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Sensors, Volume 18, Issue 2 (February 2018)

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Cover Story (view full-size image) Pec and co-workers report a random access preamble (RAP) design technique for underwater acoustic [...] Read more.
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Open AccessArticle Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors
Sensors 2018, 18(2), 679; https://doi.org/10.3390/s18020679
Received: 16 January 2018 / Revised: 16 February 2018 / Accepted: 22 February 2018 / Published: 24 February 2018
Cited by 1 | PDF Full-text (2627 KB) | HTML Full-text | XML Full-text
Abstract
Getting a good feature representation of data is paramount for Human Activity Recognition (HAR) using wearable sensors. An increasing number of feature learning approaches—in particular deep-learning based—have been proposed to extract an effective feature representation by analyzing large amounts of data. However, getting
[...] Read more.
Getting a good feature representation of data is paramount for Human Activity Recognition (HAR) using wearable sensors. An increasing number of feature learning approaches—in particular deep-learning based—have been proposed to extract an effective feature representation by analyzing large amounts of data. However, getting an objective interpretation of their performances faces two problems: the lack of a baseline evaluation setup, which makes a strict comparison between them impossible, and the insufficiency of implementation details, which can hinder their use. In this paper, we attempt to address both issues: we firstly propose an evaluation framework allowing a rigorous comparison of features extracted by different methods, and use it to carry out extensive experiments with state-of-the-art feature learning approaches. We then provide all the codes and implementation details to make both the reproduction of the results reported in this paper and the re-use of our framework easier for other researchers. Our studies carried out on the OPPORTUNITY and UniMiB-SHAR datasets highlight the effectiveness of hybrid deep-learning architectures involving convolutional and Long-Short-Term-Memory (LSTM) to obtain features characterising both short- and long-term time dependencies in the data. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time
Sensors 2018, 18(2), 678; https://doi.org/10.3390/s18020678
Received: 8 December 2017 / Revised: 8 February 2018 / Accepted: 13 February 2018 / Published: 24 February 2018
Cited by 1 | PDF Full-text (8022 KB) | HTML Full-text | XML Full-text
Abstract
For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work
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For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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Open AccessArticle Quadrature Errors and DC Offsets Calibration of Analog Complex Cross-Correlator for Interferometric Passive Millimeter-Wave Imaging Applications
Sensors 2018, 18(2), 677; https://doi.org/10.3390/s18020677
Received: 20 December 2017 / Revised: 15 February 2018 / Accepted: 20 February 2018 / Published: 24 February 2018
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Abstract
The design and calibration of the cross-correlator are crucial issues for interferometric imaging systems. In this paper, an analog complex cross-correlator with output DC offsets and amplitudes calibration capability is proposed for interferometric passive millimeter-wave security sensing applications. By employing digital potentiometers in
[...] Read more.
The design and calibration of the cross-correlator are crucial issues for interferometric imaging systems. In this paper, an analog complex cross-correlator with output DC offsets and amplitudes calibration capability is proposed for interferometric passive millimeter-wave security sensing applications. By employing digital potentiometers in the low frequency amplification circuits of the correlator, the outputs characteristics of the correlator could be digitally controlled. A measurement system and a corresponding calibration scheme were developed in order to eliminate the output DC offsets and the quadrature amplitude error between the in-phase and the quadrature correlating subunits of the complex correlator. By using vector modulators to provide phase controllable correlated noise signals, the measurement system was capable of obtaining the output correlation circle of the correlator. When injected with −18 dBm correlated noise signals, the calibrated quadrature amplitude error was 0.041 dB and the calibrated DC offsets were under 26 mV, which was only 7.1% of the uncalibrated value. Furthermore, we also described a quadrature errors calibration algorithm in order to estimate the quadrature phase error and in order to improve the output phase accuracy of the correlator. After applying this calibration, we were able to reduce the output phase error of the correlator to 0.3°. Full article
(This article belongs to the Special Issue Sensors for Microwave Imaging and Detection)
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Open AccessArticle An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors
Sensors 2018, 18(2), 676; https://doi.org/10.3390/s18020676
Received: 6 January 2018 / Revised: 8 February 2018 / Accepted: 20 February 2018 / Published: 24 February 2018
Cited by 1 | PDF Full-text (6824 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper aims to assess the use of Inertial Measurement Unit (IMU) sensors to identify gait asymmetry by extracting automatic gait features. We design and develop an android app to collect real time synchronous IMU data from legs. The results from our method
[...] Read more.
This paper aims to assess the use of Inertial Measurement Unit (IMU) sensors to identify gait asymmetry by extracting automatic gait features. We design and develop an android app to collect real time synchronous IMU data from legs. The results from our method are validated using a Qualisys Motion Capture System. The data are collected from 10 young and 10 older subjects. Each performed a trial in a straight corridor comprising 15 strides of normal walking, a turn around and another 15 strides. We analyse the data for total distance, total time, total velocity, stride, step, cadence, step ratio, stance, and swing. The accuracy of detecting the stride number using the proposed method is 100% for young and 92.67% for older subjects. The accuracy of estimating travelled distance using the proposed method for young subjects is 97.73% and 98.82% for right and left legs; and for the older, is 88.71% and 89.88% for right and left legs. The average travelled distance is 37.77 (95% CI ± 3.57) meters for young subjects and is 22.50 (95% CI ± 2.34) meters for older subjects. The average travelled time for young subjects is 51.85 (95% CI ± 3.08) seconds and for older subjects is 84.02 (95% CI ± 9.98) seconds. The results show that wearable sensors can be used for identifying gait asymmetry without the requirement and expense of an elaborate laboratory setup. This can serve as a tool in diagnosing gait abnormalities in individuals and opens the possibilities for home based self-gait asymmetry assessment. Full article
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
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Open AccessFeature PaperReview Integrated Affinity Biosensing Platforms on Screen-Printed Electrodes Electrografted with Diazonium Salts
Sensors 2018, 18(2), 675; https://doi.org/10.3390/s18020675
Received: 29 January 2018 / Revised: 15 February 2018 / Accepted: 20 February 2018 / Published: 24 February 2018
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Abstract
Adequate selection of the electrode surface and the strategies for its modification to enable subsequent immobilization of biomolecules and/or nanomaterials integration play a major role in the performance of electrochemical affinity biosensors. Because of the simplicity, rapidity and versatility, electrografting using diazonium salt
[...] Read more.
Adequate selection of the electrode surface and the strategies for its modification to enable subsequent immobilization of biomolecules and/or nanomaterials integration play a major role in the performance of electrochemical affinity biosensors. Because of the simplicity, rapidity and versatility, electrografting using diazonium salt reduction is among the most currently used functionalization methods to provide the attachment of an organic layer to a conductive substrate. This particular chemistry has demonstrated to be a powerful tool to covalently immobilize in a stable and reproducible way a wide range of biomolecules or nanomaterials onto different electrode surfaces. Considering the great progress and interesting features arisen in the last years, this paper outlines the potential of diazonium chemistry to prepare single or multianalyte electrochemical affinity biosensors on screen-printed electrodes (SPEs) and points out the existing challenges and future directions in this field. Full article
(This article belongs to the Special Issue Screen-Printed Electrodes)
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Open AccessArticle Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems
Sensors 2018, 18(2), 674; https://doi.org/10.3390/s18020674
Received: 29 December 2017 / Revised: 7 February 2018 / Accepted: 15 February 2018 / Published: 24 February 2018
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Abstract
Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although
[...] Read more.
Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries. In addition, we extend our game model and analyze the extortion strategy, which can enable one participant to obtain more payoff by extorting his/her opponents. The evaluation results show that the defender can combat this strategy by encouraging competition among the adversaries, and significantly suppress the total payoff of the adversaries via setting the proper penalty factor. Full article
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Open AccessArticle A Feasibility Study on the Use of a Structured Light Depth-Camera for Three-Dimensional Body Measurements of Dairy Cows in Free-Stall Barns
Sensors 2018, 18(2), 673; https://doi.org/10.3390/s18020673
Received: 6 December 2017 / Revised: 15 February 2018 / Accepted: 21 February 2018 / Published: 24 February 2018
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Abstract
Frequent checks on livestock’s body growth can help reducing problems related to cow infertility or other welfare implications, and recognizing health’s anomalies. In the last ten years, optical methods have been proposed to extract information on various parameters while avoiding direct contact with
[...] Read more.
Frequent checks on livestock’s body growth can help reducing problems related to cow infertility or other welfare implications, and recognizing health’s anomalies. In the last ten years, optical methods have been proposed to extract information on various parameters while avoiding direct contact with animals’ body, generally causes stress. This research aims to evaluate a new monitoring system, which is suitable to frequently check calves and cow’s growth through a three-dimensional analysis of their bodies’ portions. The innovative system is based on multiple acquisitions from a low cost Structured Light Depth-Camera (Microsoft Kinect™ v1). The metrological performance of the instrument is proved through an uncertainty analysis and a proper calibration procedure. The paper reports application of the depth camera for extraction of different body parameters. Expanded uncertainty ranging between 3 and 15 mm is reported in the case of ten repeated measurements. Coefficients of determination R² > 0.84 and deviations lower than 6% from manual measurements where in general detected in the case of head size, hips distance, withers to tail length, chest girth, hips, and withers height. Conversely, lower performances where recognized in the case of animal depth (R² = 0.74) and back slope (R² = 0.12). Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite
Sensors 2018, 18(2), 672; https://doi.org/10.3390/s18020672
Received: 14 December 2017 / Revised: 12 February 2018 / Accepted: 14 February 2018 / Published: 24 February 2018
Cited by 3 | PDF Full-text (28018 KB) | HTML Full-text | XML Full-text
Abstract
The Chinese GF-3 satellite launched in August 2016 is a Synthetic Aperture Radar (SAR) satellite that has the largest number of imaging modes in the world. It achieves a free switch in the spotlight, stripmap, scanSAR, wave, global observation and other imaging modes.
[...] Read more.
The Chinese GF-3 satellite launched in August 2016 is a Synthetic Aperture Radar (SAR) satellite that has the largest number of imaging modes in the world. It achieves a free switch in the spotlight, stripmap, scanSAR, wave, global observation and other imaging modes. In order to further utilize GF-3 SAR images, an automatic and fast image registration procedure needs to be done. In this paper, we propose a novel image registration technique for GF-3 images of different imaging modes. The proposed algorithm consists of two stages: coarse registration and fine registration. In the first stage, we combine an adaptive sampling method with the SAR-SIFT algorithm to efficiently eliminate obvious translation, rotation and scale differences between the reference and sensed images. In the second stage, uniformly-distributed control points are extracted, then the fast normalized cross-correlation of an improved phase congruency model is utilized as a new similarity metric to match the reference image and the coarse-registered image in a local search region. Moreover, a selection strategy is used to remove outliers. Experimental results on several GF-3 SAR images of different imaging modes show that the proposed algorithm gives a robust, efficient and precise registration performance, compared with other state-of-the-art algorithms for SAR image registration. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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Open AccessArticle Study of Impact Damage in PVA-ECC Beam under Low-Velocity Impact Loading Using Piezoceramic Transducers and PVDF Thin-Film Transducers
Sensors 2018, 18(2), 671; https://doi.org/10.3390/s18020671
Received: 3 January 2018 / Revised: 21 February 2018 / Accepted: 21 February 2018 / Published: 24 February 2018
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Abstract
Compared to conventional concrete, polyvinyl alcohol fiber reinforced engineering cementitious composite (PVA-ECC) offers high-strength, ductility, formability, and excellent fatigue resistance. However, impact-induced structural damage is a major concern and has not been previously characterized in PVA-ECC structures. We investigate the damage of PVA-ECC
[...] Read more.
Compared to conventional concrete, polyvinyl alcohol fiber reinforced engineering cementitious composite (PVA-ECC) offers high-strength, ductility, formability, and excellent fatigue resistance. However, impact-induced structural damage is a major concern and has not been previously characterized in PVA-ECC structures. We investigate the damage of PVA-ECC beams under low-velocity impact loading. A series of ball-drop impact tests were performed at different drop weights and heights to simulate various impact energies. The impact results of PVA-ECC beams were compared with mortar beams. A combination of polyvinylidene fluoride (PVDF) thin-film sensors and piezoceramic-based smart aggregate were used for impact monitoring, which included impact initiation and crack evolution. Short-time Fourier transform (STFT) of the signal received by PVDF thin-film sensors was performed to identify impact events, while active-sensing approach was utilized to detect impact-induced crack evolution by the attenuation of a propagated guided wave. Wavelet packet-based energy analysis was performed to quantify failure development under repeated impact tests. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Error Analysis of the K-Rb-21Ne Comagnetometer Space-Stable Inertial Navigation System
Sensors 2018, 18(2), 670; https://doi.org/10.3390/s18020670
Received: 7 November 2017 / Revised: 7 February 2018 / Accepted: 21 February 2018 / Published: 24 February 2018
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Abstract
According to the application characteristics of the K-Rb-21Ne comagnetometer, a space-stable navigation mechanization is designed and the requirements of the comagnetometer prototype are presented. By analysing the error propagation rule of the space-stable Inertial Navigation System (INS), the three biases, the
[...] Read more.
According to the application characteristics of the K-Rb-21Ne comagnetometer, a space-stable navigation mechanization is designed and the requirements of the comagnetometer prototype are presented. By analysing the error propagation rule of the space-stable Inertial Navigation System (INS), the three biases, the scale factor of the z-axis, and the misalignment of the x- and y-axis non-orthogonal with the z-axis, are confirmed to be the main error source. A numerical simulation of the mathematical model for each single error verified the theoretical analysis result of the system’s error propagation rule. Thus, numerical simulation based on the semi-physical data result proves the feasibility of the navigation scheme proposed in this paper. Full article
(This article belongs to the Special Issue Inertial Sensors for Positioning and Navigation)
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Open AccessArticle The Design of a Single-Bit CMOS Image Sensor for Iris Recognition Applications
Sensors 2018, 18(2), 669; https://doi.org/10.3390/s18020669
Received: 10 January 2018 / Revised: 22 February 2018 / Accepted: 23 February 2018 / Published: 24 February 2018
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Abstract
This paper presents a single-bit CMOS image sensor (CIS) that uses a data processing technique with an edge detection block for simple iris segmentation. In order to recognize the iris image, the image sensor conventionally captures high-resolution image data in digital code, extracts
[...] Read more.
This paper presents a single-bit CMOS image sensor (CIS) that uses a data processing technique with an edge detection block for simple iris segmentation. In order to recognize the iris image, the image sensor conventionally captures high-resolution image data in digital code, extracts the iris data, and then compares it with a reference image through a recognition algorithm. However, in this case, the frame rate decreases by the time required for digital signal conversion of multi-bit digital data through the analog-to-digital converter (ADC) in the CIS. In order to reduce the overall processing time as well as the power consumption, we propose a data processing technique with an exclusive OR (XOR) logic gate to obtain single-bit and edge detection image data instead of multi-bit image data through the ADC. In addition, we propose a logarithmic counter to efficiently measure single-bit image data that can be applied to the iris recognition algorithm. The effective area of the proposed single-bit image sensor (174 × 144 pixel) is 2.84 mm2 with a 0.18 μm 1-poly 4-metal CMOS image sensor process. The power consumption of the proposed single-bit CIS is 2.8 mW with a 3.3 V of supply voltage and 520 frame/s of the maximum frame rates. The error rate of the ADC is 0.24 least significant bit (LSB) on an 8-bit ADC basis at a 50 MHz sampling frequency. Full article
(This article belongs to the Special Issue Image Sensors)
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Open AccessArticle Mn4+-Doped Magnesium Titanate—A Promising Phosphor for Self-Referenced Optical Temperature Sensing
Sensors 2018, 18(2), 668; https://doi.org/10.3390/s18020668
Received: 17 January 2018 / Revised: 18 February 2018 / Accepted: 22 February 2018 / Published: 24 February 2018
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Abstract
Phosphors based on magnesium titanate activated with Mn4+ ions are of great interest because, when excited with blue light, they display a strong red-emitting luminescence. They are characterized by a luminescence decay which is strongly temperature dependent in the range from
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Phosphors based on magnesium titanate activated with Mn 4 + ions are of great interest because, when excited with blue light, they display a strong red-emitting luminescence. They are characterized by a luminescence decay which is strongly temperature dependent in the range from −50 C to 150 C, making these materials very promising for temperature sensing in the biochemical field. In this work, the optical and thermal properties of the luminescence of Mg 2 TiO 4 are investigated for different Mn 4 + doping concentrations. The potential of this material for temperature sensing is demonstrated by fabricating a fiber optic temperature microsensor and by comparing its performance against a standard resistance thermometer. The response of the fiber optic sensor is exceptionally fast, with a response time below 1 s in the liquid phase and below 1.1 s in the gas phase. Full article
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Open AccessArticle Second Generation Small Pixel Technology Using Hybrid Bond Stacking
Sensors 2018, 18(2), 667; https://doi.org/10.3390/s18020667
Received: 2 November 2017 / Revised: 26 January 2018 / Accepted: 13 February 2018 / Published: 24 February 2018
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Abstract
In this work, OmniVision’s second generation (Gen2) of small-pixel BSI stacking technologies is reviewed. The key features of this technology are hybrid-bond stacking, deeper back-side, deep-trench isolation, new back-side composite metal-oxide grid, and improved gate oxide quality. This Gen2 technology achieves state-of-the-art low-light
[...] Read more.
In this work, OmniVision’s second generation (Gen2) of small-pixel BSI stacking technologies is reviewed. The key features of this technology are hybrid-bond stacking, deeper back-side, deep-trench isolation, new back-side composite metal-oxide grid, and improved gate oxide quality. This Gen2 technology achieves state-of-the-art low-light image-sensor performance for 1.1, 1.0, and 0.9 µm pixel products. Additional improvements on this technology include less than 100 ppm white-pixel process and a high near-infrared (NIR) QE technology. Full article
(This article belongs to the Special Issue Special Issue on the 2017 International Image Sensor Workshop (IISW))
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Open AccessArticle SmartVeh: Secure and Efficient Message Access Control and Authentication for Vehicular Cloud Computing
Sensors 2018, 18(2), 666; https://doi.org/10.3390/s18020666
Received: 2 January 2018 / Revised: 4 February 2018 / Accepted: 15 February 2018 / Published: 24 February 2018
Cited by 2 | PDF Full-text (1399 KB) | HTML Full-text | XML Full-text
Abstract
With the growing number of vehicles and popularity of various services in vehicular cloud computing (VCC), message exchanging among vehicles under traffic conditions and in emergency situations is one of the most pressing demands, and has attracted significant attention. However, it is an
[...] Read more.
With the growing number of vehicles and popularity of various services in vehicular cloud computing (VCC), message exchanging among vehicles under traffic conditions and in emergency situations is one of the most pressing demands, and has attracted significant attention. However, it is an important challenge to authenticate the legitimate sources of broadcast messages and achieve fine-grained message access control. In this work, we propose SmartVeh, a secure and efficient message access control and authentication scheme in VCC. A hierarchical, attribute-based encryption technique is utilized to achieve fine-grained and flexible message sharing, which ensures that vehicles whose persistent or dynamic attributes satisfy the access policies can access the broadcast message with equipped on-board units (OBUs). Message authentication is enforced by integrating an attribute-based signature, which achieves message authentication and maintains the anonymity of the vehicles. In order to reduce the computations of the OBUs in the vehicles, we outsource the heavy computations of encryption, decryption and signing to a cloud server and road-side units. The theoretical analysis and simulation results reveal that our secure and efficient scheme is suitable for VCC. Full article
(This article belongs to the Special Issue Security, Trust and Privacy for Sensor Networks)
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Open AccessArticle High-Speed Interrogation for Large-Scale Fiber Bragg Grating Sensing
Sensors 2018, 18(2), 665; https://doi.org/10.3390/s18020665
Received: 21 January 2018 / Revised: 8 February 2018 / Accepted: 11 February 2018 / Published: 24 February 2018
Cited by 2 | PDF Full-text (2998 KB) | HTML Full-text | XML Full-text
Abstract
A high-speed interrogation scheme for large-scale fiber Bragg grating (FBG) sensing arrays is presented. This technique employs parallel computing and pipeline control to modulate incident light and demodulate the reflected sensing signal. One Electro-optic modulator (EOM) and one semiconductor optical amplifier (SOA) were
[...] Read more.
A high-speed interrogation scheme for large-scale fiber Bragg grating (FBG) sensing arrays is presented. This technique employs parallel computing and pipeline control to modulate incident light and demodulate the reflected sensing signal. One Electro-optic modulator (EOM) and one semiconductor optical amplifier (SOA) were used to generate a phase delay to filter reflected spectrum form multiple candidate FBGs with the same optical path difference (OPD). Experimental results showed that the fastest interrogation delay time for the proposed method was only about 27.2 us for a single FBG interrogation, and the system scanning period was only limited by the optical transmission delay in the sensing fiber owing to the multiple simultaneous central wavelength calculations. Furthermore, the proposed FPGA-based technique had a verified FBG wavelength demodulation stability of ±1 pm without average processing. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle User Access Management Based on Network Pricing for Social Network Applications
Sensors 2018, 18(2), 664; https://doi.org/10.3390/s18020664
Received: 20 December 2017 / Revised: 30 January 2018 / Accepted: 13 February 2018 / Published: 24 February 2018
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Abstract
Social applications play a very important role in people’s lives, as users communicate with each other through social networks on a daily basis. This presents a challenge: How does one receive high-quality service from social networks at a low cost? Users can access
[...] Read more.
Social applications play a very important role in people’s lives, as users communicate with each other through social networks on a daily basis. This presents a challenge: How does one receive high-quality service from social networks at a low cost? Users can access different kinds of wireless networks from various locations. This paper proposes a user access management strategy based on network pricing such that networks can increase its income and improve service quality. Firstly, network price is treated as an optimizing access parameter, and an unascertained membership algorithm is used to make pricing decisions. Secondly, network price is adjusted dynamically in real time according to network load. Finally, selecting a network is managed and controlled in terms of the market economy. Simulation results show that the proposed scheme can effectively balance network load, reduce network congestion, improve the user's quality of service (QoS) requirements, and increase the network’s income. Full article
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Open AccessArticle Estimation of Handgrip Force from SEMG Based on Wavelet Scale Selection
Sensors 2018, 18(2), 663; https://doi.org/10.3390/s18020663
Received: 15 January 2018 / Revised: 17 February 2018 / Accepted: 22 February 2018 / Published: 24 February 2018
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Abstract
This paper proposes a nonlinear correlation-based wavelet scale selection technology to select the effective wavelet scales for the estimation of handgrip force from surface electromyograms (SEMG). The SEMG signal corresponding to gripping force was collected from extensor and flexor forearm muscles during the
[...] Read more.
This paper proposes a nonlinear correlation-based wavelet scale selection technology to select the effective wavelet scales for the estimation of handgrip force from surface electromyograms (SEMG). The SEMG signal corresponding to gripping force was collected from extensor and flexor forearm muscles during the force-varying analysis task. We performed a computational sensitivity analysis on the initial nonlinear SEMG-handgrip force model. To explore the nonlinear correlation between ten wavelet scales and handgrip force, a large-scale iteration based on the Monte Carlo simulation was conducted. To choose a suitable combination of scales, we proposed a rule to combine wavelet scales based on the sensitivity of each scale and selected the appropriate combination of wavelet scales based on sequence combination analysis (SCA). The results of SCA indicated that the scale combination VI is suitable for estimating force from the extensors and the combination V is suitable for the flexors. The proposed method was compared to two former methods through prolonged static and force-varying contraction tasks. The experiment results showed that the root mean square errors derived by the proposed method for both static and force-varying contraction tasks were less than 20%. The accuracy and robustness of the handgrip force derived by the proposed method is better than that obtained by the former methods. Full article
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
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Open AccessArticle Leader-Follower Formation Control of UUVs with Model Uncertainties, Current Disturbances, and Unstable Communication
Sensors 2018, 18(2), 662; https://doi.org/10.3390/s18020662
Received: 22 January 2018 / Revised: 16 February 2018 / Accepted: 20 February 2018 / Published: 23 February 2018
Cited by 2 | PDF Full-text (5120 KB) | HTML Full-text | XML Full-text
Abstract
Unmanned underwater vehicles (UUVs) have rapidly developed as mobile sensor networks recently in the investigation, survey, and exploration of the underwater environment. The goal of this paper is to develop a practical and efficient formation control method to improve work efficiency of multi-UUV
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Unmanned underwater vehicles (UUVs) have rapidly developed as mobile sensor networks recently in the investigation, survey, and exploration of the underwater environment. The goal of this paper is to develop a practical and efficient formation control method to improve work efficiency of multi-UUV sensor networks. Distributed leader-follower formation controllers are designed based on a state feedback and consensus algorithm. Considering that each vehicle is subject to model uncertainties and current disturbances, a second-order integral UUV model with a nonlinear function is established using the state feedback linearized method under current disturbances. For unstable communication among UUVs, communication failure and acoustic link noise interference are considered. Two-layer random switching communication topologies are proposed to solve the problem of communication failure. For acoustic link noise interference, accurate representation of valid communication information and noise stripping when designing controllers is necessary. Effective communication topology weights are designed to represent the validity of communication information interfered by noise. Utilizing state feedback and noise stripping, sufficient conditions for design formation controllers are proposed to ensure UUV formation achieves consensus under model uncertainties, current disturbances, and unstable communication. The stability of formation controllers is proven by the Lyapunov-Razumikhin theorem, and the validity is verified by simulation results. Full article
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Open AccessArticle Metal Nanoparticles/Porous Silicon Microcavity Enhanced Surface Plasmon Resonance Fluorescence for the Detection of DNA
Sensors 2018, 18(2), 661; https://doi.org/10.3390/s18020661
Received: 1 February 2018 / Revised: 15 February 2018 / Accepted: 16 February 2018 / Published: 23 February 2018
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Abstract
A porous silicon microcavity (PSiMC) with resonant peak wavelength of 635 nm was fabricated by electrochemical etching. Metal nanoparticles (NPs)/PSiMC enhanced fluorescence substrates were prepared by the electrostatic adherence of Au NPs that were distributed in PSiMC. The Au NPs/PSiMC device was used
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A porous silicon microcavity (PSiMC) with resonant peak wavelength of 635 nm was fabricated by electrochemical etching. Metal nanoparticles (NPs)/PSiMC enhanced fluorescence substrates were prepared by the electrostatic adherence of Au NPs that were distributed in PSiMC. The Au NPs/PSiMC device was used to characterize the target DNA immobilization and hybridization with its complementary DNA sequences marked with Rhodamine red (RRA). Fluorescence enhancement was observed on the Au NPs/PSiMC device substrate; and the minimum detection concentration of DNA ran up to 10 pM. The surface plasmon resonance (SPR) of the MC substrate; which is so well-positioned to improve fluorescence enhancement rather the fluorescence enhancement of the high reflection band of the Bragg reflector; would welcome such a highly sensitive in biosensor. Full article
(This article belongs to the Special Issue Recent Advances in Nucleic Acid Sensors)
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Open AccessArticle Enhanced Humidity Sensitivity with Silicon Nanopillar Array by UV Light
Sensors 2018, 18(2), 660; https://doi.org/10.3390/s18020660
Received: 22 January 2018 / Revised: 19 February 2018 / Accepted: 21 February 2018 / Published: 23 February 2018
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Abstract
The sensitivity of silicon nanopillar array for relative humidity (RH) with UV illumination was investigated in this work. The silicon nanopillar array was prepared by nanosphere lithography. Electrical measurements were performed on its sensing performance with and without UV irradiation. It was found
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The sensitivity of silicon nanopillar array for relative humidity (RH) with UV illumination was investigated in this work. The silicon nanopillar array was prepared by nanosphere lithography. Electrical measurements were performed on its sensing performance with and without UV irradiation. It was found that UV light improved the humidity sensitivity with different UV light wavelengths and power. The sensor response and recovery time were reduced. Furthermore, the turn-on threshold voltage and the operating voltage both decreased. These sensing characteristics can mainly be attributed to the electron-hole pairs generated by UV light. These electron-hole pairs promote the adsorption and desorption processes. The results indicate that silicon nanopillar array materials with UV irradiation might be competitive as novel sensing materials for fabricating humidity sensors with high performances. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Application of Improved 5th-Cubature Kalman Filter in Initial Strapdown Inertial Navigation System Alignment for Large Misalignment Angles
Sensors 2018, 18(2), 659; https://doi.org/10.3390/s18020659
Received: 22 December 2017 / Revised: 20 February 2018 / Accepted: 21 February 2018 / Published: 23 February 2018
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Abstract
In view of the fact the accuracy of the third-degree Cubature Kalman Filter (CKF) used for initial alignment under large misalignment angle conditions is insufficient, an improved fifth-degree CKF algorithm is proposed in this paper. In order to make full use of the
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In view of the fact the accuracy of the third-degree Cubature Kalman Filter (CKF) used for initial alignment under large misalignment angle conditions is insufficient, an improved fifth-degree CKF algorithm is proposed in this paper. In order to make full use of the innovation on filtering, the innovation covariance matrix is calculated recursively by an innovative sequence with an exponent fading factor. Then a new adaptive error covariance matrix scaling algorithm is proposed. The Singular Value Decomposition (SVD) method is used for improving the numerical stability of the fifth-degree CKF in this paper. In order to avoid the overshoot caused by excessive scaling of error covariance matrix during the convergence stage, the scaling scheme is terminated when the gradient of azimuth reaches the maximum. The experimental results show that the improved algorithm has better alignment accuracy with large misalignment angles than the traditional algorithm. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Methionine-Capped Gold Nanoclusters as a Fluorescence-Enhanced Probe for Cadmium(II) Sensing
Sensors 2018, 18(2), 658; https://doi.org/10.3390/s18020658
Received: 20 December 2017 / Revised: 5 February 2018 / Accepted: 5 February 2018 / Published: 23 February 2018
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Abstract
Gold nanoclusters (Au NCs) have been considered as novel heavy metal ions sensors due to their ultrafine size, photo-stability and excellent fluorescent properties. In this study, a green and facile method was developed for the preparation of fluorescent water-soluble gold nanoclusters with methionine
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Gold nanoclusters (Au NCs) have been considered as novel heavy metal ions sensors due to their ultrafine size, photo-stability and excellent fluorescent properties. In this study, a green and facile method was developed for the preparation of fluorescent water-soluble gold nanoclusters with methionine as a stabilizer. The nanoclusters emit orange fluorescence with excitation/emission peaks at 420/565 nm and a quantum yield of about 1.46%. The fluorescence of the Au NCs is selectively and sensitively enhanced by addition of Cd(II) ions attributed to the Cd(II) ion-induced aggregation of nanoclusters. This finding was further used to design a fluorometric method for the determination of Cd(II) ions, which had a linear response in the concentration range from 50 nM to 35 μM and a detection limit of 12.25 nM. The practicality of the nanoprobe was validated in various environmental water samples and milk powder samples, with a fairly satisfactory recovery percent. Full article
(This article belongs to the Special Issue Fluorescent Probes and Sensors) Printed Edition available
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Open AccessArticle A Method for Dynamically Selecting the Best Frequency Hopping Technique in Industrial Wireless Sensor Network Applications
Sensors 2018, 18(2), 657; https://doi.org/10.3390/s18020657
Received: 29 December 2017 / Revised: 9 February 2018 / Accepted: 20 February 2018 / Published: 23 February 2018
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Abstract
Industrial wireless applications often share the communication channel with other wireless technologies and communication protocols. This coexistence produces interferences and transmission errors which require appropriate mechanisms to manage retransmissions. Nevertheless, these mechanisms increase the network latency and overhead due to the retransmissions. Thus,
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Industrial wireless applications often share the communication channel with other wireless technologies and communication protocols. This coexistence produces interferences and transmission errors which require appropriate mechanisms to manage retransmissions. Nevertheless, these mechanisms increase the network latency and overhead due to the retransmissions. Thus, the loss of data packets and the measures to handle them produce an undesirable drop in the QoS and hinder the overall robustness and energy efficiency of the network. Interference avoidance mechanisms, such as frequency hopping techniques, reduce the need for retransmissions due to interferences but they are often tailored to specific scenarios and are not easily adapted to other use cases. On the other hand, the total absence of interference avoidance mechanisms introduces a security risk because the communication channel may be intentionally attacked and interfered with to hinder or totally block it. In this paper we propose a method for supporting the design of communication solutions under dynamic channel interference conditions and we implement dynamic management policies for frequency hopping technique and channel selection at runtime. The method considers several standard frequency hopping techniques and quality metrics, and the quality and status of the available frequency channels to propose the best combined solution to minimize the side effects of interferences. A simulation tool has been developed and used in this work to validate the method. Full article
(This article belongs to the Special Issue Smart Industrial Wireless Sensor Networks)
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Open AccessArticle Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module
Sensors 2018, 18(2), 656; https://doi.org/10.3390/s18020656
Received: 24 January 2018 / Revised: 15 February 2018 / Accepted: 21 February 2018 / Published: 23 February 2018
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Abstract
Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the
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Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system. Full article
(This article belongs to the Special Issue Selected Sensor Related Papers from ICI2017)
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Open AccessReview Microwave Sensors for Breast Cancer Detection
Sensors 2018, 18(2), 655; https://doi.org/10.3390/s18020655
Received: 31 January 2018 / Revised: 18 February 2018 / Accepted: 20 February 2018 / Published: 23 February 2018
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Abstract
Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold
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Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold standard X-ray mammography for detecting breast cancer. The microwave breast image quality is affected by the microwave sensor, sensor array, the number of sensors in the array and the size of the sensor. In fact, microwave sensor array and sensor play an important role in the microwave breast imaging system. Numerous microwave biosensors have been developed for biomedical applications, with particular focus on breast tumor detection. Compared to the conventional medical imaging and biosensor techniques, these microwave sensors not only enable better cancer detection and improve the image resolution, but also provide attractive features such as label-free detection. This paper aims to provide an overview of recent important achievements in microwave sensors for biomedical imaging applications, with particular focus on breast cancer detection. The electric properties of biological tissues at microwave spectrum, microwave imaging approaches, microwave biosensors, current challenges and future works are also discussed in the manuscript. Full article
(This article belongs to the Special Issue Label-Free Biosensors)
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Open AccessArticle Using a Second Order Sigma-Delta Control to Improve the Performance of Metal-Oxide Gas Sensors
Sensors 2018, 18(2), 654; https://doi.org/10.3390/s18020654
Received: 31 January 2018 / Revised: 19 February 2018 / Accepted: 19 February 2018 / Published: 23 February 2018
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Abstract
Controls of surface potential have been proposed to accelerate the time response of MOX gas sensors. These controls use temperature modulations and a feedback loop based on first-order sigma-delta modulators to keep constant the surface potential. Changes in the surrounding gases, therefore, must
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Controls of surface potential have been proposed to accelerate the time response of MOX gas sensors. These controls use temperature modulations and a feedback loop based on first-order sigma-delta modulators to keep constant the surface potential. Changes in the surrounding gases, therefore, must be compensated by average temperature produced by the control loop, which is the new output signal. The purpose of this paper is to present a second order sigma-delta control of the surface potential for gas sensors. With this new control strategy, it is possible to obtain a second order zero of the quantization noise in the output signal. This provides a less noisy control of the surface potential, while at the same time some undesired effects of first order modulators, such as the presence of plateaus, are avoided. Experiments proving these performance improvements are presented using a gas sensor made of tungsten oxide nanowires. Plateau avoidance and second order noise shaping is shown with ethanol measurements. Full article
(This article belongs to the Special Issue Gas Sensors based on Semiconducting Metal Oxides)
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Open AccessArticle Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature
Sensors 2018, 18(2), 653; https://doi.org/10.3390/s18020653
Received: 7 November 2017 / Revised: 5 February 2018 / Accepted: 7 February 2018 / Published: 23 February 2018
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Abstract
Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target
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Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle The Spectrum Analysis Solution (SAS) System: Theoretical Analysis, Hardware Design and Implementation
Sensors 2018, 18(2), 652; https://doi.org/10.3390/s18020652
Received: 22 December 2017 / Revised: 15 February 2018 / Accepted: 20 February 2018 / Published: 22 February 2018
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Abstract
This paper describes a multichannel super-heterodyne signal analyzer, called the Spectrum Analysis Solution (SAS), which performs multi-purpose spectrum sensing to support spectrally adaptive and cognitive radar applications. The SAS operates from ultrahigh frequency (UHF) to the S-band and features a wideband channel with
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This paper describes a multichannel super-heterodyne signal analyzer, called the Spectrum Analysis Solution (SAS), which performs multi-purpose spectrum sensing to support spectrally adaptive and cognitive radar applications. The SAS operates from ultrahigh frequency (UHF) to the S-band and features a wideband channel with eight narrowband channels. The wideband channel acts as a monitoring channel that can be used to tune the instantaneous band of the narrowband channels to areas of interest in the spectrum. The data collected from the SAS has been utilized to develop spectrum sensing algorithms for the budding field of spectrum sharing (SS) radar. Bandwidth (BW), average total power, percent occupancy (PO), signal-to-interference-plus-noise ratio (SINR), and power spectral entropy (PSE) have been examined as metrics for the characterization of the spectrum. These metrics are utilized to determine a contiguous optimal sub-band (OSB) for a SS radar transmission in a given spectrum for different modalities. Three OSB algorithms are presented and evaluated: the spectrum sensing multi objective (SS-MO), the spectrum sensing with brute force PSE (SS-BFE), and the spectrum sensing multi-objective with brute force PSE (SS-MO-BFE). Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle A Cross-Layer, Anomaly-Based IDS for WSN and MANET
Sensors 2018, 18(2), 651; https://doi.org/10.3390/s18020651
Received: 30 October 2017 / Revised: 16 February 2018 / Accepted: 19 February 2018 / Published: 22 February 2018
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Abstract
Intrusion detection system (IDS) design for mobile adhoc networks (MANET) is a crucial component for maintaining the integrity of the network. The need for rapid deployment of IDS capability with minimal data availability for training and testing is an important requirement of such
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Intrusion detection system (IDS) design for mobile adhoc networks (MANET) is a crucial component for maintaining the integrity of the network. The need for rapid deployment of IDS capability with minimal data availability for training and testing is an important requirement of such systems, especially for MANETs deployed in highly dynamic scenarios, such as battlefields. This work proposes a two-level detection scheme for detecting malicious nodes in MANETs. The first level deploys dedicated sniffers working in promiscuous mode. Each sniffer utilizes a decision-tree-based classifier that generates quantities which we refer to as correctly classified instances (CCIs) every reporting time. In the second level, the CCIs are sent to an algorithmically run supernode that calculates quantities, which we refer to as the accumulated measure of fluctuation (AMoF) of the received CCIs for each node under test (NUT). A key concept that is used in this work is that the variability of the smaller size population which represents the number of malicious nodes in the network is greater than the variance of the larger size population which represents the number of normal nodes in the network. A linear regression process is then performed in parallel with the calculation of the AMoF for fitting purposes and to set a proper threshold based on the slope of the fitted lines. As a result, the malicious nodes are efficiently and effectively separated from the normal nodes. The proposed scheme is tested for various node velocities and power levels and shows promising detection performance even at low-power levels. The results presented also apply to wireless sensor networks (WSN) and represent a novel IDS scheme for such networks. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Optical Method for Estimating the Chlorophyll Contents in Plant Leaves
Sensors 2018, 18(2), 650; https://doi.org/10.3390/s18020650
Received: 3 January 2018 / Revised: 16 February 2018 / Accepted: 18 February 2018 / Published: 22 February 2018
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Abstract
This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance), a novel optical arrangement
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This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance), a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD) meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica, Canavalia ensiforme, and Lycopersicon esculentum. Experimental results showed that—in terms of accuracy and processing speed—the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica, where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap. Full article
(This article belongs to the Special Issue Optical Biochemical Sensor Systems and Applications)
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