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Sensors, Volume 22, Issue 9 (May-1 2022) – 503 articles

Cover Story (view full-size image): Advances in printing technologies have revolutionized approaches to the design of low-cost gas sensors and multisensor arrays, including lab-on-chip platforms, meeting the expectations of cost efficiency, simplicity, good reproducibility, and resolution. In this review, these technologies are discussed employing an extensive review of the recent literature with proper attention to the resolution, ink properties, benefits, and drawbacks of the methods. Using such protocols, producers may tune the sensor properties rather easily, like a composer, applying materials in pristine and hetero-structured phases on various substrates, including flexible ones. View this paper
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21 pages, 12134 KiB  
Article
Design, Manufacture, Test and Experiment of Six-Axis Force Torque Sensor for Chinese Experimental Module Manipulator
by Yongjun Sun
Sensors 2022, 22(9), 3603; https://doi.org/10.3390/s22093603 - 9 May 2022
Cited by 3 | Viewed by 2823
Abstract
A novel six-axis force/torque sensor (F/T sensor) for an Experimental Module Manipulator (EMM) in the Chinese Space Station (CSS) is developed in this paper. First, we designed the elastomer structure of the F/T sensor and used the analytical method and the finite element [...] Read more.
A novel six-axis force/torque sensor (F/T sensor) for an Experimental Module Manipulator (EMM) in the Chinese Space Station (CSS) is developed in this paper. First, we designed the elastomer structure of the F/T sensor and used the analytical method and the finite element method to analyze the strain, in order to accomplish the strain gauges’ layout. Then, the electrical system was designed, which mainly realizes the acquisition of force/torque information, temperature and serial communication with the end effector (EE). Following this, we analyzed and designed the adaptability of the F/T sensor to the space environment. After this, the manufacturing process of the sensor was introduced in detail, and the F/T sensor was calibrated by a pulley weight system. Finally, the sensor was tested on the space environment adaptability of mechanical vibration and thermal vacuum on the ground. The test results show that the developed sensor has the ability to accurately measure three-dimensional force and three-dimensional moment information on orbit, which provides necessary conditions for the on-orbit fine operation of EMM. Full article
(This article belongs to the Topic Space Robotics)
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13 pages, 4067 KiB  
Communication
Detection of Interlayered Illite/Smectite Clay Minerals with XRD, SEM Analyses and Reflectance Spectroscopy
by Fiorenza Deon, Frank van Ruitenbeek, Harald van der Werff, Mark van der Meijde and Camilla Marcatelli
Sensors 2022, 22(9), 3602; https://doi.org/10.3390/s22093602 - 9 May 2022
Cited by 6 | Viewed by 3905
Abstract
Accurate determination of clay minerals can be challenging due to the natural occurrence of interlayered phases, i.e., layers of different clay species such as illite and smectite. The overlap of peaks of the constituent minerals (e.g., illite and smectite), and the similarity of [...] Read more.
Accurate determination of clay minerals can be challenging due to the natural occurrence of interlayered phases, i.e., layers of different clay species such as illite and smectite. The overlap of peaks of the constituent minerals (e.g., illite and smectite), and the similarity of diffraction patterns when not treated with ethylene glycol, hampers identification, especially when the clay content is low. We investigated the occurrence of interlayered illite/smectite in a rock sample from Rodalquilar, Spain, using X-ray diffraction, scanning electron microscopy and reflectance spectroscopy in the short-wave infrared wavelength range. For the first time, a precise determination of interlayered I/S conducted on the extracted clay fraction treated with ethylene glycol using such different approaches was provided. X-ray diffraction results demonstrated the presence of an I/S peak at around 8.4° in the untreated fraction coupled with a peak splitting at 6.7° and 9.4° 2θ when solvated with ethylene glycol. While spectroscopy indicated the occurrence of interlayered structures as a mixture of the two constituent minerals, the results of X-ray analysis showed that the interlayered clay consisted of two discrete phases (illite and smectite). The two discrete phases were observed in both the whole rock analysis and in the extracted clay fraction. This study shows that X-ray diffraction and validation with a scanning electron microscope is a mandatory, integrating tool for detecting interlayered phases since reflectance spectroscopy alone cannot be used to differentiate between interlayered clay minerals and non-interlayered mixtures. This work highlights the limits and advantages of three sensors (X-ray diffraction, scanning electron microscopy and reflectance spectroscopy) to investigate clay mixtures and interlayering, representing a significant contribution to confidence in the interpretation of interlayered clays, this being essential in mineral exploration and prospecting. Full article
(This article belongs to the Section Optical Sensors)
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28 pages, 2270 KiB  
Review
Perimeter Intrusion Detection by Video Surveillance: A Survey
by Devashish Lohani, Carlos Crispim-Junior, Quentin Barthélemy, Sarah Bertrand, Lionel Robinault and Laure Tougne Rodet
Sensors 2022, 22(9), 3601; https://doi.org/10.3390/s22093601 - 9 May 2022
Cited by 10 | Viewed by 5853
Abstract
In recent times, we have seen a massive rise in vision-based applications, such as video anomaly detection, motion detection, object tracking, people counting, etc. Most of these tasks are well defined, with a clear idea of the goal, along with proper datasets and [...] Read more.
In recent times, we have seen a massive rise in vision-based applications, such as video anomaly detection, motion detection, object tracking, people counting, etc. Most of these tasks are well defined, with a clear idea of the goal, along with proper datasets and evaluation procedures. However, perimeter intrusion detection (PID), which is one of the major tasks in visual surveillance, still needs to be formally defined. A perimeter intrusion detection system (PIDS) aims to detect the presence of an unauthorized object in a protected outdoor site during a certain time. Existing works vaguely define a PIDS, and this has a direct impact on the evaluation of methods. In this paper, we mathematically define it. We review the existing methods, datasets and evaluation protocols based on this definition. Furthermore, we provide a suitable evaluation protocol for real-life application. Finally, we evaluate the existing systems on available datasets using different evaluation schemes and metrics. Full article
(This article belongs to the Special Issue Unusual Behavior Detection Based on Machine Learning)
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19 pages, 8200 KiB  
Article
A 12-b Subranging SAR ADC Using Detect-and-Skip Switching and Mismatch Calibration for Biopotential Sensing Applications
by Cong Luong Nguyen, Huu Nhan Phan and Jong-Wook Lee
Sensors 2022, 22(9), 3600; https://doi.org/10.3390/s22093600 - 9 May 2022
Cited by 2 | Viewed by 2550
Abstract
This paper presents a 12-b successive approximation register (SAR) analog-to-digital converter (ADC) for biopotential sensing applications. To reduce the digital-to-analog converter (DAC) switching energy of the high-resolution ADC, we combine merged-capacitor-switching (MCS) and detect-and-skip (DAS) methods, successfully embedded in the subranging structure. The [...] Read more.
This paper presents a 12-b successive approximation register (SAR) analog-to-digital converter (ADC) for biopotential sensing applications. To reduce the digital-to-analog converter (DAC) switching energy of the high-resolution ADC, we combine merged-capacitor-switching (MCS) and detect-and-skip (DAS) methods, successfully embedded in the subranging structure. The proposed method saves 96.7% of switching energy compared to the conventional method. Without an extra burden on the realization of the calibration circuit, we achieve mismatch calibration by reusing the on-chip DAC. The mismatch data are processed in the digital domain to compensate for the nonlinearity caused by the DAC mismatch. The ADC is realized using a 0.18 μm CMOS process with a core area of 0.7 mm2. At the sampling rate fS = 9 kS/s, the ADC achieves a signal-to-noise ratio and distortion (SINAD) of 67.4 dB. The proposed calibration technique improves the spurious-free dynamic range (SFDR) by 7.2 dB, resulting in 73.5 dB. At an increased fS = 200 kS/s, the ADC achieves a SINAD of 65.9 dB and an SFDR of 68.8 dB with a figure-of-merit (FoM) of 13.2 fJ/conversion-step. Full article
(This article belongs to the Section Biosensors)
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19 pages, 11022 KiB  
Article
Research on Fast Recognition and Localization of an Electric Vehicle Charging Port Based on a Cluster Template Matching Algorithm
by Pengkun Quan, Ya’nan Lou, Haoyu Lin, Zhuo Liang, Dongbo Wei and Shichun Di
Sensors 2022, 22(9), 3599; https://doi.org/10.3390/s22093599 - 9 May 2022
Cited by 8 | Viewed by 2273
Abstract
With the gradual maturity of driverless and automatic parking technologies, electric vehicle charging has been gradually developing in the direction of automation. However, the pose calculation of the charging port (CP) is an important part of realizing automatic charging, and it represents a [...] Read more.
With the gradual maturity of driverless and automatic parking technologies, electric vehicle charging has been gradually developing in the direction of automation. However, the pose calculation of the charging port (CP) is an important part of realizing automatic charging, and it represents a problem that needs to be solved urgently. To address this problem, this paper proposes a set of efficient and accurate methods for determining the pose of an electric vehicle CP, which mainly includes the search and aiming phases. In the search phase, the feature circle algorithm is used to fit the ellipse information to obtain the pixel coordinates of the feature point. In the aiming phase, contour matching and logarithmic evaluation indicators are used in the cluster template matching algorithm (CTMA) proposed in this paper to obtain the matching position. Based on the image deformation rate and zoom rates, a matching template is established to realize the fast and accurate matching of textureless circular features and complex light fields. The EPnP algorithm is employed to obtain the pose information, and an AUBO-i5 robot is used to complete the charging gun insertion. The results show that the average CP positioning errors (x, y, z, Rx, Ry, and Rz) of the proposed algorithm are 0.65 mm, 0.84 mm, 1.24 mm, 1.11 degrees, 0.95 degrees, and 0.55 degrees. Further, the efficiency of the positioning method is improved by 510.4% and the comprehensive plug-in success rate is 95%. Therefore, the proposed CTMA in this paper can efficiently and accurately identify the CP while meeting the actual plug-in requirements. Full article
(This article belongs to the Topic Intelligent Transportation Systems)
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31 pages, 815 KiB  
Review
Mitigating the Impact of the COVID-19 Pandemic on Adult Cancer Patients through Telehealth Adoption: A Systematic Review
by Aileen Murphy, Ann Kirby, Amy Lawlor, Frances J. Drummond and Ciara Heavin
Sensors 2022, 22(9), 3598; https://doi.org/10.3390/s22093598 - 9 May 2022
Cited by 12 | Viewed by 3496
Abstract
During the first wave of the COVID-19 pandemic, the delivery of life-saving and life-prolonging health services for oncology care and supporting services was delayed and, in some cases, completely halted, as national health services globally shifted their attention and resources towards the pandemic [...] Read more.
During the first wave of the COVID-19 pandemic, the delivery of life-saving and life-prolonging health services for oncology care and supporting services was delayed and, in some cases, completely halted, as national health services globally shifted their attention and resources towards the pandemic response. Prior to March 2020, telehealth was starting to change access to health services. However, the onset of the global pandemic may mark a tipping point for telehealth adoption in healthcare delivery. We conducted a systematic review of literature published between January 2020 and March 2021 examining the impact of the COVID-19 pandemic on adult cancer patients. The review’s inclusion criteria focused on the economic, social, health, and psychological implications of COVID-19 on cancer patients and the availability of telehealth services emerged as a key theme. The studies reviewed revealed that the introduction of new telehealth services or the expansion of existing telehealth occurred to support and enable the continuity of oncology and related services during this extraordinary period. Our analysis points to several strengths and weaknesses associated with telehealth adoption and use amongst this cohort. Evidence indicates that while telehealth is not a panacea, it can offer a “bolstering” solution during a time of disruption to patients’ access to essential cancer diagnostic, treatment, and aftercare services. The innovative use of telehealth has created opportunities to reimagine the delivery of healthcare services beyond COVID-19. Full article
(This article belongs to the Special Issue Advances in E-health and Mobile Health Monitoring)
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27 pages, 6424 KiB  
Article
End-to-End Sentence-Level Multi-View Lipreading Architecture with Spatial Attention Module Integrated Multiple CNNs and Cascaded Local Self-Attention-CTC
by Sanghun Jeon and Mun Sang Kim
Sensors 2022, 22(9), 3597; https://doi.org/10.3390/s22093597 - 9 May 2022
Cited by 7 | Viewed by 2509
Abstract
Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in real-world scenarios, most VSR studies have focused solely on [...] Read more.
Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in real-world scenarios, most VSR studies have focused solely on frontal face pictures. To address this issue, we propose an end-to-end sentence-level multi-view VSR architecture for faces captured from four different perspectives (frontal, 30°, 45°, and 60°). The encoder uses multiple convolutional neural networks with a spatial attention module to detect minor changes in the mouth patterns of similarly pronounced words, and the decoder uses cascaded local self-attention connectionist temporal classification to collect the details of local contextual information in the immediate vicinity, which results in a substantial performance boost and speedy convergence. To compare the performance of the proposed model for experiments on the OuluVS2 dataset, the dataset was divided into four different perspectives, and the obtained performance improvement was 3.31% (0°), 4.79% (30°), 5.51% (45°), 6.18% (60°), and 4.95% (mean), respectively, compared with the existing state-of-the-art performance, and the average performance improved by 9.1% compared with the baseline. Thus, the suggested design enhances the performance of multi-view VSR and boosts its usefulness in real-world applications. Full article
(This article belongs to the Special Issue Future Speech Interfaces with Sensors and Machine Intelligence)
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14 pages, 4559 KiB  
Communication
High-Frequency Vibration Analysis of Piezoelectric Array Sensor under Lateral-Field-Excitation Based on Crystals with 3 m Point Group
by Jiachao Xu, Hao Shi, Fei Sun, Zehuan Tang, Shuanghuizhi Li, Dudu Chen, Tingfeng Ma, Iren Kuznetsova, Ilya Nedospasov and Chao Zhang
Sensors 2022, 22(9), 3596; https://doi.org/10.3390/s22093596 - 9 May 2022
Cited by 1 | Viewed by 1854
Abstract
Based on Mindlin’s first-order plate theory, the high-frequency vibrations of piezoelectric bulk acoustic wave array sensors under lateral-field-excitation based on crystals with 3 m point group are analyzed, and the spectral-frequency relationships are solved, based on which, the optimal length–thickness ratio of the [...] Read more.
Based on Mindlin’s first-order plate theory, the high-frequency vibrations of piezoelectric bulk acoustic wave array sensors under lateral-field-excitation based on crystals with 3 m point group are analyzed, and the spectral-frequency relationships are solved, based on which, the optimal length–thickness ratio of the piezoelectric crystal plate is determined. Then, the dynamic capacitance diagram is obtained by a forced vibration analysis of the piezoelectric crystal plate. The resonant mode conforming to good energy trapping is further obtained. The frequency interferences between different resonator units are calculated, and the influences of the spacing between two resonant units on the frequency interference with different electrode widths and spacings are analyzed. Finally, the safe spacings between resonator units are obtained. As the electrode spacing value of the left unit increases, the safe spacing d0 between the two resonator units decreases, and the frequency interference curve tends to zero faster. When the electrode spacings of two resonator units are equal, the safe distance is largest, and the frequency interference curve tends to zero slowest. The theoretical results are verified further by finite element method. The analysis model of high frequency vibrations of strongly coupled piezoelectric bulk acoustic array device based on LiTaO3 crystals with 3 m point group proposed in this paper can provide reliable theoretical guidance for size optimization designs of strongly coupled piezoelectric array sensors under lateral-field-excitation. Full article
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10 pages, 5849 KiB  
Communication
The Effect of Sun Tan Lotion on Skin by Using Skin TEWL and Skin Water Content Measurements
by Perry Xiao and Daqing Chen
Sensors 2022, 22(9), 3595; https://doi.org/10.3390/s22093595 - 9 May 2022
Cited by 5 | Viewed by 2122
Abstract
Stratum corneum (SC) is the outermost skin layer. SC hydration is important for its cosmetic properties and barrier function. SC trans-epidermal water loss (TEWL) measurements and skin water content measurements are two key indexes used for SC characterisation. The instrument stability and accuracy [...] Read more.
Stratum corneum (SC) is the outermost skin layer. SC hydration is important for its cosmetic properties and barrier function. SC trans-epidermal water loss (TEWL) measurements and skin water content measurements are two key indexes used for SC characterisation. The instrument stability and accuracy are vitally important when measuring small changes. In this paper, we present our latest study on the effect of sun tan lotion on skin by using skin TEWL and skin water content measurements. We developed techniques to improve the measurement stability and to visualise small changes, as well as developed machine learning algorithms for processing the skin capacitive images. The overall results show that TEWL and skin water content measurements are capable of measuring the subtle changes of skin conditions due to the application of sun tan lotions. The results show that the TEWL values decreased after the sun tan lotion application. The sun tan lotion with SPF 20 had the lowest decrease, whilst the sun tan lotion with SPF 50+ had the highest decrease. The results also show that the skin water content increased after the sun tan lotion application, with SPF 20 having the highest increase, whilst SPF 50+ had the lowest increase. Full article
(This article belongs to the Special Issue Capacitive Fingerprint Sensors and Applications)
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15 pages, 1720 KiB  
Review
Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach
by Temitope Emmanuel Komolafe, Cheng Zhang, Oluwatosin Atinuke Olagbaju, Gang Yuan, Qiang Du, Ming Li, Jian Zheng and Xiaodong Yang
Sensors 2022, 22(9), 3594; https://doi.org/10.3390/s22093594 - 9 May 2022
Cited by 4 | Viewed by 2746
Abstract
Background: Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers. Methods: Two [...] Read more.
Background: Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers. Methods: Two independent reviewers identified screening on diagnostic studies from 1 January 2015 to 30 December 2021, with at least reported sensitivity and specificity for both CBBCT and DBT. A univariate pooled meta-analysis was performed using the random-effects model to estimate the sensitivity and specificity while other diagnostic parameters like the area under the ROC curve (AUC), positive likelihood ratio (LR+), and negative likelihood ratio (LR) were estimated using the bivariate model. Results: The pooled sensitivity specificity, LR+ and LR and AUC at 95% confidence interval are 86.7% (80.3–91.2), 87.0% (79.9–91.8), 6.28 (4.40–8.96), 0.17 (0.12–0.25) and 0.925 for the 17 included studies in DBT arm, respectively, while, 83.7% (54.6–95.7), 71.3% (47.5–87.2), 2.71 (1.39–5.29), 0.20 (0.04–1.05), and 0.831 are the pooled sensitivity specificity, LR+ and LR and AUC for the five studies in the CBBCT arm, respectively. Conclusions: Our study demonstrates that DBT shows improved diagnostic performance over CBBCT regarding all estimated diagnostic parameters; with the statistical improvement in the AUC of DBT over CBBCT. The CBBCT might be a useful modality for breast cancer detection, thus we recommend more prospective studies on CBBCT application. Full article
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23 pages, 8454 KiB  
Article
A Two-Step Fusion Method of Wi-Fi FTM for Indoor Positioning
by Shenglei Xu, Yunjia Wang and Minghao Si
Sensors 2022, 22(9), 3593; https://doi.org/10.3390/s22093593 - 9 May 2022
Cited by 3 | Viewed by 2921
Abstract
The Wi-Fi fine time measurement (FTM) protocol specified in the IEEE 802.11-2016 standard provides a new two-way ranging approach to enhance positioning capability. Similar to other wireless signals, the accuracy of the real-time range measurement of FTM is influenced by various errors. In [...] Read more.
The Wi-Fi fine time measurement (FTM) protocol specified in the IEEE 802.11-2016 standard provides a new two-way ranging approach to enhance positioning capability. Similar to other wireless signals, the accuracy of the real-time range measurement of FTM is influenced by various errors. In this work, the characteristics of the ranging errors is analyzed and an abstract ranging model is introduced. From the perspective of making full use of the range measurements from FTM, this paper designs two positioning steps and proposes a fusion method to refine the performance of indoor positioning. The first step is named single-point positioning, locating the position with the real-time range measurements based on the geometric principle. The second step is named the improved matching positioning, which constructs a distance database by utilizing the existing scene information and uses the modified matching algorithm to obtain the position. In view of the different positioning accuracies and error distributions from the results of the aforementioned two steps, a fusion method using the indirect adjustment principle is proposed to adjust the positioning results, and the advantages of the matching scene information and the range measurements are served simultaneously. Finally, a number of tests are conducted to assess the performance of the proposed method. The experimental results demonstrate that the precision and stability of indoor positioning are improved by the proposed fusion method. Full article
(This article belongs to the Section Navigation and Positioning)
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27 pages, 9636 KiB  
Article
Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts
by Mohamed Khalafalla Hassan, Sharifah Hafizah Syed Ariffin, N. Effiyana Ghazali, Mutaz Hamad, Mosab Hamdan, Monia Hamdi, Habib Hamam and Suleman Khan
Sensors 2022, 22(9), 3592; https://doi.org/10.3390/s22093592 - 9 May 2022
Cited by 6 | Viewed by 2402
Abstract
Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resource planning and forecasting are essential steps for [...] Read more.
Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resource planning and forecasting are essential steps for resource allocation. This study proposes a reliable hybrid dynamic bandwidth slice forecasting framework that combines the long short-term memory (LSTM) neural network and local smoothing methods to improve the network forecasting model. Moreover, the proposed framework can dynamically react to all the changes occurring in the data series. Backbone traffic was used to validate the proposed method. As a result, the forecasting accuracy improved significantly with the proposed framework and with minimal data loss from the smoothing process. The results showed that the hybrid moving average LSTM (MLSTM) achieved the most remarkable improvement in the training and testing forecasts, with 28% and 24% for long-term evolution (LTE) time series and with 35% and 32% for the multiprotocol label switching (MPLS) time series, respectively, while robust locally weighted scatter plot smoothing and LSTM (RLWLSTM) achieved the most significant improvement for upstream traffic with 45%; moreover, the dynamic learning framework achieved improvement percentages that can reach up to 100%. Full article
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18 pages, 2568 KiB  
Article
A Novel Scheme for Controller Selection in Software-Defined Internet-of-Things (SD-IoT)
by Jehad Ali and Byeong-hee Roh
Sensors 2022, 22(9), 3591; https://doi.org/10.3390/s22093591 - 9 May 2022
Cited by 11 | Viewed by 2126
Abstract
The software-defined networking (SDN) standard decouples the data and control planes. SDN is used in the Internet of Things (IoT) due to its programmability, central view and deployment of innovative protocols, and is known as SD-IoT. However, in SD-IoT, controller selection has never [...] Read more.
The software-defined networking (SDN) standard decouples the data and control planes. SDN is used in the Internet of Things (IoT) due to its programmability, central view and deployment of innovative protocols, and is known as SD-IoT. However, in SD-IoT, controller selection has never been studied. Controllers control the network and react to dynamic changes in SD-IoT. As sensors communicate frequently with the controller in SD-IoT, there is a degradation in performance with scalability and an increase in flow requests. Hence, the controller performance and selection are critical for SD-IoT. However, one controller’s support for certain functions is high while another’s is poor. There are various SD-IoT controllers, and choosing the best one might be a multi-criteria choice. An analytical network decision making process- (ANDP) based technique is employed here to identify feature-based optimal controllers in SD-IoT. The experimental analysis quantifies the high-weight controller from the feature-based comparison. An ANDP-based feature-based controller selection strategy is suggested, which selects the controller with the best feature set first, before comparing performance. This paper’s main contribution is to evaluate the ANDP for SD-IoT controller selection based on its features and performance validation in the SD-IoT environment. The simulation results suggest that the proposed controller outperforms the controller selected with previous schemes. Choosing an optimal controller in SD-IoT reduces the delay in both normal and heavy traffic scenarios. The suggested controller also increases throughput while using the central processing unit (CPU) efficiently and reduces the recovery latency in case of failures in the network. Full article
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10 pages, 271 KiB  
Article
Consequences of Patellar Tendinopathy on Isokinetic Knee Strength and Jumps in Professional Volleyball Players
by Marie Chantrelle, Pierre Menu, Marie Gernigon, Bastien Louguet, Marc Dauty and Alban Fouasson-Chailloux
Sensors 2022, 22(9), 3590; https://doi.org/10.3390/s22093590 - 9 May 2022
Cited by 3 | Viewed by 2946
Abstract
Patellar tendinopathy (PT) in professional volleyball players can have an impact on their careers. We evaluated the impact of this pathology in this specific population in terms of isokinetic strength and jumping performances. Thirty-six professional male volleyball players (mean age: 24.8 ± 5.2) [...] Read more.
Patellar tendinopathy (PT) in professional volleyball players can have an impact on their careers. We evaluated the impact of this pathology in this specific population in terms of isokinetic strength and jumping performances. Thirty-six professional male volleyball players (mean age: 24.8 ± 5.2) performed isokinetic knee assessments, single-leg countermovement jumps and one leg hop test. They filled out the Victorian Institute of Sport Assessment-Patella (VISA-P) score. Two groups were assessed: “PT group” (n = 15) and “control group” (n = 21). The VISA-P score was lower in the PT group (p < 0.0001). No difference was found between the isokinetic strength limb symmetry index and the jump performance limb symmetry index. The healthy legs of the control group were compared with the affected (PT+) and the unaffected legs (PT−) of the PT group. Compared with the healthy legs, both PT+ and PT− legs showed decreased values of quadriceps and hamstring strengths. Only PT+ legs scored lower than healthy legs in countermovement jumps and hop tests. No differences were found between PT+ and PT− legs for muscle strengths and jumps. A low correlation existed between quadriceps strength and jumping performances (r > 0.3; p < 0.001). Volleyball players with PT showed a decrease in the isokinetic knee strength. This strength deficit was found both on the symptomatic legs and the asymptomatic ones. Jumps were only significantly altered on the pathological legs. Highlighting that the unaffected limbs were also impaired in addition to the affected limbs may help provide a better adaptation of the rehabilitation management. Full article
(This article belongs to the Special Issue Sensor Technologies for Human Health Monitoring)
36 pages, 3911 KiB  
Review
A Review of Fundamental Optimization Approaches and the Role of AI Enabling Technologies in Physical Layer Security
by Mulugeta Kassaw Tefera, Zengwang Jin and Shengbing Zhang
Sensors 2022, 22(9), 3589; https://doi.org/10.3390/s22093589 - 9 May 2022
Cited by 5 | Viewed by 2973
Abstract
With the proliferation of 5G mobile networks within next-generation wireless communication, the design and optimization of 5G networks are progressing in the direction of improving the physical layer security (PLS) paradigm. This phenomenon is due to the fact that traditional methods for the [...] Read more.
With the proliferation of 5G mobile networks within next-generation wireless communication, the design and optimization of 5G networks are progressing in the direction of improving the physical layer security (PLS) paradigm. This phenomenon is due to the fact that traditional methods for the network optimization of PLS fail to adapt new features, technologies, and resource management to diversified demand applications. To improve these methods, future 5G and beyond 5G (B5G) networks will need to rely on new enabling technologies. Therefore, approaches for PLS design and optimization that are based on artificial intelligence (AI) and machine learning (ML) have been corroborated to outperform traditional security technologies. This will allow future 5G networks to be more intelligent and robust in order to significantly improve the performance of system design over traditional security methods. With the objective of advancing future PLS research, this review paper presents an elaborate discussion on the design and optimization approaches of wireless PLS techniques. In particular, we focus on both signal processing and information-theoretic security approaches to investigate the optimization techniques and system designs of PLS strategies. The review begins with the fundamental concepts that are associated with PLS, including a discussion on conventional cryptographic techniques and wiretap channel models. We then move on to discuss the performance metrics and basic optimization schemes that are typically adopted in PLS design strategies. The research directions for secure system designs and optimization problems are then reviewed in terms of signal processing, resource allocation and node/antenna selection. Thereafter, the applications of AI and ML technologies in the optimization and design of PLS systems are discussed. In this context, the ML- and AI-based solutions that pertain to end-to-end physical layer joint optimization, secure resource allocation and signal processing methods are presented. We finally conclude with discussions on future trends and technical challenges that are related to the topics of PLS system design and the benefits of AI technologies. Full article
(This article belongs to the Section Intelligent Sensors)
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18 pages, 5745 KiB  
Article
Multi-Color Space Network for Salient Object Detection
by Kyungjun Lee and Jechang Jeong
Sensors 2022, 22(9), 3588; https://doi.org/10.3390/s22093588 - 9 May 2022
Cited by 3 | Viewed by 2315
Abstract
The salient object detection (SOD) technology predicts which object will attract the attention of an observer surveying a particular scene. Most state-of-the-art SOD methods are top-down mechanisms that apply fully convolutional networks (FCNs) of various structures to RGB images, extract features from them, [...] Read more.
The salient object detection (SOD) technology predicts which object will attract the attention of an observer surveying a particular scene. Most state-of-the-art SOD methods are top-down mechanisms that apply fully convolutional networks (FCNs) of various structures to RGB images, extract features from them, and train a network. However, owing to the variety of factors that affect visual saliency, securing sufficient features from a single color space is difficult. Therefore, in this paper, we propose a multi-color space network (MCSNet) to detect salient objects using various saliency cues. First, the images were converted to HSV and grayscale color spaces to obtain saliency cues other than those provided by RGB color information. Each saliency cue was fed into two parallel VGG backbone networks to extract features. Contextual information was obtained from the extracted features using atrous spatial pyramid pooling (ASPP). The features obtained from both paths were passed through the attention module, and channel and spatial features were highlighted. Finally, the final saliency map was generated using a step-by-step residual refinement module (RRM). Furthermore, the network was trained with a bidirectional loss to supervise saliency detection results. Experiments on five public benchmark datasets showed that our proposed network achieved superior performance in terms of both subjective results and objective metrics. Full article
(This article belongs to the Section Sensing and Imaging)
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14 pages, 5061 KiB  
Article
Mechanism of Magnetic Flux Leakage Detection Method Based on the Slotted Ferromagnetic Lift-Off Layer
by Jian Tang, Rongbiao Wang, Gongzhe Qiu, Yu Hu and Yihua Kang
Sensors 2022, 22(9), 3587; https://doi.org/10.3390/s22093587 - 9 May 2022
Cited by 7 | Viewed by 2319
Abstract
Magnetic flux leakage (MFL) testing is widely used in non-destructive testing of ferromagnetic components. In view of the serious attenuation of the leakage magnetic field (LMF) caused by the transmission of LMF in the lift-off layer between the measuring point and the workpiece, [...] Read more.
Magnetic flux leakage (MFL) testing is widely used in non-destructive testing of ferromagnetic components. In view of the serious attenuation of the leakage magnetic field (LMF) caused by the transmission of LMF in the lift-off layer between the measuring point and the workpiece, this paper introduces an MFL detection method based on the slotted ferromagnetic lift-off layer (SFLL). The conventional non-ferromagnetic lift-off layer is changed to a ferromagnetic lift-off layer with a rectangular slot. The magnetic sensor is fixed above the slot and scans the workpiece together with the lift-off layer. First, the detection mechanism of the new method was studied by an equivalent LMF coil model. The permeability perturbation effect and the magnetization enhancement effect were analyzed in the new method. Based on the detection mechanism, the lift-off tolerance of the new method was investigated. Then, the LMF enhancement and lift-off tolerance of the new method in the steel plate detection model were studied. Finally, experiments were conducted to compare the new method with the conventional method. The simulation and experimental results show that the slotted ferromagnetic lift-off layer enhances the amplitude of the MFL signal and is tolerant to the lift-off value. This method provides a new idea for optimizing the design of the MFL sensor and improving the sensitivity of MFL detection at a large lift-off value. Full article
(This article belongs to the Section Industrial Sensors)
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17 pages, 444 KiB  
Article
Extracting the Secrets of OpenSSL with RAMBleed
by Chihiro Tomita, Makoto Takita, Kazuhide Fukushima, Yuto Nakano, Yoshiaki Shiraishi and Masakatu Morii
Sensors 2022, 22(9), 3586; https://doi.org/10.3390/s22093586 - 9 May 2022
Cited by 3 | Viewed by 2090
Abstract
Concomitant with the increasing density of semiconductors, various attacks that threaten the integrity and security of dynamic random access memory (DRAM) have been devised. Among these, a side-channel attack called RAMBleed is a prolific one that utilizes a general user-level account without special [...] Read more.
Concomitant with the increasing density of semiconductors, various attacks that threaten the integrity and security of dynamic random access memory (DRAM) have been devised. Among these, a side-channel attack called RAMBleed is a prolific one that utilizes a general user-level account without special rights to read secret information. Studies have reported that it can be used to obtain OpenSSH secret keys. However, a technique for deriving the Rivest–Shamir–Adleman (RSA) secret keys used in OpenSSL under realistic parameters and environments has not been reported. We propose a method that uses RAMBleed to obtain OpenSSL secret keys and demonstrate its efficacy using the example of an Apache server. The proposed method exploits the fact that, in the operation of an Apache server that uses OpenSSL, the RSA private keys are deployed on DRAM at a set time. Although the result of reading this secret information contains a few errors, error-free secret information is obtainable when it is used with RSA cryptanalysis techniques. We performed a series of attacks incorporating RAMBleed and eventually retrieved the OpenSSL RSA private key, indicating that secret information is obtainable with high probability. The proposed method can easily and externally be executed without administrator privileges on a server using DRAM that is vulnerable to RAMBleed, showing that RAMBleed is also a major threat to OpenSSL. Full article
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16 pages, 1973 KiB  
Article
Early Detection of Grapevine (Vitis vinifera) Downy Mildew (Peronospora) and Diurnal Variations Using Thermal Imaging
by Bar Cohen, Yael Edan, Asher Levi and Victor Alchanatis
Sensors 2022, 22(9), 3585; https://doi.org/10.3390/s22093585 - 8 May 2022
Cited by 14 | Viewed by 2956
Abstract
Agricultural industry is facing a serious threat from plant diseases that cause production and economic losses. Early information on disease development can improve disease control using suitable management strategies. This study sought to detect downy mildew (Peronospora) on grapevine (Vitis [...] Read more.
Agricultural industry is facing a serious threat from plant diseases that cause production and economic losses. Early information on disease development can improve disease control using suitable management strategies. This study sought to detect downy mildew (Peronospora) on grapevine (Vitis vinifera) leaves at early stages of development using thermal imaging technology and to determine the best time during the day for image acquisition. In controlled experiments, 1587 thermal images of grapevines grown in a greenhouse were acquired around midday, before inoculation, 1, 2, 4, 5, 6, and 7 days after an inoculation. In addition, images of healthy and infected leaves were acquired at seven different times during the day between 7:00 a.m. and 4:30 p.m. Leaves were segmented using the active contour algorithm. Twelve features were derived from the leaf mask and from meteorological measurements. Stepwise logistic regression revealed five significant features used in five classification models. Performance was evaluated using K-folds cross-validation. The support vector machine model produced the best classification accuracy of 81.6%, F1 score of 77.5% and area under the curve (AUC) of 0.874. Acquiring images in the morning between 10:40 a.m. and 11:30 a.m. resulted in 80.7% accuracy, 80.5% F1 score, and 0.895 AUC. Full article
(This article belongs to the Special Issue Robotics and Sensors Technology in Agriculture)
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19 pages, 5904 KiB  
Article
Change in Electrical Resistance of SMA (NiTi) Wires during Cyclic Stretching
by Sebastian Sławski, Marek Kciuk and Wojciech Klein
Sensors 2022, 22(9), 3584; https://doi.org/10.3390/s22093584 - 8 May 2022
Cited by 6 | Viewed by 2665
Abstract
In this article, the use of Nickel Titanium (NiTi) alloy as a sensor is examined. A cyclic stretching test, that has various elongations (0.5 and 1%), is administered to NiTi wires with various diameters and lengths. It is assumed that the elongation enables [...] Read more.
In this article, the use of Nickel Titanium (NiTi) alloy as a sensor is examined. A cyclic stretching test, that has various elongations (0.5 and 1%), is administered to NiTi wires with various diameters and lengths. It is assumed that the elongation enables an observation of the change in electrical resistance of the NiTi wires, due to martensite reorientation. During the test, the stretching force, the displacement, and the electrical resistance of the NiTi wires are measured. Following the test, the resistance of all the tested samples differed compared to the starting position. Conducted research indicates that NiTi wires are very sensitive to resistance change when they are deformed. A large difference in NiTi electrical resistance was visible in all samples during the first stretching cycle. For longer wires, with a smaller diameter, resistance change was visible during almost all of the stretching cycles. However, the observed changes were very small. Based on the obtained results, it can be justifiably stated that NiTi wires could be used to build deformation sensors, which operate both online and offline. Moreover, NiTi wires with a small diameter could be used to create cyclic loading sensors. Such sensors can be used in self-sensing applications or in structural health monitoring. Full article
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24 pages, 4953 KiB  
Article
BioTouch: Reliable Re-Authentication via Finger Bio-Capacitance and Touching Behavior
by Chong Zhang, Songfan Li, Yihang Song, Qianhe Meng, Li Lu and Mengshu Hou
Sensors 2022, 22(9), 3583; https://doi.org/10.3390/s22093583 - 8 May 2022
Cited by 1 | Viewed by 2771
Abstract
Re-authentication continuously checks to see if a user is authorized during a whole usage session, enhancing secrecy capabilities for computational devices, especially against insider attacks. However, it is challenging to design a reliable re-authentication scheme with accuracy, transparency and robustness. Specifically, the approaches [...] Read more.
Re-authentication continuously checks to see if a user is authorized during a whole usage session, enhancing secrecy capabilities for computational devices, especially against insider attacks. However, it is challenging to design a reliable re-authentication scheme with accuracy, transparency and robustness. Specifically, the approaches of using biometric features (e.g., fingerprint, iris) are often accurate in identifying users but not transparent to them due to the need for user cooperation. On the other hand, while the approaches exploiting behavior features (e.g., touch-screen gesture, movement) are often transparent in use, their applications suffer from low accuracy and robustness as behavior information collected is subjective and may change frequently over different use situations and even user’s motion. In this paper, we propose BioTouch, a reliable re-authentication scheme that satisfies all the above requirements. First, BioTouch utilizes multiple features (finger capacitance and touching behavior) to identify the user for better accuracy. Second, BioTouch automatically works during user operation on capacitive-touch devices, achieving transparency without the need for manual assistance. Finally, by applying finger bio-capacitance, BioTouch is also robust to various conditions, as this feature is determined by the user’s physical characteristics and will not change by different user positions and motions. We implement BioTouch for proof-of-concept and conduct comprehensive evaluations. The results show that BioTouch can flag 98% of anomalous behaviors within ten touching operations and achieve up to 99.84% accuracy during usage. Full article
(This article belongs to the Special Issue Trustworthy Sensing with Human-and-Environment-in-the-Loop)
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16 pages, 647 KiB  
Review
Can the Eight Hop Test Be Measured with Sensors? A Systematic Review
by Luís Pimenta, Nuno M. Garcia, Eftim Zdravevski, Ivan Chorbev, Vladimir Trajkovik, Petre Lameski, Carlos Albuquerque and Ivan Miguel Pires
Sensors 2022, 22(9), 3582; https://doi.org/10.3390/s22093582 - 8 May 2022
Viewed by 2928
Abstract
Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various [...] Read more.
Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb. This paper presents a systematic review on the use of sensors for measuring functional movements during the execution of the Eight Hop Test, focusing primarily on the use of sensors, related diseases, and different methods implemented. Firstly, an automated search was performed on the publication databases: PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Secondly, the publications related to the Eight-Hop Test and sensors were filtered according to several search criteria and 15 papers were finally selected to be analyzed in detail. Our analysis found that the Eight Hop Test measurements can be performed with motion, force, and imaging sensors. Full article
(This article belongs to the Special Issue Mobile Health Technologies for Ambient Assisted Living and Healthcare)
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25 pages, 4844 KiB  
Article
A Novel Smart Contract Vulnerability Detection Method Based on Information Graph and Ensemble Learning
by Lejun Zhang, Jinlong Wang, Weizheng Wang, Zilong Jin, Chunhui Zhao, Zhennao Cai and Huiling Chen
Sensors 2022, 22(9), 3581; https://doi.org/10.3390/s22093581 - 8 May 2022
Cited by 30 | Viewed by 5382
Abstract
Blockchain presents a chance to address the security and privacy issues of the Internet of Things; however, blockchain itself has certain security issues. How to accurately identify smart contract vulnerabilities is one of the key issues at hand. Most existing methods require large-scale [...] Read more.
Blockchain presents a chance to address the security and privacy issues of the Internet of Things; however, blockchain itself has certain security issues. How to accurately identify smart contract vulnerabilities is one of the key issues at hand. Most existing methods require large-scale data support to avoid overfitting; machine learning (ML) models trained on small-scale vulnerability data are often difficult to produce satisfactory results in smart contract vulnerability prediction. However, in the real world, collecting contractual vulnerability data requires huge human and time costs. To alleviate these problems, this paper proposed an ensemble learning (EL)-based contract vulnerability prediction method, which is based on seven different neural networks using contract vulnerability data for contract-level vulnerability detection. Seven neural network (NN) models were first pretrained using an information graph (IG) consisting of source datasets, which then were integrated into an ensemble model called Smart Contract Vulnerability Detection method based on Information Graph and Ensemble Learning (SCVDIE). The effectiveness of the SCVDIE model was verified using a target dataset composed of IG, and then its performances were compared with static tools and seven independent data-driven methods. The verification and comparison results show that the proposed SCVDIE method has higher accuracy and robustness than other data-driven methods in the target task of predicting smart contract vulnerabilities. Full article
(This article belongs to the Special Issue Blockchain of Things: Benefits, Challenges and Future Directions)
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17 pages, 1980 KiB  
Article
Virtual Breathalyzer: Towards the Detection of Intoxication Using Motion Sensors of Commercial Wearable Devices
by Ben Nassi, Jacob Shams, Lior Rokach and Yuval Elovici
Sensors 2022, 22(9), 3580; https://doi.org/10.3390/s22093580 - 8 May 2022
Cited by 2 | Viewed by 2830
Abstract
Driving under the influence of alcohol is a widespread phenomenon in the US where it is considered a major cause of fatal accidents. In this research, we present Virtual Breathalyzer, a novel approach for detecting intoxication from the measurements obtained by the sensors [...] Read more.
Driving under the influence of alcohol is a widespread phenomenon in the US where it is considered a major cause of fatal accidents. In this research, we present Virtual Breathalyzer, a novel approach for detecting intoxication from the measurements obtained by the sensors of smartphones and wrist-worn devices. We formalize the problem of intoxication detection as the supervised machine learning task of binary classification (drunk or sober). In order to evaluate our approach, we conducted a field experiment and collected 60 free gait samples from 30 patrons of three bars using a Microsoft Band and Samsung Galaxy S4. We validated our results against an admissible breathalyzer used by the police. A system based on this concept successfully detected intoxication and achieved the following results: 0.97 AUC and 0.04 FPR, given a fixed TPR of 1.0. Our approach can be used to analyze the free gait of drinkers when they walk from the car to the bar and vice versa, using wearable devices which are ubiquitous and more widespread than admissible breathalyzers. This approach can be utilized to alert people, or even a connected car, and prevent people from driving under the influence of alcohol. Full article
(This article belongs to the Collection Sensors for Gait, Human Movement Analysis, and Health Monitoring)
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20 pages, 4705 KiB  
Article
Efficient Path Planning for Mobile Robot Based on Deep Deterministic Policy Gradient
by Hui Gong, Peng Wang, Cui Ni and Nuo Cheng
Sensors 2022, 22(9), 3579; https://doi.org/10.3390/s22093579 - 8 May 2022
Cited by 21 | Viewed by 3884
Abstract
When a traditional Deep Deterministic Policy Gradient (DDPG) algorithm is used in mobile robot path planning, due to the limited observable environment of mobile robots, the training efficiency of the path planning model is low, and the convergence speed is slow. In this [...] Read more.
When a traditional Deep Deterministic Policy Gradient (DDPG) algorithm is used in mobile robot path planning, due to the limited observable environment of mobile robots, the training efficiency of the path planning model is low, and the convergence speed is slow. In this paper, Long Short-Term Memory (LSTM) is introduced into the DDPG network, the former and current states of the mobile robot are combined to determine the actions of the robot, and a Batch Norm layer is added after each layer of the Actor network. At the same time, the reward function is optimized to guide the mobile robot to move faster towards the target point. In order to improve the learning efficiency, different normalization methods are used to normalize the distance and angle between the mobile robot and the target point, which are used as the input of the DDPG network model. When the model outputs the next action of the mobile robot, mixed noise composed of Gaussian noise and Ornstein–Uhlenbeck (OU) noise is added. Finally, the simulation environment built by a ROS system and a Gazebo platform is used for experiments. The results show that the proposed algorithm can accelerate the convergence speed of DDPG, improve the generalization ability of the path planning model and improve the efficiency and success rate of mobile robot path planning. Full article
(This article belongs to the Section Sensors and Robotics)
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17 pages, 3346 KiB  
Review
A Review on VCII Applications in Signal Conditioning for Sensors and Bioelectrical Signals: New Opportunities
by Leila Safari, Gianluca Barile, Vincenzo Stornelli and Giuseppe Ferri
Sensors 2022, 22(9), 3578; https://doi.org/10.3390/s22093578 - 8 May 2022
Cited by 3 | Viewed by 2768
Abstract
This study reviews second-generation voltage conveyor (VCII)-based read-out circuits for sensors and bioelectrical signal conditioning from existing literature. VCII is the dual circuit of a second-generation current conveyor (CCII), which provides the possibility of processing signals in the current domain while providing output [...] Read more.
This study reviews second-generation voltage conveyor (VCII)-based read-out circuits for sensors and bioelectrical signal conditioning from existing literature. VCII is the dual circuit of a second-generation current conveyor (CCII), which provides the possibility of processing signals in the current domain while providing output signals in the voltage form. The scope of this paper is to discuss the benefits and opportunities of new VCII-based read-out circuits over traditional ones and bioelectrical signals. The achieved main benefits compared to conventional circuits are the simpler read-out circuits, producing an output signal in a voltage form that can be directly used, improved accuracy, possibility of gain adjustment using a single grounded resistor, and the possibility of connecting several SiPM sensors to the readout circuit. The circuits studied in this paper include VCII- based read-out circuits suitable for all types of sensors configured in the current-mode Wheatstone bridge (CMWB) topology, the VCII-based read-out circuits solutions reported for silicon photomultiplier, spiral-shaped ultrasonic PVDF and differential capacitive sensors, and, finally, a simple readout circuitry for sensing bioelectrical signals. There are still not many VCII-based readout circuits, and we hope that the outcome of this study will enhance this area of research and inspire new ideas. Full article
(This article belongs to the Special Issue Electronics for Sensors, Volume 2)
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24 pages, 3827 KiB  
Article
CBGRU: A Detection Method of Smart Contract Vulnerability Based on a Hybrid Model
by Lejun Zhang, Weijie Chen, Weizheng Wang, Zilong Jin, Chunhui Zhao, Zhennao Cai and Huiling Chen
Sensors 2022, 22(9), 3577; https://doi.org/10.3390/s22093577 - 7 May 2022
Cited by 40 | Viewed by 4969
Abstract
In the context of the rapid development of blockchain technology, smart contracts have also been widely used in the Internet of Things, finance, healthcare, and other fields. There has been an explosion in the number of smart contracts, and at the same time, [...] Read more.
In the context of the rapid development of blockchain technology, smart contracts have also been widely used in the Internet of Things, finance, healthcare, and other fields. There has been an explosion in the number of smart contracts, and at the same time, the security of smart contracts has received widespread attention because of the financial losses caused by smart contract vulnerabilities. Existing analysis tools can detect many smart contract security vulnerabilities, but because they rely too heavily on hard rules defined by experts when detecting smart contract vulnerabilities, the time to perform the detection increases significantly as the complexity of the smart contract increases. In the present study, we propose a novel hybrid deep learning model named CBGRU that strategically combines different word embedding (Word2Vec, FastText) with different deep learning methods (LSTM, GRU, BiLSTM, CNN, BiGRU). The model extracts features through different deep learning models and combine these features for smart contract vulnerability detection. On the currently publicly available dataset SmartBugs Dataset-Wild, we demonstrate that the CBGRU hybrid model has great smart contract vulnerability detection performance through a series of experiments. By comparing the performance of the proposed model with that of past studies, the CBGRU model has better smart contract vulnerability detection performance. Full article
(This article belongs to the Special Issue Blockchain of Things: Benefits, Challenges and Future Directions)
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37 pages, 17397 KiB  
Article
A New RF Energy Harvesting System Based on Two Architectures to Enhance the DC Output Voltage for WSN Feeding
by Chemseddine Benkalfate, Achour Ouslimani, Abed-Elhak Kasbari and Mohammed Feham
Sensors 2022, 22(9), 3576; https://doi.org/10.3390/s22093576 - 7 May 2022
Cited by 8 | Viewed by 4451
Abstract
In this paper, a new RF Energy Harvesting (RF-EH) system for Wireless Sensor Network (WSN) feeding is proposed. It is based on two different monitored architectures using switch circuits controlled by the input powers. One architecture is more adapted to high input powers [...] Read more.
In this paper, a new RF Energy Harvesting (RF-EH) system for Wireless Sensor Network (WSN) feeding is proposed. It is based on two different monitored architectures using switch circuits controlled by the input powers. One architecture is more adapted to high input powers and the other to low input powers. The two different architectures and the system are designed and realized on Teflon glass substrate with a relative permittivity of 2.1 and thickness of 0.67 mm. They are tested separately as a function of the distance from the relay antenna. A new multiband antenna with a size of 40 × 30 mm2 is used for both architectures and the system. The measured antenna gains are 2.7 dB, 2.9 dB, and 2.55 dB for the frequencies of 1.8 GHz, 2.1 GHz, and 2.66 GHz corresponding to the mobile communication networks, respectively. The rectifier consists of two Schottky diodes forming a full-wave rectifier and voltage doubler. The maximum measured RF-to-DC conversion efficiency is 71.5%. The proposed RF-EH system provides a maximum DC output voltage of 5.6 V and 3.15 V for an open and 2 kΩ resistance load, respectively. Full article
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12 pages, 1466 KiB  
Communication
Novel Receive Antenna Selection Scheme for Precoding-Aided Spatial Modulation with Lattice Reduction
by Sangchoon Kim
Sensors 2022, 22(9), 3575; https://doi.org/10.3390/s22093575 - 7 May 2022
Cited by 1 | Viewed by 1618
Abstract
In this paper, a new receive antenna subset (RAS) selection scheme is proposed for precoding-aided spatial modulation (PSM). First, a lattice reduction (LR)-based precoder is employed instead of a conventional zero-forcing (ZF) precoder. It is analytically shown that a full diversity gain can [...] Read more.
In this paper, a new receive antenna subset (RAS) selection scheme is proposed for precoding-aided spatial modulation (PSM). First, a lattice reduction (LR)-based precoder is employed instead of a conventional zero-forcing (ZF) precoder. It is analytically shown that a full diversity gain can be achieved by the LR-based ZF precoder without RAS selection. Then, an optimal LR-based RAS selection criterion is derived for the over-determined LR-based PSM systems, and a suboptimal selection algorithm is additionally presented. It is also shown that optimal and suboptimal RAS selection algorithms based on LR improve the BER performance of the LR-based PSM system. Further, the overall diversity order of the over-determined LR-based PSM systems with optimal LR-based RAS selection is analyzed. Finally, diversity analysis and simulation results show that the LR-ZF-based PSM system with optimal LR-based RAS selection outperforms the conventional ZF-based PSM system with conventional optimal RAS selection. Full article
(This article belongs to the Special Issue Next Generation Radio Communication Technologies)
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13 pages, 1591 KiB  
Article
Research on Dual-Frequency Electromagnetic False Alarm Interference Effect of a Typical Radar
by Xue Du, Guanghui Wei, Kai Zhao, Hongze Zhao and Xuxu Lyu
Sensors 2022, 22(9), 3574; https://doi.org/10.3390/s22093574 - 7 May 2022
Cited by 3 | Viewed by 1581
Abstract
In order to master the position variation rule of radar false alarm signal under continuous wave (CW) electromagnetic interference and reveal the mechanism of CW on radar, taking a certain type of stepping frequency radar as the research object, theoretical analysis of the [...] Read more.
In order to master the position variation rule of radar false alarm signal under continuous wave (CW) electromagnetic interference and reveal the mechanism of CW on radar, taking a certain type of stepping frequency radar as the research object, theoretical analysis of the imaging mechanism of radar CW electromagnetic interference false alarm signals from the perspective of time-frequency decoupling and receiver signal processing. Secondly, electromagnetic interference injection method is used to test the single-frequency and dual-frequency electromagnetic interference effect of the tested equipment. The results show that under the single frequency CW electromagnetic interference, the sensitive bandwidth of false alarm signal is about ±75 MHz, and the position of false alarm signal irregularity changes. Under the in-band dual-frequency CW electromagnetic interference, the position of non-intermodulation false alarm signal is similar to that of single frequency. However, the distance difference of two non-intermodulation false alarm signals is regular. In addition, the positions of the second-order intermodulation false alarm signals of the tested radar are also regular, and its position changes with the change of the second-order intermodulation frequency difference. Full article
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