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Sensors, Volume 19, Issue 11 (June-1 2019)

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Cover Story (view full-size image) Non-specific adsorption (NSA) is a persistent problem that negatively affects all biosensors, [...] Read more.
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Open AccessArticle
A Combined H 2 / H Approach for Robust Joint Actuator and Sensor Fault Estimation: Application to a DC Servo-Motor System
Sensors 2019, 19(11), 2648; https://doi.org/10.3390/s19112648
Received: 17 April 2019 / Revised: 31 May 2019 / Accepted: 6 June 2019 / Published: 11 June 2019
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Abstract
The main objective of this paper is to develop an actuator and sensor fault estimation framework taking into account various uncertainty sources. In particular, these are divided into three groups: sensor measurement noise, process-external exogenous disturbances, as well as unknown fault dynamics. Unlike [...] Read more.
The main objective of this paper is to develop an actuator and sensor fault estimation framework taking into account various uncertainty sources. In particular, these are divided into three groups: sensor measurement noise, process-external exogenous disturbances, as well as unknown fault dynamics. Unlike the approaches presented in the literature, here they are not processed in the same way but treated separately in a suitably tailored fashion. Finally, the approach resolves to minimizing their effect on the fault estimation error in either the H 2 or H sense. As a result, a mixed performance–based actuator fault estimation framework is obtained, along with its convergence conditions. The final part of the paper presents performance analysis results obtained for a DC servo-motor. Subsequently, another three-tank-system-based example is presented. In both cases, the proposed approach is compared with an alternative one, which clearly exhibits its superiority. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Approaching the Communication Constraints of Ethereum-Based Decentralized Applications
Sensors 2019, 19(11), 2647; https://doi.org/10.3390/s19112647
Received: 10 April 2019 / Revised: 30 May 2019 / Accepted: 6 June 2019 / Published: 11 June 2019
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Abstract
Those working on Blockchain technologies have described several new innovative directions and novel services in the Internet of things (IoT), including decentralized trust, trusted and verifiable execution of smart contracts, and machine-to-machine communications and automation that reach beyond the mere exchange of data. [...] Read more.
Those working on Blockchain technologies have described several new innovative directions and novel services in the Internet of things (IoT), including decentralized trust, trusted and verifiable execution of smart contracts, and machine-to-machine communications and automation that reach beyond the mere exchange of data. However, applying blockchain principles in the IoT is a challenge due to the constraints of the end devices. Because of fierce cost pressure, the hardware resources in these devices are usually reduced to the minimum necessary for operation. To achieve the high coverage needed, low bitrate mobile or wireless technologies are frequently applied, so the communication is often constrained, too. These constraints make the implementation of blockchain nodes for IoT as standalone end-devices impractical or even impossible. We therefore investigated possible design approaches to decentralized applications based on the Ethereum blockchain for the IoT. We proposed and evaluated three application architectures differing in communication, computation, storage, and security requirements. In a pilot setup we measured and analyzed the data traffic needed to run the blockchain clients and their applications. We found out that with the appropriate designs and the remote server architecture we can strongly reduce the storage and communication requirements imposed on devices, with predictable security implications. Periodic device traffic is reduced to 2400 B/s (HTTP) and 170 B/s (Websocket) from about 18 kB/s in the standalone-device full client architecture. A notification about a captured blockchain event and the corresponding verification resulted in about 2000 B of data. A transaction sent from the application to the client resulted in an about 500 B (HTTP) and 300 B message (Websocket). The key store location, which affects the serialization of a transaction, only had a small influence on the transaction-related data. Raw transaction messages were 45 B larger than when passing the JSON transaction objects. These findings provide directions for fog/cloud IoT application designers to avoid unrealistic expectations imposed upon their IoT devices and blockchain technologies, and enable them to select the appropriate system design according to the intended use case and system constraints. However, for very low bit-rate communication networks, new communication protocols for device to blockchain-client need to be considered. Full article
(This article belongs to the Special Issue Smart Monitoring and Control in the Future Internet of Things)
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Open AccessArticle
A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose
Sensors 2019, 19(11), 2646; https://doi.org/10.3390/s19112646
Received: 18 January 2019 / Revised: 16 February 2019 / Accepted: 25 February 2019 / Published: 11 June 2019
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Abstract
Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be [...] Read more.
Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages. Full article
(This article belongs to the Special Issue Electronic Noses)
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Open AccessArticle
Transfer Learning Assisted Classification and Detection of Alzheimer’s Disease Stages Using 3D MRI Scans
Sensors 2019, 19(11), 2645; https://doi.org/10.3390/s19112645
Received: 5 April 2019 / Revised: 3 June 2019 / Accepted: 6 June 2019 / Published: 11 June 2019
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Abstract
Alzheimer’s disease effects human brain cells and results in dementia. The gradual deterioration of the brain cells results in disability of performing daily routine tasks. The treatment for this disease is still not mature enough. However, its early diagnosis may allow restraining the [...] Read more.
Alzheimer’s disease effects human brain cells and results in dementia. The gradual deterioration of the brain cells results in disability of performing daily routine tasks. The treatment for this disease is still not mature enough. However, its early diagnosis may allow restraining the spread of disease. For early detection of Alzheimer’s through brain Magnetic Resonance Imaging (MRI), an automated detection and classification system needs to be developed that can detect and classify the subject having dementia. These systems also need not only to classify dementia patients but to also identify the four progressing stages of dementia. The proposed system works on an efficient technique of utilizing transfer learning to classify the images by fine-tuning a pre-trained convolutional network, AlexNet. The architecture is trained and tested over the pre-processed segmented (Grey Matter, White Matter, and Cerebral Spinal Fluid) and un-segmented images for both binary and multi-class classification. The performance of the proposed system is evaluated over Open Access Series of Imaging Studies (OASIS) dataset. The algorithm showed promising results by giving the best overall accuracy of 92.85% for multi-class classification of un-segmented images. Full article
(This article belongs to the Special Issue Edge Computing for Biomedical Signal Processing)
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Open AccessArticle
An Expert System for Quantification of Bradykinesia Based on Wearable Inertial Sensors
Sensors 2019, 19(11), 2644; https://doi.org/10.3390/s19112644
Received: 3 April 2019 / Revised: 15 May 2019 / Accepted: 4 June 2019 / Published: 11 June 2019
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Abstract
Wearable sensors and advanced algorithms can provide significant decision support for clinical practice. Currently, the motor symptoms of patients with neurological disorders are often visually observed and evaluated, which may result in rough and subjective quantification. Using small inertial wearable sensors, fine repetitive [...] Read more.
Wearable sensors and advanced algorithms can provide significant decision support for clinical practice. Currently, the motor symptoms of patients with neurological disorders are often visually observed and evaluated, which may result in rough and subjective quantification. Using small inertial wearable sensors, fine repetitive and clinically important movements can be captured and objectively evaluated. In this paper, a new methodology is designed for objective evaluation and automatic scoring of bradykinesia in repetitive finger-tapping movements for patients with idiopathic Parkinson’s disease and atypical parkinsonism. The methodology comprises several simple and repeatable signal-processing techniques that are applied for the extraction of important movement features. The decision support system consists of simple rules designed to match universally defined criteria that are evaluated in clinical practice. The accuracy of the system is calculated based on the reference scores provided by two neurologists. The proposed expert system achieved an accuracy of 88.16% for files on which neurologists agreed with their scores. The introduced system is simple, repeatable, easy to implement, and can provide good assistance in clinical practice, providing a detailed analysis of finger-tapping performance and decision support for symptom evaluation. Full article
(This article belongs to the Special Issue Wearable Sensors and Devices for Healthcare Applications)
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Open AccessArticle
Accurate Driver Detection Exploiting Invariant Characteristics of Smartphone Sensors
Sensors 2019, 19(11), 2643; https://doi.org/10.3390/s19112643
Received: 25 March 2019 / Revised: 28 May 2019 / Accepted: 7 June 2019 / Published: 11 June 2019
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Abstract
Distracted driving jeopardizes the safety of the driver and others. Numerous solutions have been proposed to prevent distracted driving, but the number of related accidents has not decreased. Such a deficiency comes from fragile system designs where drivers are detected exploiting sensory features [...] Read more.
Distracted driving jeopardizes the safety of the driver and others. Numerous solutions have been proposed to prevent distracted driving, but the number of related accidents has not decreased. Such a deficiency comes from fragile system designs where drivers are detected exploiting sensory features from strictly controlled vehicle-riding actions and unreliable driving events. We propose a system called ADDICT (Accurate Driver Detection exploiting Invariant Characteristics of smarTphone sensors), which identifies the driver utilizing the inconsistency between gyroscope and magnetometer dynamics and the interplay between electromagnetic field emissions and engine startup vibrations. These features are invariantly observable regardless of smartphone positions and vehicle-riding actions. To evaluate the feasibility of ADDICT, we conducted extensive experiments with four participants and three different vehicles by varying vehicle-riding scenarios. Our evaluation results demonstrated that ADDICT identifies the driver’s smartphone with 89.1% average accuracy for all scenarios and >85% under the extreme scenario, at a marginal cost of battery consumption. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Fog Computing Model to Orchestrate the Consumption and Production of Energy in Microgrids
Sensors 2019, 19(11), 2642; https://doi.org/10.3390/s19112642
Received: 4 April 2019 / Revised: 4 June 2019 / Accepted: 5 June 2019 / Published: 11 June 2019
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Abstract
Energy advancement and innovation have generated several challenges for large modernized cities, such as the increase in energy demand, causing the appearance of the small power grid with a local source of supply, called the Microgrid. A Microgrid operates either connected to the [...] Read more.
Energy advancement and innovation have generated several challenges for large modernized cities, such as the increase in energy demand, causing the appearance of the small power grid with a local source of supply, called the Microgrid. A Microgrid operates either connected to the national centralized power grid or singly, as a power island mode. Microgrids address these challenges using sensing technologies and Fog-Cloudcomputing infrastructures for building smart electrical grids. A smart Microgrid can be used to minimize the power demand problem, but this solution needs to be implemented correctly so as not to increase the amount of data being generated. Thus, this paper proposes the use of Fog computing to help control power demand and manage power production by eliminating the high volume of data being passed to the Cloud and decreasing the requests’ response time. The GridLab-d simulator was used to create a Microgrid, where it is possible to exchange information between consumers and generators. Thus, to understand the potential of the Fog in this scenario, a performance evaluation is performed to verify how factors such as residence number, optimization algorithms, appliance shifting, and energy sources may influence the response time and resource usage. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Development of a Bendable Outsole Biaxial Ground Reaction Force Measurement System
Sensors 2019, 19(11), 2641; https://doi.org/10.3390/s19112641
Received: 8 May 2019 / Revised: 3 June 2019 / Accepted: 4 June 2019 / Published: 11 June 2019
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Abstract
Wearable ground reaction force (GRF) measurement systems make it possible to measure the GRF in any environment, unlike a commercial force plate. When performing kinetic analysis with the GRF, measurement of multiaxial GRF is important for evaluating forward and lateral motion during natural [...] Read more.
Wearable ground reaction force (GRF) measurement systems make it possible to measure the GRF in any environment, unlike a commercial force plate. When performing kinetic analysis with the GRF, measurement of multiaxial GRF is important for evaluating forward and lateral motion during natural gait. In this paper, we propose a bendable GRF measurement system that can measure biaxial (vertical and anterior-posterior) GRF without interrupting the natural gait. Eight custom small biaxial force sensors based on an optical sensing mechanism were installed in the proposed system. The interference between two axes on the custom sensor was minimized by the independent application of a cantilever structure for the two axes, and the hysteresis and repeatability of the custom sensor were investigated. After developing the system by the installation of force sensors, we found that the degree of flexibility of the developed system was comparable to that of regular shoes by investigating the forefoot bending stiffness. Finally, we compared vertical GRF (vGRF) and anterior-posterior GRF (apGRF) measured from the developed system and force plate at the same time when the six subjects walked, ran, and jumped on the force plate to evaluate the performance of the GRF measurement system. Full article
(This article belongs to the Special Issue Wearable Sensors and Devices for Healthcare Applications)
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Open AccessArticle
An Improved Genetic Algorithm for Path-Planning of Unmanned Surface Vehicle
Sensors 2019, 19(11), 2640; https://doi.org/10.3390/s19112640
Received: 9 April 2019 / Revised: 27 May 2019 / Accepted: 5 June 2019 / Published: 11 June 2019
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Abstract
The genetic algorithm (GA) is an effective method to solve the path-planning problem and help realize the autonomous navigation for and control of unmanned surface vehicles. In order to overcome the inherent shortcomings of conventional GA such as population premature and slow convergence [...] Read more.
The genetic algorithm (GA) is an effective method to solve the path-planning problem and help realize the autonomous navigation for and control of unmanned surface vehicles. In order to overcome the inherent shortcomings of conventional GA such as population premature and slow convergence speed, this paper proposes the strategy of increasing the number of offsprings by using the multi-domain inversion. Meanwhile, a second fitness evaluation was conducted to eliminate undesirable offsprings and reserve the most advantageous individuals. The improvement could help enhance the capability of local search effectively and increase the probability of generating excellent individuals. Monte-Carlo simulations for five examples from the library for the travelling salesman problem were first conducted to assess the effectiveness of algorithms. Furthermore, the improved algorithms were applied to the navigation, guidance, and control system of an unmanned surface vehicle in a real maritime environment. Comparative study reveals that the algorithm with multi-domain inversion is superior with a desirable balance between the path length and time-cost, and has a shorter optimal path, a faster convergence speed, and better robustness than the others. Full article
(This article belongs to the Special Issue Multi-Sensor Fusion and Data Analysis)
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Open AccessArticle
Capacitive Bio-Inspired Flow Sensing Cupula
Sensors 2019, 19(11), 2639; https://doi.org/10.3390/s19112639
Received: 22 May 2019 / Revised: 5 June 2019 / Accepted: 8 June 2019 / Published: 11 June 2019
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Abstract
Submersible robotics have improved in efficiency and versatility by incorporating features found in aquatic life, ranging from thunniform kinematics to shark skin textures. To fully realize these benefits, sensor systems must be incorporated to aid in object detection and navigation through complex flows. [...] Read more.
Submersible robotics have improved in efficiency and versatility by incorporating features found in aquatic life, ranging from thunniform kinematics to shark skin textures. To fully realize these benefits, sensor systems must be incorporated to aid in object detection and navigation through complex flows. Again, inspiration can be taken from biology, drawing on the lateral line sensor systems and neuromast structures found on fish. To maintain a truly soft-bodied robot, a man-made flow sensor must be developed that is entirely complaint, introducing no rigidity to the artificial “skin.” We present a capacitive cupula inspired by superficial neuromasts. Fabricated via lost wax methods and vacuum injection, our 5 mm tall device exhibits a sensitivity of 0.5 pF/mm (capacitance versus tip deflection) and consists of room temperature liquid metal plates embedded in a soft silicone body. In contrast to existing capacitive examples, our sensor incorporates the transducers into the cupula itself rather than at its base. We present a kinematic theory and energy-based approach to approximate capacitance versus flow, resulting in equations that are verified with a combination of experiments and COMSOL simulations. Full article
(This article belongs to the Special Issue Soft Sensors)
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Open AccessReview
Passive Gamma-Ray and Neutron Imaging Systems for National Security and Nuclear Non-Proliferation in Controlled and Uncontrolled Detection Areas: Review of Past and Current Status
Sensors 2019, 19(11), 2638; https://doi.org/10.3390/s19112638
Received: 28 April 2019 / Revised: 31 May 2019 / Accepted: 8 June 2019 / Published: 11 June 2019
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Abstract
Global concern for the illicit transportation and trafficking of nuclear materials and other radioactive sources is on the rise, with efficient and rapid security and non-proliferation technologies in more demand than ever. Many factors contribute to this issue, including the increasing number of [...] Read more.
Global concern for the illicit transportation and trafficking of nuclear materials and other radioactive sources is on the rise, with efficient and rapid security and non-proliferation technologies in more demand than ever. Many factors contribute to this issue, including the increasing number of terrorist cells, gaps in security networks, politically unstable states across the globe and the black-market trading of radioactive sources to unknown parties. The use of passive gamma-ray and neutron detection and imaging technologies in security-sensitive areas and ports has had more impact than most other techniques in detecting and deterring illicit transportation and trafficking of illegal radioactive materials. This work reviews and critically evaluates these techniques as currently utilised within national security and non-proliferation applications and proposes likely avenues of development. Full article
(This article belongs to the Special Issue Radiation Sensing: Design and Deployment of Sensors and Detectors)
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Open AccessArticle
Analysis of a Low-Cost EEG Monitoring System and Dry Electrodes toward Clinical Use in the Neonatal ICU
Sensors 2019, 19(11), 2637; https://doi.org/10.3390/s19112637
Received: 12 April 2019 / Revised: 3 June 2019 / Accepted: 9 June 2019 / Published: 11 June 2019
Cited by 1 | Viewed by 437 | PDF Full-text (4493 KB) | HTML Full-text | XML Full-text
Abstract
Electroencephalography (EEG) is an important clinical tool for monitoring neurological health. However, the required equipment, expertise, and patient preparation inhibits its use outside of tertiary care. Non-experts struggle to obtain high-quality EEG due to its low amplitude and artefact susceptibility. Wet electrodes are [...] Read more.
Electroencephalography (EEG) is an important clinical tool for monitoring neurological health. However, the required equipment, expertise, and patient preparation inhibits its use outside of tertiary care. Non-experts struggle to obtain high-quality EEG due to its low amplitude and artefact susceptibility. Wet electrodes are currently used, which require abrasive/conductive gels to reduce skin-electrode impedance. Advances in dry electrodes, which do not require gels, have simplified this process. However, the assessment of dry electrodes on neonates is limited due to health and safety barriers. This study presents a simulation framework for assessing the quality of EEG systems using a neonatal EEG database, without the use of human participants. The framework is used to evaluate a low-cost EEG acquisition system and compare performance of wet and dry (Micro Transdermal Interface Platforms (MicroTIPs), g.tec-g.SAHARA) electrodes using accurately acquired impedance models. A separate experiment assessing the electrodes on adult participants was conducted to verify the simulation framework’s efficacy. Dry electrodes have higher impedance than wet electrodes, causing a reduction in signal quality. However, MicroTIPs perform comparably to wet electrodes at the frontal region and g.tec-g.SAHARA performs well at the occipital region. Using the simulation framework, a 25dB signal-to-noise ratio (SNR) was obtained for the low-cost EEG system. The tests on adults closely matched the simulated results. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle
An Industrial Micro-Defect Diagnosis System via Intelligent Segmentation Region
Sensors 2019, 19(11), 2636; https://doi.org/10.3390/s19112636
Received: 8 May 2019 / Revised: 5 June 2019 / Accepted: 6 June 2019 / Published: 11 June 2019
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Abstract
In the field of machine vision defect detection for a micro workpiece, it is very important to make the neural network realize the integrity of the mask in analyte segmentation regions. In the process of the recognition of small workpieces, fatal defects are [...] Read more.
In the field of machine vision defect detection for a micro workpiece, it is very important to make the neural network realize the integrity of the mask in analyte segmentation regions. In the process of the recognition of small workpieces, fatal defects are always contained in borderline areas that are difficult to demarcate. The non-maximum suppression (NMS) of intersection over union (IOU) will lose crucial texture information especially in the clutter and occlusion detection areas. In this paper, simple linear iterative clustering (SLIC) is used to augment the mask as well as calibrate the score of the mask. We propose an SLIC head of object instance segmentation in proposal regions (Mask R-CNN) containing a network block to learn the quality of the predict masks. It is found that parallel K-means in the limited region mechanism in the SLIC head improved the confidence of the mask score, in the context of our workpiece. A continuous fine-tune mechanism was utilized to continuously improve the model robustness in a large-scale production line. We established a detection system, which included an optical fiber locator, telecentric lens system, matrix stereoscopic light, a rotating platform, and a neural network with an SLIC head. The accuracy of defect detection is effectively improved for micro workpieces with clutter and borderline areas. Full article
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Open AccessArticle
User-Oriented ICT Cloud Architecture for High-Accuracy GNSS-Based Services
Sensors 2019, 19(11), 2635; https://doi.org/10.3390/s19112635
Received: 19 April 2019 / Revised: 31 May 2019 / Accepted: 8 June 2019 / Published: 11 June 2019
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Abstract
We introduce a new information and communication technology (ICT) cloud-based architecture for Global Navigation Satellite System (GNSS) high-accuracy solutions, offering also a commercial overview of GNSS downstream market to show how the developed innovation is thought to fit in the real context. The [...] Read more.
We introduce a new information and communication technology (ICT) cloud-based architecture for Global Navigation Satellite System (GNSS) high-accuracy solutions, offering also a commercial overview of GNSS downstream market to show how the developed innovation is thought to fit in the real context. The designed architecture is featured by dynamic scalability, increased integrity, and greater agility of the ICT system. The novelty of the solution developed is a customized ICT architecture, obtained through unique and privileged access to user communities in the frame of the H2020 project TREASURE, allowing the development of a solution entirely driven by user needs. The economic outlook of GNSS downstream markets evolution highlights how the technology proposed effectively matches the evolving business environment, specifically in regard to the increasing need for flexibility and competitive advantage deriving from services. The simultaneous adoption of the technical and commercial perspective is meant to offer interesting findings to both the scientific community and GNSS industry, creating synergies previously unexplored. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Performance Analysis of a Defected Ground-Structured Antenna Loaded with Stub-Slot for 5G Communication
Sensors 2019, 19(11), 2634; https://doi.org/10.3390/s19112634
Received: 2 April 2019 / Revised: 19 April 2019 / Accepted: 21 April 2019 / Published: 10 June 2019
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Abstract
In this paper, a defected ground-structured antenna with a stub-slot configuration is proposed for future 5G wireless applications. A simple stub-slot configuration is used in the patch antenna to get the dual band frequency response in the 5G mid-band and the upper unlicensed [...] Read more.
In this paper, a defected ground-structured antenna with a stub-slot configuration is proposed for future 5G wireless applications. A simple stub-slot configuration is used in the patch antenna to get the dual band frequency response in the 5G mid-band and the upper unlicensed frequency region. Further, a 2-D double period Electronic band gap (EBG) structure has been implemented as a defect in the metallic ground plane to get a wider impedance bandwidth. The size of the slots and their positions are optimized to get a considerably high impedance bandwidth of 12.49% and 4.49% at a passband frequency of 3.532 GHz and 6.835 GHz, respectively. The simulated and measured realized gain and reflection coefficients are in good agreement for both operating bandwidths. The overall antenna structure size is 33.5 mm × 33.5 mm. The antenna is fabricated and compared with experimental results. The proposed antenna shows a stable radiation pattern and high realized gain with wide impedance bandwidth using the EBG structure, which are necessary for the requirements of IoT applications offered by 5G technology. Full article
(This article belongs to the Section Internet of Things)
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Open AccessArticle
Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects
Sensors 2019, 19(11), 2633; https://doi.org/10.3390/s19112633
Received: 18 April 2019 / Revised: 24 May 2019 / Accepted: 6 June 2019 / Published: 10 June 2019
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Abstract
Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively [...] Read more.
Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively mentioned in the literature over the last decade. However, an in-depth analysis of the weighted combination methods of AOA and RSSI in shadowing environments is still missing in the state-of-the-art. This paper proposes several weighted combinations of the two RSSI and AOA components in the form of pAOA + qRSSI, devises the mathematical model for analyzing shadowing effects, and evaluates these weighted combination localization methods from both accuracy and precision perspectives. Our simulations show that increasing the number of anchors does not necessarily improve the precision and accuracy, that the AOA component is less susceptible to shadowing than the RSSI one, and that increasing the weight of the AOA component and reducing that of the RSSI component help improve the accuracy and precision at high Signal-to-Noise Ratios (SNRs). This observation suggests that some power control algorithm could be used to increase automatically the transmitted power when the channel experiences large shadowing to maintain a high SNR, thus guaranteeing both accuracy and precision of the weighted combination localization techniques. Full article
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Open AccessArticle
The AMERIGO Lander and the Automatic Benthic Chamber (CBA): Two New Instruments to Measure Benthic Fluxes of Dissolved Chemical Species
Sensors 2019, 19(11), 2632; https://doi.org/10.3390/s19112632
Received: 28 April 2019 / Revised: 2 June 2019 / Accepted: 5 June 2019 / Published: 10 June 2019
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Abstract
Marine environments are currently subject to strong ecological pressure due to local and global anthropic stressors, such as pollutants and atmospheric inputs, which also cause ocean acidification and warming. These strains can result in biogeochemical cycle variations, environmental pollution, and changes in benthic-pelagic [...] Read more.
Marine environments are currently subject to strong ecological pressure due to local and global anthropic stressors, such as pollutants and atmospheric inputs, which also cause ocean acidification and warming. These strains can result in biogeochemical cycle variations, environmental pollution, and changes in benthic-pelagic coupling processes. Two new devices, the Amerigo Lander and the Automatic Benthic Chamber (CBA), have been developed to measure the fluxes of dissolved chemical species between sediment and the water column, to assess the biogeochemical cycle and benthic-pelagic coupling alterations due to human activities. The Amerigo Lander can operate in shallow as well as deep water (up to 6000 m), whereas the CBA has been developed for the continental shelf (up to 200 m). The lander can also be used to deploy a range of instruments on the seafloor, to study the benthic ecosystems. The two devices have successfully been tested in a variety of research tasks and environmental impact assessments in shallow and deep waters. Their measured flux data show good agreement and are also consistent with previous data. Full article
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Open AccessArticle
Experimental Investigation on a Cable Structure Equipped with an Electrodynamic Damper and Its Monitoring Strategy through Energy Harvesting
Sensors 2019, 19(11), 2631; https://doi.org/10.3390/s19112631
Received: 25 April 2019 / Revised: 24 May 2019 / Accepted: 7 June 2019 / Published: 10 June 2019
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Abstract
The vibration of cables in a cable-supported bridge affects its serviceability and safety. Therefore, cable dampers are essential for vibration control, monitoring, and the further maintenance of such bridges. In this study, the vibration control performance of an electrodynamic damper applied to a [...] Read more.
The vibration of cables in a cable-supported bridge affects its serviceability and safety. Therefore, cable dampers are essential for vibration control, monitoring, and the further maintenance of such bridges. In this study, the vibration control performance of an electrodynamic damper applied to a cable used in a footbridge was experimentally verified considering the major design variables of the damper. The damping performance was analyzed by varying the damping ratio according to the excitation condition and external circuit resistance. The acceleration and displacement at each measurement point and the frequency-domain response decreased. Considering the dominant response conditions of the cables in the bridge, an effective additional attenuation was observed. In addition, the harvesting power considering the measurement frequency and power loss was sufficient to operate a wireless measuring sensor by examining the energy harvesting performance from the cable measurement data of an actual bridge in service. Finally, a stepwise operation strategy for a cable vibration monitoring system was suggested and examined by analyzing the meteorological observation data and the power output according to the wind environment. The results demonstrate the feasibility of using an electrodynamic damper to build an integrated monitoring system capable of simultaneous cable vibration reduction and energy harvesting. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Design of UAV Downwash Airflow Field Detection System Based on Strain Effect Principle
Sensors 2019, 19(11), 2630; https://doi.org/10.3390/s19112630
Received: 30 April 2019 / Revised: 5 June 2019 / Accepted: 6 June 2019 / Published: 10 June 2019
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Abstract
Accurate measurement of the downwash flow field of plant protection unmanned aerial vehicles (UAVs) is essential for analyzing the spatial distribution of droplets. To realize on-line rapid detection of the downwash flow field of a multi-rotor UAV, a flexible polypropylene detection device based [...] Read more.
Accurate measurement of the downwash flow field of plant protection unmanned aerial vehicles (UAVs) is essential for analyzing the spatial distribution of droplets. To realize on-line rapid detection of the downwash flow field of a multi-rotor UAV, a flexible polypropylene detection device based on the principle of full bridge strain effect was proposed. Its performance principle was based on the physical deformation caused by wind pressure. The Fluid Flow and Static Structural modules of ANSYS 16.0 finite element software were used to simulate one-way fluid-solid coupling interaction. The surface of the resistive strain gauge embedded in the flexible detecting structure responded well to wind speed variation, hence it was suitable for downwash airflow wind field detection. By solving the strain force on the surface of the flexible detection structure, the length and layout of the grating wire of the strain gauge on the surface of the flexible detection structure were optimized. Meanwhile at 4 m·s−1 wind speed, the output voltage at varied bridge flexible acquisition systems in the acquisition card was measured. Results indicated coefficient of variation of 3.67%, 1.63% and 1.5%, respectively, which proved the good data acquisition consistency of the system. Through calibration test, the regression equation for the relationship between output voltage and wind speed for three unique sensor signal measuring circuits was established. The determination coefficients R2 for single bridge, half bridge and full bridge circuits were 0.9885, 0.9866 and 0.9959, respectively. In conclusion, by applying the multi-rotor plant protection UAV test platform, the results indicated the maximum relative error of the wind speed at each sampling point of the system at 1.0 m altitude was below 5.61%. Simulated and measured value had an RMSE maximum error of 0.1246 m·s−1. Moreover, downwash airflow detection not only has high accuracy but also has high sensitivity. Thus, there is convenience and practicability in the plant protection offered by this approach. The rapid measurement of UAV wind field and the established two-dimensional wind field model can provide a basis for precise application of agricultural aviation. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessFeature PaperReview
Monitoring Methods of Human Body Joints: State-of-the-Art and Research Challenges
Sensors 2019, 19(11), 2629; https://doi.org/10.3390/s19112629
Received: 26 April 2019 / Revised: 28 May 2019 / Accepted: 4 June 2019 / Published: 10 June 2019
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Abstract
The world’s population is aging: the expansion of the older adult population with multiple physical and health issues is now a huge socio-economic concern worldwide. Among these issues, the loss of mobility among older adults due to musculoskeletal disorders is especially serious as [...] Read more.
The world’s population is aging: the expansion of the older adult population with multiple physical and health issues is now a huge socio-economic concern worldwide. Among these issues, the loss of mobility among older adults due to musculoskeletal disorders is especially serious as it has severe social, mental and physical consequences. Human body joint monitoring and early diagnosis of these disorders will be a strong and effective solution to this problem. A smart joint monitoring system can identify and record important musculoskeletal-related parameters. Such devices can be utilized for continuous monitoring of joint movements during the normal daily activities of older adults and the healing process of joints (hips, knees or ankles) during the post-surgery period. A viable monitoring system can be developed by combining miniaturized, durable, low-cost and compact sensors with the advanced communication technologies and data processing techniques. In this study, we have presented and compared different joint monitoring methods and sensing technologies recently reported. A discussion on sensors’ data processing, interpretation, and analysis techniques is also presented. Finally, current research focus, as well as future prospects and development challenges in joint monitoring systems are discussed. Full article
(This article belongs to the Section State-of-the-Art Sensors Technologies)
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Open AccessArticle
Study of Out-Of-Hospital Access to HIS System: A Security Perspective
Sensors 2019, 19(11), 2628; https://doi.org/10.3390/s19112628
Received: 25 April 2019 / Revised: 5 June 2019 / Accepted: 5 June 2019 / Published: 10 June 2019
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Abstract
In light of the need for Extramural Hospital Information System (HIS) access through mobile devices outside the hospital, this research analyzes situational information security threats, including the circumstances in which a mobile device may get lost and personal data may be stolen. Moreover, [...] Read more.
In light of the need for Extramural Hospital Information System (HIS) access through mobile devices outside the hospital, this research analyzes situational information security threats, including the circumstances in which a mobile device may get lost and personal data may be stolen. Moreover, the system needs to be implemented in accordance with the regulations. Based on the security threat analysis, it is proposed to use a security control module to provide a security-enabled HIS proxy module, two-way authentication module, and One-Time Password (OTP). The sending module and cryptographic technology computing module with Micro SD encryption card form a set of HIS extension system, which includes the SMS OTP method to simultaneously verify the two-way authentication mechanism of a user and the device that the user owns. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICKII 2019)
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Open AccessArticle
Robust Least-SquareLocalization Based on Relative Angular Matrix in Wireless Sensor Networks
Sensors 2019, 19(11), 2627; https://doi.org/10.3390/s19112627
Received: 8 May 2019 / Revised: 1 June 2019 / Accepted: 3 June 2019 / Published: 10 June 2019
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Abstract
Accurate position information plays an important role in wireless sensor networks (WSN), and cooperative positioning based on cooperation among agents is a promising methodology of providing such information. Conventional cooperative positioning algorithms, such as least squares (LS), rely on approximate position estimates obtained [...] Read more.
Accurate position information plays an important role in wireless sensor networks (WSN), and cooperative positioning based on cooperation among agents is a promising methodology of providing such information. Conventional cooperative positioning algorithms, such as least squares (LS), rely on approximate position estimates obtained from prior measurements. This paper explores the fundamental mechanism underlying the least squares algorithm’s sensitivity to the initial position selection and approaches to dealing with such sensitivity. This topic plays an essential role in cooperative positioning, as it determines whether a cooperative positioning algorithm can be implemented ubiquitously. In particular, a sufficient and unnecessary condition for the least squares cost function to be convex is found and proven. We then propose a robust algorithm for wireless sensor network positioning that transforms the cost function into a globally convex function by detecting the null space of the relative angle matrix when all the targets are located inside the convex polygon formed by its neighboring nodes. Furthermore, we advance one step further and improve the algorithm to apply it in both the time of arrival (TOA) and angle of arrival/time of arrival (AOA/TOA) scenarios. Finally, the performance of the proposed approach is quantified via simulations, and the results show that the proposed method has a high positioning accuracy and is robust in both line-of-sight (LOS) and non-line-of-sight (NLOS) positioning environments. Full article
(This article belongs to the Special Issue Sensors Localization in Indoor Wireless Networks)
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Open AccessArticle
A Novel Frequency Domain Impedance Sensor with a Perforated Cylinder Coaxial Design for In-Situ Measuring Soil Matric Potential
Sensors 2019, 19(11), 2626; https://doi.org/10.3390/s19112626
Received: 13 March 2019 / Revised: 24 May 2019 / Accepted: 5 June 2019 / Published: 10 June 2019
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Abstract
Soil matric potential is an important parameter for agricultural and environmental research and applications. In this study, we developed a novel sensor to determine fast and in-situ the soil matric potential. The probe of the soil matric potential sensor comprises a perforated coaxial [...] Read more.
Soil matric potential is an important parameter for agricultural and environmental research and applications. In this study, we developed a novel sensor to determine fast and in-situ the soil matric potential. The probe of the soil matric potential sensor comprises a perforated coaxial stainless steel cylinder filled with a porous material (gypsum). With a pre-determined gypsum water retention curve, the probe can determine the gypsum matric potential through measuring its water content. The matric potential of soil surrounding the probe is inferred by the reading of the sensor after the soil reaches a hydraulic equilibrium with the gypsum. The sensor was calibrated by determining the gypsum water retention curve using a pressure plate method and tested in three soil samples with different textures. The results showed that the novel sensor can determine the water retention curves of the three soil samples from saturated to dry when combined with a soil water content sensor. The novel sensor can respond fast to the changes of the soil matric potential due to its small volume. Future research could explore the application for agriculture field crop irrigation. Full article
(This article belongs to the Special Issue Sensors in Agriculture 2019)
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Open AccessArticle
Mobile Code Anti-Reversing Scheme Based on Bytecode Trapping in ART
Sensors 2019, 19(11), 2625; https://doi.org/10.3390/s19112625
Received: 31 March 2019 / Revised: 30 May 2019 / Accepted: 6 June 2019 / Published: 10 June 2019
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Abstract
As interest in Internet of Things environments rapidly increases throughout the IT convergence field, compatibility with mobile devices must be provided to enable personalized services. The security of mobile platforms and applications is critical because security vulnerabilities of mobile devices can be spread [...] Read more.
As interest in Internet of Things environments rapidly increases throughout the IT convergence field, compatibility with mobile devices must be provided to enable personalized services. The security of mobile platforms and applications is critical because security vulnerabilities of mobile devices can be spread to all things in these environments. Android, the leading open mobile platform, has long used the Dalvik virtual machine as its runtime system. However, it has recently been completely replaced by a new runtime system, namely Android Runtime (ART). The change from Android’s Dalvik to ART means that the existing Dalvik bytecode-based application execution structure has been changed to a machine code-based application execution structure. Consequently, a detailed understanding of ART, such as new file formats and execution switching methods between codes, is required from the viewpoint of application security. In this paper, we demonstrate that an existing Dalvik-based application vulnerability can be exploited as-is in ART. This is because existing Dalvik executable files coexist in the ART executable file, and these Dalvik bytecodes and compiled machine codes have one-to-one mapping relationships. We then propose an ART-based application protection scheme to secure this by dynamically eliminating the one-to-one mapping. In addition, the proposed scheme is implemented to evaluate its reverse engineering resistance and performance through experiments. Full article
(This article belongs to the Special Issue Internet of Things for Smart Homes)
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Open AccessArticle
Using Wearable and Non-Invasive Sensors to Measure Swallowing Function: Detection, Verification, and Clinical Application
Sensors 2019, 19(11), 2624; https://doi.org/10.3390/s19112624
Received: 4 May 2019 / Revised: 6 June 2019 / Accepted: 7 June 2019 / Published: 9 June 2019
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Abstract
Background: A widely used method for assessing swallowing dysfunction is the videofluoroscopic swallow study (VFSS) examination. However, this method has a risk of radiation exposure. Therefore, using wearable, non-invasive and radiation-free sensors to assess swallowing function has become a research trend. This study [...] Read more.
Background: A widely used method for assessing swallowing dysfunction is the videofluoroscopic swallow study (VFSS) examination. However, this method has a risk of radiation exposure. Therefore, using wearable, non-invasive and radiation-free sensors to assess swallowing function has become a research trend. This study addresses the use of a surface electromyography sensor, a nasal airflow sensor, and a force sensing resistor sensor to monitor the coordination of respiration and larynx movement which are considered the major indicators of the swallowing function. The demand for an autodetection program that identifies the swallowing patterns from multiple sensors is raised. The main goal of this study is to show that the sensor-based measurement using the proposed detection program is able to detect early-stage swallowing disorders, which specifically, are useful for the assessment of the coordination between swallowing and respiration. Methods: Three sensors were used to collect the signals from submental muscle, nasal cavity, and thyroid cartilage, respectively, during swallowing. An analytic swallowing model was proposed based on these sensors. A set of temporal parameters related to the swallowing events in this model were defined and measured by an autodetection algorithm. The verification of this algorithm was accomplished by comparing the results from the sensors with the results from the VFSS. A clinical application of the long-term smoking effect on the swallowing function was detected by the proposed sensors and the program. Results: The verification results showed that the swallowing patterns obtained from the sensors strongly correlated with the laryngeal movement monitored from the VFSS. The temporal parameters measured from these two methods had insignificant delays which were all smaller than 0.03 s. In the smoking effect application, this study showed that the differences between the swallowing function of smoking and nonsmoking participants, as well as their disorders, is revealed by the sensor-based method without the VFSS examination. Conclusions: This study showed that the sensor-based non-invasive measurement with the proposed detection algorithm is a viable method for temporal parameter measurement of the swallowing function. Full article
(This article belongs to the Special Issue Wearable Sensors in Healthcare: Methods, Algorithms, Applications)
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Open AccessArticle
Real-Time Automatic Calculation of Euro Coins and Banknotes in a Cash Drawer
Sensors 2019, 19(11), 2623; https://doi.org/10.3390/s19112623
Received: 9 May 2019 / Revised: 5 June 2019 / Accepted: 6 June 2019 / Published: 9 June 2019
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Abstract
A very interesting and useful complement to classical cash-registers is presented in this paper, coming up with a real-time auto-counting solution for the money inside a cash drawer. The system allows knowing not only the total amount of money but also how many [...] Read more.
A very interesting and useful complement to classical cash-registers is presented in this paper, coming up with a real-time auto-counting solution for the money inside a cash drawer. The system allows knowing not only the total amount of money but also how many coins and banknotes there are of each value. The embedded solution developed has been intended to become a low-cost solution, allowing better control over the money and helping both owners and workers in the establishments. By using this system, new utilities including automatic final balancing, instant error handling when making operations, and the lack of certain types of banknotes or coins inside the drawer or the excess of some in a certain compartment, could be implemented. Coins-counting solution is based on their weight, and small individual scales made by load cells have been integrated in each coin compartment. With respect to the banknotes, an innovative alternative based on the electrical properties of capacitors is presented. Additionally, considering the relevance of interoperability in today’s systems, a Bluetooth module has been integrated into the system, allowing for data to be accessed remotely from any smartphone, tablet or computer within the range of the module. In this work, an Android application to both control and interact with the system has also been designed. Full article
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Open AccessArticle
Grid Based Spherical CNN for Object Detection from Panoramic Images
Sensors 2019, 19(11), 2622; https://doi.org/10.3390/s19112622
Received: 29 April 2019 / Revised: 24 May 2019 / Accepted: 6 June 2019 / Published: 9 June 2019
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Abstract
Recently proposed spherical convolutional neural networks (SCNNs) have shown advantages over conventional planar CNNs on classifying spherical images. However, two factors hamper their application in an objection detection task. First, a convolution in S2 (a two-dimensional sphere in three-dimensional space) or SO(3) (three-dimensional [...] Read more.
Recently proposed spherical convolutional neural networks (SCNNs) have shown advantages over conventional planar CNNs on classifying spherical images. However, two factors hamper their application in an objection detection task. First, a convolution in S2 (a two-dimensional sphere in three-dimensional space) or SO(3) (three-dimensional special orthogonal group) space results in the loss of an object’s location. Second, overlarge bandwidth is required to preserve a small object’s information on a sphere because the S2/SO(3) convolution must be performed on the whole sphere, instead of a local image patch. In this study, we propose a novel grid-based spherical CNN (G-SCNN) for detecting objects from spherical images. According to input bandwidth, a sphere image is transformed to a conformal grid map to be the input of the S2/SO3 convolution, and an object’s bounding box is scaled to cover an adequate area of the grid map. This solves the second problem. For the first problem, we utilize a planar region proposal network (RPN) with a data augmentation strategy that increases rotation invariance. We have also created a dataset including 600 street view panoramic images captured from a vehicle-borne panoramic camera. The dataset contains 5636 objects of interest annotated with class and bounding box and is named as WHU (Wuhan University) panoramic dataset. Results on the dataset proved our grid-based method is extremely better than the original SCNN in detecting objects from spherical images, and it outperformed several mainstream object detection networks, such as Faster R-CNN and SSD. Full article
(This article belongs to the Section Optical Sensors)
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Open AccessArticle
Non-Contact Temperature Control System Applicable to Polymerase Chain Reaction on a Lab-on-a-Disc
Sensors 2019, 19(11), 2621; https://doi.org/10.3390/s19112621
Received: 29 April 2019 / Revised: 29 May 2019 / Accepted: 6 June 2019 / Published: 9 June 2019
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Abstract
Polymerase chain reaction (PCR) and the visual inspection of fluorescent amplicons for detection are commonly used procedures in nucleic acid tests. However, it has been extremely challenging to incorporate PCR onto a lab-on-a-disc (PCR–LOD) as it involves controlling the complicated and precise heating [...] Read more.
Polymerase chain reaction (PCR) and the visual inspection of fluorescent amplicons for detection are commonly used procedures in nucleic acid tests. However, it has been extremely challenging to incorporate PCR onto a lab-on-a-disc (PCR–LOD) as it involves controlling the complicated and precise heating steps during thermal cycling and the measurement of reagent temperature. Additionally, a non-contact temperature control system without any connecting attachments needs to be implemented to facilitate the rotation of the PCR–LOD. This study presents a non-contact temperature control system to integrate conventional PCR onto an LOD. The experimental results demonstrate that our proposed system provides one-stop detection capabilities for Salmonella with a stable PCR amplification in a single PCR–LOD. Full article
(This article belongs to the Special Issue Sensors and Lab-on-a-Chip)
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Open AccessReview
Towards the Recognition of the Emotions of People with Visual Disabilities through Brain–Computer Interfaces
Sensors 2019, 19(11), 2620; https://doi.org/10.3390/s19112620
Received: 11 April 2019 / Revised: 22 May 2019 / Accepted: 7 June 2019 / Published: 9 June 2019
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Abstract
A brain–computer interface is an alternative for communication between people and computers, through the acquisition and analysis of brain signals. Research related to this field has focused on serving people with different types of motor, visual or auditory disabilities. On the other hand, [...] Read more.
A brain–computer interface is an alternative for communication between people and computers, through the acquisition and analysis of brain signals. Research related to this field has focused on serving people with different types of motor, visual or auditory disabilities. On the other hand, affective computing studies and extracts information about the emotional state of a person in certain situations, an important aspect for the interaction between people and the computer. In particular, this manuscript considers people with visual disabilities and their need for personalized systems that prioritize their disability and the degree that affects them. In this article, a review of the state of the techniques is presented, where the importance of the study of the emotions of people with visual disabilities, and the possibility of representing those emotions through a brain–computer interface and affective computing, are discussed. Finally, the authors propose a framework to study and evaluate the possibility of representing and interpreting the emotions of people with visual disabilities for improving their experience with the use of technology and their integration into today’s society. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Image Fusion for High-Resolution Optical Satellites Based on Panchromatic Spectral Decomposition
Sensors 2019, 19(11), 2619; https://doi.org/10.3390/s19112619
Received: 15 April 2019 / Revised: 30 May 2019 / Accepted: 6 June 2019 / Published: 9 June 2019
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Abstract
Ratio transformation methods are widely used for image fusion of high-resolution optical satellites. The premise for the use the ratio transformation is that there is a zero-bias linear relationship between the panchromatic band and the corresponding multi-spectral bands. However, there are bias terms [...] Read more.
Ratio transformation methods are widely used for image fusion of high-resolution optical satellites. The premise for the use the ratio transformation is that there is a zero-bias linear relationship between the panchromatic band and the corresponding multi-spectral bands. However, there are bias terms and residual terms with large values in reality, depending on the sensors, the response spectral ranges, and the land-cover types. To address this problem, this paper proposes a panchromatic and multi-spectral image fusion method based on the panchromatic spectral decomposition (PSD). The low-resolution panchromatic and multi-spectral images are used to solve the proportionality coefficients, the bias coefficients, and the residual matrixes. These coefficients are substituted into the high-resolution panchromatic band and decompose it into the high-resolution multi-spectral bands. The experiments show that this method can make the fused image acquire high color fidelity and sharpness, it is robust to different sensors and features, and it can be applied to the panchromatic and multi-spectral fusion of high-resolution optical satellites. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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