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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]

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]

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 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]

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]

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]

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]

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]

The NASA/NGA Shuttle Radar Topography Mission (SRTM) collected interferometric radar data which has been used by the Jet Propulsion Laboratory to generate a near-global topography data product for latitudes smaller than 60°. One of the primary goals of the mission was to produce a data set that was globally consistent and with quantified errors. To achieve this goal, an extensive global ground campaign was conducted by NGA and NASA to collect ground truth that would allow for the global validation of this unique data set. This paper documents the results of this SRTM validation effort using this global data set. The table shown below summarizes our results (all quantities represent 90 percent errors in meters). [ABSTRACT FROM AUTHOR]

Abstract: NASA has been making statistical measurements of the orbital debris environment for more than a decade using the MIT Lincoln Laboratory Haystack radar. The goal has been to characterize the environment for debris sizes as small as possible. Like all sensors which operate in the presence of noise, the Haystack radar has limited sensitivity. As the returned energy from small targets begins to approach the sensitivity limit of the radar, the probability-of-detection decreases, eventually approaching zero. The slope of the cumulative size distribution of debris begins to flatten out. This paper explores the possibility of extending the cumulative size distribution to smaller sizes by adjusting the distribution for probability-of-detection. [Copyright &y& Elsevier]

This paper describes four different systems that we have developed for capturing various manners of gesture near interactive surfaces. The first is a low-cost scanning laser rangefinder adapted to accurately track the position of bare hands in a plane just above a large projection display. The second is an acoustic system that detects the position of taps on a large, continuous surface (such as a table, wall, or window) by measuring the differential time-of-arrival of the acoustic shock impulse at several discrete locations. The third is a sensate carpet that uses a grid of piezoelectric wire to measure the dynamic location and pressure of footfalls. The fourth is a swept radio frequency (RF) tag reader that measures the height, approximate location, and other properties (orientation or a control variable like pressure) of objects containing passive, magnetically coupled resonant tags, and updates the continuous parameters of all tagged objects at 30 Hz. In addition to discussing the technologies and surveying different approaches, sample applications are given for each system. [ABSTRACT FROM AUTHOR]

Potential NASA optical missions such as the Space Interferometer Mission require actuators for precision positioning to accuracies of the order of nanometers. Commercially available multilayer piezoelectric stack actuators are being considered for driving these precision mirror positioning mechanisms. These mechanisms have potential mission operational requirements that exceed 5 years for one mission life. To test the feasibility of using these commercial actuators for these applications and to determine their reliability and the redundancy requirements, a life test study was undertaken. The nominal actuator requirements for the most critical actuators on the Space Interferometry Mission (SIM) in terms of number of cycles was estimated from the Modulation Optics Mechanism (MOM) and Pathlength control Optics Mechanism (POM) and these requirements were used to define the study. At a nominal drive frequency of 250 Hz, one mission life is calculated to be 40 billion cycles. In this study, a set of commercial PZT stacks configured in a potential flight actuator configuration (pre-stressed to 18 MPa and bonded in flexures) were tested for up to 100 billion cycles. Each test flexure allowed for two sets of primary and redundant stacks to be mechanically connected in series. The tests were controlled using an automated software control and data acquisition system that set up the test parameters and monitored the waveform of the stack electrical current and voltage. The samples were driven between 0 and 20 V at 2000 Hz to accelerate the life test and mimic the voltage amplitude that is expected to be applied to the stacks during operation. During the life test, 10 primary stacks were driven and 10 redundant stacks, mechanically in series with the driven stacks, were open-circuited. The stroke determined from a strain gauge, the temperature and humidity in the chamber, and the temperature of each individual stack were recorded. Other properties of the stacks, including the displacement from a capacitance gap sensor and impedance spectra were measured at specific intervals. The average degradation in the stroke over the life test was found to be small (≪3%) for the primary stacks and ≪4% for the redundant stacks. It was noted that about half of the stroke reduction occurred within the first 10 billion cycles. At the end of the life test, it was found that the actuator could recover about half of the lost stroke by applying a dc voltage of 100 V at room temperature. The data up to 100 billion cycles for these tests and the analysis of the experimental results are presented in this paper. [ABSTRACT FROM PUBLISHER]

The article discusses the importance of mesoscale network for climate and weather forecasting and its direct relation to the development of society. Topics include the history of weather observations and data collection in U.S., utilization of various meteorological instrumentation such as the referencing evapotranspiration and precipitation measurement, and the use of sensors and microprocessing units by mesonet stations.

Presents an introduction for several research papers on modeling uncertainties in geospatial data and analysis published in the August 2004 issue of the "Photogrammetric Engineering and Remote Sensing" periodical. Range of research issues addressed by the articles; Author credits; Implications on the sector.

The northeast U.S. extratropical cyclone of 8-9 February 2013 produced blizzard conditions and more than 0.6-0.9 m (2-3 ft) of snow from Long Island through eastern New England. A surprising aspect of this blizzard was the development and rapid weakening of a snowband to the northwest of the cyclone center with radar ref lectivity factor exceeding 55 dB Z. Because the radar reflectivity within snowbands in winter storms rarely exceeds 40 dB Z, this event warranted further investigation. The high radar reflectivity was due to mixed-phase microphysics in the snowband, characterized by high differential reflectivity ( ZDR > 2 dB) and low correlation coefficient (CC < 0.9), as measured by the operational dual-polarization radar in Upton, New York (KOKX). Consistent with these radar observations, heavy snow and ice pellets (both sleet and graupel) were observed. Later, as the reflectivity decreased to less than 40 dB Z, surface observations indicated a transition to primarily high-intensity dry snow, consistent with lower-tropospheric cold advection. Therefore, the rapid decrease of the 50+ dB Z reflectivity resulted from the transition from higher-density, mixed-phase precipitation to lower-density, dry-snow crystals and aggregates. This case study indicates the value that dual-polarization radar can have in an operational forecast environment for determining the variability of frozen precipitation (e.g., ice pellets, dry snow aggregates) on relatively small spatial scales. [ABSTRACT FROM AUTHOR]

This article presents an interview with Eric Stern, a Yale University graduate student, about a new nanowire design for an immunodetection device which resulted from the modification of a conventional silicon-based approach. When asked about the original goal of the project, Stern said the goal was to develop a general sensor that could detect chemical and biological agents and be worn by every soldier.

A methodology for using a calibrated filter radiometer to measure and monitor the spectral radiance of calibration sources is described. An example is presented using the NIST calibration sphere source that is used to support the NASA Earth Observing remote-sensing program. [ABSTRACT FROM AUTHOR]

A new approach to extracting sea surface wind speed from high-frequency radar Doppler spectra is presented. Based on certain appropriate approximations associated with the Doppler region close to the first-order (Bragg) peaks, the second-order radar cross section equation is differentiated. Once Doppler shifts due to ocean currents are removed from the data, an expression that relates the wind speed to the frequency position of the second-order peak is derived. The method is applied to simulated noisy data as well as to field data obtained from a Seasonde (a product of CODAR Oceans Sensors) in Breezy Point, NY. In the latter case, the retrieved wind speeds are then compared to ground truth data measured by an anemometer from a National Oceanic and Atmospheric Administration weather station located in the vicinity of the illuminated patch of ocean. Subject to certain constraints as detailed in the manuscript, the algorithm shows significant promise. [ABSTRACT FROM AUTHOR]

A data fusion-based, multisensory detection system, called “Volume Sensor”, was developed under the Advanced Damage Countermeasures (ADC) portion of the US Navy's Future Naval Capabilities program (FNC) to meet reduced manning goals. A diverse group of sensing modalities was chosen to provide an automated damage control monitoring capability that could be constructed at a relatively low cost and also easily integrated into existing ship infrastructure. Volume Sensor employs an efficient, scalable, and adaptable design framework that can serve as a template for heterogeneous sensor network integration for situational awareness. In the development of Volume Sensor, a number of challenges were addressed and met with solutions that are applicable to heterogeneous sensor networks of any type. These solutions include: 1) a uniform, but general format for encapsulating sensor data, 2) a communications protocol for the transfer of sensor data and command and control of networked sensor systems, 3) the development of event specific data fusion algorithms, and 4) the design and implementation of modular and scalable system architecture. In full-scale testing on a shipboard environment, two prototype Volume Sensor systems demonstrated the capability to provide highly accurate and timely situational awareness regarding damage control events while simultaneously imparting a negligible footprint on the ship's 100 Mbps Ethernet network and maintaining smooth and reliable operation in a real-time fashion. [ABSTRACT FROM AUTHOR]

The article reports on the study conducted by Radu Stoleru of Texas A&M University and John A. Stankovic and Sang H. Son of the University of Virginia on node localization in wireless sensor networks and the potential of localization protocol composability in the U.S. There are several wireless sensor network (WSN) systems are developed for several domains including military surveillance, environmental monitoring, habitat monitoring and structural monitoring. When researchers studied how one can effectively locate sensor nodes at low cost, they failed because despite the myriads of schemes available in the market, no robust localization system has potential to provide the solution needed. Presented are the details of the research.

Transmit beampattern design is a critically important task in many fields including defense and homeland security as well as biomedical applications. Flexible transmit beampattern designs can be achieved by exploiting the waveform diversity offered by an array of sensors that transmit probing signals chosen at will. Unlike a standard phased-array, which transmits scaled versions of a single waveform, a waveform diversity-based system offers the flexibility of choosing how the different probing signals are correlated with one another. Recently proposed techniques for waveform diversity-based transmit beampattern design have focused on the optimization of the covariance matrix R of the waveforms, as optimizing a performance metric directly with respect to the waveform matrix is a more complicated operation. Given an R, obtained in a previous optimization stage or simply pre-specified, the problem becomes that of determining a signal waveform matrix X whose covariance matrix is equal or close to R, and which also satisfies some practically motivated constraints (such as constant-modulus or low peak-to-average-power ratio constraints). We propose a cyclic optimization algorithm for the synthesis of such an X, which (approximately) realizes a given optimal covariance matrix R under various practical constraints. A numerical example is presented to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The design and performance of a shipboard-integrated system for underway skin and bulk temperature is presented. The system consists of the Calibrated Infrared In situ Measurement System (CIRIMS) and through-hull temperature sensors. The CIRIMS is an autonomous shipboard radiometer system that measures the sea surface skin temperature Tskin for validation of satellite-derived sea surface temperature products. General design considerations for shipboard radiometer systems are discussed and the philosophy behind the CIRIMS design is presented. Unique features of the design include a constant temperature housing to stabilize instrument drift, a two-point dynamic calibration procedure, separate sky- and sea-viewing radiometers for simultaneous measurements, and the ability to use an infrared transparent window for environmental protection. Laboratory testing and field deployments are used to establish an estimated error budget, which includes instrumentation and environmental uncertainties. The combination of this testing and field comparison to the Marine-Atmosphere Emitted Radiance Interferometer (M-AERI) and Infrared SST Autonomous Radiometer (ISAR) instruments indicates that the CIRIMS meets the design goal of ±0.10°C accuracy. Temperature and pressure sensors were installed in custom-designed through-hull ports on the NOAA research vessel (R/V) Ronald H. Brown and the University of Washington R/V Thomas G. Thompson to complement the CIRIMS measurements. The ports allow sensors to be installed while the ship is in water and can accommodate a variety of sensors. The combined system provides the ability to measure near-surface temperature profiles from the skin to a depth of 5 m while underway. [ABSTRACT FROM AUTHOR]

The development of the National Lightning Detection Network (NLDN) can be traced from the initial funding by the Electric Power Research Institute in June 1983. This support, when coupled with a small National Science Foundation-sponsored research program at the State University of New York at Albany, would lead in just six years to the coverage of 48 states by a network of lightning detectors providing the location and physical characteristics of nearly all cloud-to-ground lightning flashes in the continental United States. The generous sharing of data from existing federal lightning detection networks provided one-third of this national coverage. The measured lightning characteristics included stroke location to an accuracy of roughly 2 km, polarity and peak current estimates, and flash multiplicity or number of strokes within the flash. The development of satellite communications during this period ensured the receipt of data and the transmission of flash characteristics to consumers in the university, government, and private sectors. The history of the NLDN development is a story driven by technology with its roots in the 1970s. The future of lightning detection is embodied within the current satellite plans for a Geostationary Lightning Mapper to observe total lightning in the Western Hemisphere as part of the Geostationary Operational Environmental Satellite-R (GOESR) program, with launch dates as early as 2014. [ABSTRACT FROM AUTHOR]

Electric-field measurements made in and near clouds during two airborne field programs are presented. Aircraft equipped with multiple electric-field mills and cloud physics sensors were flown near active convection and into thunderstorm anvil and debris clouds. The magnitude of the electric field was measured as a function of position with respect to the cloud edge to provide an observational basis for modifications to the lightning launch commit criteria (LLCC) used by the U.S. space program. These LLCC are used to reduce the risk that an ascending launch vehicle will trigger a lightning strike that could cause the loss of the mission or vehicle. Even with fields of tens of kV m-1 inside electrically active convective clouds, the fields external to these clouds decay to less than 3 kV m-1 within 15 km of cloud edge. Fields that exceed 3 kV m-1 were not found external to anvil and debris clouds. [ABSTRACT FROM AUTHOR]

The article focuses on the application of aviation weather products safety for observations of meteorological satellites based in the U.S. These satellites include the turbulence, convective storms, and volcanic ash that carried out within national aviation forecasting systems. It is stated that the fundamental objective of the Advanced Satellite Aviation-Weather Products (ASAP) program is to support the existing Federal Aviation Administration (FAA) weather Product Development Teams. These satellites can play an important role in validating current weather products with researchers gaining experience in the use of advanced sensors.

To assess the spatial structures and temporal evolutions of distinct physical processes on the West Florida Shelf, patterns of ocean current variability are extracted from a joint HF radar and ADCP dataset acquired from August to September 2003 using Self-Organizing Map (SOM) analyses. Three separate ocean–atmosphere frequency bands are considered: semidiurnal, diurnal, and subtidal. The currents in the semidiurnal band are relatively homogeneous in space, barotropic, clockwise polarized, and have a neap-spring modulation consistent with semidiurnal tides. The currents in the diurnal band are less homogeneous, more baroclinic, and clockwise polarized, consistent with a combination of diurnal tides and near-inertial oscillations. The currents in the subtidal frequency band are stronger and with more complex patterns consistent with wind and buoyancy forcing. The SOM is shown to be a useful technique for extracting ocean current patterns with dynamically distinctive spatial and temporal structures sampled by HF radar and supporting in situ measurements. [ABSTRACT FROM AUTHOR]

Fingerprint friction ridge details are generally described in a hierarchical order at three different levels, namely, Level 1 (pattern), Level 2 (minutia points), and Level 3 (pores and ridge contours). Although latent print examiners frequently take advantage of Level 3 features to assist in identification, Automated Fingerprint Identification Systems (AFIS) currently rely only on Level 1 and Level 2 features. In fact, the Federal Bureau of Investigation's (FBI) standard of fingerprint resolution for AFIS is 500 pixels per inch (ppi), which is inadequate for capturing Level 3 features, such as pores. With the advances in fingerprint sensing technology, many sensors are now equipped with dual resolution (500 ppi/1,000 ppi) scanning capability. However, increasing the scan resolution alone does not necessarily provide any performance improvement in fingerprint matching, unless an extended feature set is utilized. As a result, a systematic study to determine how much performance gain one can achieve by introducing Level 3 features in AFIS is highly desired. We propose a hierarchical matching system that utilizes features at all the three levels extracted from 1,000 ppi fingerprint scans. Level 3 features, including pores and ridge contours, are automatically extracted using Gabor filters and wavelet transform and are locally matched using the Iterative Closest Point (ICP) algorithm. Our experiments show that Level 3 features carry significant discriminatory information. There is a relative reduction of 20 percent in the equal error rate (EER) of the matching system when Level 3 features are employed in combination with Level 1 and 2 features. This significant performance gain is consistently observed across various quality fingerprint images. [ABSTRACT FROM AUTHOR]

Although previous climatologies over central Arizona show a summer diurnal precipitation cycle, on any given day precipitation may differ dramatically from this climatology. The purpose of this study is to investigate the intraseasonal variability of diurnal storm development over Arizona and explore the relationship to the synoptic-scale flow and Phoenix soundings during the 1997 and 1999 North American monsoons. Radar reflectivity mosaics constructed from Phoenix and Flagstaff Weather Surveillance Radar-1988 Doppler reflectivity data reveal six repeated storm development patterns or regimes. The diurnal evolution of each regime is illustrated by computing frequency maps of 25 dBZ and greater reflectivity during 3-h periods. These regimes are named to reflect their regional and temporal characteristics: dry regime, eastern mountain regime, central-eastern mountain regime, central-eastern mountain and Sonoran-isolated regime, central-eastern mountain and Sonoran regime, and nondiurnal regime. Composites constructed from the NCEP–NCAR 40-Year Reanalysis Project data show that regime occurrence is related to the north–south location of the 500-hPa geopotential height ridge axis of the Bermuda high and the east–west location of the 500-hPa monsoon boundary, a boundary between dry air to the west and moist air to the east. Consequently, precipitable water from the 1200 UTC Phoenix soundings is the best parameter for discriminating the six regimes. [ABSTRACT FROM AUTHOR]

A high-resolution radar data assimilation system is presented for high-resolution numerical weather prediction models. The system is under development at the Naval Research Laboratory for the Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System. A variational approach is used to retrieve three-dimensional dynamical fields of atmospheric conditions from multiple-Doppler radar observations of radial velocity within a limited area. The methodology is described along with a preliminary evaluation of the impact of assimilated radar data on model forecasts using a case study of a squall line that occurred along the east coast of the United States on 9 May 2003. Results from the experiments show a significant impact from the assimilated radar radial velocity data on the model forecast of not just dynamical but also hydrological fields at all model levels for the duration of the storm. A verification system has also been developed to assess the radar data assimilation impact, and the results show improvements in the three-dimensional wind forecasts but relatively small changes in the prediction of storm locations. This study highlights the need to develop a continuous radar data assimilation system to maximize the impact of the data. [ABSTRACT FROM AUTHOR]

Different ways to simultaneously control event sensing reliability and device utilization in a beacon-enabled IEEE 802.15.4 sensor cluster are investigated. Activity management is achieved through probabilistic control of the duration of active and inactive (i.e., service and sleep) periods. The probabilistic control parameters are derived as functions of the required event sensing reliability, device utilization, medium access control and physical layer parameters, and network size. [ABSTRACT FROM AUTHOR]

Describes the sensors developed at the University of Texas at Austin Center for Electromechanics to monitor speed, sense rotor position and detect fault condition. Features of the sensors; Performance requirements for the sensor; Information on current viewing resistor.

The second part of a history of the use of storm surveillance radars by operational military and civil weather services in the United States is presented. This part describes the genesis and evolution of two operational Doppler weather radars, the Next-Generation Weather Radar and Terminal Doppler Weather Radar. [ABSTRACT FROM AUTHOR]