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In their paper on the last glaciation of Shetland, Golledge et al. (2008) concluded on the basis of a remote sensing study that during that period Shetland had been overrun by ice from Scandinavia. Since the method of study they used does not reveal the sense of the direction in which the ice flowed and since they ignored earlier ground-based work involving striations which do reveal the sense of direction of ice flow their conclusions have no scientific basis. [ABSTRACT FROM AUTHOR]

In this paper, a recursive filtering problem is analyzed for nonlinear systems with sensor saturation under duty cycle scheduling (DCS). The sensor saturation is taken into account to describe practical engineering better. The DCS is introduced to conserve energy by alternating sensor nodes between active and dormant states. The considered problem aims to design a collaboration-prediction-based recursive filtering algorithm for nonlinear systems with sensor saturation such that, under the sparse measurements due to DCS, satisfactory filtering performance is guaranteed. By solving a set of matrix difference equations, the upper bound on the filtering error covariance is first obtained, and then the gain matrix of the filter that minimizes the upper limit is calculated. In addition, the boundedness of the upper bound of the filtering error covariance is analyzed. Finally, the effectiveness of the proposed collaboration-prediction-based recursive filtering algorithm is verified by the simulation example. [ABSTRACT FROM AUTHOR]

The Greenhouse Gas Monitoring Instrument (GMI) onboard the Chinese hyperspectral satellite GF5–02 can provide abundant observations of global atmospheric CO2, which plays an important role in climate research. CO2 retrieval precision is the key to determining the application value of the GMI. To reduce the influence of atmospheric scattering on retrieval, we combined the Directional Polarimetric Camera (DPC) data on the same satellite to improve the anti-interference ability of GMI CO2 retrieval and ensure its retrieval precision. To realize the reliability and feasibility of the collaborative use of the GMI and DPC, this paper designs the pointing registration method of the GMI based on coastline observations, the spatial resolution matching method and the collaborative cloud screening method of the GMI and DPC observations. Combined with the DPC, which supplied the spectral data and aerosol product, the retrieval ability of the coupled bidirectional reflectance distribution function CO2 retrieval (CBCR) method developed for GMI CO2 retrieval was improved, with the retrieval efficiency of CO2 products increasing by 27%, and the CO2 retrieval precision increasing from 3.3 ppm to 2.7 ppm. Moreover, collaborative use not only guaranteed the GMI's ability to detect global and area CO2 concentration distribution characteristics, such as significant concentration differences between the Northern and Southern Hemispheres in winter and high CO2 concentrations in urban agglomeration areas caused by human activities, but also extended the GMI's potential for monitoring anomalous events, such as the Tonga volcanic eruption. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Remote Sensing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Exploring the driving factors behind urban polycentricity is of paramount significance for advancing the implementation of urban polycentric strategies. In this, paper takes 41 cities in the China's Yangtze River Delta region are taken as the research objects, and the degree of urban polycentricity is measured using non-parametric and social network methods. Then, the geographic probe method is applied to reveal the driving factors of the spatial differentiation of urban polycentricity. The research results showed that (1) the distribution of hot and cold spots of the urban polycentricity index was roughly the same between 2006 and 2015, while and the distribution of hot and cold spots of the urban polycentricity index varied greatly between 2015 and 2020. (2) In 2010, the proportions of the secondary and industry tertiary industries and the topographic relief were the main driving factors of urban polycentricity. By 2020, the population size and topographic relief were the key drivers of urban polycentricity. [ABSTRACT FROM AUTHOR]

This paper is concerned with the distributed filtering problem for a class of delayed nonlinear systems with random sensor saturation (RSS) under a dynamic event-triggered mechanism. The nonlinear function is assumed to satisfy the Lipschitz condition. A dynamic event-triggered mechanism is employed to further reduce the innovation transmission frequencies among the adjacent nodes. Both the Bernoulli distributed random variables and saturation function are employed to model the phenomenon of RSS. The aim of this paper is to design a sub-optimal filter such that the covariance of the filtering error has an upper bound, which is minimized by appropriately computing the filter gain. Furthermore, the error boundedness is analysed and a sufficient criterion is presented to ensure that the filtering error is mean-square bounded. Finally, a numerical example is provided to verify the effectiveness of the proposed filtering algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the distributed recursive fault estimation problem for a class of discrete time-varying systems with binary encoding schemes over a sensor network. The fault signal with zero second-order difference is taken into account to reflect the sensor failures. Since the communication bandwidth in practice is constrained, the binary encoding schemes are exploited to regulate the signal transmission from the neighbouring sensors to the local fault estimator. In addition, due to the influence of channel noises, each bit might change with a small crossover probability. In the presence of sensor faults and bit errors, an upper bound for the estimation error covariance matrix is ensured and minimized at each time step via designing the gain matrices of the estimator. Finally, the effectiveness of the method is verified by a simulation. [ABSTRACT FROM AUTHOR]

Computer vision is now playing a vital role in modern UAV (Unmanned Aerial Vehicle) systems. However, the on-board real-time small object detection for UAVs remains challenging. This paper presents an end-to-end ViT (Vision Transformer) detector, named Sparse ROI-based Deformable DETR (SRDD), to make ViT model available to UAV on-board systems. We embed a scoring network in the transformer T-encoder to selectively prune the redundant tokens, at the same time, introduce ROI-based detection refinement module in the decoder to optimise detection performance while maintaining end-to-end detection pipeline. By using scoring networks, we compress the Transformer encoder/decoder to 1/3-layer structure, which is far slim compared with DETR. With the help of lightweight backbone ResT and dynamic anchor box, we relieve the memory insufficient of on-board SoC. Experiment on UAVDT dataset shows the proposed SRDD method achieved 50.2% mAP (outperforms Deformable DETR at least 7%). In addition, the lightweight version of SRDD achieved 51.08% mAP with 44% Params reduction. [ABSTRACT FROM AUTHOR]

Nowadays, much of user interface is based on touch and the touch sensors have been common for displays, Internet of things (IoT) projects, or robotics. They can be found in lamps, touch screens of smartphones, or other wide arrays of applications as well. However, the conventional touch sensors, fabricated from rigid materials, are bulky, inflexible, hard, and hard-to-wear devices. The current IoT trend has made these touch sensors increasingly important when it added in the skin or clothing to affect different aspects of human life flexibly and comfortably. The paper provides an overview of the recent developments in this field. We discuss exciting advances in materials, fabrications, enhancements, and applications of flexible wearable sensors under view of touch-sensing. Therein, the review describes the theoretical principles of touch sensors, including resistive, capacitive, and piezoelectric types. Following that, the conventional and novel materials, as well as manufacturing technologies of flexible sensors are considered to. Especially, this review highlights the multidisciplinary approaches such as e-skins, e-textiles, e-healthcare, and e-control of flexible touch sensors. Finally, we summarize the challenges and opportunities that use is key to widespread development and adoption for future research. [ABSTRACT FROM AUTHOR]

Object location is a fundamental yet challenging problem in object detection. In the remote sensing image, different imaging projection directions make the same object have various rotation angles, and in some scenes, the object distribution is relatively dense. Most of the existing deep learning-based object detection algorithms utilize horizontal bounding box to locate objects, which causes inaccurate location of the objects with dense distribution or arbitrary direction, thus leading to the detection misses. In this paper, we propose an arbitrary-angle bounding box based object location and embed it into the Faster R-CNN, developing a new framework called Rotated Faster R-CNN (R-FRCNN) for object detection in remote sensing image. In R-FRCNN, we specially improve anchor ratios to adapt to the objects like ship with large aspect ratio and increase the weights of the horizontal bounding box regression to reduce the interference of the arbitrary-angle bounding box on the horizontal bounding box prediction. Comprehensive experiments on a public dataset and a self-assembled dataset (which we make publically available) show the superior performance of our method compared to standalone state-of-the-art object detectors. [ABSTRACT FROM AUTHOR]

This paper presents the result of an investigation into the utility of the Structure Sensor developed by Occipital Inc. and accuracy of its output for 3D surveying of interiors of buildings in relation to Surveying (Cadastral Survey) Regulation 2005 in Victoria, Australia. The paper investigates data acquisition issues, defines guidelines to obtain the best reconstruction result, and evaluates the result against the requirements set by the Regulation. The findings suggest a mixed result. The sensor delivers more accurate outputs for the smaller room sizes. Also, the accuracy does not meet the requirements, but it was found to be close to what is expected in the Regulation. Finally, the paper argues that the device is user-friendly enough to be used by non-experts for crowdsourcing indoor information and, the accuracy of its output can meet the needs of other domains such as indoor navigation and public safety. [ABSTRACT FROM AUTHOR]

This paper focuses on the fault estimation problem for a class of nonlinear systems with sensor gain degradation and stochastic protocol (SP) based on strong tracking filtering. The phenomenon of the sensor gain degradation is described by sequences of stochastic variables in a known interval. The stochastic protocol (SP) is used to deal with possible data conflicts in multi-signal transmission. The augmented system is constructed by combining the original system state vectors and the related faults into an augmented state vectors. The strong tracking filter (STF) is designed by introducing a fading factor into the filter structure to solve the problem of burst faults. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed filter. [ABSTRACT FROM AUTHOR]

In this paper, the problem of secure state estimation for cyber physical systems (CPSs) with state delay and sparse sensor attacks is studied. An algorithm combining set cover approach and adaptive switching mechanism is proposed, which can realize off-line acquisition of candidate set and accurately locate the real attack mode. The contributions of this algorithm are that it can greatly reduce the search space, eliminate the impact of attacks on state estimation, improve the estimation speed and ensure the real-time performance of state estimation under the premise of effective estimation. The sufficient condition for the existence of the observer is obtained. Finally, the rapidity and effectiveness of the designed observer are verified by two examples. [ABSTRACT FROM AUTHOR]

In this paper, a novel sun sensor which has been applied on orbit since 2018 is introduced. The remote data transmitted from the satellite is analyzed to show its performance. In the lighting area, the sun sensor can give the sun vector which used for the attitude determination. From the data, the center point error is found to be the most significant factor that affects the accuracy of the sun sensor. In the "Sun pointing" work mode, the real output of the sun sensor is different from the theoretical output. The data from the star sensor is used for compensating the center point error based on ellipse fitting. The triad algorithm is affected by the center point error of the sun sensor. The simulation only considers this kind of error. And the result shows that it can decrease the Euler angle errors, so that improves the accuracy of triad algorithm. [ABSTRACT FROM AUTHOR]

The present paper presents an innovative approach for the numerical modeling of piezo-electric transducers for the health-monitoring of layered structures. The numerical approach has been developed in the frameworks of the Carrera Unified Formulation. This computational tool allows refined numerical models to be derived in a unified and efficient fashion. The use of higher-order models and the capability to connect different kinematic models using the node-dependent kinematic approach has led to an efficient modeling technique for global-local analysis. This approach can refine the model only in those regions where it is required, e.g., the areas where piezo-electric transducers are placed. The model has been used to study embedded and surface-mounted sensors. The accuracy of the present model has been verified by comparing the current results with numerical and experimental data from the literature. Different modeling solutions have been developed, mixing one-, two- and three-dimensional finite elements. The results show that the use of the present modeling technique allows the computational cost to be reduced with respect to the classical approaches preserving the accuracy of the results in the critical areas. [ABSTRACT FROM AUTHOR]

Collecting complex information on the status of machinery is the enabler for advanced maintenance activities, and one of the main players in this process is the sensor. This paper describes modern maintenance strategies that lead to Condition-Based Maintenance. This paper discusses the sensors that can be used to support maintenance, as of different categories, spanning from common off-the-shelf sensors, to specialized sensors monitoring very specific characteristics, and to virtual sensors. This paper also presents four different real-world examples of project pilots that make use of the described sensors and draws a comparison between them. In particular, each scenario has unique characteristics requiring different families of sensors, but on the other hand provides similar characteristics on other aspects. [ABSTRACT FROM AUTHOR]

This paper investigates maneuvering-target tracking problem based on a multisensor system and interacting multiple model (IMM). The estimation is performed by a novel particle filter (PF) with a capability to deal with the state-dependent noises and interference of the sensors' coverage environment. An adaptive sensor selection algorithm, where some sensors are selected in each stage based on the signal-to-interference pulse noise ratio (SINR) and participate in the state estimation, is proposed. To deal with the effect of interference, we focus on designing and implementing the sensor selection algorithm, where a multisensor system with nonuniform arrays is derived by solving a convex optimization problem. On this basis, a nonuniform array of sensors is selected in each time interval aiming at maximizing the SINR of the received information from the undercoverage area. This would allow tracking in practical environments experiences interference. This method also is able to reduce the tracking error rate. [ABSTRACT FROM AUTHOR]

The paper herein is concerned with the system of interrogating the signals, entering from rotation sensors. The systems for analyzing the sensors thereof most often require capacity's reference measurement. It allows obtaining the measurement's higher resolution comparing to single-channel systems, in which it is impossible to measure the reference power. In case of single-channel solutions, there is most frequently tracked the wavelength shift, corresponding to the extreme, according to spectral specifications. [ABSTRACT FROM AUTHOR]

Wireless sensors are widely used in the Internet of things. In this paper, the S-MAC protocol is enhanced by extending IEEE802.11 data frame and combining data and energy priority, so as to solve the portability problem of priority data. The improved strategy enables the wireless sensor nodes to transmit data and energy according to the priority and network load in the process of data transmission competition window to reduce unnecessary conflicts. The improved protocol simulation test using NS2 simulation platform shows that the improved S-MAC protocol reduces the data transmission delay of sending different levels of priority information, achieves balanced network load, and prolongs the network life time. [ABSTRACT FROM AUTHOR]

The unmanned aerial vehicle (UAV) is one of the mobile robots which has grown rapidly in popularity in recent years. UAVs have been used in various activities to convey important information on the aerial transportation system. However, an application to get real-time information from UAVs remains a challenging task. Therefore, this paper presents an integration system to optimise the use of UAVs for aerial surveillance. The proposed system explains the design and implementation a UAV system which consists of on-board and ground stations. The on-board system has the function to send UAV flight data, send aerial images and carry items using a gripper which equipped with sensors to detect obstacles. The ground station has the function to control UAV flights, receive and display UAV flight data and aerial images, display the attitude of the UAV and send commands to move the camera and gripper. Flight controllers in this system use non-linear complementary filter on SO(3) to estimate the attitude of the UAV and proportional-integral (PI) controller to stabilise the UAV flight. By providing the real-time acquisition data of the UAV, we believe this system can be a useful tool for many implementations using UAV. [ABSTRACT FROM AUTHOR]

The quick development of the smart factory and prognostic and health management (PHM), in the fields of aeronautic, automotive and green energies, is evidencing a need for sensors able to monitor the behavior of composite materials all along their life at the closest of the matter. In situ fabricated conductive polymer nanocomposite (CPC) sensors are bringing an interesting solution to this prospect as they can be integrated homogeneously in the core of composites to probe their deformations and damage. In particular fatigue which is one important mode of failure of polymer composites can be monitored from early signs of damage until the final breakage by analyzing the piezo-resistive response of quantum resistive strain sensors (sQRS) made of carbon nanotubes. We have developed all these aspects in the paper taking the example of a classical glass fibers/epoxy composite instrumented in its core with two sQRS to monitor its short and long term fatigue behavior. [ABSTRACT FROM AUTHOR]

The presence of process-induced strains induced by various manufacturing and operational factors is one of the characteristics of polymer composite materials (PCM). Conventional methods of registration and evaluation of process-induced strains can be laborious, time-consuming and demanding in terms of technical applications. The employment of embedded fibre-optic strain sensors (FOSS) offers a real prospect of measuring residual strains. This paper demonstrates the potential for using embedded FOSS for recording technological strains in a PCM plate. The PCM plate is manufactured from prepreg, using the direct compression-moulding method. In this method, the prepared reinforcing package is placed inside a mould, heated, and then exposed to compaction pressure. The examined technology can be used for positioning FOSS between the layers of the composite material. Fibre-optic sensors, interacting with the material of the examined object, make it possible to register the evolution of the strain process during all stages of polymer-composite formation. FOSS data were recorded with interrogator ASTRO X 327. The obtained data were processed using specially developed algorithms. [ABSTRACT FROM AUTHOR]

The satellite laser geometry calibration method based on terrain matching (terrain matching calibration) has been extensively employed in satellite laser geometry calibration for its simplicity and lack of need for ground probes. In this study, the key factors for the accuracy of the above-mentioned calibration method, i.e. namely the terrain slope and the number of laser points, are examined with the GaoFen-7 (GF-7) satellite as an example. Terrain is classified into six levels in according with the slope classification standards, i.e. Flat (<2°), Micro-slope (2°-5°), Gentleslope (5°-15°), Moderate-slope (15°-25°), Slope (25°-35°) and Steep-slope (35°-55°). Moreover, a different number of laser points are randomly selected from each the respective terrain slope for calibration. The accuracy of calibration is verified using the true laser pointing obtained based on the ground detector calibration method. As indicated by the experimental results, the terrain matching calibration achieves the optimal experimental conditions when there are over 50 laser points with a terrain slope greater than 15°, or there exist over 20 laser points with a terrain slope greater than 25°. In both cases, the laser pointing accuracy after calibration can exceed 3 arc seconds. This study can provide technical guidance for high-precision terrain matching calibration. [ABSTRACT FROM AUTHOR]

Traditional fault detection and isolation (FDI) methods analyze a residual signal to detect and isolate sensor faults. The residual signal is the difference between the sensor measurements and the estimated outputs of the system based on an observer. The traditional residual-based FDI methods, however, have some limitations. First, they require that the observer has reached its steady state. In addition, residual-based methods may not detect some sensor faults, such as faults on critical sensors that result in an unobservable system. Furthermore, the system may be in jeopardy if actions required for mitigating the impact of the faulty sensors are not taken before the faulty sensors are identified. The contribution of this paper is to propose three new methods to address these limitations. Faults that occur during the observers' transient state can be detected by analysing the convergence rate of the estimation error. Open-loop observers, which do not rely on sensor information, are used to detect faults on critical sensors. By switching among different observers, we can potentially mitigate the impact of the faulty sensor during the FDI process. These three methods are systematically integrated with a previously developed residual-based method to provide an improved FDI and mitigation capability framework. The overall approach is validated mathematically, and the effectiveness of the overall approach is demonstrated through simulation on a five-state suspension system. [ABSTRACT FROM AUTHOR]

The threat of slugging to production facilities has been known since the 1970s. This undesirable flow phenomenon continues to attract the attention of researchers and operators alike. The most common method for slug mitigation is by choking the valve at the exit of the riser which unfortunately could negatively affect production. The focus, therefore, is to satisfy the need for system stability and to maximize production simultaneously. Active feedback control is a promising way to achieve this. However, due to the complexity of multiphase flow systems, it is a challenge to develop a robust slug control system to achieve the desired performance using existing design tools. In this paper, a new general method for multiphase flow system stability analysis was proposed. Active feedback control was observed to optimize slug attenuation compared with manual choking. The use of soft sensors was believed to be desirable for the practical implementation of the proposed control technique. [ABSTRACT FROM AUTHOR]

Electric double layer (EDL) gating is a technique in which ions in an electrolyte modulate the charge transport in an electronic material through electrical field effects. A sub-nanogap capacitor is induced at the interface of electrolyte/semiconductor under the external electrical field and the capacitor has an ultrahigh capacitance density (~µF cm−2). Recently, EDL gating technique, as an interfacial gating, is widely used in two-dimensional (2D) crystals for various sophisticated materials characterization and device applications. This review introduces the EDL-gated transistors based on 2D materials and their applications in the field of bioinspired optoelectronic detection, sensing, logic circuits, and neuromorphic computation. [ABSTRACT FROM AUTHOR]

Many different forms of sensor fusion have been proposed each with its own niche. We propose a method of fusing multiple different sensor types. Our approach is built on the discrete belief propagation to fuse photogrammetry with GPS to generate three-dimensional (3D) point clouds. We propose using a non-parametric belief propagation similar to Sudderth et al’s work to fuse different sensors. This technique allows continuous variables to be used, is trivially parallel making it suitable for modern many-core processors, and easily accommodates varying types and combinations of sensors. By defining the relationships between common sensors, a graph containing sensor readings can be automatically generated from sensor data without knowing a priori the availability or reliability of the sensors. This allows the use of unreliable sensors which firstly, may start and stop providing data at any time and secondly, the integration of new sensor types simply by defining their relationship with existing sensors. These features allow a flexible framework to be developed which is suitable for many tasks. Using an abstract algorithm, we can instead focus on the relationships between sensors. Where possible we use the existing relationships between sensors rather than developing new ones. These relationships are used in a belief propagation algorithm to calculate the marginal probabilities of the network. In this paper, we present the initial results from this technique and the intended course for future work. [ABSTRACT FROM AUTHOR]

Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quick and timely fault detection is of great importance in control systems reliability. Undetected faulty sensors could result in irreparable damages. Although fault detection and isolation (FDI) methods in control systems have received much attention in the last decade, these techniques have not been applied for some classes of nonlinear systems yet. This paper deals with the issues of sensor fault detection and isolation for a class of Lipschitz uncertain nonlinear system. By introducing a coordinate transformation matrix for states and output, the original system is first divided into two subsystems. The first subsystem is affected by uncertainty and disturbance. The second subsystem just has sensor faults. The nonlinear term is separated to linear and pure nonlinear parts. For fault detection, two sliding mode observers (SMO) are designed for the two subsystems. The stability condition is obtained based on the Lyapunov approach. The necessary matrices and parameters are obtained by solving the linear matrix inequality (LMI) problem. Furthermore, two sliding mode observers are designed for fault isolation. Finally, the effectiveness of the proposed approach is illustrated by simulation examples. [ABSTRACT FROM AUTHOR]

Fibre optic sensor cable technology is relatively a new research area that combines a set of scientific and technical disciplines in order to meet distributed sensor system needs and quality standards. In this paper, we discuss a fibre optic sensor design with three tightly encapsulated fibres for multipurpose and multivalent sensing. It has the potential to integrate more detection and measurement techniques into a small space, and this, in turn, largely contributes to installation and cost optimizations and directly impacts investment plans and industrial success. The developed cable is tested in a specially developed high pressure and high temperature chamber. Furthermore, it is demonstrated that the proposed sensor cable offers the possibility of detection and distributed measurement of temperature, pressure, bending and vibrations. [ABSTRACT FROM AUTHOR]

Clinicians seek an accurate method to assess muscle contractility during activities to better guide treatment. We investigated application of a conductive electroactive polymer sensor as a novel wearable surface mechanomyography (sMMG) sensor for quantifying muscle contractility. The radial displacement of a muscle during a contraction is detected by the physically stretched dielectric elastomer component of the sMMG sensor which quantifies the changes in capacitance. The duration of muscle activation times for quadriceps, hamstrings, and gastrocnemius muscles demonstrated strong correlation between sMMG and EMG during a parallel squat activity and isometric contractions. A moderate to strong correlation was demonstrated between the sMMG isometric muscle activation times and force output times from a dynamometer. The potential wearable application of an electroactive polymer sensor to measure muscle contraction time is supported. [ABSTRACT FROM AUTHOR]

The paper considers key limitation of the feedback linearisation controller designed for nonlinear systems based on the imperfect nominal dynamics model and sensors. The model-reality differences cause signal leakages in the feedback linearised dynamics. As the leakages are the functions of the process variables, the resulting overall dynamics are again nonlinear with strong additive nonlinearities and the expected decoupling of the system dynamics is missing. In the paper, instead of using advanced control tools, we prove the robustness of the feedback linearisation method can also be significantly enhanced by employing several simple and classical methods cooperatively. For clear description and explanation, the methodology was illustrated based on a two-link manipulator case study, a classical multi-input multi-output coupled nonlinear system. The methods have genetic potential so that they can be applicable to a variety of case study systems and also further developed to become general methodologies. [ABSTRACT FROM PUBLISHER]

This paper presents a development of a low-cost miniature humidity sensor with an interdigitated aluminium electrode connected in parallel on quartz substrate. Interdigitated capacitive device has been fabricated using the photolithography method. The aluminium electrode was covered with sensitive film of a nanoporous thin film of γ-Al2O3 made from novel sol–gel technique. Nanostructured thin film offers very high surface to volume ratio with distribution of micro pores for moisture detection. Pore morphologies of the film have been studied by field emission electron microscope and X-ray diffraction methods. Impedance measurement of the miniature capacitive humidity sensor toward relative humidity was investigated at room temperature by Agilent 4294A impedance analyzer (Agilent, Santa Clara, CA, USA). The device exhibits short response and recovery times and good repeatability. [ABSTRACT FROM AUTHOR]

Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on the spheroconical monopole antenna theory, we design a novel type of ultra-high frequency (UHF) sensor for partial discharge (PD) location in substations. With a spheroconical structure, this sensor is featured by broadband, omnidirectional capability, high sensitivity, low reflection loss, and constant group delay, meeting the requirements of omnidirectional detection of discharge sources. A UHF sensor array made up of several sensors of this type can implement spatial location of discharge sources. To verify the discharge source location performance of the sensor array, we construct a PD experimental platform in the laboratory. The PD source location results indicate that the location system based on a UHF sensor array accurately locates PD sources. Therefore, the UHF sensor developed in this paper can be applied to spatial location of PD sources in substations. [ABSTRACT FROM AUTHOR]

Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The widely used CMOS Active Pixel Sensors (APS) in space imaging mission are vulnerable to radiations known as Single Event Transient (SET). This paper focus on 3T and 4T CMOS APS with technology from 130 nm scaling down to 32 nm, simulated using various Linear Energy Transfer (LET) magnitudes ranging from 3.3 to 67.7 MeV.cm2/mg. Larger transient currents were observed at higher LET for both APS architectures. The peak drain current of 3T increases with slightly steeper slope by roughly 8% than 4T due to the difficulty of electron transfer in 4T. In 3T, 130 nm, 90 nm, 65 nm and 45 nm override the 32 nm technology by 13.93%, 9.09%, 4.43% and 2.06%, respectively. The total charge collection of the 3T is constantly higher than the 4T APS by the ratio of at least 1.25 indicates 4T has a higher radiation hardness. A bright spot degradation is expected to occur in the image if the transient signal is more than 20% of the original signal which mainly attributed to the lower operating voltage and smaller nodal capacitance. From this study, 4T CMOS APS shown more radiation hardness than the 3T CMOS APS and 32 nm technology exhibits lowest radiation-tolerant. [ABSTRACT FROM AUTHOR]

Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research. [ABSTRACT FROM AUTHOR]

Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper is intended to generate unbiased state estimates of a three-phase induction motor using derivative-free state estimation algorithms. The use of intrusive sensors located within the air-gap of the machine has typically been plagued by complexities and lack of robustness. Moreover, any eventual damage in the sensor results in the substitution of the whole motor. On the other hand, there have been major efforts to reduce the cost of high performance systems, besides increasing the versatility of the motor that all necessitate the use of state observers, thereby eliminating the sensors and their interfaces. In this work, a comparative analysis of the three derivative-free non-linear filtering schemes to estimate the states of a three-phase induction motor on the simulated model is presented. The efficacy of ensemble Kalman filter (EnKF) against the traditional sampling importance re-sampling particle filter (SIR-PF) and unscented Kalman filter (UKF) is illustrated. Comparative Monte Carlo simulation results are investigated comprehensively with respect to three different scenarios, namely step changes in load torque, speed reversal, and low speed operation. Computer simulations have been carried out in the presence of additive state and measurement uncertainties and from the extensive simulation studies, it is being inferred that the SIR-PF fails to generate accurate state estimates in the presence of step changes in the load torque as it does not take into account the most current observation in the sampling stage, whereas EnKF and UKF work well. Moreover, when compared on the basis of the sum of squares of the estimation errors (SSEE), which is very often used as the performance index, the performance of the unconstrained estimation algorithm using the EnKF is found to be significantly better than those obtained using UKF and SIR-PF formulations for all the scenarios taken for the simulation study. The results throw light on alleviating the intrinsic intricacies encountered in SIR-PF in parlance with the observer theory. [ABSTRACT FROM AUTHOR]

Antineutrinos are electrically neutral, nearly massless fundamental particles produced in large numbers in the cores of nuclear reactors and in nuclear explosions. In the half century since their discovery, major advances in the understanding of their properties, and in detector technology, have opened the door to a new discipline-Applied Antineutrino Physics. Because antineutrinos are inextricably linked to the process of nuclear fission, there are many applications of interest in nuclear nonproliferation. This paper presents a comprehensive survey of applied antineutrino physics relevant for nonproliferation, summarizes recent advances in the field, describes the overlap of this nascent discipline with other ongoing fundamental and applied antineutrino research, and charts a course for research and development for future applications. It is intended as a resource for policymakers, researchers, and the wider nuclear nonproliferation community. [ABSTRACT FROM AUTHOR]

Wheat is the main grain crop in China. The planted area has increased to more than 300 million mu (about 20 million ha) and the rate of machinery harvest has reached about 80%. It is difficult to provide accurate information of wheat yield per mu in different areas. This makes national macro-management and safeguarding food security difficult. The combine harvester onboard information platform studied in this paper has two functions. First, it detects geographical information, harvested area and crop yield per mu and, second it reports the state of the harvester and diagnoses faults. The information platform provides service information for the driver which improves reliability. In addition, it can send this information to an information centre through a GSM (mobile phone) message module, and this centre can forward the information to government administration and research institutes through the network. The on board information platform cored with SCM 80C196 confirms geographical information of the harvester by GPS (global positioning system) to create an electronic map of the harvest area with actual harvest width and distance of travel. With measurements taken when unloading the grain, crop yield per mu can be calculated and the running status of the harvester as well as fault diagnosis through monitoring sensors can be appraised. Experiment shows that the measurement accuracy of harvest area and thus of yield per mu is about 95%. [ABSTRACT FROM AUTHOR]

This paper describes a method for tracking a bronchoscope by combining a position sensor and image registration. A bronchoscopy guidance system is a tool for providing real-time navigation information acquired from pre-operative CT images to a physician during a bronchoscopic examination. In this system, one of the fundamental functions is tracking a bronchoscope's camera motion. Recently, a very small electromagnetic position sensor has become available. It is possible to insert this sensor into a bronchoscope's working channel to obtain the bronchoscope's camera motion. However, the accuracy of its output is inadequate for bronchoscope tracking. The proposed combination of the sensor and image registration between real and virtual bronchoscopic images derived from CT images is quite useful for improving tracking accuracy. Furthermore, this combination has enabled us to achieve a real-time bronchoscope guidance system. We performed evaluation experiments for the proposed method using a rubber phantom model. The experimental results showed that the proposed system allowed the bronchoscope's camera motion to be tracked at 2.5 frames per second. [ABSTRACT FROM AUTHOR]

This paper investigates the possibility of using the motion of a patient's anterior surface in combination with a motion model to compensate for internal respiratory motion during tracked biopsies. Position data from two electromagnetically tracked sensors, one placed on the patient's sternum, the other incorporated into a biopsy needle, were acquired during a liver biopsy. The data were used to evaluate the correlation between the position measurements of the two sensors and to derive an affine motion model to assess respiratory motion compensation for image-guided interventional procedures. The correlation reached up to 94% for ranges of steady respiration. The residual motion of the internal sensor after compensation is reduced by a factor of approximately four. [ABSTRACT FROM AUTHOR]

In wireless communication, noise and fading affect the radio signals. Multiple antennas one of the solutions to nullify these affects. In this paper, authors proposed an improved sensing detector for wireless regional area networks. The presented scheme uses two detectors concept, detectors imply multiple antennas, follows selection combination to select best signals. The proposed model not only improves the detection performance but also decreases the sensing time. Out of the two detectors the first one is energy detector with single adaptive threshold and second one is energy detector with two adaptive thresholds. The thresholds are adaptive as they are dependent on noise variance (), and the value of this noise variance changes according to the noise signal. Both the detectors work simultaneously and their output is then fed to a decision devise which takes the decision using OR rule. In the proposed scheme more than one antenna has been used and is compared with existing sensing techniques. Results show that the proposed an improved sensing detector technique while number of antennas (Nr) = 2, improves the detection performance by 24.6, 53.4, 37.9, and 49.6%, as compared to existing schemes (i.e. EDT-ASS-2015 scheme, ED and cyclo-2010, adaptive SS-2012, and conventional-ED) scheme at −12 dB SNR respectively. Meanwhile, proposed technique also decreases sensing time in the order of 47.0, 49.0, and 53.2 ms as compared to existing schemes (EDT-ASS-2015, Adaptive SS-2012, and ED and Cyclo-2010) scheme at −20 dB SNR respectively. Further, in cooperative SS the local decisions from each cognitive radio are transferred to a fusion center which makes the final decision and shares the decision to every cognitive radio. It is also found that the proposed detection technique with CSS when number of CR users (k) = 10, and Nr = 2, achieves spectrum detection performance in the order of 0.9 for SNR value of as low as −20 dB. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAV) have been used in a variety of fields in the last decade. In forestry, they have been used to estimate tree heights and crowns with different sensors. This approach, with a consumer-grade onboard system camera, is becoming popular because it is cheaper and faster than traditional photogrammetric methods and UAV-light detecting and ranging systems (UAV-LiDAR). In this study, UAV-based imagery reconstruction, processing, and local maximum filter methods are used to obtain individual tree heights from a coniferous urban forest. A low-cost onboard camera and a UAV with a 96-cm wingspan made it possible to acquire high resolution aerial images (6.41 cm average ground sampling distance), ortho-images, digital elevation models, and point clouds in one flight. Canopy height model, obtained by extracting the digital surface model from the digital terrain model, was filtered locally based on the pixel-based window size using the provided algorithm. For accuracy assessment, ground-based tree height measurements were made. There was a high 94% correlation and a root-mean-square error of 28 cm. This study highlights the accuracy of the method and compares favourably to more expensive methods. [ABSTRACT FROM AUTHOR]

Composite structures are sensitive to impact damage in practical engineering. Electric resistance change method (ERCM) is an ideal technique for damage monitoring of composite structures. Due to the anisotropy of fiber-resin matrix composites, impact location monitoring is difficult, and research on impact location of fiber composite laminates (FRPs) is limited. A preparation method of MXene/CNT/CuNps thin film sensor is proposed. According to the modeling simulation and theoretical calculation, the resistance change characteristics of the thin film sensor are obtained, the relationship between the impact distance and the resistance change is established, and the sensor array is designed. A three-point localization algorithm and a weight function compensation localization algorithm are proposed, which can improve the imaging accuracy of the impact position. The impact point location was observed and analyzed using ultrasonic C-scan technology. The results show that the weight function compensation positioning algorithm can accurately locate the impact of the composite structure, and the error in the X direction is 7.1%, the error in the Y direction is 0.03%, which verifies the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Manufacturing companies continuously capture shop floor information using sensors technologies, Manufacturing Execution Systems (MES), Enterprise Resource Planning systems. The volumes of data collected by these technologies are growing and the pace of that growth is accelerating. Manufacturing data is constantly changing but immediately relevant. Collecting and analysing them on a real-time basis can lead to increased productivity. Particularly, prioritising improvement activities such as cycle time improvement, setup time reduction and maintenance activities on bottleneck machines is an important part of the operations management process on the shop floor to improve productivity. The first step in that process is the identification of bottlenecks. This paper introduces a purely data-driven shifting bottleneck detection algorithm to identify the bottlenecks from the real-time data of the machines as captured by MES. The developed algorithm detects the current bottleneck at any given time, the average and the non-bottlenecks over a time interval. The algorithm has been tested over real-world MES data sets of two manufacturing companies, identifying the potentials and the prerequisites of the data-driven method. The main prerequisite of the proposed data-driven method is that all the states of the machine should be monitored by MES during the production run. [ABSTRACT FROM PUBLISHER]

This paper is concerned with event-triggered autonomous platoon control with probabilistic sensor and actuator failures. A new platoon model is established, in which the effect of event-triggered scheme and probabilistic failures are involved. Based on the model, the criteria for the exponential stability and co-designing both the trigger parameters and the output feedback are derived by using the Lyapunov method. The theoretical results show that the proposed controller would be able to safely maintain a smaller inter-vehicle spacing and the platoon would be string stable. The effectiveness and advantage of the presented methodology are demonstrated by numerical simulations. [ABSTRACT FROM PUBLISHER]