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Concussions, a prevalent public health concern in the United States, often result from mild traumatic brain injuries (mTBI), notably in sports such as American football. There is limited exploration of smart-textile-based sensors for measuring the head impacts associated with concussions in sports and recreational activities. In this paper, we describe the development and construction of a smart textile impact sensor (STIS) and validate STIS functionality under high magnitude impacts. This STIS can be inserted into helmet cushioning to determine head impact force. The designed 2 × 2 STIS matrix is composed of a number of material layered structures, with a sensing surface made of semiconducting polymer composite (SPC). The SPC dimension was modified in the design iteration to increase sensor range, responsiveness, and linearity. This was to be applicable in high impact situations. A microcontroller board with a biasing circuit was used to interface the STIS and read the sensor's response. A pendulum test setup was constructed to evaluate various STISs with impact forces. A camera and Tracker software were used to monitor the pendulum swing. The impact forces were calculated by measuring the pendulum bob's velocity and acceleration. The performance of the various STISs was measured in terms of voltage due to impact force, with forces varying from 180 to 722 N. Through data analysis, the threshold impact forces in the linear range were determined. Through an analysis of linear regression, the sensors' sensitivity was assessed. Also, a simplified model was developed to measure the force distribution in the 2 × 2 STIS areas from the measured voltages. The results showed that improving the SPC thickness could obtain improved sensor behavior. However, for impacts that exceeded the threshold, the suggested sensor did not respond by reflecting the actual impact forces, but it gave helpful information about the impact distribution on the sensor regardless of the accurate expected linear response. Results showed that the proposed STIS performs satisfactorily within a range and has the potential to be used in the development of an e-helmet with a large STIS matrix that could cover the whole head within the e-helmet. This work also encourages future research, especially on the structure of the sensor that could withstand impacts which in turn could improve the overall range and performance and would accurately measure the impact in concussion-causing impact ranges. [ABSTRACT FROM AUTHOR]

Weigh-in-motion (WIM) systems are essential for efficient transportation and monitoring parameters such as vehicle number, speed, and weight to ensure regulatory compliance and enhance road safety. Recently, WIM measurements using the Glass Fiber Reinforced Polymer Fiber Bragg Grating (GFRP-FBG) sensors have shown robustness and effectiveness. However, the accuracy of weight evaluation using the WIM systems based on GFRP-FBG sensors can be significantly influenced by the vehicle-wandering effect, which introduces uncertainties in wheel position determination and weight calculations. This paper assessed the impact of vehicle wandering on the accuracy of a WIM measurement system based on GFRP-FBG sensors by utilizing a new hybrid sensor-camera system that integrates roadside cameras and in-pavement GFRP-FBG sensors. The detailed methodology and framework of the developed hybrid system are introduced, followed by field testing on Highway I-94 in the United States. The field testing results indicate that by using the hybrid system, the wheel load detection accuracy of the WIM system based on GFRP-FBG sensors can be controlled to be a Type I or Type III WIM according to the ASTM 1318E-09 standard, with an average accuracy ranging from 87.83% to 94.65%. At the same time, when the wander distance is less than or equal to 9 cm, the developed WIM system proves to be very cost-effective as it only comprises two GFRP-FBG sensors, one temperature FBG sensor, and one camera. These findings indicate the practical potential to enhance the accuracy of WIM systems based on GFRP-FBG sensors designed for highways for low-coast, reliable, and accurate measurements by addressing vehicle wandering effects. [ABSTRACT FROM AUTHOR]

This paper investigates the potential vertical guidance performance of global positioning system (GPS)/wide area augmentation system (WAAS) user avionics sensor when the modernized GPS and Galileo are available. This paper will first investigate the airborne receiver code noise and multipath (CNMP) confidence (σair). The σair will be the dominant factor in the availability analysis of an L1-L5 dual-frequency GPS/WAAS user avionics sensor. This paper uses the MATLAB Algorithm Availability Simulation Tool (MAAST) to determine the required values for the σair, so that an L1-L5 dual-frequency GPS/WAAS user avionics sensor can meet the vertical guidance requirements of APproach with Vertical guidance (APV) II and CATegory (CAT) I over conterminous United States (CONUS). A modified MAAST that includes the Galileo satellite constellation is used to determine under what user configurations WAAS could be an APV II system or a CAT I system over CONUS. Furthermore, this paper examines the combinations of possible improvements in signal models and the addition of Galileo to determine if GPS/WAAS user avionics sensor could achieve 10 m Vertical Alert Limit (VAL) within the service volume. Finally, this paper presents the future vertical guidance performance of GPS user avionics sensor for the United States' WAAS, Japanese MTSAT-based satellite augmentation system (MSAS) and European geostationary navigation overlay service (EGNOS). [ABSTRACT FROM AUTHOR]

Natural disasters affect structural health of buildings, thus directly impacting public safety. Continuous structural monitoring can be achieved by deploying an Internet of things network of distributed sensors in buildings to capture floor movement. These sensors can be used to compute the displacements of each floor, which can then be employed to assess building damage after a seismic event. The peak relative floor displacement is computed, which is directly related to damage level according to the United States federal agencies standards. With this information, the building inventory can be classified into immediate occupancy, life safety, or collapse prevention categories. In this paper, we propose a zero velocity update technique to minimize displacement estimation error. Theoretical derivation and experimental validation are presented. In addition, we investigate modeling sensor error and interstory drift ratio distribution. Moreover, we discuss the impact of sensor error on the achieved building classification accuracy. [ABSTRACT FROM AUTHOR]

Epilepsy is one of the most common neurological disorders affecting a significant portion of the world’s population and approximately 2.5 million people in the United States. Important biomedical research effort is focused on the development of energy efficient devices for the real-time detection of seizures. In this paper, we propose an Internet of Medical Things (IoMT)-based automated seizure detection system which will detect a seizure from electroencephalography (EEG) signals using a voltage level detector (VLD) and a signal rejection algorithm (SRA). The proposed system analyzes neural signals continuously and extracts the hyper-synchronous pulses for the detection of seizure onset. Within a time frame, if the number of pulses exceeds a predefined threshold value, a seizure is declared. The SRA reduces false detections, which in turn enhances the accuracy of the seizure detector. The design was validated using system-level simulations and consumer electronics proof of concept. The proposed seizure detector reports a sensitivity of 96.9% and specificity of 97.5%. The use of minimal circuitry can lead to reduction of power consumption compared to many contemporary approaches. The proposed approach can be generalized to other sensor modalities and the use of wearable or implantable solutions, or a combination of the two. [ABSTRACT FROM AUTHOR]

Although they share many common qualities in design and operation, mesonetworks across the United States were established independently and organically over the last several decades. In numerous instances, the unique ways each network matured and developed new protocols has led to important lessons learned. These experiences have been shared in informal ways among various network operators over the years to promote reliable operation. As existing networks begin to introduce new sensors and technologies, and as new networks come online, there is a common need for guidance on best practices. This paper aims to formally provide recommendations to improve and harmonize the various aspects of operating a "mesonet," including siting, sensors, maintenance, quality assurance, and data processing. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to demonstrate the theoretical relationship between the layout of four-sensor dynamic acoustic array tracking system and systematic observation accuracy, and provide an algorithm to determine the optimal arrangement of four-sensor acoustic array and an indicator to evaluate acoustic array system measurement accuracy. Design/methodology/approach – In the present paper, the measurement principle of the four-sensor dynamic acoustic array tracking system is analyzed, and the system observation model and the conversion relationship between models are established. Subsequently, the optimization algorithm for the four-sensor dynamic acoustic array is deduced, the theoretical optimal arrangement of the four-sensor dynamic acoustic array tracking measurement system is obtained based on the optimal position dilution of precision function (PDOPF) of 2D target, and the static experimental study on sound-source bearing estimation is designed. The theoretical results are compared with the experimental results of the present study. Findings – The measurement accuracy of the four-sensor dynamic acoustic array tracking system is largely dependent on the layout of the acoustic sensor. Theoretical studies and experimental results demonstrated that an optimal PDPOF can be used to analyze the rationality of the layout. It can also serve as an indicator for the layout of the four-sensor dynamic acoustic array tracking system. Originality/value – The PDOPF value is presented as an indicator for the evaluation of the four-sensor dynamic acoustic array systematic observation accuracy based on theoretical analysis. The feasibility of the indicator and the rationality of the sensor layout in practical engineering application are verified through experimental studies on sound-source bearing estimation. The higher the PDOPF value is, the lower the accuracy of the system will be. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to provide a technical description of the sensors and instruments used on NASA's Mars Science Laboratory mission. Design/methodology/approach – Following an introduction, this paper describes the various sensors and instruments used on the mission. The sampling systems, power source and communication technologies are also considered. Findings – This shows that the Mars Science Laboratory is equipped with an array of sophisticated analytical instruments, sensors and cameras which will yield a unique insight into the Martian environment. Originality/value – This paper provides details of the sensors and instruments being deployed on NASA's latest robotic mission to the surface of Mars. [ABSTRACT FROM AUTHOR]

This paper aims at designing an intelligent online tyre pressure monitoring system (TPMS). The objective of this work is to display the tyre pressure of the tyre and also give the indication about the quality. The data corresponding to the tyre pressure is obtained with a high precision MEMS pressure sensor. The output of the MEMS pressure sensor is amplified and transmitted to the processing unit placed on the dash of the vehicle using wireless communication (RF). The processing is carried on using fuzzy logic algorithms on LabVIEW platform. The output pressure is displayed along with the indicator representing the quality. Indicator is green when the tyre pressure is in the desired range specified by the manufacturer. Yellow when the pressure has dropped and need to be inflated. Red indicates tyre pressure is below the safety driving conditions. After testing and validating the entire system using LabVIEW. The entire code is converted to verilog code and dumped on to FPGA chip (Spartan 3E) using FPGA module of LabVIEW with CompactRIO, for implementation of FPGA chip on real time system. The system after implementing on real time system measured actual pressure of tyre online. [ABSTRACT FROM AUTHOR]

The scale of nano-sized objects requires very precise position determination. The state-of-the-art manipulators involve accurate nanometer positioning. This paper presents the design, fabrication process, and testing of a capacitance-based displacement sensor. The nanopositioner application required active sensing area dimensions to be hundreds of micrometers, making it necessary to develop sensor electrodes that are a few micrometers in size. The advantages of the sensor presented are its noninvasive method and very low voltage necessary for signal conditioning. Initial results suggest good linearity and sensitivity of 0.001 \pF/\mu\m, permitting a reliable displacement resolution on the order of 100 nm. [ABSTRACT FROM AUTHOR]

Lightning in all corners of the world is monitored by one or more land- or space-based lightning locating systems (LLSs). The applications that have driven these developments are numerous and varied. This paper describes the history leading to modern LLSs that sense lightning radiation fields at multiple remote sensors, focusing on the interactions between enabling technology, scientific discovery, technical development, and uses of the data. An overview of all widely used detection and location methods is provided, including a general discussion of their relative strengths and weaknesses for various applications. The U.S. National Lightning Detection Network (NLDN) is presented as a case study, since this LLS has been providing real-time lightning information since the early 1980s, and has provided continental-scale (U.S.) information to research and operational users since 1989. This network has also undergone a series of improvements during its >20-year life in response to evolving detection technologies and expanding requirements for applications. Recent analyses of modeled and actual performance of the current NLDN are also summarized. The paper concludes with a view of the short- and long-term requirements for improved lightning measurements that are needed to address some open scientific questions and fill the needs of emerging applications. [ABSTRACT FROM AUTHOR]

Significant to the current and future needs of Homeland Security, Counterdrug and the warfighter support, enhancing the vision capabilities of already established and familiar airframes for expanded mission requirements is preferential to physical remodelling or the design and development of specialized aircraft. The modular design of equipment compatible with existing airframes, for a variety of alternative and novel applications, has many benefits, the most practical being those of reduced cost and time towards implementation. A brief survey is conducted which examines the Lockheed Martin C-130 airframe as a prime candidate for surveillance and reconnaissance remote sensing expansion capabilities. This paper provides a short survey of the Oculus sensor pallet system that has been designed following multiple guidelines to ensure that any specified number of various remote sensing technologies may be simultaneously mounted and deployed with minimal operator effort and without undue concern for the needs of effective mission compliance. West Virginia University (WVU) was tasked with the design and construction of a fully prototyped and integrated two-pallet system to meet the needs of multiple air-based sensor requirements with provisions for expansion and upgrade. The resulting prototyped design is a storable Ro-Ro two-palletized system. Parameters of the Oculus roll-on, roll-off (Ro-Ro) two-pallet system, which deploys equipment directly from the C-130s rear cargo door, is explored and a listing of supported surveillance and reconnaissance missions is provided. [ABSTRACT FROM AUTHOR]

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called ‘aggregators.’ Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments. [ABSTRACT FROM AUTHOR]

Rain-rate retrievals from passive microwave sensors are useful for a number of applications related to weather forecasting. For example, in the United States, such estimates are useful for offshore rainfall systems approaching land and in regions where the Weather Surveillance Radar-1988 Doppler (WSR-88D) network is inadequate. Improvements have been made to the rain-rate retrieval from the Advanced Microwave Sounding Unit (AMSU) on board the National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites (POESs). The new features of the improved rain-rate algorithm include a two-stream correction of the satellite brightness temperatures at 89 and 150 GHz, cloud- and rain-type classification for better retrieval of rain rate, and removal of the two ad hoc thresholds in the ice water path (IWP) and effective diameter (De) retrieval where the scattering signals are very small. In this paper, the new algorithm has been compared to the previous NOAA operational algorithm. In particular, the better utilization of the measurements at and above 150 GHz is shown to produce improved sensitivity to light rainfall associated with winter season storm systems. This improvement is demonstrated through a wintertime case study over southern California during February 2003. [ABSTRACT FROM AUTHOR]

Impulse radio (IR) and especially time-hopping IR (TH-IR) systems have attracted considerable attention since their introduction in the context of ultra wideband (UWB) systems in the early 1990s. Recently, with the U.S. Federal Communications Commission actions allowing for the wide-spread use of UWB radio systems, the interest in these systems has grown further. These systems promise to deliver high data rates in multiple access communication channels with very simple transmitter and receiver designs. The importance of multiuser detection for achieving high data rates with these systems has already been established in several studies. This paper studies several low-complexity multiuser detectors specifically designed for TH-IR radio systems. It is demonstrated that many multiuser detectors developed primarily for direct-sequence code division multiple access (DSCDMA) systems can be used essentially without any change in TH-IR receivers. Further, several novel, low-complexity multiuser detectors that exploit the special signal structure used for transmission by TH-LR systems are developed. These novel detectors are analyzed both theoretically and via simulations. It is shown that a very simple iterative multiuser detector yields performance that is similar to that of a single-user system. [ABSTRACT FROM AUTHOR]

The United States Centers for Disease Control and Prevention considers saliva contact the lead transmission mean of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19). Saliva droplets or aerosols expelled by sneezing, coughing, breathing, and talking may carry this virus. People in close distance may be exposed directly to these droplets or indirectly when touching the droplets that fall on surrounding surfaces and ending up contracting COVID-19 after touching the mucosa tissue of their faces. It is of great interest to quickly and effectively detect the presence of SARS-CoV-2 in an environment, but the existing methods only work in laboratory settings, to the best of our knowledge. However, it may be possible to detect the presence of saliva in the environment and proceed with prevention measures. However, detecting saliva itself has not been documented in the literature. On the other hand, many sensors that detect different organic components in saliva to monitor a person's health and diagnose different diseases, ranging from diabetes to dental health, have been proposed and they may be used to detect the presence of saliva. This paper surveys sensors that detect organic and inorganic components of human saliva. Humidity sensors are also considered in the detection of saliva because a large portion of saliva is water. Moreover, sensors that detect infectious viruses are also included as they may also be embedded into saliva sensors for a confirmation of the presence of the virus. A classification of sensors by their working principles and the substances they detect is presented, including the sensors' specifications, sample size, and sensitivity. Indications of which sensors are portable and suitable for field application are presented. This paper also discusses future research and challenges that must be resolved to realize practical saliva sensors. Such sensors may help minimize the spread of not only COVID-19 but also other infectious diseases. [ABSTRACT FROM AUTHOR]

This paper describes new methods to reach safety targets for sense-and-avoid sensors for unmanned aircraft systems by evaluating integrity and continuity risks. These methods can be used to set sensor requirements. The closest-point-of-approach distance and time to closest point of approach, τ, are used to measure the hazards associated with the intruder aircraft. The contribution to knowledge in this paper is a new method that uses hazard state estimates and estimate error to establish 1) the integrity risk of the sense-and-avoid system not detecting imminent loss of self-separation, and 2) the probability of false alert, the flight-path continuity risk. A sensitivity analysis evaluates the impact on integrity and continuity of sensor noise, range, and sample interval. The methods described in this paper can be used to set potential sense-and-avoid sensor requirements for unmanned aircraft system integration into the National Airspace System. [ABSTRACT FROM AUTHOR]

• Current remote sensing applications in nut crops were reviewed comprehensively. • Available and suitable platforms (UAS, Aircraft, Satellite) and sensors were discussed thoroughly. • Current and anticipated analytic pipelines based on the increasing data size were presented. • Sensor calibration, feature extraction, and data fusion were identified as the most noticeable knowledge gaps in remote sensing applications for nut crops. Due to their high protein content, nuts (almond, walnut, and pistachio) are among the main substitutes for meat, with a growing share of the food basket in the United States. However, the rapidly growing acreage of these crops, new legislations, the necessity of minimizing the environmental footprint, and a cost-effective production demand certain managerial practices based on precision agriculture and remote sensing, which have shown promising results in food production. This paper presents a comprehensive review of remote sensing platforms, sensors, applications, and analytic pipelines with a focus on nut crops, even though the materials are applicable for other specialty crops. In this regard, the paper is divided into five main sections: First, the problems and potential solutions are elaborated in the introduction. Second, the available platforms: satellites, manned aircraft, and UASs are discussed. Then the sensors used for remote sensing, their working principle, and the pros and cons of each are presented. Next, practiced and suggested applications of remote sensing data are reviewed. Finally, data processing and analytics needed to produce and interpret reliable results are highlighted. Key findings are listed as: 1) The acreage of the nut orchards and the purpose of the studies determine the fitting sensor and platform. 2) Although various sensors are available and reported to have promising results in other crops, they have not been used for nut crops. 3) Accurate sensor calibration is crucial for repeatable results as well as temporal and inter-field comparisons. 4) Except for water management, most remote sensing applications are limitedly studied in nut orchards, creating some research opportunities. 5) Finally, increasing data size requires new machine learning techniques and data fusion frameworks to handle all variables and fill the knowledge gap. [ABSTRACT FROM AUTHOR]

DEPFET detectors are silicon (Si) active pixel sensors designed and manufactured in the Max-Planck-Institut semiconductor lab. Their high spatial resolution and high energy resolution in X-rays make them attractive for particle tracking in colliders and for X-ray astronomy. This technology is foreseen for the Wide Field Imager of the International X-ray Observatory currently in study with ESA, NASA, and JAXA. New DEPFET matrixes with 256\,\times\,256 pixels of 75-\mum pitch have been produced, mounted on ceramic boards with dedicated front-end electronics and integrated in a new setup able to acquire large-format images and spectra. Excellent homogeneity has been observed. Energy resolution as low as 127 eV FWHM at 5.9 keV has been obtained including all single events of the matrix back illuminated at -45\,^\circC and read out at a 300-frames/s rate. This paper presents experimental methods and results. [ABSTRACT FROM AUTHOR]

This paper describes a 10 V Josephson Voltage Standard (JVS) direct comparison between the National Institute of Standards and Technology (NIST) and the Instituto Nacional de Metrologia, Normalização e Qualidade Industrial (INMETRO) using automatic data acquisition. The results were in agreement to within 1.1 nV and the mean difference between the two JVSs at 10 V is 0.54 nV with a pooled combined standard uncertainty of 1.48 nV. Considering a recent JVS comparison between NIST and the Bureau International des Poids et Mesures (BIPM), the difference between INMETRO and the BIPM thus was found to be -0.26 nV with a standard uncertainty of 1.76 nV. INMETRO JVS improvements since the 2006 INMETRO-BIPM comparison are also described. [ABSTRACT FROM AUTHOR]

Using multiple, heterogeneous sensors in surveillance systems is desirable, not only to tolerate sensor failures, but also to increase the accuracy of the event detection process and to provide complementary capability under different operating conditions. In the operation of multiple, heterogeneous sensors, we may encounter inconsistent sensor observations. Motivated by the need to make coherent decisions, we propose in this study a decision scheme to determine the right interpretations of sensor outputs when conflict arises. The proposed decision rule considers sensor heterogeneity in a surveillance system, while attempting to minimize the expected misclassification cost. Case studies of the surveillance sensor system in a major U.S. port demonstrate that the proposed decision scheme achieves a better robustness in the presence of sensor failures than the popular k-out-of-n decision fusion rule. [ABSTRACT FROM AUTHOR]

Validation is an important and particularly challenging task for remote sensing of soil moisture. A key issue in the validation of soil moisture products is the disparity in spatial scales between satellite and in situ observations. Conventional measurements of soil moisture are made at a point, whereas satellite sensors provide an integrated area/volume value for a much larger spatial extent. In this paper, four soil moisture networks were developed and used as part of the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) validation program. Each network is located in a different climatic region of the U.S., and provides estimates of the average soil moisture over highly instrumented experimental watersheds and surrounding areas that approximate the size of the AMSR-E footprint. Soil moisture measurements have been made at these validation sites on a continuous basis since 2002, which provided a seven-year period of record for this analysis. The National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) standard soil moisture products were compared to the network observations, along with two alternative soil moisture products developed using the single-channel algorithm (SCA) and the land parameter retrieval model (LPRM). The metric used for validation is the root-mean-square error (rmse) of the soil moisture estimate as compared to the in situ data. The mission requirement for accuracy defined by the space agencies is 0.06 \m^3/\m^3. The statistical results indicate that each algorithm performs differently at each site. Neither the NASA nor the JAXA standard products provide reliable estimates for all the conditions represented by the four watershed sites. The JAXA algorithm performs better than the NASA algorithm under light-vegetation conditions, but the NASA algorithm is more reliable for moderate vegetation. However, both algorithms have a moderate to large bias in all cases. The SCA had the lowest overall rmse with a small bias. The LPRM had a very large overestimation bias and retrieval errors. When site-specific corrections were applied, all algorithms had approximately the same error level and correlation. These results clearly show that there is much room for improvement in the algorithms currently in use by JAXA and NASA. They also illustrate the potential pitfalls in using the products without a careful evaluation. [ABSTRACT FROM AUTHOR]

Detecting mud hazards is a significant challenge to unmanned ground vehicle (UGV) autonomous off-road navigation. A military UGV stuck in a body of mud during a mission may need to be sacrificed or rescued, both unattractive options. The Jet Propulsion Laboratory is currently developing a daytime mud detection capability under the U.S. Army Research Laboratory Robotics Collaborative Technology Alliances program using UGV-mounted sensors. To perform robust mud detection under all conditions, we expect that multiple sensors will be necessary. A passive mud detection solution is desirable to meet future combat system requirements. To characterize the advantages and disadvantages of candidate passive sensors, outdoor data collections have been performed on wet and dry soil using visible, multispectral (including near-infrared), shortwave infrared, midwave infrared, long-wave infrared, polarization, and stereo sensors. In this paper, we examine the cues for mud detection that each of these sensors provide, along with their deficiencies, and we illustrate localizing detected mud in a world model that can used by a UGV to plan safe paths. We mostly limit our examination to mud detection during the daytime under ideal conditions: isolated wet soil surrounded by dry soil during nominal weather, i.e., no precipitation, calm wind, and near-average temperatures. © 2010 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

For many sensor network applications such as military or homeland security, it is essential for users (sinks) to access the sensor network while they are moving. Sink mobility brings new challenges to secure routing in large-scale sensor networks. Previous studies on sink mobility have mainly focused on efficiency and effectiveness of data dissemination without security consideration. Also, studies and experiences have shown that considering security during design time is the best way to provide security for sensor network routing. This paper presents an energy-efficient secure routing and key management for mobile sinks in sensor networks, called SCODEplus. It is a significant extension of our previous study in five aspects: (1) Key management scheme and routing protocol are considered during design time to increase security and efficiency; (2) The network topology is organized in a hexagonal plane which supports more efficiency than previous square-grid topology; (3) The key management scheme can eliminate the impacts of node compromise attacks on links between non-compromised nodes; (4) Sensor node deployment is based on Gaussian distribution which is more realistic than uniform distribution; (5) No GPS or like is required to provide sensor node location information. Our security analysis demonstrates that the proposed scheme can defend against common attacks in sensor networks including node compromise attacks, replay attacks, selective forwarding attacks, sinkhole and wormhole, Sybil attacks, HELLO flood attacks. Both mathematical and simulation-based performance evaluation show that the SCODEplus significantly reduces the communication overhead, energy consumption, packet delivery latency while it always delivers more than 97 percent of packets successfully. [ABSTRACT FROM AUTHOR]

Purpose -- The purpose of this paper is to develop an electronic solution to effectively lock swivelling wheel steering positions to driver-control. Simple and affordable systems are described to assist forklift users in steering their walkie type forklifts or pallet jacks across sloping ground. Design/methodology/approach -- A rolling road was created as an assessment tool and trials with both the test bed and in real situations were conducted to evaluate the new systems. The small swivel detector that was created could be successfully attached to swivelling wheel swivel bearings. Findings -- The new system was successful, robust and was not affected by changeable parameters. The simple systems assisted hand truck operators in steering their forklifts across sloping ground without veering off course. The systems overcame the problems associated with forklifts that steer using two swivelling wheels and meant that less work was required from hand truck operators as their forklifts tended to travel in the desired direction Research limitations/implications -- Experiments demonstrated that calibrating forklift controllers for straight-line balance and optimizing motor-compensation did not solve this problem. Instead, swivelling wheel angle was selected to provide feedback. At the point when veer is first detected, a forklift has already begun to alter course and the job of the correction system is to minimize this drift from the desired course. Practical implications -- The forklifts and pallet jacks often steer by having swivelling wheels but problems with this configuration occur when a forklift is driven along sloping ground because they can swivel in the direction of the slope. Gravity then causes the forklift or pallet jack to start an unwanted turn or "veer" and the vehicle goes in an unintended direction. This situation is exacerbated for vehicles with switch controls, as switches cannot provide fine control to trim and compensate. Originality/value -- Each year in the United States, over 100 employees are killed and 36,000 are seriously injured in accidents involving forklift trucks and pallet carriers. This is the second leading cause of occupational fatalities in "industrial" type workplaces. The research aims to make the use of this type of equipment safer and the systems can be attached to many standard forklifts and pallet jacks. [ABSTRACT FROM AUTHOR]

Frisch-ring CdZnTe detectors have demonstrated both good energy resolution, < 1% FWHM at 662 keV, and good efficiency in detecting gamma rays, highlighting the strong potential of CdZnTe materials for such applications. We are designing a hand-held gamma-ray spectrometer based on Frisch-ring detectors at Brookhaven National Laboratory. It employs an 8 × 8 CdZnTe detector array to achieve a high volume of 19.2 cm³, so greatly improving detection efficiency. By using the front-end application-specific integrated circuits (ASICs) developed at BNL, this spectrometer has a small profile and high energy-resolution. It includes a signal processing circuit, digitization and storage circuits, a high-voltage module, and a universal serial bus (USB) interface. In this paper, we detail the system's structure and report the results of our tests with it. [ABSTRACT FROM AUTHOR]

Abstract: Remote sensing with sensors mounted on satellites or aircrafts is much needed for resource management, environmental monitoring, disaster response, and homeland defense. Remote sensing data considered include those from multispectral, hyperspectral, radar, optical, and infrared sensors. Classification is often one of the major tasks in information processing. For example, we need to identify vegetations, waterways, and man-made structures from remote sensing of earth. The large amount of data available makes remote sensing data uniquely suitable for statistical pattern recognition. This paper will address several issues on statistical pattern recognition that are related to information processing in remote sensing. Though the paper is largely tutorial in nature, some specific issues considered are image models for characterization of contextual information, neural networks for image classification, and the performance measures. Either to supplement the capability of sensors or to effectively utilize the enormous amount of sensor data, many advances in statistical pattern recognition can be very useful in machine recognition of the data. The potentials and opportunities of using statistical pattern recognition in remote sensing are indeed unlimited. [Copyright &y& Elsevier]

Purpose - This paper seeks to consider recent nanosensor developments and the various routes to market through reference to companies which are commercialising these products. Design/methodology/approach - This paper initially discusses nanosensor markets and applications. It then illustrates progress in commercial exploitation by considering a number of nanosensor companies and their products. Findings - This paper shows that the commercialisation of nanosensors is still in its infancy but a range of products is now reaching the market. In addition to probes for atomic force and scanning probe microscopy, which presently comprise the bulk of the market, innovative biosensors, gas and chemical sensors are having a growing impact. Many of the supply companies are US-based with strong links to universities and have frequently raised significant venture finance and subsequent funds from government agencies involved with defence, homeland security and healthcare. Several of the world's large, high-technology companies are also pursuing nanosensor developments. Originality/value - This paper provides an insight into the present-day state of nanosensor commercialisation and gives examples of nanosensor companies and their products. [ABSTRACT FROM AUTHOR]

A pocket radiation detection system has been developed at the Idaho National Engineering and Environmental Laboratory for homeland security applications. It can detect both neutrons and gamma rays instantaneously. This sensor has been designed with an emphasis on compactness, recognizing the widespread need for a radiation detection instrument that could provide both neutron and gamma-ray detection in a single, portable unit. It is very small, extremely sensitive, versatile, and easy to operate. It can detect gamma rays and neutrons in a radiation field as tow as 10 μR/h above the ambient background, which makes it ideal for use in national security applications. The detection system is based on a technique of using a combination of two sensors made of lithium isotopes 6Li and 7Li. It operates on one rechargeable Li-ion battery and is small enough to be put in a pocket or clipped to a belt. In this paper, the detection technique used in developing this prototype sensor as well as its performance will be presented. [ABSTRACT FROM AUTHOR]

The evolution of the submarine and the development of radio communication are interrelated. From the earliest days, the effectiveness of a submarine as a war-fighting vessel was linked to its ability to receive orders via the then new medium of radio. This paper traces the earliest work that linked the two together — particularly from the viewpoint of the antenna as the ship's electronic "ears" — to the present, where work is being done to provide the "silent service" with the communications sensors needed to participate fully in the battle space of the future. [ABSTRACT FROM AUTHOR]

Neutrons generated in Inertial Confinement Fusion (ICF) experiments provide valuable information to interpret the conditions reached in the plasma. The neutron time-of-flight (nToF) technique is well suited for measuring the neutron energy spectrum due to the short time (100 ps) over which neutrons are typically emitted in ICF experiments. By locating detectors 10s of meters from the source, the neutron energy spectrum can be measured to high precision. We present a contextual review of the current state of the art in nToF detectors at ICF facilities in the United States, outlining the physics that can be measured, the detector technologies currently deployed and analysis techniques used. [ABSTRACT FROM AUTHOR]

The paper analyzes the impact of the sensor reading errors on parameters that affect the production costs of a leading US industrial gas supply company. For this purpose, a systematic methodology is applied first to determine the relationship between the system output and input parameters and second to identify the assigned input sensors whose readings need to be improved in a prioritized manner based on the strength of those input-output relationships. The two main criteria used to prioritize these sensors are the decrease in production costs and the decrease in production costs' volatility obtained when the selected sensor's precision is improved. To illustrate the effectiveness of the proposed approach, we first apply it to a simplified version of the real supply network model where the results can be readily validated with the simulated data. Next, we apply and test the proposed approach in the real supply network model with historical data. [ABSTRACT FROM AUTHOR]

Reports that real-time pressure mapping and nip profiling system manufacturer Sensor Products Inc. of New Jersey has received an initial order for three units of its Dynamic Nip (D-Nip) profiling system. Orders received by Sensor from Metso Paper; Features of the process control tool.

Space situational awareness (SSA) is becoming increasingly challenging with the proliferation of resident space objects (RSOs), ranging from CubeSats to mega-constellations. Sensors within the United States Space Surveillance Network are tasked to repeatedly detect, characterize, and track these RSOs to retain custody and estimate their attitude. The majority of these sensors consist of ground-based sensors with a narrow field of view and must be slew at a finite rate from one RSO to another during observations. This results in a complex combinatorial problem that poses a major obstacle to the SSA sensor tasking problem. In this work, we successfully applied deep reinforcement learning (DRL) to overcome the curse of dimensionality and optimally task a ground-based sensor. We trained several DRL agents using proximal policy optimization and population-based training in a simulated SSA environment. The DRL agents outperformed myopic policies in both objective metrics of RSOs' state uncertainties and the number of unique RSOs observed over a 90-min observation window. The agents' robustness to changes in RSO orbital regimes, observation window length, observer's location, and sensor properties are also examined. The robustness of the DRL agents allows them to be applied to any arbitrary locations and scenarios. [ABSTRACT FROM AUTHOR]

Abstract: Automated alignment for the National Ignition Facility (NIF) is accomplished using a large-scale parallel control system that directs 192 laser beams along the 300m optical path. The beams are then focused down to a 50μ spot in the middle of the target chamber. The entire process is completed in less than 50min. The alignment system commands 9000 stepping motors for extremely precise adjustment of mirrors and other optics. 41 control loops per beamline perform parallel processing services running on a LINUX cluster to analyze high-resolution images of the beams and their references. This paper describes the status the NIF automatic alignment system and the challenges encountered as NIF development has transitioned from building the laser, to becoming a research project supporting a 24h, 7 days/week laser facility. NIF is now a continuously operated system where performance monitoring is increasingly more critical for operation, maintenance, and commissioning tasks. Equipment wear and the effects of high energy neutrons from fusion experiments are issues which affect alignment efficiency and accuracy. New sensors needing automatic alignment assistance are common. System modifications to improve efficiency and accuracy are prevalent. Handling these evolving alignment and maintenance needs while minimizing the impact on NIF experiment schedule is expected to be an on-going challenge for the planned 30 year operational life of NIF. [Copyright &y& Elsevier]

The environmental impact of aviation is enormous given the fact that in the US alone there are nearly 6 million flights per year of commercial aircraft. This situation has driven numerous policy and procedural measures to help develop environmentally friendly technologies which are safe and affordable and reduce the environmental impact of aviation. However, many of these technologies require significant initial investment in newer aircraft fleets and modifications to existing regulations which are both long and costly enterprises. We propose to use an anomaly detection method based on Virtual Sensors to help detect overconsumption of fuel in aircraft which relies only on the data recorded during flight of most existing commercial aircraft, thus significantly reducing the cost and complexity of implementing this method. The Virtual Sensors developed here are ensemble-learning regression models for detecting the overconsumption of fuel based on instantaneous measurements of the aircraft state. This approach requires no additional information about standard operating procedures or other encoded domain knowledge. We present experimental results on three data sets and compare five different Virtual Sensors algorithms. The first two data sets are publicly available and consist of a simulated data set from a flight simulator and a real-world turbine disk. We show the ability to detect anomalies with high accuracy on these data sets. These sets contain seeded faults, meaning that they have been deliberately injected into the system. The second data set is from real-world fleet of 84 jet aircraft where we show the ability to detect fuel overconsumption which can have a significant environmental and economic impact. To the best of our knowledge, this is the first study of its kind in the aviation domain. [ABSTRACT FROM AUTHOR]

Abstract: The paper illustrates some marine survey AUVs plus their features and typical configurations, and analyzes their key technologies through classification and analysis, which are currently existed or under development. Their composition can be divided into basic modules and functional modules. Basic modules include central processing system, propeller system, power supply system and navigation system etc. Meanwhile, functional modules refer to auxiliary sensor and survey equipment. As for AUV applied in marine survey, designer should pay more consideration to the running state in high velocity flow and strengthen the control of side thrust. The configurations of marine survey AUVs from companies like Kongsberg in Norway, Hydroid in U.S., Bluefin Robotics in U.S. and Hafmynd in Iceland are analyzed and classified. The research and development process of domestic AUV are also be reviewed. As AUV can collect data with highly efficiency and better quality, it will replace traditional means of surface vessels with towed systems for its portability. Easy use of AUV can significantly reduce fuel consumption of ships, which will be widely used in marine survey in the future as a cost-effective method. [Copyright &y& Elsevier]

Abstract: We adapted and optimized a method to quantify the cellulose, hemicellulose, xylan, arabinan, mannan, galactan contents in lignocellulosic biomass. This method is based on a neutral detergent extraction (NDE) of the interfering biomass components, followed by a sulfuric acid hydrolysis (SAH) of the structural polysaccharides, and a liquid chromatography with charged aerosol detection (LC-CAD) to analyze the released monosaccharides. The first step of this NDE-SAH-LC-CAD method aims at removing all compounds that interfere with the subsequent sulphuric acid hydrolysis or with the subsequent chromatographic quantification of the cellulosic and hemicellulosic monosaccharides. This step includes starch hydrolysis with an analytical thermostable α-amylase followed by an extraction of soluble compounds by a Van Soest neutral detergent solution (NDE). The aim of this paper was to assess the precision of this method when choosing fiber sorghum (Sorghum bicolor (L.) Moench), tall fescue (Festuca arundinacea Schreb.) and fiber hemp (Cannabis sativa L.) as representative lignocellulosic biomass. The cellulose content of fiber sorghum, tall fescue and fiber hemp determined by the NDE-SAH-LC-CAD method were 28.7±1.0, 29.7±1.0 and 43.6±1.2g/100g dry matter, respectively, and their hemicellulose content were 18.6±0.5, 16.5±0.5 and 14.5±0.2g/100g dry matter, respectively. Cellulose, mannan and galactan contents were higher in fiber hemp (dicotyledon) as compared to tall fescue and fiber sorghum (monocotyledons). The xylan, arabinan and total hemicellulose contents were higher in tall fescue and fiber sorghum as compared to fiber hemp. The precision of the NDE-SAH-LC-CAD method was better for polysaccharide concentration levels above 1g/100g dry matter. Galactan analysis offered a lower precision, due to a lower CAD response intensity to galactose as compared to the other monosaccharides. The dispersions of the results (expanded uncertainty) of the NDE-SAH-LC-CAD method were smaller as compared to the Van Soest (VS) method. In addition, the NDE-SAH-LC-CAD method was able to provide additional information on the composition of the hemicellulose (xylan, arabinan, mannan and galactan content) that is not provided by the Van Soest method. The NDE-SAH-LC-CAD method offers also the advantage of a better specificity for hemicellulose and cellulose, as compared to the NREL and Uppsala methods. [Copyright &y& Elsevier]

A number of significant airplane accidents have resulted from windshear encounters during takeoff or landing. In these situations the radar signal received may be affected by a strong ground clutter that may make the conventional windshear detection algorithms implemented on ground-based systems unusable. Typically, the solution to this problem is to employ a clutter rejection filter and then process the filter output to derive weather information. In this study, a parametric bimodal spectral model of the raw radar signal from an airborne Doppler weather radar is proposed. The bimodal shape of the model has been defined as a superposition of clutter and windshear. The model can be used to define a windshear detection algorithm that can also directly estimate the physical weather parameters by using the estimated model parameters without using a clutter rejection pre-filter. Owing to the impossibility of testing a windshear detection system in a realistic environment, a simulated windshear data base has been developed by National Aeronautics and Space Administration (NASA) and Federal Aviation Administration (FAA) during their windshear research programme. The purpose of this study is to define a parametric bimodal spectral model and demonstrate its validity on the NASA-FAA windshear certification data set. [ABSTRACT FROM AUTHOR]