poor fit (SE = 913.1 <span class="html-italic">dB</span><sup>2</sup>) (<b>b</b>). Black: radar observation. Grey: Radar-Centric Ground Detection (RCGD) ground echo model.</p> Full article ">
<p>Examples of false positives: an obstacle would be erroneously labeled as ground considering only the SE (<b>a</b>); an obstacle in the vicinity of ground would be flagged as ground (<b>b</b>). Black: radar observation. Grey: RCGD ground echo model.</p> Full article ">
<p>Histogram of the ground model features in the training set: squared error (Left), range spread (<b>Center</b>), maximum intensity (<b>Right</b>).</p> Full article ">
<p>The experimental platform Mantis (<b>a</b>); urban path followed during the experiment (<b>b</b>); performed by fastening Mantis on a manned utility vehicle (<b>c</b>).</p> Full article ">
19277 KiB  
Article
Loop Closing Detection in RGB-D SLAM Combining Appearance and Geometric Constraints
by Heng Zhang, Yanli Liu and Jindong Tan
Sensors 2015, 15(6), 14639-14660; https://doi.org/10.3390/s150614639 - 19 Jun 2015
Cited by 18 | Viewed by 8155
Abstract
A kind of multi feature points matching algorithm fusing local geometric constraints is proposed for the purpose of quickly loop closing detection in RGB-D Simultaneous Localization and Mapping (SLAM). The visual feature is encoded with BRAND (binary robust appearance and normals descriptor), which [...] Read more.
A kind of multi feature points matching algorithm fusing local geometric constraints is proposed for the purpose of quickly loop closing detection in RGB-D Simultaneous Localization and Mapping (SLAM). The visual feature is encoded with BRAND (binary robust appearance and normals descriptor), which efficiently combines appearance and geometric shape information from RGB-D images. Furthermore, the feature descriptors are stored using the Locality-Sensitive-Hashing (LSH) technique and hierarchical clustering trees are used to search for these binary features. Finally, the algorithm for matching of multi feature points using local geometric constraints is provided, which can effectively reject the possible false closure hypotheses. We demonstrate the efficiency of our algorithms by real-time RGB-D SLAM with loop closing detection in indoor image sequences taken with a handheld Kinect camera and comparative experiments using other algorithms in RTAB-Map dealing with a benchmark dataset. Full article
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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<p>The diagram of loop closing. There is a certain degree of error in the observation of each step. When the robot (or the camera) observes the area that have been seen in the past, a new constraint can be added to correct a series of poses. This may be repeated several times. With these new constraints, the accumulated error of map building and localization can be considerably reduced.</p> Full article ">
<p>The schematic diagram of LSH.</p> Full article ">
<p>Illustration for the matching of multi feature points using local geometric constraints. (<b>a</b>) For each one of the two salient points, 3D point relative to the camera coordinate system is computed using the depth information, and then 3D distance <span class="html-italic">d<sub>S<sub>i</sub></sub></span> in between salient points can be calculated; (<b>b</b>) The binary descriptors are computed for two salient points in the query image, these descriptors are used to retrieve best binary match from the hash table Q. The distance <span class="html-italic">d<sub>xy<sub>i</sub></sub></span> in between pairs of 3D points in the world (map points) can be calculated.</p> Full article ">
<p>Experimental results of the sequence captured in our lab using our algorithms. (<b>a</b>) at 148 s; (<b>b</b>) at 167 s; (<b>c</b>) at 189 s; (<b>d</b>) at 190 s; (<b>e</b>) at 205 s; (<b>f</b>) the final map.</p> Full article ">
<p>Total processing time of every key frame of the sequence captured in our lab using our approach.</p> Full article ">
<p>Loop closure detection for the sequence captured in our lab using our approach.</p> Full article ">
<p>Experimental results of sequence “freiburg3_long_office_household”. (<b>a</b>) at 66 s; (<b>b</b>) at 68 s; (<b>c</b>) at 70 s; (<b>d</b>) at 71 s; (<b>e</b>) at 72 s; (<b>f</b>) at 81 s.</p> Full article ">
2458 KiB  
Article
Fingerprint Liveness Detection in the Presence of Capable Intruders
by Ana F. Sequeira and Jaime S. Cardoso
Sensors 2015, 15(6), 14615-14638; https://doi.org/10.3390/s150614615 - 19 Jun 2015
Cited by 25 | Viewed by 6711
Abstract
Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the use of a previously known material. This assumption [...] Read more.
Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the use of a previously known material. This assumption has led to the use of supervised techniques to estimate the performance of the methods, using both live and spoof samples to train the predictive models and evaluate each type of fake samples individually. Additionally, the background was often included in the sample representation, completely distorting the decision process. Therefore, we propose that an automatic segmentation step should be performed to isolate the fingerprint from the background and truly decide on the liveness of the fingerprint and not on the characteristics of the background. Also, we argue that one cannot aim to model the fake samples completely since the material used by the intruder is unknown beforehand. We approach the design by modeling the distribution of the live samples and predicting as fake the samples very unlikely according to that model. Our experiments compare the performance of the supervised approaches with the semi-supervised ones that rely solely on the live samples. The results obtained differ from the ones obtained by the more standard approaches which reinforces our conviction that the results in the literature are misleadingly estimating the true vulnerability of the biometric system. Full article
(This article belongs to the Section Physical Sensors)
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<p>Fingerprint recognition system block diagram.</p> Full article ">
<p>Finger Play-Doh mold and silicon model.</p> Full article ">
<p>Example of differences in background area in two pairs of real and fake fingerprint images from two different datasets (images were degraded for privacy purposes). (<b>a</b>) Pair of real and fake fingerprint images with a small area of background (Biometrika dataset); (<b>b</b>) Pair of real and fake fingerprint images with a significant area of background (Crossmatch dataset).</p> Full article ">
<p>Illustrative Example. Black crosses and dark blue circles are fake and real samples in the training set. Light blue circles are real samples; gray crosses are fake samples from materials present in the training set; orange crosses are fake samples from a new material. The red curve represents the model learnt from the training samples.</p> Full article ">
<p>Main steps of the segmentation method (adapted from [<a href="#b34-sensors-15-14615" class="html-bibr">34</a>]).</p> Full article ">
<p>Examples of the result obtained by the segmentation method (images were degraded for privacy purposes). (<b>a</b>) Pair of original and segmented fingerprint images (Biometrika dataset); (<b>b</b>) Pair of original and segmented fingerprint images (Crossmatch dataset).</p> Full article ">
6919 KiB  
Article
Citizen Sensors for SHM: Towards a Crowdsourcing Platform
by Ekin Ozer, Maria Q. Feng and Dongming Feng
Sensors 2015, 15(6), 14591-14614; https://doi.org/10.3390/s150614591 - 19 Jun 2015
Cited by 76 | Viewed by 8648
Abstract
This paper presents an innovative structural health monitoring (SHM) platform in terms of how it integrates smartphone sensors, the web, and crowdsourcing. The ubiquity of smartphones has provided an opportunity to create low-cost sensor networks for SHM. Crowdsourcing has given rise to citizen [...] Read more.
This paper presents an innovative structural health monitoring (SHM) platform in terms of how it integrates smartphone sensors, the web, and crowdsourcing. The ubiquity of smartphones has provided an opportunity to create low-cost sensor networks for SHM. Crowdsourcing has given rise to citizen initiatives becoming a vast source of inexpensive, valuable but heterogeneous data. Previously, the authors have investigated the reliability of smartphone accelerometers for vibration-based SHM. This paper takes a step further to integrate mobile sensing and web-based computing for a prospective crowdsourcing-based SHM platform. An iOS application was developed to enable citizens to measure structural vibration and upload the data to a server with smartphones. A web-based platform was developed to collect and process the data automatically and store the processed data, such as modal properties of the structure, for long-term SHM purposes. Finally, the integrated mobile and web-based platforms were tested to collect the low-amplitude ambient vibration data of a bridge structure. Possible sources of uncertainties related to citizens were investigated, including the phone location, coupling conditions, and sampling duration. The field test results showed that the vibration data acquired by smartphones operated by citizens without expertise are useful for identifying structural modal properties with high accuracy. This platform can be further developed into an automated, smart, sustainable, cost-free system for long-term monitoring of structural integrity of spatially distributed urban infrastructure. Citizen Sensors for SHM will be a novel participatory sensing platform in the way that it offers hybrid solutions to transitional crowdsourcing parameters. Full article
(This article belongs to the Special Issue Sensors and Smart Cities)
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Figure 1

Figure 1
<p>Integration scheme of system platforms.</p> Full article ">Figure 2
<p>User login, recording, and submission screenshots, respectively.</p> Full article ">Figure 3
<p>Digital signal processing operations applied on the server-side.</p> Full article ">Figure 4
<p>Screenshot from the web interface showing the SHM results page.</p> Full article ">Figure 5
<p>Inner and outer views, dimensions, and sensor layout of the pedestrian link bridge.</p> Full article ">Figure 6
<p>1st, 2nd, and 3rd modal frequencies (8.46, 18.95, 29.67 Hz) and mode shapes from FDD by reference accelerometers.</p> Full article ">Figure 7
<p>Acceleration time histories and Fourier spectra samples from Test 3 and Test 6.</p> Full article ">Figure 8
<p>Fourier spectra from the average of 40 samples for Test 1–6.</p> Full article ">Figure 9
<p>Identified frequencies obtained from different samples.</p> Full article ">Figure 10
<p>Arias intensities obtained from different samples.</p> Full article ">Figure 11
<p>Modal identification results from Test 1–6 and crowdsourcing.</p> Full article ">Figure 12
<p>Acceleration time histories and Fourier spectra samples from pedestrian-induced vibrations.</p> Full article ">
648 KiB  
Article
On-Board Event-Based State Estimation for Trajectory Approaching and Tracking of a Vehicle
by Miguel Martínez-Rey, Felipe Espinosa, Alfredo Gardel and Carlos Santos
Sensors 2015, 15(6), 14569-14590; https://doi.org/10.3390/s150614569 - 19 Jun 2015
Cited by 17 | Viewed by 6606
Abstract
For the problem of pose estimation of an autonomous vehicle using networked external sensors, the processing capacity and battery consumption of these sensors, as well as the communication channel load should be optimized. Here, we report an event-based state estimator (EBSE) consisting of [...] Read more.
For the problem of pose estimation of an autonomous vehicle using networked external sensors, the processing capacity and battery consumption of these sensors, as well as the communication channel load should be optimized. Here, we report an event-based state estimator (EBSE) consisting of an unscented Kalman filter that uses a triggering mechanism based on the estimation error covariance matrix to request measurements from the external sensors. This EBSE generates the events of the estimator module on-board the vehicle and, thus, allows the sensors to remain in stand-by mode until an event is generated. The proposed algorithm requests a measurement every time the estimation distance root mean squared error (DRMS) value, obtained from the estimator’s covariance matrix, exceeds a threshold value. This triggering threshold can be adapted to the vehicle’s working conditions rendering the estimator even more efficient. An example of the use of the proposed EBSE is given, where the autonomous vehicle must approach and follow a reference trajectory. By making the threshold a function of the distance to the reference location, the estimator can halve the use of the sensors with a negligible deterioration in the performance of the approaching maneuver. Full article
(This article belongs to the Special Issue Cyber-Physical Systems)
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<p>General description of the system showing the most important elements: the vehicle (controller and estimator) and sensors linked by a wireless network.</p> Full article ">
<p>Flowchart of the event-based state estimator (EBSE), executed by the vehicle and the sensors.</p> Full article ">
<p>Diagram explaining the relation <a href="#FD26" class="html-disp-formula">Equation (26)</a> between the distance to the reference location and the size of the uncertainty region.</p> Full article ">
<p>Adaptive distance threshold function <span class="html-italic">D</span><sub>thr</sub> as a function of the distance to the reference location.</p> Full article ">
<p>Diagram showing the reference trajectory and the camera locations. Each camera's field of view (FOV) is given.</p> Full article ">
<p>Comparison of the trajectory followed by the three sampling schemes, as well as the reference trajectory. The position of the camera sensors and their field-of-view (FOV) are also shown.</p> Full article ">
<p>Measurement rate and evolution of the distance root mean squared error (DRMS) over time for the three estimation methods. The threshold values are also shown. The approaching time (until the eighth second of the simulation) is zoomed in the plot in the top left corner.</p> Full article ">
<p>Distance to the point of the corresponding reference trajectory over time for the first eight seconds of the simulation (approaching time).</p> Full article ">
1484 KiB  
Review
DNA-Based Nanobiosensors as an Emerging Platform for Detection of Disease
by Khalid M. Abu-Salah, Mohammed M. Zourob, Fouzi Mouffouk, Salman A. Alrokayan, Manal A. Alaamery and Anees A. Ansari
Sensors 2015, 15(6), 14539-14568; https://doi.org/10.3390/s150614539 - 19 Jun 2015
Cited by 109 | Viewed by 16476
Abstract
Detection of disease at an early stage is one of the biggest challenges in medicine. Different disciplines of science are working together in this regard. The goal of nanodiagnostics is to provide more accurate tools for earlier diagnosis, to reduce cost and to [...] Read more.
Detection of disease at an early stage is one of the biggest challenges in medicine. Different disciplines of science are working together in this regard. The goal of nanodiagnostics is to provide more accurate tools for earlier diagnosis, to reduce cost and to simplify healthcare delivery of effective and personalized medicine, especially with regard to chronic diseases (e.g., diabetes and cardiovascular diseases) that have high healthcare costs. Up-to-date results suggest that DNA-based nanobiosensors could be used effectively to provide simple, fast, cost-effective, sensitive and specific detection of some genetic, cancer, and infectious diseases. In addition, they could potentially be used as a platform to detect immunodeficiency, and neurological and other diseases. This review examines different types of DNA-based nanobiosensors, the basic principles upon which they are based and their advantages and potential in diagnosis of acute and chronic diseases. We discuss recent trends and applications of new strategies for DNA-based nanobiosensors, and emphasize the challenges in translating basic research to the clinical laboratory. Full article
(This article belongs to the Section Biosensors)
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Figure 1

Figure 1
<p>A schematic diagram shows basic biosensor assembly with a biological recognition element, transducer, and processor.</p> Full article ">Figure 2
<p>Different types of nanostructures-based transducers to which DNA can be attached.</p> Full article ">Figure 3
<p>Chemical structure of the QDs-ConA-β-CDs-AuNPs nanobiosensor and schematic illustration of its FRET-based operating principles.</p> Full article ">Figure 4
<p>Schematic presentation of immobilization of thiolated single-stranded probe DNA on the surface of ZnO for hybridization detection in double-stranded DNA (target DNA).</p> Full article ">Figure 5
<p>Schematic illustration of preparation of the nanostructured film of mixed (DNA-nanomaterial/SPE) [<a href="#B113-sensors-15-14539" class="html-bibr">113</a>].</p> Full article ">Figure 6
<p>QD-aptamer conjugate serving as both a drug delivery vehicle and a fluorescence imaging agent.</p> Full article ">
860 KiB  
Article
Simultaneous Voltammetric/Amperometric Determination of Sulfide and Nitrite in Water at BDD Electrode
by Anamaria Baciu, Magdalena Ardelean, Aniela Pop, Rodica Pode and Florica Manea
Sensors 2015, 15(6), 14526-14538; https://doi.org/10.3390/s150614526 - 19 Jun 2015
Cited by 31 | Viewed by 7213
Abstract
This work reported new voltammetric/amperometric-based protocols using a commercial boron-doped diamond (BDD) electrode for simple and fast simultaneous detection of sulfide and nitrite from water. Square-wave voltammetry operated under the optimized working conditions of 0.01 V step potential, 0.5 V modulation amplitude and [...] Read more.
This work reported new voltammetric/amperometric-based protocols using a commercial boron-doped diamond (BDD) electrode for simple and fast simultaneous detection of sulfide and nitrite from water. Square-wave voltammetry operated under the optimized working conditions of 0.01 V step potential, 0.5 V modulation amplitude and 10 Hz frequency allowed achieving the best electroanalytical parameters for the simultaneous detection of nitrite and sulfide. For practical in-field detection applications, the multiple-pulsed amperometry technique was operated under optimized conditions, i.e., −0.5 V/SCE for a duration of 0.3 s as conditioning step, +0.85 V/SCE for a duration of 3 s that assure the sulfide oxidation and +1.25 V/SCE for a duration of 0.3 s, where the nitrite oxidation occurred, which allowed the simultaneously detection of sulfide and nitrite without interference between them. Good accuracy was found for this protocol in comparison with standardized methods for each anion. Also, no interference effect was found for the cation and anion species, which are common in the water matrix. Full article
(This article belongs to the Section Chemical Sensors)
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Figure 1

Figure 1
<p>(<b>a</b>) Cyclic voltammograms recorded at a BDD electrode in 0.1 M Na<sub>2</sub>SO<sub>4</sub> supporting electrolyte (curve 1) in the presence of 0.02–0.1 mM sulfide (curves 2–5; Inset of figure), and 0.02–0.1 mM nitrite (curves 6–10) at a potential scan rate of 0.05 Vs<sup>−1</sup> in a potential range from +0.5 to +1.5 V/SCE; (<b>b</b>) Calibration plots of the current <span class="html-italic">vs</span>. anion concentration recorded at E = +0.89 V <span class="html-italic">vs</span>. SCE for sulfide and E = +1.4 V <span class="html-italic">vs.</span> SCE for nitrite.</p> Full article ">Figure 2
<p>(<b>a</b>) Differential-pulsed voltammograms recorded at the BDD electrode in 0.1 M Na<sub>2</sub>SO<sub>4</sub> supporting electrolyte (curve 1) in a mixture of 0.02–0.2 mM sulfide and nitrite (curves 2–11), under 0.2 V modulation amplitude, 0.01 V step potential, and 0.1 V·s<sup>−1</sup> scan rate in a potential range from +0.25 to +1.5 V/SCE; (<b>b</b>) Calibration plot of the current <span class="html-italic">vs</span>. anions concentration recorded at E= +0.775 V <span class="html-italic">vs</span>. SCE for sulfide, respectively, and at E = +1.275 V <span class="html-italic">vs</span>. SCE for nitrite.</p> Full article ">Figure 3
<p>(<b>a</b>) Square-wave voltammograms recorded on a BDD electrode under 0.01 V step potential and 0.2 V modulation amplitude, 10 Hz frequency, 0.1 V·s<sup>−1</sup> scan rate, between −0.25 and +1.5 V <span class="html-italic">vs</span>. SCE in 0.1 M Na<sub>2</sub>SO<sub>4</sub> supporting electrolyte (curve 1) and in the presence of mixtures of 0.02–0.2 mM sulfide and nitrite concentrations (curves 2–11); (<b>b</b>) Calibration plots of the current <span class="html-italic">vs</span>. anion concentrations recorded at: E = +0.8 V/SCE for sulfide concentration and E = +1.3 V/SCE for nitrite concentration.</p> Full article ">Figure 4
<p>(<b>a</b>) Square-wave voltammograms recorded on a BDD electrode under 0.01 V step potential and 0.2 V modulation amplitude, 10 Hz frequency, scan rate 0.1 V·s<sup>−1</sup>, between −0.25 and +1.5 V <span class="html-italic">vs</span>. SCE in 0.1 M Na<sub>2</sub>SO<sub>4</sub> supporting electrolyte (curve 1) in the presence of 0.02–0.1 mM mixtures of sulfide (curves 2–6; Inset of figure), and 0.02–0.1 mM nitrite (curves 7–11). (<b>b</b>) Calibration plots of the current <span class="html-italic">vs</span>. anion concentration recorded at: E = 0.8 V/SCE <span class="html-italic">vs</span>. sulfide concentration and E = +1.3 V/SCE <span class="html-italic">vs</span>. nitrite concentration.</p> Full article ">Figure 5
<p>(<b>a</b>) Chronoamperograms recorded at BDD electrode in 0.1 M Na<sub>2</sub>SO<sub>4</sub> supporting electrolyte (curve 1) in the presence of 0.02–0.1 mM nitrite (curves 2–6) in a mixture of 0.02–0.1 mM sulfide and 0.1 mM nitrite (curves 7–11), at the potential values of E<sub>1</sub> = +0.85 V/SCE for sulfide and E<sub>2</sub> = +1.25 V/SCE for nitrite; (<b>b</b>) Calibration plot of the current <span class="html-italic">vs</span>. anion concentration recorded at E<sub>1</sub> = +0.85 V/SCE for sulfide (curves 7–11), respectively E<sub>2</sub> = +1.25 V/SCE (curves 2–6) for nitrite.</p> Full article ">Figure 6
<p>(<b>a</b>) Multiple-pulsed amperograms recorded at a BDD electrode in 0.1 M Na<sub>2</sub>SO<sub>4</sub> supporting electrolyte and adding consecutively and continuously each of 0.02 mM nitrite and respective, sulfide, recorded at E<sub>1</sub> = −0.5 V/SCE, E<sub>2</sub> = +0.85 V/SCE, E<sub>3</sub> = +1.25 V/SCE; (<b>b</b>) Calibration plot of the current <span class="html-italic">vs</span>. anion concentration recorded at: E<sub>2</sub> = +0.85 V/SCE <span class="html-italic">vs</span>. sulfide concentration and E<sub>3</sub> = +1.3 V/SCE <span class="html-italic">vs</span>. nitrite concentration.</p> Full article ">Figure 7
<p>(<b>a</b>) Multiple-pulsed amperograms recorded at a BDD electrode in 0.1 M Na<sub>2</sub>SO<sub>4</sub> supporting electrolyte and adding continuously a mixture of 0.02 mM NO<sub>2</sub><sup>−</sup> and 0.02 mM S<sup>2−</sup>, recorded at E<sub>1</sub> = −0.5 V/SCE, E<sub>2</sub> = +0.85 V/SCE, E<sub>3</sub> = +1.25 V/SCE; (<b>b</b>) Calibration plot of the current <span class="html-italic">vs</span>. anion concentration recorded at: E<sub>2</sub> = +0.85 V/SCE <span class="html-italic">vs</span>. sulfide concentration and E<sub>3</sub> = +1.3 V/SCE <span class="html-italic">vs</span>. nitrite concentration.</p> Full article ">
801 KiB  
Review
The Role of Infrared Thermography as a Non-Invasive Tool for the Detection of Lameness in Cattle
by Maher Alsaaod, Allan L. Schaefer, Wolfgang Büscher and Adrian Steiner
Sensors 2015, 15(6), 14513-14525; https://doi.org/10.3390/s150614513 - 18 Jun 2015
Cited by 56 | Viewed by 9054
Abstract
The use of infrared thermography for the identification of lameness in cattle has increased in recent years largely because of its non-invasive properties, ease of automation and continued cost reductions. Thermography can be used to identify and determine thermal abnormalities in animals by [...] Read more.
The use of infrared thermography for the identification of lameness in cattle has increased in recent years largely because of its non-invasive properties, ease of automation and continued cost reductions. Thermography can be used to identify and determine thermal abnormalities in animals by characterizing an increase or decrease in the surface temperature of their skin. The variation in superficial thermal patterns resulting from changes in blood flow in particular can be used to detect inflammation or injury associated with conditions such as foot lesions. Thermography has been used not only as a diagnostic tool, but also to evaluate routine farm management. Since 2000, 14 peer reviewed papers which discuss the assessment of thermography to identify and manage lameness in cattle have been published. There was a large difference in thermography performance in these reported studies. However, thermography was demonstrated to have utility for the detection of contralateral temperature difference and maximum foot temperature on areas of interest. Also apparent in these publications was that a controlled environment is an important issue that should be considered before image scanning. Full article
(This article belongs to the Section Physical Sensors)
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<p>Infrared thermography image of the right rear foot (lateral aspect) as described by Alsaaod <span class="html-italic">et al.</span> [<a href="#B26-sensors-15-14513" class="html-bibr">26</a>,<a href="#B28-sensors-15-14513" class="html-bibr">28</a>]. R1 is the area of interest for measurement of the maximal temperature of the coronary band, defined as the hottest pixel measured by thermography in the junction between the skin and the horn of the claw; R2 is the area of interest for measurement of the maximal temperature of the skin, defined as the hottest pixel measured by thermography in the skin area, neighbouring R1 proximally.</p> Full article ">
972 KiB  
Article
Hands-On Experiences in Deploying Cost-Effective Ambient-Assisted Living Systems
by Athanasios Dasios, Damianos Gavalas, Grammati Pantziou and Charalampos Konstantopoulos
Sensors 2015, 15(6), 14487-14512; https://doi.org/10.3390/s150614487 - 18 Jun 2015
Cited by 45 | Viewed by 11500
Abstract
Older adults’ preferences to remain independent in their own homes along with the high costs of nursing home care have motivated the development of Ambient Assisted Living (AAL) technologies which aim at improving the safety, health conditions and wellness of the elderly. This [...] Read more.
Older adults’ preferences to remain independent in their own homes along with the high costs of nursing home care have motivated the development of Ambient Assisted Living (AAL) technologies which aim at improving the safety, health conditions and wellness of the elderly. This paper reports hands-on experiences in designing, implementing and operating UbiCare, an AAL based prototype system for elderly home care monitoring. The monitoring is based on the recording of environmental parameters like temperature and light intensity as well as micro-level incidents which allows one to infer daily activities like moving, sitting, sleeping, usage of electrical appliances and plumbing components. The prototype is built upon inexpensive, off-the-shelf hardware (e.g., various sensors, Arduino microcontrollers, ZigBee-compatible wireless communication modules) and license-free software, thereby ensuring low system deployment costs. The network comprises nodes placed in a house’s main rooms or mounted on furniture, one wearable node, one actuator node and a centralized processing element (coordinator). Upon detecting significant deviations from the ordinary activity patterns of individuals and/or sudden falls, the system issues automated alarms which may be forwarded to authorized caregivers via a variety of communication channels. Furthermore, measured environmental parameters and activity incidents may be monitored through standard web interfaces. Full article
(This article belongs to the Special Issue Sensors and Smart Cities)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Plan view of the UbiCare deployment environment.</p> Full article ">Figure 2
<p>Experimental testbed architecture of UbiCare.</p> Full article ">Figure 3
<p>(<b>a</b>) The bathroom node; (<b>b</b>) the bedroom node; (<b>c</b>) the kitchen node; (<b>d</b>) magnetic contact switch mounted on the fridge; (<b>e</b>) the living room node; (<b>f</b>) the dining table chair’s force sensing resistor and node; (<b>g</b>) the wearable node; (<b>h</b>) the coordinator node.</p> Full article ">Figure 3 Cont.
<p>(<b>a</b>) The bathroom node; (<b>b</b>) the bedroom node; (<b>c</b>) the kitchen node; (<b>d</b>) magnetic contact switch mounted on the fridge; (<b>e</b>) the living room node; (<b>f</b>) the dining table chair’s force sensing resistor and node; (<b>g</b>) the wearable node; (<b>h</b>) the coordinator node.</p> Full article ">Figure 4
<p>Illustration of the hardware components and wiring of the bedroom node.</p> Full article ">Figure 5
<p>Schematic representation of the bedroom node’s pin connections.</p> Full article ">Figure 6
<p>Visualization of activity monitoring; (<b>a</b>) Time spent (minutes per hour for a selected day) on bed; (<b>b</b>) toilet flush activation occurrences per day.</p> Full article ">
1072 KiB  
Article
DEADS: Depth and Energy Aware Dominating Set Based Algorithm for Cooperative Routing along with Sink Mobility in Underwater WSNs
by Amara Umar, Nadeem Javaid, Ashfaq Ahmad, Zahoor Ali Khan, Umar Qasim, Nabil Alrajeh and Amir Hayat
Sensors 2015, 15(6), 14458-14486; https://doi.org/10.3390/s150614458 - 18 Jun 2015
Cited by 53 | Viewed by 6387
Abstract
Performance enhancement of Underwater Wireless Sensor Networks (UWSNs) in terms of throughput maximization, energy conservation and Bit Error Rate (BER) minimization is a potential research area. However, limited available bandwidth, high propagation delay, highly dynamic network topology, and high error probability leads to [...] Read more.
Performance enhancement of Underwater Wireless Sensor Networks (UWSNs) in terms of throughput maximization, energy conservation and Bit Error Rate (BER) minimization is a potential research area. However, limited available bandwidth, high propagation delay, highly dynamic network topology, and high error probability leads to performance degradation in these networks. In this regard, many cooperative communication protocols have been developed that either investigate the physical layer or the Medium Access Control (MAC) layer, however, the network layer is still unexplored. More specifically, cooperative routing has not yet been jointly considered with sink mobility. Therefore, this paper aims to enhance the network reliability and efficiency via dominating set based cooperative routing and sink mobility. The proposed work is validated via simulations which show relatively improved performance of our proposed work in terms the selected performance metrics. Full article
(This article belongs to the Section Sensor Networks)
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<p>Network model.</p> Full article ">
<p>Rule 3: <span class="html-italic">D<sub>D</sub></span> &lt;<span class="html-italic">D<sub>R</sub></span> &lt;<span class="html-italic">D<sub>S</sub></span>.</p> Full article ">
<p>Depth thresholds based on number of neighbors</p> Full article ">
<p>Selection of relay and destination nodes.</p> Full article ">
<p>Selection of <span class="html-italic">DS</span> and <span class="html-italic">CC</span> nodes in a sub-graph.</p> Full article ">
<p>Specifications of linear mobility path followed by MSs.</p> Full article ">
<p>Data routing in the network with linear sink mobility pattern.</p> Full article ">
<p>Specifications of elliptical mobility path followed by MSs.</p> Full article ">
<p>Data routing in the network with elliptical sink mobility pattern.</p> Full article ">
3560 KiB  
Article
Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars
by Shashidhar Patil, Harinadha Reddy Chintalapalli, Dubeom Kim and Youngho Chai
Sensors 2015, 15(6), 14435-14457; https://doi.org/10.3390/s150614435 - 18 Jun 2015
Cited by 7 | Viewed by 8090
Abstract
In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with [...] Read more.
In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems)
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Figure 1
<p>Dynamic gesture-based expressive control interface system.</p> Full article ">Figure 2
<p>Wireless motion sensor system.</p> Full article ">Figure 3
<p>Complementary filter block diagram.</p> Full article ">Figure 4
<p>Hand gesture segmentation and recognition.</p> Full article ">Figure 5
<p>Acceleration and gyro-based gesture segmentation.</p> Full article ">Figure 6
<p>Mimic gesture patterns for kicking and punching actions.</p> Full article ">Figure 7
<p>Expressive motion synthesis.</p> Full article ">Figure 8
<p>Avatar control using dynamic gesture mapping.</p> Full article ">Figure 9
<p>Kicking motions of avatar.</p> Full article ">Figure 10
<p>Punching motions of avatar.</p> Full article ">Figure 11
<p>Motion curves of RightUpLeg and LeftArm joints.</p> Full article ">Figure 12
<p>Spatial and temporal variations in kicking motions of avatar.</p> Full article ">
4189 KiB  
Article
Submersible Spectrofluorometer for Real-Time Sensing of Water Quality
by Adriana Puiu, Luca Fiorani, Ivano Menicucci, Marco Pistilli and Antonia Lai
Sensors 2015, 15(6), 14415-14434; https://doi.org/10.3390/s150614415 - 18 Jun 2015
Cited by 17 | Viewed by 8700
Abstract
In this work, we present a newly developed submersible spectrofluorometer (patent pending) applied to real-time sensing of water quality, suitable for monitoring some important indicators of the ecological status of natural waters such as chlorophyll-a, oil and protein-like material. For the optomechanical realization [...] Read more.
In this work, we present a newly developed submersible spectrofluorometer (patent pending) applied to real-time sensing of water quality, suitable for monitoring some important indicators of the ecological status of natural waters such as chlorophyll-a, oil and protein-like material. For the optomechanical realization of the apparatus, a novel conceptual design has been adopted in order to avoid filters and pumps while maintaining a high signal-to-noise ratio. The elimination of filters and pumps has the advantage of greater system simplicity and especially of avoiding the risk of sample degradation. The use of light-emitting diodes as an excitation source instead of Xe lamps or laser diodes helped save on size, weight, power consumption and costs. For sensor calibration we performed measurements on water samples with added chlorophyll prepared in the laboratory. The sensor functionality was tested during field campaigns conducted at Albano Lake in Latium Region of Italy as well as in the Herzliya Harbor, a few kilometers North East of Tel Aviv in Israel. The obtained results are reported in the paper. The sensitivity achieved for chlorophyll-a detection was found to be at least 0.2 µg/L. Full article
(This article belongs to the Special Issue Modern Technologies for Sensing Pollution in Air, Water, and Soil)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>LEDs used for fluorescence excitation: (<b>a</b>) UV-LED emitting 280 nm; (<b>b</b>) blue LED emitting 450 nm.</p> Full article ">Figure 2
<p>The water region observed by the spectrometer is illuminated by the UV and blue LEDs. Water and optoelectronic devices are separated by a quartz window (NHI-1191 by Helios Italquartz, Milan/Italy) with transmittance greater than 90%.</p> Full article ">Figure 3
<p>Technical drawing of the external chamber.</p> Full article ">Figure 4
<p>View of the chamber cover: A—safety pressure valve; B—electrical connector; C—gas inlet; D—quartz glass window covering the LEDs and the spectrometer.</p> Full article ">Figure 5
<p>Electronic layout of the sensor.</p> Full article ">Figure 6
<p>Detail of the electronic assembly: (<b>a</b>) printed circuit board; (<b>b</b>) assembled sensor.</p> Full article ">Figure 7
<p>Instrument block diagram.</p> Full article ">Figure 8
<p>Image of the assembled prototype.</p> Full article ">Figure 9
<p>Panel of the data processing software showing: (<b>a</b>) unprocessed spectra; (<b>b</b>) results of the automatic data processing.</p> Full article ">Figure 10
<p>Location of the two sites where the sensor was tested and some pictures taken during the campaigns: (<b>a</b>,<b>c</b>) Albano Lake (Italy); (<b>b</b>,<b>d</b>) Herzliya Harbor (Israel).</p> Full article ">Figure 11
<p>Geographical position of Stations 1, 2 and 3 in Herzliya Harbor.</p> Full article ">Figure 12
<p>Laboratory calibration: (<b>a</b>) spectra of Milli-Q water (C0) and five different concentrations of Chl-a in Milli-Q water (C1—most concentrated to C5—less concentrated); (<b>b</b>) graphical representation of the calibration data.</p> Full article ">Figure 13
<p>Clay interference on Chl-a detection (<b>a</b>); relative differences between the blank (sample without clay) and different turbid samples (<b>b</b>).</p> Full article ">Figure 14
<p>Effects of temperature on Chl-a detection (<b>a</b>); relative differences between the reference sample (4 °C) and samples of water containing a fixed amount of Chl-a at different temperatures (<b>b</b>).</p> Full article ">Figure 15
<p>Cyanobacteria (<span class="html-italic">P. rubescens</span>) fluorescence spectra.</p> Full article ">Figure 16
<p>Diesel oil, tryptophan and Milli-Q water fluorescence spectra measured upon excitation at 280 nm.</p> Full article ">
20188 KiB  
Article
Forward Looking Radar Imaging by Truncated Singular Value Decomposition and Its Application for Adverse Weather Aircraft Landing
by Yulin Huang, Yuebo Zha, Yue Wang and Jianyu Yang
Sensors 2015, 15(6), 14397-14414; https://doi.org/10.3390/s150614397 - 18 Jun 2015
Cited by 36 | Viewed by 6468
Abstract
The forward looking radar imaging task is a practical and challenging problem for adverse weather aircraft landing industry. Deconvolution method can realize the forward looking imaging but it often leads to the noise amplification in the radar image. In this paper, a forward [...] Read more.
The forward looking radar imaging task is a practical and challenging problem for adverse weather aircraft landing industry. Deconvolution method can realize the forward looking imaging but it often leads to the noise amplification in the radar image. In this paper, a forward looking radar imaging based on deconvolution method is presented for adverse weather aircraft landing. We first present the theoretical background of forward looking radar imaging task and its application for aircraft landing. Then, we convert the forward looking radar imaging task into a corresponding deconvolution problem, which is solved in the framework of algebraic theory using truncated singular decomposition method. The key issue regarding the selecting of the truncated parameter is addressed using generalized cross validation approach. Simulation and experimental results demonstrate that the proposed method is effective in achieving angular resolution enhancement with suppressing the noise amplification in forward looking radar imaging. Full article
(This article belongs to the Section Remote Sensors)
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<p>The diagram of scanning radar for aircraft landing.</p> Full article ">
<p>The diagram of signal model of forward looking radar.</p> Full article ">
<p>Antenna pattern.</p> Full article ">
<p>Location of targets in simulated scene.</p> Full article ">
<p>The definition of peak to valley point difference in dB.</p> Full article ">
<p>Angular super-resolution results obtained using different methods under SNR = 10 dB and 5 dB, respectively. (<b>a</b>) Echo data with noise level is 10 dB; (<b>b</b>) Angular super-resolution result of Guan's method after 15 iterations; (<b>c</b>) Angular super-resolution result of the proposed method; (<b>d</b>) Echo data with noise level is 0 dB; (<b>e</b>) Angular super-resolution result of Guan's method after 35 iterations; (<b>f</b>) Angular super-resolution results of the proposed method.</p> Full article ">
<p>The valuation of generalized cross-validation (GCV) function versus truncation parameters with different noise levels. (<b>a</b>) SNR = 10 dB; (<b>b</b>) SNR = 0 dB.</p> Full article ">
<p>(<b>a</b>) Evolution of the relative error (ReErr) along the noise SNRs for the simulations; (<b>b</b>) Evolution of the structure similarity (SSIM) along the noise SNRs for the simulations.</p> Full article ">
<p>(<b>a</b>) Optical image of imaging scene; (<b>b</b>) Radar platform and five corner reflectors in the scene; (<b>c</b>) The schematic plot of the distribution of trihedral reflector; (<b>d</b>) Enlargement of trihedral reflector.</p> Full article ">
1983 KiB  
Article
Managing Emergency Situations in the Smart City: The Smart Signal
by Ángel Asensio, Teresa Blanco, Rubén Blasco, Álvaro Marco and Roberto Casas
Sensors 2015, 15(6), 14370-14396; https://doi.org/10.3390/s150614370 - 18 Jun 2015
Cited by 22 | Viewed by 8087
Abstract
In a city there are numerous items, many of them unnoticed but essential; this is the case of the signals. Signals are considered objects with reduced technological interest, but in this paper we prove that making them smart and integrating in the IoT [...] Read more.
In a city there are numerous items, many of them unnoticed but essential; this is the case of the signals. Signals are considered objects with reduced technological interest, but in this paper we prove that making them smart and integrating in the IoT (Internet of Things) could be a relevant contribution to the Smart City. This paper presents the concept of Smart Signal, as a device conscious of its context, with communication skills, able to offer the best message to the user, and as a ubiquitous element that contributes with information to the city. We present the design considerations and a real implementation and validation of the system in one of the most challenging environments that may exist in a city: a tunnel. The main advantages of the Smart Signal are the improvement of the actual functionality of the signal providing new interaction capabilities with users and a new sensory mechanism of the Smart City. Full article
(This article belongs to the Special Issue Sensors and Smart Cities)
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<p>Smart Signal architecture.</p> Full article ">Figure 2
<p>Operation cycle of Smart Signal.</p> Full article ">Figure 3
<p><span class="html-italic">Smart Signal</span> concept applied to emergency signaling in tunnels. The Smart Signals provide indications adapted to the emergency characteristics.</p> Full article ">Figure 4
<p>Render and signal prototype.</p> Full article ">Figure 5
<p>Signal layers scheme: pictogram, retro-reflective, photo-luminescent, and LED layers.</p> Full article ">Figure 6
<p>Block diagram of the electronic device.</p> Full article ">Figure 7
<p>Electronic device.</p> Full article ">Figure 8
<p>Smart Signal System infrastructure.</p> Full article ">Figure 9
<p>Gateway software architecture.</p> Full article ">Figure 10
<p>Uses of a <span class="html-italic">Smart Signal</span> with phosphorescent support.</p> Full article ">Figure 11
<p>Distribution of routers and <span class="html-italic">Smart Signals</span> in Monrepos I tunnel.</p> Full article ">Figure 12
<p>Details of setup around coordination station (scenario to test the perception).</p> Full article ">Figure 13
<p>Snapshot during setup process. The closest signal (hanging on the wall) is turned off and the rest are turned on.</p> Full article ">Figure 14
<p>Examples of scenarios for simulating an emergency (in each of them, the emergency exit is a virtual point only known to the evaluator.</p> Full article ">Figure 15
<p>Routes and signals that depend on each router: (<b>a</b>) Initial snapshot; (<b>b</b>,<b>c</b>) simulating successive drop of nodes.</p> Full article ">Figure 16
<p>Latency intervals (within a 95% interval) of signals.</p> Full article ">
2522 KiB  
Article
Application of Cavity Enhanced Absorption Spectroscopy to the Detection of Nitric Oxide, Carbonyl Sulphide, and Ethane—Breath Biomarkers of Serious Diseases
by Jacek Wojtas
Sensors 2015, 15(6), 14356-14369; https://doi.org/10.3390/s150614356 - 17 Jun 2015
Cited by 35 | Viewed by 7251
Abstract
The paper presents one of the laser absorption spectroscopy techniques as an effective tool for sensitive analysis of trace gas species in human breath. Characterization of nitric oxide, carbonyl sulphide and ethane, and the selection of their absorption lines are described. Experiments with [...] Read more.
The paper presents one of the laser absorption spectroscopy techniques as an effective tool for sensitive analysis of trace gas species in human breath. Characterization of nitric oxide, carbonyl sulphide and ethane, and the selection of their absorption lines are described. Experiments with some biomarkers showed that detection of pathogenic changes at the molecular level is possible using this technique. Thanks to cavity enhanced spectroscopy application, detection limits at the ppb-level and short measurements time (<3 s) were achieved. Absorption lines of reference samples of the selected volatile biomarkers were probed using a distributed feedback quantum cascade laser and a tunable laser system consisting of an optical parametric oscillator and difference frequency generator. Setup using the first source provided a detection limit of 30 ppb for nitric oxide and 250 ppb for carbonyl sulphide. During experiments employing a second laser, detection limits of 0.9 ppb and 0.3 ppb were obtained for carbonyl sulphide and ethane, respectively. The conducted experiments show that this type of diagnosis would significantly increase chances for effective therapy of some diseases. Additionally, it offers non-invasive and real time measurements, high sensitivity and selectivity as well as minimizing discomfort for patients. For that reason, such sensors can be used in screening for early detection of serious diseases. Full article
(This article belongs to the Special Issue Chemical Sensors based on In Situ Spectroscopy)
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<p>(<b>a</b>) The absorption of NO at pressures of 1 atm (<b>b</b>) and of 0.1 atm for concentrations occurring in human breath: NO—35 ppb, CO<sub>2</sub>—5%, H<sub>2</sub>O after the drying procedure—279 ppm.</p> Full article ">Figure 2
<p>(<b>a</b>) The absorption of the OCS at pressures of 1 atm (<b>b</b>) and of 0.1 atm for concentrations occurring in human breath: OCS—10 ppb, CO—10 ppm, CO<sub>2</sub>—5%, H<sub>2</sub>O after the drying procedure—279 ppm.</p> Full article ">Figure 3
<p>(<b>a</b>) The absorption of C<sub>2</sub>H<sub>6</sub> at pressures of 1 atm (<b>b</b>) and of 0.1 atm for concentrations occurring in human breath: C<sub>2</sub>H<sub>6</sub>—10 ppb, NH<sub>3</sub>—2 ppm, CH<sub>4</sub>—1.7 ppm, H<sub>2</sub>O after the drying procedure—279 ppm.</p> Full article ">Figure 4
<p>(<b>a</b>) Comparison of lasers linewidths and the nitric oxide absorption spectrum; (<b>b</b>) and block diagram of the experimental setup.</p> Full article ">Figure 5
<p>Example of the NO concentration measurements in human breath at atmospheric pressure.</p> Full article ">Figure 6
<p>(<b>a</b>) The decay time changes of radiation in the optical cavity filled with reference concentration of NO (<b>b</b>) and OCS registered in the CEAS setup equipped with the tested QCL.</p> Full article ">Figure 7
<p>(<b>a</b>) Example of measurements results for ethane reference samples (<b>b</b>) and for OCS reference samples registered in the CEAS setup equipped with the PG711-DFG-SH system.</p> Full article ">
4091 KiB  
Article
Electrical Characterization of 3D Au Microelectrodes for Use in Retinal Prostheses
by Sangmin Lee, Jae Hyun Ahn, Jong-Mo Seo, Hum Chung and Dong-Il Cho
Sensors 2015, 15(6), 14345-14355; https://doi.org/10.3390/s150614345 - 17 Jun 2015
Cited by 15 | Viewed by 5975
Abstract
In order to provide high-quality visual information to patients who have implanted retinal prosthetic devices, the number of microelectrodes should be large. As the number of microelectrodes is increased, the dimensions of each microelectrode must be decreased, which in turn results in an [...] Read more.
In order to provide high-quality visual information to patients who have implanted retinal prosthetic devices, the number of microelectrodes should be large. As the number of microelectrodes is increased, the dimensions of each microelectrode must be decreased, which in turn results in an increased microelectrode interface impedance and decreased injection current dynamic range. In order to improve the trade-off envelope between the number of microelectrodes and the current injection characteristics, a 3D microelectrode structure can be used as an alternative. In this paper, the electrical characteristics of 2D and 3D Au microelectrodes were investigated. In order to examine the effects of the structural difference, 2D and 3D Au microelectrodes with different base areas but similar effective surface areas were fabricated and evaluated. Interface impedances were measured and similar dynamic ranges were obtained for both 2D and 3D Au microelectrodes. These results indicate that more electrodes can be implemented in the same area if 3D designs are used. Furthermore, the 3D Au microelectrodes showed substantially enhanced electrical durability characteristics against over-injected stimulation currents, withstanding electrical currents that are much larger than the limit measured for 2D microelectrodes of similar area. This enhanced electrical durability property of 3D Au microelectrodes is a new finding in microelectrode research, and makes 3D microelectrodes very desirable devices. Full article
(This article belongs to the Section Biosensors)
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<p>Fabrication processes and results. (<b>a</b>) 2D Au MEA; (<b>b</b>) 3D Au MEA.</p> Full article ">Figure 1 Cont.
<p>Fabrication processes and results. (<b>a</b>) 2D Au MEA; (<b>b</b>) 3D Au MEA.</p> Full article ">Figure 2
<p>Experimental setup. (<b>a</b>) Interface impedance measurement (schematic of impedance measurement (left), fabricated MEA on PCB (right)); (<b>b</b>) Charge injection limit measurement (schematic of current stimulator (left), experimental setup (right)).</p> Full article ">Figure 3
<p>Electrical properties of 2D and 3D Au microelectrodes. (<b>a</b>) Measured interface impedance results (red and black circles) and parameterized interface impedance results using three-element-circuit model (red and black lines); (<b>b</b>) Theoretical current injection limit derived from three-element-circuit model using SPICE (at bias voltage 1 V).</p> Full article ">Figure 4
<p>Time domain output of electrical durability evaluation. (<b>a</b>) 2D Au microelectrode; (<b>b</b>) 3D Au microelectrode.</p> Full article ">Figure 5
<p>Microscopic image of microelectrode before and after signal distortion. (<b>a</b>) 2D Au microelectrode; (<b>b</b>) 3D Au microelectrode.</p> Full article ">Figure 6
<p>Cyclic voltammetry results of 2D and 3D Au microelectrode.</p> Full article ">
2708 KiB  
Article
Fast Measurement and Reconstruction of Large Workpieces with Freeform Surfaces by Combining Local Scanning and Global Position Data
by Zhe Chen, Fumin Zhang, Xinghua Qu and Baoqiu Liang
Sensors 2015, 15(6), 14328-14344; https://doi.org/10.3390/s150614328 - 17 Jun 2015
Cited by 20 | Viewed by 5683
Abstract
In this paper, we propose a new approach for the measurement and reconstruction of large workpieces with freeform surfaces. The system consists of a handheld laser scanning sensor and a position sensor. The laser scanning sensor is used to acquire the surface and [...] Read more.
In this paper, we propose a new approach for the measurement and reconstruction of large workpieces with freeform surfaces. The system consists of a handheld laser scanning sensor and a position sensor. The laser scanning sensor is used to acquire the surface and geometry information, and the position sensor is utilized to unify the scanning sensors into a global coordinate system. The measurement process includes data collection, multi-sensor data fusion and surface reconstruction. With the multi-sensor data fusion, errors accumulated during the image alignment and registration process are minimized, and the measuring precision is significantly improved. After the dense accurate acquisition of the three-dimensional (3-D) coordinates, the surface is reconstructed using a commercial software piece, based on the Non-Uniform Rational B-Splines (NURBS) surface. The system has been evaluated, both qualitatively and quantitatively, using reference measurements provided by a commercial laser scanning sensor. The method has been applied for the reconstruction of a large gear rim and the accuracy is up to 0.0963 mm. The results prove that this new combined method is promising for measuring and reconstructing the large-scale objects with complex surface geometry. Compared with reported methods of large-scale shape measurement, it owns high freedom in motion, high precision and high measurement speed in a wide measurement range. Full article
(This article belongs to the Section Physical Sensors)
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<p>(<b>a</b>) The original point cloud; (<b>b</b>) Reconstruction surface; (<b>c</b>) Error distribution diagram.</p> Full article ">Figure 2
<p>Schematic of the combined system.</p> Full article ">Figure 3
<p>Measuring the distance between region 1 and region 3.</p> Full article ">Figure 4
<p>(<b>a</b>) TBR for the laser tracker mounted on a nest; (<b>b</b>) RRTs pasted on the object; (<b>c</b>) RRT pasted on the center of a 1.5-inch tip on the nest to assess the same point with the laser tracker and MAXscan.</p> Full article ">Figure 5
<p>The standard values of the distances between the points measured by the laser tracker. (<b>a</b>) The measurement of AB, AC and AD; (<b>b</b>) The measurement of AE and AF.</p> Full article ">Figure 6
<p>The length of AB, AC and AD measured only by MAXscan.</p> Full article ">Figure 7
<p>The layout of the reference global position points.</p> Full article ">Figure 8
<p>Measurement error of the lengths of AC and AD using the combined method.</p> Full article ">Figure 9
<p>The error comparison by two methods: (<b>a</b>) The measured object is AC; (<b>b</b>) The measured object is AD.</p> Full article ">Figure 10
<p>(<b>a</b>) Measurement error of AE and AF using the scanner; (<b>b</b>) Measurement error of AE and AF using the combined method.</p> Full article ">Figure 11
<p>The ring gauge with the reference global position points.</p> Full article ">Figure 12
<p>The results of the deviation comparison.</p> Full article ">Figure 13
<p>(<b>a</b>) A large-scale gear rim; (<b>b</b>) The original cloud.</p> Full article ">Figure 14
<p>The fitting result comparison: (<b>a</b>) The point data; (<b>b</b>) The conventional method; (<b>c</b>) The proposed method.</p> Full article ">Figure 15
<p>(<b>a</b>) The fitting surface; (<b>b</b>) Error distribution diagram.</p> Full article ">
4790 KiB  
Article
An Indoor Mobile Location Estimator in Mixed Line of Sight/Non-Line of Sight Environments Using Replacement Modified Hidden Markov Models and an Interacting Multiple Model
by Jingyu Ru, Chengdong Wu, Zixi Jia, Yufang Yang, Yunzhou Zhang and Nan Hu
Sensors 2015, 15(6), 14298-14327; https://doi.org/10.3390/s150614298 - 17 Jun 2015
Cited by 5 | Viewed by 5686
Abstract
Localization as a technique to solve the complex and challenging problems besetting line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions has recently attracted considerable attention in the wireless sensor network field. This paper proposes a strategy for eliminating NLOS localization errors during calculation of the [...] Read more.
Localization as a technique to solve the complex and challenging problems besetting line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions has recently attracted considerable attention in the wireless sensor network field. This paper proposes a strategy for eliminating NLOS localization errors during calculation of the location of mobile terminals (MTs) in unfamiliar indoor environments. In order to improve the hidden Markov model (HMM), we propose two modified algorithms, namely, modified HMM (M-HMM) and replacement modified HMM (RM-HMM). Further, a hybrid localization algorithm that combines HMM with an interacting multiple model (IMM) is proposed to represent the velocity of mobile nodes. This velocity model is divided into a high-speed and a low-speed model, which means the nodes move at different speeds following the same mobility pattern. Each moving node continually switches its state based on its probability. Consequently, to improve precision, each moving node uses the IMM model to integrate the results from the HMM and its modified forms. Simulation experiments conducted show that our proposed algorithms perform well in both distance estimation and coordinate calculation, with increasing accuracy of localization of the proposed algorithms in the order M-HMM, RM-HMM, and HMM + IMM. The simulations also show that the three algorithms are accurate, stable, and robust. Full article
(This article belongs to the Section Sensor Networks)
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<p>(<b>a</b>) Discrete approximate schematic diagram; (<b>b</b>) NLOS/LOS condition schematic diagram.</p> Full article ">Figure 2
<p>An instance of the value of the RSS power measured. (<b>a</b>) Example of receive signal; (<b>b</b>) RSS power delay profile model; (<b>c</b>) Example of log-likelihood function for the signal measured by AP.</p> Full article ">Figure 2 Cont.
<p>An instance of the value of the RSS power measured. (<b>a</b>) Example of receive signal; (<b>b</b>) RSS power delay profile model; (<b>c</b>) Example of log-likelihood function for the signal measured by AP.</p> Full article ">Figure 3
<p>PDF comparison for Gaussian kernel distributions and exponential distributions.</p> Full article ">Figure 4
<p>Examples of <span class="html-italic">P</span>(<span class="html-italic">m<sup>i</sup></span>│<span class="html-italic">m<sup>i</sup></span><sup>‒1</sup>) PDF models. The arrows represent the forward direction of the MT: (<b>a</b>) Circular Gaussian PDF with deviation σ<span class="html-italic"><sub>v</sub></span> = 3 in [<a href="#B16-sensors-15-14298" class="html-bibr">16</a>]; (<b>b</b>) Trajectory of (<b>a</b>). (<b>c</b>) Gaussian distribution with variable ΔQ and σ = 0.5; (<b>d</b>) Trajectory of (c); (<b>e</b>) PDF with <math display="inline"> <semantics> <mrow> <mi>Δ</mi> <mi>Q</mi> <mtext> </mtext> <mi>ϵ</mi> <mtext> </mtext> <mrow> <mo>[</mo> <mrow> <mo>−</mo> <mn>90</mn> <mo>°</mo> <mo>,</mo> <mtext> </mtext> <mn>90</mn> <mo>°</mo> </mrow> <mo>]</mo> </mrow> </mrow> </semantics> </math>.</p> Full article ">Figure 5
<p>Flow diagram of D/TA.</p> Full article ">Figure 6
<p>Flow diagram of the location algorithm.</p> Full article ">Figure 7
<p>Flow diagram of HMM location algorithm.</p> Full article ">Figure 8
<p>Flow diagram of the M-HMM algorithm.</p> Full article ">Figure 9
<p>The two models proposed in this paper.</p> Full article ">Figure 10
<p>Flow diagram of the IMM algorithm.</p> Full article ">Figure 11
<p>Updating of weights.</p> Full article ">Figure 12
<p>Simulation trajectory of various algorithms: (<b>a</b>) Trajectory estimated by the ML algorithm; (<b>b</b>) Trajectory estimated by the D/TA estimation in [<a href="#B16-sensors-15-14298" class="html-bibr">16</a>]; (<b>c</b>) Trajectory according to I-D/TA estimation; (<b>d</b>) Trajectory estimated by the PF algorithm; (<b>e</b>) Trajectory estimated by the M-HMM algorithm; (<b>f</b>) Trajectory using RM-HMM estimation.</p> Full article ">Figure 13
<p>LOS/NLOS situations.</p> Full article ">Figure 14
<p>Means and variances of the six algorithms.</p> Full article ">Figure 15
<p>CDF analysis of the six algorithms.</p> Full article ">Figure 16
<p>Analysis of five dispersion points based on <span class="html-italic">P</span>(<span class="html-italic">y<sup>i</sup></span>│<span class="html-italic">m<sup>i</sup></span>).</p> Full article ">Figure 17
<p>PDFs of the high- and low-speed models and the original path.</p> Full article ">Figure 18
<p>Simulation trajectories of different algorithms. (<b>a</b>) EKF; (<b>b</b>) ML; (<b>c</b>) D/TA; (<b>d</b>) I-D/TA; (<b>e</b>) PF; (<b>f</b>) M-HMM; (<b>g</b>) IMM-D/TA; (<b>h</b>) IMM + RM-HMM; (<b>i</b>) IMM + M-HMM.</p> Full article ">Figure 19
<p>CDF analysis of various algorithms.</p> Full article ">Figure 20
<p>Means and variances of the nine algorithms.</p> Full article ">Figure 21
<p>Transformation of patterns in the simulation.</p> Full article ">Figure 22
<p>The error distribution of the improved algorithm.</p> Full article ">Figure 23
<p>The trajectory of the MT in simulation.</p> Full article ">Figure 24
<p>The trajectory of the MT in practice.</p> Full article ">Figure 25
<p>Relationship between <span class="html-italic">h<sub>ij</sub></span> and <span class="html-italic">Va</span>.</p> Full article ">Figure 26
<p>Relationship between P and <span class="html-italic">Va</span>.</p> Full article ">
2760 KiB  
Article
A Room Temperature H2 Sensor Fabricated Using High Performance Pt-Loaded SnO2 Nanoparticles
by Sheng-Chang Wang and Muhammad Omar Shaikh
Sensors 2015, 15(6), 14286-14297; https://doi.org/10.3390/s150614286 - 17 Jun 2015
Cited by 41 | Viewed by 7752
Abstract
Highly sensitive H2 gas sensors were prepared using pure and Pt-loaded SnO2 nanoparticles. Thick film sensors (~35 μm) were fabricated that showed a highly porous interconnected structure made of high density small grained nanoparticles. Using Pt as catalyst improved sensor response [...] Read more.
Highly sensitive H2 gas sensors were prepared using pure and Pt-loaded SnO2 nanoparticles. Thick film sensors (~35 μm) were fabricated that showed a highly porous interconnected structure made of high density small grained nanoparticles. Using Pt as catalyst improved sensor response and reduced the operating temperature for achieving high sensitivity because of the negative temperature coefficient observed in Pt-loaded SnO2. The highest sensor response to 1000 ppm H2 was 10,500 at room temperature with a response time of 20 s. The morphology of the SnO2 nanoparticles, the surface loading concentration and dispersion of the Pt catalyst and the microstructure of the sensing layer all play a key role in the development of an effective gas sensing device. Full article
(This article belongs to the Special Issue Gas Sensors—Designs and Applications)
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<p>(<b>a</b>) XRD of nanocrystals obtained after a reaction temperature of 30 min and 3 h in air; (<b>b</b>) Schematic of crystal structure during phasic transformation of tin oxide to tin dioxide; (<b>c</b>) Bright-field TEM image and HRTEM (inset) of SnO nanosheets; (<b>d</b>) SAED image of SnO nanosheets; (<b>e</b>) Bright-field TEM image and HRTEM (inset) of SnO<sub>2</sub> nanoparticles; (<b>f</b>) SAED image of SnO<sub>2</sub> nanoparticles.</p> Full article ">Figure 2
<p>(<b>a</b>) Gas sensitivity as a function of operating temperature for pure SnO<sub>2</sub> thick film sensor. Change in resistance of pure SnO<sub>2</sub> gas sensors on exposure to 1000 ppm of H<sub>2</sub> for 10 cycles at an operating temperature of (<b>b</b>) 200 °C, (<b>c</b>) 300 °C and (<b>d</b>) 400 °C.</p> Full article ">Figure 3
<p>(<b>a</b>) XRD result of sensing film loaded with different concentrations of Pt; (<b>b</b>) Schematic illustration of thick film sensor utilizing interdigitated Pt electrodes. SEM image showing (<b>c</b>) top view and (<b>d</b>) cross sectional morphology of sensing film.</p> Full article ">Figure 4
<p>Change in resistance of SnO<sub>2</sub> gas sensors with different Pt loading concentrations upon exposure to 1000 ppm of H<sub>2</sub> gas at an operating temperature of (<b>a</b>) 25 °C and (<b>b</b>) 300 °C.</p> Full article ">
3361 KiB  
Article
Novel Gyroscopic Mounting for Crystal Oscillators to Increase Short and Medium Term Stability under Highly Dynamic Conditions
by Maryam Abedi, Tian Jin and Kewen Sun
Sensors 2015, 15(6), 14261-14285; https://doi.org/10.3390/s150614261 - 17 Jun 2015
Cited by 1 | Viewed by 5920
Abstract
In this paper, a gyroscopic mounting method for crystal oscillators to reduce the impact of dynamic loads on their output stability has been proposed. In order to prove the efficiency of this mounting approach, each dynamic load-induced instability has been analyzed in detail. [...] Read more.
In this paper, a gyroscopic mounting method for crystal oscillators to reduce the impact of dynamic loads on their output stability has been proposed. In order to prove the efficiency of this mounting approach, each dynamic load-induced instability has been analyzed in detail. A statistical study has been performed on the elevation angle of the g-sensitivity vector of Stress Compensated-cut (SC-cut) crystals. The analysis results show that the proposed gyroscopic mounting method gives good performance for host vehicle attitude changes. A phase noise improvement of 27 dB maximum and 5.7 dB on average can be achieved in the case of steady state loads, while under sinusoidal vibration conditions, the maximum and average phase noise improvement are as high as 24 dB and 7.5 dB respectively. With this gyroscopic mounting method, random vibration-induced phase noise instability is reduced 30 dB maximum and 8.7 dB on average. Good effects are apparent for crystal g-sensitivity vectors with low elevation angle φ and azimuthal angle β. under highly dynamic conditions, indicating the probability that crystal oscillator instability will be significantly reduced by using the proposed mounting approach. Full article
(This article belongs to the Section Physical Sensors)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Highly dynamic host vehicle with installed crystal oscillator.</p> Full article ">Figure 2
<p>Angular orientation of load <math display="inline"> <semantics> <mrow> <mover accent="true"> <mi>A</mi> <mo stretchy="true">→</mo> </mover> </mrow> </semantics> </math> and g-sensitivity vector <math display="inline"> <semantics> <mrow> <mover accent="true"> <mi mathvariant="normal">Γ</mi> <mo stretchy="true">→</mo> </mover> </mrow> </semantics> </math> of crystal blank. (<b>a</b>) Typical state; (<b>b</b>) Critical state (β = 0); (<b>c</b>) Neutral acceleration.</p> Full article ">Figure 3
<p>Modeling of gyroscopic mounting instrument. (<b>a</b>) Gyroscopic-mounting; (<b>b</b>) Dynamic load applied; (<b>c</b>) Mounting on PCB.</p> Full article ">Figure 4
<p>Prototype of gyroscopic mounting instrument.</p> Full article ">Figure 5
<p>Distribution of angle |φ| for different SC-cut crystals.</p> Full article ">Figure 6
<p>Crystal oscillator subjected to attitude and altitude changes of host vehicle. (<b>a</b>) Host vehicle trajectory ground track; (<b>b</b>) Attitude and altitude of host vehicle; Adapted from [<a href="#B7-sensors-15-14261" class="html-bibr">7</a>]. (<b>c</b>) Orientation of g, Γ and time variant angle δ on crystal.</p> Full article ">Figure 7
<p>Attitude and altitude changes of host vehicle-induced clock bias.</p> Full article ">Figure 8
<p>Longitudinal steady state acceleration for the Ariane 5 launch vehicle. Adapted from [<a href="#B7-sensors-15-14261" class="html-bibr">7</a>].</p> Full article ">Figure 9
<p>Steady state load applied on the crystal installed on the host vehicle. (<b>a</b>) Horizontally; (<b>b</b>) Vertically.</p> Full article ">Figure 10
<p>Short-term instability caused by steady state load in critical state β = 0. (<b>a</b>) Frequency deviation of fixed oscillator; (<b>b</b>) Frequency deviation of using gyroscopic mounting; (<b>c</b>) Phase noise of fixed oscillator; (<b>d</b>) Phase noise of gyroscopic mounting.</p> Full article ">Figure 11
<p>Average instability caused by steady state load. (<b>a</b>) Frequency deviation; (<b>b</b>) Phase noise.</p> Full article ">Figure 12
<p>Comparison between steady state load-induced frequency deviation and Allan safety margin. (<b>a</b>) Fixed oscillator; (<b>b</b>) Gyroscopic mounting.</p> Full article ">Figure 13
<p>Comparison between steady state load-induced phase noise and Allan safety margin. (<b>a</b>) Fixed oscillator; (<b>b</b>) Gyroscopic mounting.</p> Full article ">Figure 14
<p>Sinusoidal vibrations of the Ariane 5 launch vehicle. Adapted from [<a href="#B7-sensors-15-14261" class="html-bibr">7</a>].</p> Full article ">Figure 15
<p>Magnitude and angular orientation of sinusoidal vibrations. (<b>a</b>) α = 38.7°; (<b>b</b>) α = 31°; (<b>c</b>) α = 36.87°.</p> Full article ">Figure 16
<p>Sinusoidal vibrations-induced short term instability for critical state β = 0. (<b>a</b>) Frequency jitter of fixed oscillator; (<b>b</b>) Frequency jitter of gyroscopic mounting; (<b>c</b>) Phase noise of fixed oscillator; (<b>d</b>) Phase noise of gyroscopic mounting.</p> Full article ">Figure 17
<p>Average instability caused by sinusoidal vibration. (<b>a</b>) Frequency jitter; (<b>b</b>) Phase noise.</p> Full article ">Figure 18
<p>Comparison between sinusoidal vibrations-induced frequency jitter and Allan deviation safety margin. (<b>a</b>) Fixed oscillator; (<b>b</b>) Gyroscopic mounting.</p> Full article ">Figure 19
<p>Comparison between sinusoidal vibrations-induced phase noise and Allan deviation safety margin. (<b>a</b>) Fixed oscillator; (<b>b</b>) Gyroscopic mounting.</p> Full article ">Figure 20
<p>Random vibration applied on crystal oscillator 0 &lt; |ξ| &lt; π, 0 &lt; |β| &lt; π. (<b>a</b>) Fixed oscillator; (<b>b</b>) Oscillator on gyroscopic mounting.</p> Full article ">Figure 21
<p>Mechanical random vibration for the Ariane 4 launch vehicle. (<b>a</b>) ASD (g<sup>2</sup>/Hz); Adapted from [<a href="#B32-sensors-15-14261" class="html-bibr">32</a>]. (<b>b</b>) Time domain representation.</p> Full article ">Figure 22
<p>Maximum instability (ξ = φ) caused by random vibration for ƒ<sub>RV</sub> = 2000 (Hz). (<b>a</b>) Frequency jitter of fixed oscillator; (<b>b</b>) Frequency jitter of gyroscopic mounting; (<b>c</b>) Phase noise of fixed oscillator; (<b>d</b>) Phase noise of gyroscopic mounting.</p> Full article ">Figure 23
<p>Comparison between system instability in different states. (<b>a</b>) Maximum state ξ = φ, β = 0; (<b>b</b>) Minimum state, ξ − φ = 90°or β = 90°.</p> Full article ">Figure 24
<p>Average instability caused by random vibration. (<b>a</b>) Frequency jitter; (<b>b</b>) Phase noise.</p> Full article ">Figure 25
<p>Analysis of random vibration in frequency domain for ξ = φ, β = 0. (<b>a</b>) Frequency jitter of fixed oscillator; (<b>b</b>) Frequency jitter of gyroscopic mounting; (<b>c</b>) Phase noise of fixed oscillator; (<b>d</b>) Phase noise of gyroscopic mounting.</p> Full article ">Figure 26
<p>Analysis of random vibration in frequency domain for 0° &lt; |ξ | &lt; 180°, β = 0, φ = 2σ = 38°.(<b>a</b>) Frequency jitter of fixed oscillator; (<b>b</b>) Frequency jitter of gyroscopic mounting; (<b>c</b>) Phase noise of fixed oscillator; (<b>d</b>) Phase noise of gyroscopic mounting.</p> Full article ">
1122 KiB  
Article
Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines
by Lara Del Val, Alberto Izquierdo-Fuente, Juan J. Villacorta and Mariano Raboso
Sensors 2015, 15(6), 14241-14260; https://doi.org/10.3390/s150614241 - 17 Jun 2015
Cited by 12 | Viewed by 5378
Abstract
Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques [...] Read more.
Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements. Full article
(This article belongs to the Section Physical Sensors)
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<p>Hyperplane for binary classification.</p> Full article ">Figure 2
<p>Classifier training.</p> Full article ">Figure 3
<p>5-fold Cross Validation.</p> Full article ">Figure 4
<p>Functional description block diagram.</p> Full article ">Figure 5
<p>Acquisition system block diagram.</p> Full article ">Figure 6
<p>Acoustic image example.</p> Full article ">Figure 7
<p>Preprocessing and parametrization techniques.</p> Full article ">Figure 8
<p>Pre-processed images: (<b>a</b>) original; (<b>b</b>) segmented; (<b>c</b>) masked; (<b>d</b>) binarized.</p> Full article ">Figure 9
<p>Line-based Image Coding.</p> Full article ">Figure 10
<p>Line-based Image Coding with position.</p> Full article ">Figure 11
<p>Geometric feature extraction.</p> Full article ">Figure 12
<p>Experiments.</p> Full article ">Figure 13
<p>Classification error rates.</p> Full article ">Figure 14
<p>Computational burden.</p> Full article ">Figure 15
<p>Error increment vs. burden reduction.</p> Full article ">
2581 KiB  
Article
Synthesis and Gas Sensing Properties of Single La-Doped SnO2 Nanobelts
by Yuemei Wu, Heng Zhang, Yingkai Liu, Weiwu Chen, Jiang Ma, Shuanghui Li and Zhaojun Qin
Sensors 2015, 15(6), 14230-14240; https://doi.org/10.3390/s150614230 - 16 Jun 2015
Cited by 26 | Viewed by 6266
Abstract
Single crystal SnO2 nanobelts (SnO2 NBs) and La-SnO2 nanobelts (La-SnO2 NBs) were synthesized by thermal evaporation. Both a single SnO2 NB sensor and a single La-SnO2 NB sensor were developed and their sensing properties were investigated. It [...] Read more.
Single crystal SnO2 nanobelts (SnO2 NBs) and La-SnO2 nanobelts (La-SnO2 NBs) were synthesized by thermal evaporation. Both a single SnO2 NB sensor and a single La-SnO2 NB sensor were developed and their sensing properties were investigated. It is found that the single La-SnO2 NB sensor had a high sensitivity of 8.76 to ethanediol at a concentration of 100 ppm at 230 °C, which is the highest sensitivity of a single SnO2 NB to ethanediol among three kinds of volatile organic (VOC) liquids studied, including ethanediol, ethanol, and acetone. The La-SnO2 NBs sensor also exhibits a high sensitivity, good selectivity and long-term stability with prompt response time to ethanediol. The mechanism behind the enhanced sensing performance of La-doped SnO2 nanobelts is discussed. Full article
(This article belongs to the Section Chemical Sensors)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic diagram of the test system.</p> Full article ">Figure 2
<p>SEM images of La-SnO<sub>2</sub> NBs (<b>a</b>); SEM images of SnO<sub>2</sub> NBs (<b>b</b>); XRD and EDX patterns of La-SnO<sub>2</sub> NBs (<b>c</b>) and (<b>d</b>), respectively.</p> Full article ">Figure 3
<p>The HRTEM and SEAD images of pure SnO<sub>2</sub> NBs (<b>a</b>) and La-SnO<sub>2</sub> NBs (<b>b</b>).</p> Full article ">Figure 4
<p>(<b>a</b>) The I–V curves of pure SnO<sub>2</sub> NB and La-SnO<sub>2</sub> NB devices; (<b>b</b>) The optical microscope image of a prepared La-SnO<sub>2</sub> NB device.</p> Full article ">Figure 5
<p>The gas sensitivity of (<b>a</b>) the La-SnO<sub>2</sub> NB and (<b>b</b>) the SnO<sub>2</sub> NB to 100 ppm gas from 170 °C to 270 °C.</p> Full article ">Figure 6
<p>The gas sensitivity of two devices to ethanediol from 5 ppm to 500 ppm at 230 °C.</p> Full article ">Figure 7
<p>The gas sensitivity of two devices to (<b>a</b>) ethanediol; (<b>b</b>) ethanol and (<b>c</b>) acetone from 10 ppm to 300 ppm at 230 °C.</p> Full article ">
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