Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2013-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

PubMed

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications.

PubMed

Kiselev, Ilia; Sysoev, Victor; Kaikov, Igor; Koronczi, Ilona; Adil Akai Tegin, Ruslan; Smanalieva, Jamila; Sommer, Martin; Ilicali, Coskan; Hauptmannl, Michael

2018-02-11

The paper deals with a functional instability of electronic nose (e-nose) units which significantly limits their real-life applications. Here we demonstrate how to approach this issue with example of an e-nose based on a metal oxide sensor array developed at the Karlsruhe Institute of Technology (Germany). We consider the instability of e-nose operation at different time scales ranging from minutes to many years. To test the e-nose we employ open-air and headspace sampling of analyte odors. The multivariate recognition algorithm to process the multisensor array signals is based on the linear discriminant analysis method. Accounting for the received results, we argue that the stability of device operation is mostly affected by accidental changes in the ambient air composition. To overcome instabilities, we introduce the add-training procedure which is found to successfully manage both the temporal changes of ambient and the drift of multisensor array properties, even long-term. The method can be easily implemented in practical applications of e-noses and improve prospects for device marketing.

On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications

PubMed Central

Kaikov, Igor; Koronczi, Ilona; Adil Akai Tegin, Ruslan; Smanalieva, Jamila; Sommer, Martin; Ilicali, Coskan; Hauptmannl, Michael

2018-01-01

The paper deals with a functional instability of electronic nose (e-nose) units which significantly limits their real-life applications. Here we demonstrate how to approach this issue with example of an e-nose based on a metal oxide sensor array developed at the Karlsruhe Institute of Technology (Germany). We consider the instability of e-nose operation at different time scales ranging from minutes to many years. To test the e-nose we employ open-air and headspace sampling of analyte odors. The multivariate recognition algorithm to process the multisensor array signals is based on the linear discriminant analysis method. Accounting for the received results, we argue that the stability of device operation is mostly affected by accidental changes in the ambient air composition. To overcome instabilities, we introduce the add-training procedure which is found to successfully manage both the temporal changes of ambient and the drift of multisensor array properties, even long-term. The method can be easily implemented in practical applications of e-noses and improve prospects for device marketing. PMID:29439468

Adaptive and mobile ground sensor array.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holzrichter, Michael Warren; O'Rourke, William T.; Zenner, Jennifer

The goal of this LDRD was to demonstrate the use of robotic vehicles for deploying and autonomously reconfiguring seismic and acoustic sensor arrays with high (centimeter) accuracy to obtain enhancement of our capability to locate and characterize remote targets. The capability to accurately place sensors and then retrieve and reconfigure them allows sensors to be placed in phased arrays in an initial monitoring configuration and then to be reconfigured in an array tuned to the specific frequencies and directions of the selected target. This report reviews the findings and accomplishments achieved during this three-year project. This project successfully demonstrated autonomousmore » deployment and retrieval of a payload package with an accuracy of a few centimeters using differential global positioning system (GPS) signals. It developed an autonomous, multisensor, temporally aligned, radio-frequency communication and signal processing capability, and an array optimization algorithm, which was implemented on a digital signal processor (DSP). Additionally, the project converted the existing single-threaded, monolithic robotic vehicle control code into a multi-threaded, modular control architecture that enhances the reuse of control code in future projects.« less

HALO: a reconfigurable image enhancement and multisensor fusion system

NASA Astrophysics Data System (ADS)

Wu, F.; Hickman, D. L.; Parker, Steve J.

2014-06-01

Contemporary high definition (HD) cameras and affordable infrared (IR) imagers are set to dramatically improve the effectiveness of security, surveillance and military vision systems. However, the quality of imagery is often compromised by camera shake, or poor scene visibility due to inadequate illumination or bad atmospheric conditions. A versatile vision processing system called HALO™ is presented that can address these issues, by providing flexible image processing functionality on a low size, weight and power (SWaP) platform. Example processing functions include video distortion correction, stabilisation, multi-sensor fusion and image contrast enhancement (ICE). The system is based around an all-programmable system-on-a-chip (SoC), which combines the computational power of a field-programmable gate array (FPGA) with the flexibility of a CPU. The FPGA accelerates computationally intensive real-time processes, whereas the CPU provides management and decision making functions that can automatically reconfigure the platform based on user input and scene content. These capabilities enable a HALO™ equipped reconnaissance or surveillance system to operate in poor visibility, providing potentially critical operational advantages in visually complex and challenging usage scenarios. The choice of an FPGA based SoC is discussed, and the HALO™ architecture and its implementation are described. The capabilities of image distortion correction, stabilisation, fusion and ICE are illustrated using laboratory and trials data.

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

PubMed Central

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-01-01

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. PMID:26007744

Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2015-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be

ArrayBridge: Interweaving declarative array processing with high-performance computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xing, Haoyuan; Floratos, Sofoklis; Blanas, Spyros

Scientists are increasingly turning to datacenter-scale computers to produce and analyze massive arrays. Despite decades of database research that extols the virtues of declarative query processing, scientists still write, debug and parallelize imperative HPC kernels even for the most mundane queries. This impedance mismatch has been partly attributed to the cumbersome data loading process; in response, the database community has proposed in situ mechanisms to access data in scientific file formats. Scientists, however, desire more than a passive access method that reads arrays from files. This paper describes ArrayBridge, a bi-directional array view mechanism for scientific file formats, that aimsmore » to make declarative array manipulations interoperable with imperative file-centric analyses. Our prototype implementation of ArrayBridge uses HDF5 as the underlying array storage library and seamlessly integrates into the SciDB open-source array database system. In addition to fast querying over external array objects, ArrayBridge produces arrays in the HDF5 file format just as easily as it can read from it. ArrayBridge also supports time travel queries from imperative kernels through the unmodified HDF5 API, and automatically deduplicates between array versions for space efficiency. Our extensive performance evaluation in NERSC, a large-scale scientific computing facility, shows that ArrayBridge exhibits statistically indistinguishable performance and I/O scalability to the native SciDB storage engine.« less

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems

PubMed Central

Park, Kyeonghwan; Kim, Seung Mok; Eom, Won-Jin; Kim, Jae Joon

2017-01-01

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors. PMID:28368355

A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems.

PubMed

Park, Kyeonghwan; Kim, Seung Mok; Eom, Won-Jin; Kim, Jae Joon

2017-04-03

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors.

Multi-sensor analysis of urban ecosystems

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei

2004-01-01

This study examines the synthesis of multiple space-based sensors to characterize the urban environment Single scene data (e.g., ASTER visible and near-IR surface reflectance, and land surface temperature data), multi-temporal data (e.g., one year of 16-day MODIS and AVHRR vegetation index data), and DMSP-OLS nighttime light data acquired in the early 1990s and 2000 were evaluated for urban ecosystem analysis. The advantages of a multi-sensor approach for the analysis of urban ecosystem processes are discussed.

Portable nuclear material detector and process

DOEpatents

Hofstetter, Kenneth J [Aiken, SC; Fulghum, Charles K [Aiken, SC; Harpring, Lawrence J [North Augusta, SC; Huffman, Russell K [Augusta, GA; Varble, Donald L [Evans, GA

2008-04-01

A portable, hand held, multi-sensor radiation detector is disclosed. The detection apparatus has a plurality of spaced sensor locations which are contained within a flexible housing. The detection apparatus, when suspended from an elevation, will readily assume a substantially straight, vertical orientation and may be used to monitor radiation levels from shipping containers. The flexible detection array can also assume a variety of other orientations to facilitate any unique container shapes or to conform to various physical requirements with respect to deployment of the detection array. The output of each sensor within the array is processed by at least one CPU which provides information in a usable form to a user interface. The user interface is used to provide the power requirements and operating instructions to the operational components within the detection array.

General software design for multisensor data fusion

NASA Astrophysics Data System (ADS)

Zhang, Junliang; Zhao, Yuming

1999-03-01

In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programing and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.

A Passive Wireless Multi-Sensor SAW Technology Device and System Perspectives

PubMed Central

Malocha, Donald C.; Gallagher, Mark; Fisher, Brian; Humphries, James; Gallagher, Daniel; Kozlovski, Nikolai

2013-01-01

This paper will discuss a SAW passive, wireless multi-sensor system under development by our group for the past several years. The device focus is on orthogonal frequency coded (OFC) SAW sensors, which use both frequency diversity and pulse position reflectors to encode the device ID and will be briefly contrasted to other embodiments. A synchronous correlator transceiver is used for the hardware and post processing and correlation techniques of the received signal to extract the sensor information will be presented. Critical device and system parameters addressed include encoding, operational range, SAW device parameters, post-processing, and antenna-SAW device integration. A fully developed 915 MHz OFC SAW multi-sensor system is used to show experimental results. The system is based on a software radio approach that provides great flexibility for future enhancements and diverse sensor applications. Several different sensor types using the OFC SAW platform are shown. PMID:23666124

Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.

PubMed

Gao, Lei; Bourke, A K; Nelson, John

2014-06-01

Physical activity has a positive impact on people's well-being and it had been shown to decrease the occurrence of chronic diseases in the older adult population. To date, a substantial amount of research studies exist, which focus on activity recognition using inertial sensors. Many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers to improve the overall recognition accuracy. In addition, the implementation of the advanced feature extraction algorithms and the complex classifiers exceed the computing ability of most current wearable sensor platforms. This paper proposes a method to adopt multiple sensors on distributed body locations to overcome this problem. The objective of the proposed system is to achieve higher recognition accuracy with "light-weight" signal processing algorithms, which run on a distributed computing based sensor system comprised of computationally efficient nodes. For analysing and evaluating the multi-sensor system, eight subjects were recruited to perform eight normal scripted activities in different life scenarios, each repeated three times. Thus a total of 192 activities were recorded resulting in 864 separate annotated activity states. The methods for designing such a multi-sensor system required consideration of the following: signal pre-processing algorithms, sampling rate, feature selection and classifier selection. Each has been investigated and the most appropriate approach is selected to achieve a trade-off between recognition accuracy and computing execution time. A comparison of six different systems, which employ single or multiple sensors, is presented. The experimental results illustrate that the proposed multi-sensor system can achieve an overall recognition accuracy of 96.4% by adopting the mean and variance features, using the Decision Tree classifier. The results demonstrate that elaborate classifiers and feature sets are not required to achieve high

Multisensor multiresolution data fusion for improvement in classification

NASA Astrophysics Data System (ADS)

Rubeena, V.; Tiwari, K. C.

2016-04-01

The rapid advancements in technology have facilitated easy availability of multisensor and multiresolution remote sensing data. Multisensor, multiresolution data contain complementary information and fusion of such data may result in application dependent significant information which may otherwise remain trapped within. The present work aims at improving classification by fusing features of coarse resolution hyperspectral (1 m) LWIR and fine resolution (20 cm) RGB data. The classification map comprises of eight classes. The class names are Road, Trees, Red Roof, Grey Roof, Concrete Roof, Vegetation, bare Soil and Unclassified. The processing methodology for hyperspectral LWIR data comprises of dimensionality reduction, resampling of data by interpolation technique for registering the two images at same spatial resolution, extraction of the spatial features to improve classification accuracy. In the case of fine resolution RGB data, the vegetation index is computed for classifying the vegetation class and the morphological building index is calculated for buildings. In order to extract the textural features, occurrence and co-occurence statistics is considered and the features will be extracted from all the three bands of RGB data. After extracting the features, Support Vector Machine (SVMs) has been used for training and classification. To increase the classification accuracy, post processing steps like removal of any spurious noise such as salt and pepper noise is done which is followed by filtering process by majority voting within the objects for better object classification.

Chemometric analysis of multisensor hyperspectral images of precipitated atmospheric particulate matter.

PubMed

Ofner, Johannes; Kamilli, Katharina A; Eitenberger, Elisabeth; Friedbacher, Gernot; Lendl, Bernhard; Held, Andreas; Lohninger, Hans

2015-09-15

The chemometric analysis of multisensor hyperspectral data allows a comprehensive image-based analysis of precipitated atmospheric particles. Atmospheric particulate matter was precipitated on aluminum foils and analyzed by Raman microspectroscopy and subsequently by electron microscopy and energy dispersive X-ray spectroscopy. All obtained images were of the same spot of an area of 100 × 100 μm(2). The two hyperspectral data sets and the high-resolution scanning electron microscope images were fused into a combined multisensor hyperspectral data set. This multisensor data cube was analyzed using principal component analysis, hierarchical cluster analysis, k-means clustering, and vertex component analysis. The detailed chemometric analysis of the multisensor data allowed an extensive chemical interpretation of the precipitated particles, and their structure and composition led to a comprehensive understanding of atmospheric particulate matter.

Joint FACET: the Canada-Netherlands initiative to study multisensor data fusion systems

NASA Astrophysics Data System (ADS)

Bosse, Eloi; Theil, Arne; Roy, Jean; Huizing, Albert G.; van Aartsen, Simon

1998-09-01

This paper presents the progress of a collaborative effort between Canada and The Netherlands in analyzing multi-sensor data fusion systems, e.g. for potential application to their respective frigates. In view of the overlapping interest in studying and comparing applicability and performance and advanced state-of-the-art Multi-Sensor Data FUsion (MSDF) techniques, the two research establishments involved have decided to join their efforts in the development of MSDF testbeds. This resulted in the so-called Joint-FACET, a highly modular and flexible series of applications that is capable of processing both real and synthetic input data. Joint-FACET allows the user to create and edit test scenarios with multiple ships, sensor and targets, generate realistic sensor outputs, and to process these outputs with a variety of MSDF algorithms. These MSDF algorithms can also be tested using typical experimental data collected during live military exercises.

Multisensor benchmark data for riot control

NASA Astrophysics Data System (ADS)

Jäger, Uwe; Höpken, Marc; Dürr, Bernhard; Metzler, Jürgen; Willersinn, Dieter

2008-10-01

Quick and precise response is essential for riot squads when coping with escalating violence in crowds. Often it is just a single person, known as the leader of the gang, who instigates other people and thus is responsible of excesses. Putting this single person out of action in most cases leads to a de-escalating situation. Fostering de-escalations is one of the main tasks of crowd and riot control. To do so, extensive situation awareness is mandatory for the squads and can be promoted by technical means such as video surveillance using sensor networks. To develop software tools for situation awareness appropriate input data with well-known quality is needed. Furthermore, the developer must be able to measure algorithm performance and ongoing improvements. Last but not least, after algorithm development has finished and marketing aspects emerge, meeting of specifications must be proved. This paper describes a multisensor benchmark which exactly serves this purpose. We first define the underlying algorithm task. Then we explain details about data acquisition and sensor setup and finally we give some insight into quality measures of multisensor data. Currently, the multisensor benchmark described in this paper is applied to the development of basic algorithms for situational awareness, e.g. tracking of individuals in a crowd.

Improved blood glucose estimation through multi-sensor fusion.

PubMed

Xiong, Feiyu; Hipszer, Brian R; Joseph, Jeffrey; Kam, Moshe

2011-01-01

Continuous glucose monitoring systems are an integral component of diabetes management. Efforts to improve the accuracy and robustness of these systems are at the forefront of diabetes research. Towards this goal, a multi-sensor approach was evaluated in hospitalized patients. In this paper, we report on a multi-sensor fusion algorithm to combine glucose sensor measurements in a retrospective fashion. The results demonstrate the algorithm's ability to improve the accuracy and robustness of the blood glucose estimation with current glucose sensor technology.

An SOI CMOS-Based Multi-Sensor MEMS Chip for Fluidic Applications.

PubMed

Mansoor, Mohtashim; Haneef, Ibraheem; Akhtar, Suhail; Rafiq, Muhammad Aftab; De Luca, Andrea; Ali, Syed Zeeshan; Udrea, Florin

2016-11-04

An SOI CMOS multi-sensor MEMS chip, which can simultaneously measure temperature, pressure and flow rate, has been reported. The multi-sensor chip has been designed keeping in view the requirements of researchers interested in experimental fluid dynamics. The chip contains ten thermodiodes (temperature sensors), a piezoresistive-type pressure sensor and nine hot film-based flow rate sensors fabricated within the oxide layer of the SOI wafers. The silicon dioxide layers with embedded sensors are relieved from the substrate as membranes with the help of a single DRIE step after chip fabrication from a commercial CMOS foundry. Very dense sensor packing per unit area of the chip has been enabled by using technologies/processes like SOI, CMOS and DRIE. Independent apparatuses were used for the characterization of each sensor. With a drive current of 10 µA-0.1 µA, the thermodiodes exhibited sensitivities of 1.41 mV/°C-1.79 mV/°C in the range 20-300 °C. The sensitivity of the pressure sensor was 0.0686 mV/(V excit kPa) with a non-linearity of 0.25% between 0 and 69 kPa above ambient pressure. Packaged in a micro-channel, the flow rate sensor has a linearized sensitivity of 17.3 mV/(L/min) -0.1 in the tested range of 0-4.7 L/min. The multi-sensor chip can be used for simultaneous measurement of fluid pressure, temperature and flow rate in fluidic experiments and aerospace/automotive/biomedical/process industries.

Multi-sensor Navigation System Design

DOT National Transportation Integrated Search

1971-03-01

This report treats the design of naviggation systems that collect data from two or more on-board measurement subsystems and precess this data in an on-board computer. Such systems are called Multi-sensor Navigation Systems. : The design begins with t...

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

PubMed Central

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-01-01

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety.

PubMed

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-06-09

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

Overseas testing of a multisensor landmine detection system: results and lessons learned

NASA Astrophysics Data System (ADS)

Keranen, Joe G.; Topolosky, Zeke

2009-05-01

The Nemesis detection system has been developed to provide an efficient and reliable unmanned, multi-sensor, groundbased platform to detect and mark landmines. The detection system consists of two detection sensor arrays: a Ground Penetrating Synthetic Aperture Radar (GPSAR) developed by Planning Systems, Inc. (PSI) and an electromagnetic induction (EMI) sensor array developed by Minelab Electronics, PTY. Limited. Under direction of the Night Vision and Electronic Sensors Directorate (NVESD), overseas testing was performed at Kampong Chhnang Test Center (KCTC), Cambodia, from May 12-30, 2008. Test objectives included: evaluation of detection performance, demonstration of real-time visualization and alarm generation, and evaluation of system operational efficiency. Testing was performed on five sensor test lanes, each consisting of a unique soil mixture and three off-road lanes which include curves, overgrowth, potholes, and non-uniform lane geometry. In this paper, we outline the test objectives, procedures, results, and lessons learned from overseas testing. We also describe the current state of the system, and plans for future enhancements and modifications including clutter rejection and feature-level fusion.

A multi-sensor scenario for coastal surveillance

NASA Astrophysics Data System (ADS)

van den Broek, A. C.; van den Broek, S. P.; van den Heuvel, J. C.; Schwering, P. B. W.; van Heijningen, A. W. P.

2007-10-01

Maritime borders and coastal zones are susceptible to threats such as drug trafficking, piracy, undermining economical activities. At TNO Defence, Security and Safety various studies aim at improving situational awareness in a coastal zone. In this study we focus on multi-sensor surveillance of the coastal environment. We present a study on improving classification results for small sea surface targets using an advanced sensor suite and a scenario in which a small boat is approaching the coast. A next generation sensor suite mounted on a tower has been defined consisting of a maritime surveillance and tracking radar system, capable of producing range profiles and ISAR imagery of ships, an advanced infrared camera and a laser range profiler. For this suite we have developed a multi-sensor classification procedure, which is used to evaluate the capabilities for recognizing and identifying non-cooperative ships in coastal waters. We have found that the different sensors give complementary information. Each sensor has its own specific distance range in which it contributes most. A multi-sensor approach reduces the number of misclassifications and reliable classification results are obtained earlier compared to a single sensor approach.

Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

PubMed

Jin, Xue-Bo; Sun, Shuli; Wei, Hong; Yang, Feng-Bao

2018-04-11

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.

ALMA Array Operations Group process overview

NASA Astrophysics Data System (ADS)

Barrios, Emilio; Alarcon, Hector

2016-07-01

ALMA Science operations activities in Chile are responsibility of the Department of Science Operations, which consists of three groups, the Array Operations Group (AOG), the Program Management Group (PMG) and the Data Management Group (DMG). The AOG includes the Array Operators and have the mission to provide support for science observations, operating safely and efficiently the array. The poster describes the AOG process, management and operational tools.

An SOI CMOS-Based Multi-Sensor MEMS Chip for Fluidic Applications †

PubMed Central

Mansoor, Mohtashim; Haneef, Ibraheem; Akhtar, Suhail; Rafiq, Muhammad Aftab; De Luca, Andrea; Ali, Syed Zeeshan; Udrea, Florin

2016-01-01

An SOI CMOS multi-sensor MEMS chip, which can simultaneously measure temperature, pressure and flow rate, has been reported. The multi-sensor chip has been designed keeping in view the requirements of researchers interested in experimental fluid dynamics. The chip contains ten thermodiodes (temperature sensors), a piezoresistive-type pressure sensor and nine hot film-based flow rate sensors fabricated within the oxide layer of the SOI wafers. The silicon dioxide layers with embedded sensors are relieved from the substrate as membranes with the help of a single DRIE step after chip fabrication from a commercial CMOS foundry. Very dense sensor packing per unit area of the chip has been enabled by using technologies/processes like SOI, CMOS and DRIE. Independent apparatuses were used for the characterization of each sensor. With a drive current of 10 µA–0.1 µA, the thermodiodes exhibited sensitivities of 1.41 mV/°C–1.79 mV/°C in the range 20–300 °C. The sensitivity of the pressure sensor was 0.0686 mV/(Vexcit kPa) with a non-linearity of 0.25% between 0 and 69 kPa above ambient pressure. Packaged in a micro-channel, the flow rate sensor has a linearized sensitivity of 17.3 mV/(L/min)−0.1 in the tested range of 0–4.7 L/min. The multi-sensor chip can be used for simultaneous measurement of fluid pressure, temperature and flow rate in fluidic experiments and aerospace/automotive/biomedical/process industries. PMID:27827904

Development of subminiature multi-sensor hot-wire probes

NASA Technical Reports Server (NTRS)

Westphal, Russell V.; Ligrani, Phillip M.; Lemos, Fred R.

1988-01-01

Limitations on the spatial resolution of multisensor hot wire probes have precluded accurate measurements of Reynolds stresses very near solid surfaces in wind tunnels and in many practical aerodynamic flows. The fabrication, calibration and qualification testing of very small single horizontal and X-array hot-wire probes which are intended to be used near solid boundaries in turbulent flows where length scales are particularly small, is described. Details of the sensor fabrication procedure are reported, along with information needed to successfully operate the probes. As compared with conventional probes, manufacture of the subminiature probes is more complex, requiring special equipment and careful handling. The subminiature probes tested were more fragile and shorter lived than conventional probes; they obeyed the same calibration laws but with slightly larger experimental uncertainty. In spite of these disadvantages, measurements of mean statistical quantities and spectra demonstrate the ability of the subminiature sensors to provide the measurements in the near wall region of turbulent boundary layers that are more accurate than conventional sized probes.

The Applicability of Incoherent Array Processing to IMS Seismic Array Stations

NASA Astrophysics Data System (ADS)

Gibbons, S. J.

2012-04-01

The seismic arrays of the International Monitoring System for the CTBT differ greatly in size and geometry, with apertures ranging from below 1 km to over 60 km. Large and medium aperture arrays with large inter-site spacings complicate the detection and estimation of high frequency phases since signals are often incoherent between sensors. Many such phases, typically from events at regional distances, remain undetected since pipeline algorithms often consider only frequencies low enough to allow coherent array processing. High frequency phases that are detected are frequently attributed qualitatively incorrect backazimuth and slowness estimates and are consequently not associated with the correct event hypotheses. This can lead to missed events both due to a lack of contributing phase detections and by corruption of event hypotheses by spurious detections. Continuous spectral estimation can be used for phase detection and parameter estimation on the largest aperture arrays, with phase arrivals identified as local maxima on beams of transformed spectrograms. The estimation procedure in effect measures group velocity rather than phase velocity and the ability to estimate backazimuth and slowness requires that the spatial extent of the array is large enough to resolve time-delays between envelopes with a period of approximately 4 or 5 seconds. The NOA, AKASG, YKA, WRA, and KURK arrays have apertures in excess of 20 km and spectrogram beamforming on these stations provides high quality slowness estimates for regional phases without additional post-processing. Seven arrays with aperture between 10 and 20 km (MJAR, ESDC, ILAR, KSRS, CMAR, ASAR, and EKA) can provide robust parameter estimates subject to a smoothing of the resulting slowness grids, most effectively achieved by convolving the measured slowness grids with the array response function for a 4 or 5 second period signal. The MJAR array in Japan recorded high SNR Pn signals for both the 2006 and 2009 North Korea

Process for forming transparent aerogel insulating arrays

DOEpatents

Tewari, Param H.; Hunt, Arlon J.

1986-01-01

An improved supercritical drying process for forming transparent silica aerogel arrays is described. The process is of the type utilizing the steps of hydrolyzing and condensing aloxides to form alcogels. A subsequent step removes the alcohol to form aerogels. The improvement includes the additional step, after alcogels are formed, of substituting a solvent, such as CO.sub.2, for the alcohol in the alcogels, the solvent having a critical temperature less than the critical temperature of the alcohol. The resulting gels are dried at a supercritical temperature for the selected solvent, such as CO.sub.2, to thereby provide a transparent aerogel array within a substantially reduced (days-to-hours) time period. The supercritical drying occurs at about 40.degree. C. instead of at about 270.degree. C. The improved process provides increased yields of large scale, structurally sound arrays. The transparent aerogel array, formed in sheets or slabs, as made in accordance with the improved process, can replace the air gap within a double glazed window, for example, to provide a substantial reduction in heat transfer. The thus formed transparent aerogel arrays may also be utilized, for example, in windows of refrigerators and ovens, or in the walls and doors thereof or as the active material in detectors for analyzing high energy elementry particles or cosmic rays.

Process for forming transparent aerogel insulating arrays

DOEpatents

Tewari, P.H.; Hunt, A.J.

1985-09-04

An improved supercritical drying process for forming transparent silica aerogel arrays is described. The process is of the type utilizing the steps of hydrolyzing and condensing aloxides to form alcogels. A subsequent step removes the alcohol to form aerogels. The improvement includes the additional step, after alcogels are formed, of substituting a solvent, such as CO/sub 2/, for the alcohol in the alcogels, the solvent having a critical temperature less than the critical temperature of the alcohol. The resulting gels are dried at a supercritical temperature for the selected solvent, such as CO/sub 2/, to thereby provide a transparent aerogel array within a substantially reduced (days-to-hours) time period. The supercritical drying occurs at about 40/sup 0/C instead of at about 270/sup 0/C. The improved process provides increased yields of large scale, structurally sound arrays. The transparent aerogel array, formed in sheets or slabs, as made in accordance with the improved process, can replace the air gap within a double glazed window, for example, to provide a substantial reduction in heat transfer. The thus formed transparent aerogel arrays may also be utilized, for example, in windows of refrigerators and ovens, or in the walls and doors thereof or as the active material in detectors for analyzing high energy elementary particles or cosmic rays.

Reducing multi-sensor data to a single time course that reveals experimental effects

PubMed Central

2013-01-01

Background Multi-sensor technologies such as EEG, MEG, and ECoG result in high-dimensional data sets. Given the high temporal resolution of such techniques, scientific questions very often focus on the time-course of an experimental effect. In many studies, researchers focus on a single sensor or the average over a subset of sensors covering a “region of interest” (ROI). However, single-sensor or ROI analyses ignore the fact that the spatial focus of activity is constantly changing, and fail to make full use of the information distributed over the sensor array. Methods We describe a technique that exploits the optimality and simplicity of matched spatial filters in order to reduce experimental effects in multivariate time series data to a single time course. Each (multi-sensor) time sample of each trial is replaced with its projection onto a spatial filter that is matched to an observed experimental effect, estimated from the remaining trials (Effect-Matched Spatial filtering, or EMS filtering). The resulting set of time courses (one per trial) can be used to reveal the temporal evolution of an experimental effect, which distinguishes this approach from techniques that reveal the temporal evolution of an anatomical source or region of interest. Results We illustrate the technique with data from a dual-task experiment and use it to track the temporal evolution of brain activity during the psychological refractory period. We demonstrate its effectiveness in separating the means of two experimental conditions, and in significantly improving the signal-to-noise ratio at the single-trial level. It is fast to compute and results in readily-interpretable time courses and topographies. The technique can be applied to any data-analysis question that can be posed independently at each sensor, and we provide one example, using linear regression, that highlights the versatility of the technique. Conclusion The approach described here combines established techniques in a

Multisensor Network System for Wildfire Detection Using Infrared Image Processing

PubMed Central

Bosch, I.; Serrano, A.; Vergara, L.

2013-01-01

This paper presents the next step in the evolution of multi-sensor wireless network systems in the early automatic detection of forest fires. This network allows remote monitoring of each of the locations as well as communication between each of the sensors and with the control stations. The result is an increased coverage area, with quicker and safer responses. To determine the presence of a forest wildfire, the system employs decision fusion in thermal imaging, which can exploit various expected characteristics of a real fire, including short-term persistence and long-term increases over time. Results from testing in the laboratory and in a real environment are presented to authenticate and verify the accuracy of the operation of the proposed system. The system performance is gauged by the number of alarms and the time to the first alarm (corresponding to a real fire), for different probability of false alarm (PFA). The necessity of including decision fusion is thereby demonstrated. PMID:23843734

Multisensor network system for wildfire detection using infrared image processing.

PubMed

Bosch, I; Serrano, A; Vergara, L

2013-01-01

This paper presents the next step in the evolution of multi-sensor wireless network systems in the early automatic detection of forest fires. This network allows remote monitoring of each of the locations as well as communication between each of the sensors and with the control stations. The result is an increased coverage area, with quicker and safer responses. To determine the presence of a forest wildfire, the system employs decision fusion in thermal imaging, which can exploit various expected characteristics of a real fire, including short-term persistence and long-term increases over time. Results from testing in the laboratory and in a real environment are presented to authenticate and verify the accuracy of the operation of the proposed system. The system performance is gauged by the number of alarms and the time to the first alarm (corresponding to a real fire), for different probability of false alarm (PFA). The necessity of including decision fusion is thereby demonstrated.

Efficient processing of two-dimensional arrays with C or C++

USGS Publications Warehouse

Donato, David I.

2017-07-20

Because fast and efficient serial processing of raster-graphic images and other two-dimensional arrays is a requirement in land-change modeling and other applications, the effects of 10 factors on the runtimes for processing two-dimensional arrays with C and C++ are evaluated in a comparative factorial study. This study’s factors include the choice among three C or C++ source-code techniques for array processing; the choice of Microsoft Windows 7 or a Linux operating system; the choice of 4-byte or 8-byte array elements and indexes; and the choice of 32-bit or 64-bit memory addressing. This study demonstrates how programmer choices can reduce runtimes by 75 percent or more, even after compiler optimizations. Ten points of practical advice for faster processing of two-dimensional arrays are offered to C and C++ programmers. Further study and the development of a C and C++ software test suite are recommended.Key words: array processing, C, C++, compiler, computational speed, land-change modeling, raster-graphic image, two-dimensional array, software efficiency

Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency

PubMed Central

Abu Bakr, Muhammad; Lee, Sukhan

2017-01-01

The paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fields of engineering and control due to its superior performance over the centralized one in terms of flexibility, robustness to failure and cost effectiveness in infrastructure and communication. However, distributed multisensor data fusion is not without technical challenges to overcome: namely, dealing with cross-correlation and inconsistency among state estimates and sensor data. In this paper, we review the key theories and methodologies of distributed multisensor data fusion available to date with a specific focus on handling unknown correlation and data inconsistency. We aim at providing readers with a unifying view out of individual theories and methodologies by presenting a formal analysis of their implications. Finally, several directions of future research are highlighted. PMID:29077035

Information Measures for Multisensor Systems

DTIC Science & Technology

2013-12-11

permuted to generate spectra that were non- physical but preserved the entropy of the source spectra. Another 1000 spectra were constructed to mimic co...Research Laboratory (NRL) has yielded probabilistic models for spectral data that enable the computation of information measures such as entropy and...22308 Chemical sensing Information theory Spectral data Information entropy Information divergence Mass spectrometry Infrared spectroscopy Multisensor

Multisensor systems today and tomorrow: Machine control, diagnosis and thermal compensation

NASA Astrophysics Data System (ADS)

Nunzio, D'Addea

2000-05-01

Multisensor techniques that deal with control of tribology test rig and with diagnosis and thermal error compensation of machine tools are the starting point for some consideration about the use of these techniques as in fuzzy and neural net systems. The author comes to conclusion that anticipatory systems and multisensor techniques will have in the next future a great improvement and a great development mainly in the thermal error compensation of machine tools.

Integrating Scientific Array Processing into Standard SQL

NASA Astrophysics Data System (ADS)

Misev, Dimitar; Bachhuber, Johannes; Baumann, Peter

2014-05-01

We live in a time that is dominated by data. Data storage is cheap and more applications than ever accrue vast amounts of data. Storing the emerging multidimensional data sets efficiently, however, and allowing them to be queried by their inherent structure, is a challenge many databases have to face today. Despite the fact that multidimensional array data is almost always linked to additional, non-array information, array databases have mostly developed separately from relational systems, resulting in a disparity between the two database categories. The current SQL standard and SQL DBMS supports arrays - and in an extension also multidimensional arrays - but does so in a very rudimentary and inefficient way. This poster demonstrates the practicality of an SQL extension for array processing, implemented in a proof-of-concept multi-faceted system that manages a federation of array and relational database systems, providing transparent, efficient and scalable access to the heterogeneous data in them.

Adaptive multisensor fusion for planetary exploration rovers

NASA Technical Reports Server (NTRS)

Collin, Marie-France; Kumar, Krishen; Pampagnin, Luc-Henri

1992-01-01

The purpose of the adaptive multisensor fusion system currently being designed at NASA/Johnson Space Center is to provide a robotic rover with assured vision and safe navigation capabilities during robotic missions on planetary surfaces. Our approach consists of using multispectral sensing devices ranging from visible to microwave wavelengths to fulfill the needs of perception for space robotics. Based on the illumination conditions and the sensors capabilities knowledge, the designed perception system should automatically select the best subset of sensors and their sensing modalities that will allow the perception and interpretation of the environment. Then, based on reflectance and emittance theoretical models, the sensor data are fused to extract the physical and geometrical surface properties of the environment surface slope, dielectric constant, temperature and roughness. The theoretical concepts, the design and first results of the multisensor perception system are presented.

Calibrating a novel multi-sensor physical activity measurement system.

PubMed

John, D; Liu, S; Sasaki, J E; Howe, C A; Staudenmayer, J; Gao, R X; Freedson, P S

2011-09-01

Advancing the field of physical activity (PA) monitoring requires the development of innovative multi-sensor measurement systems that are feasible in the free-living environment. The use of novel analytical techniques to combine and process these multiple sensor signals is equally important. This paper describes a novel multi-sensor 'integrated PA measurement system' (IMS), the lab-based methodology used to calibrate the IMS, techniques used to predict multiple variables from the sensor signals, and proposes design changes to improve the feasibility of deploying the IMS in the free-living environment. The IMS consists of hip and wrist acceleration sensors, two piezoelectric respiration sensors on the torso, and an ultraviolet radiation sensor to obtain contextual information (indoors versus outdoors) of PA. During lab-based calibration of the IMS, data were collected on participants performing a PA routine consisting of seven different ambulatory and free-living activities while wearing a portable metabolic unit (criterion measure) and the IMS. Data analyses on the first 50 adult participants are presented. These analyses were used to determine if the IMS can be used to predict the variables of interest. Finally, physical modifications for the IMS that could enhance the feasibility of free-living use are proposed and refinement of the prediction techniques is discussed.

Multisensor system and artificial intelligence in housing for the elderly.

PubMed

Chan, M; Bocquet, H; Campo, E; Val, T; Estève, D; Pous, J

1998-01-01

To improve the safety of a growing proportion of elderly and disabled people in the developed countries, a multisensor system based on Artificial Intelligence (AI), Advanced Telecommunications (AT) and Information Technology (IT) has been devised and fabricated. Thus, the habits and behaviours of these populations will be recorded without disturbing their daily activities. AI will diagnose any abnormal behavior or change and the system will warn the professionals. Gerontology issues are presented together with the multisensor system, the AI-based learning and diagnosis methodology and the main functionalities.

A system for activity recognition using multi-sensor fusion.

PubMed

Gao, Lei; Bourke, Alan K; Nelson, John

2011-01-01

This paper proposes a system for activity recognition using multi-sensor fusion. In this system, four sensors are attached to the waist, chest, thigh, and side of the body. In the study we present two solutions for factors that affect the activity recognition accuracy: the calibration drift and the sensor orientation changing. The datasets used to evaluate this system were collected from 8 subjects who were asked to perform 8 scripted normal activities of daily living (ADL), three times each. The Naïve Bayes classifier using multi-sensor fusion is adopted and achieves 70.88%-97.66% recognition accuracies for 1-4 sensors.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation.

PubMed

Tkach, Itshak; Jevtić, Aleksandar; Nof, Shimon Y; Edan, Yael

2018-03-02

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors' performance, tasks' priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems.

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

PubMed

Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

2015-11-06

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

Hybrid Arrays for Chemical Sensing

NASA Astrophysics Data System (ADS)

Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

In recent years, multisensory approaches to environment monitoring for chemical detection as well as other forms of situational awareness have become increasingly popular. A hybrid sensor is a multimodal system that incorporates several sensing elements and thus produces data that are multivariate in nature and may be significantly increased in complexity compared to data provided by single-sensor systems. Though a hybrid sensor is itself an array, hybrid sensors are often organized into more complex sensing systems through an assortment of network topologies. Part of the reason for the shift to hybrid sensors is due to advancements in sensor technology and computational power available for processing larger amounts of data. There is also ample evidence to support the claim that a multivariate analytical approach is generally superior to univariate measurements because it provides additional redundant and complementary information (Hall, D. L.; Linas, J., Eds., Handbook of Multisensor Data Fusion, CRC, Boca Raton, FL, 2001). However, the benefits of a multisensory approach are not automatically achieved. Interpretation of data from hybrid arrays of sensors requires the analyst to develop an application-specific methodology to optimally fuse the disparate sources of data generated by the hybrid array into useful information characterizing the sample or environment being observed. Consequently, multivariate data analysis techniques such as those employed in the field of chemometrics have become more important in analyzing sensor array data. Depending on the nature of the acquired data, a number of chemometric algorithms may prove useful in the analysis and interpretation of data from hybrid sensor arrays. It is important to note, however, that the challenges posed by the analysis of hybrid sensor array data are not unique to the field of chemical sensing. Applications in electrical and process engineering, remote sensing, medicine, and of course, artificial

Optical sensors and multisensor arrays containing thin film electroluminescent devices

DOEpatents

Aylott, Jonathan W.; Chen-Esterlit, Zoe; Friedl, Jon H.; Kopelman, Raoul; Savvateev, Vadim N.; Shinar, Joseph

2001-12-18

Optical sensor, probe and array devices for detecting chemical biological, and physical analytes. The devices include an analyte-sensitive layer optically coupled to a thin film electroluminescent layer which activates the analyte-sensitive layer to provide an optical response. The optical response varies depending upon the presence of an analyte and is detected by a photodetector and analyzed to determine the properties of the analyte.

An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph.

PubMed

Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe

2017-03-21

An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method.

ARC - A source of multisensor satellite data for polar science

NASA Technical Reports Server (NTRS)

Van Woert, Michael L.; Whritner, Robert H.; Waliser, Duane E.; Bromwich, David H.; Comiso, J. C.

1992-01-01

The NSF's Antarctic Research Center (ARC) has been established to furnish real-time polar-orbiting satellite data in support of Antarctic field studies, as well as to maintain a multisensor satellite data (MSD) archive for retrospective data analysis. An account is presently given of the ways in which the complementary nature of an MSD set can deepen understanding of Antarctic physical processes. An active microwave SAR with 30-m resolution and a radar altimeter will be added to the ARC resources later in this decade, as will the Earth Observing System.

Performance evaluation of an asynchronous multisensor track fusion filter

NASA Astrophysics Data System (ADS)

Alouani, Ali T.; Gray, John E.; McCabe, D. H.

2003-08-01

Recently the authors developed a new filter that uses data generated by asynchronous sensors to produce a state estimate that is optimal in the minimum mean square sense. The solution accounts for communications delay between sensors platform and fusion center. It also deals with out of sequence data as well as latent data by processing the information in a batch-like manner. This paper compares, using simulated targets and Monte Carlo simulations, the performance of the filter to the optimal sequential processing approach. It was found that the new asynchronous Multisensor track fusion filter (AMSTFF) performance is identical to that of the extended sequential Kalman filter (SEKF), while the new filter updates its track at a much lower rate than the SEKF.

Multisensor fusion for the detection of mines and minelike targets

NASA Astrophysics Data System (ADS)

Hanshaw, Terilee

1995-06-01

The US Army's Communications and Electronics Command through the auspices of its Night Vision and Electronics Sensors Directorate (CECOM-NVESD) is actively applying multisensor techniques to the detection of mine targets. This multisensor research results from the 'detection activity' with its broad range of operational conditions and targets. Multisensor operation justifies significant attention by yielding high target detection and low false alarm statistics. Furthermore, recent advances in sensor and computing technologies make its practical application realistic and affordable. The mine detection field-of-endeavor has since its WWI baptismal investigated the known spectra for applicable mine observation phenomena. Countless sensors, algorithms, processors, networks, and other techniques have been investigated to determine candidacy for mine detection. CECOM-NVESD efforts have addressed a wide range of sensors spanning the spectrum from gravity field perturbations, magentic field disturbances, seismic sounding, electromagnetic fields, earth penetrating radar imagery, and infrared/visible/ultraviolet surface imaging technologies. Supplementary analysis has considered sensor candidate applicability by testing under field conditions (versus laboratory), in determination of fieldability. As these field conditions directly effect the probability of detection and false alarms, sensor employment and design must be considered. Consequently, as a given sensor's performance is influenced directly by the operational conditions, tradeoffs are necessary. At present, mass produced and fielded mine detection techniques are limited to those incorporating a single sensor/processor methodology such as, pulse induction and megnetometry, as found in hand held detectors. The most sensitive fielded systems can detect minute metal components in small mine targets but result in very high false alarm rates reducing velocity in operation environments. Furthermore, the actual speed of

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation †

PubMed Central

Nof, Shimon Y.; Edan, Yael

2018-01-01

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors’ performance, tasks’ priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems. PMID:29498683

Removing Background Noise with Phased Array Signal Processing

NASA Technical Reports Server (NTRS)

Podboy, Gary; Stephens, David

2015-01-01

Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

Case-Based Multi-Sensor Intrusion Detection

NASA Astrophysics Data System (ADS)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

Determination of urine ionic composition with potentiometric multisensor system.

PubMed

Yaroshenko, Irina; Kirsanov, Dmitry; Kartsova, Lyudmila; Sidorova, Alla; Borisova, Irina; Legin, Andrey

2015-01-01

The ionic composition of urine is a good indicator of patient's general condition and allows for diagnostics of certain medical problems such as e.g., urolithiasis. Due to environmental factors and malnutrition the number of registered urinary tract cases continuously increases. Most of the methods currently used for urine analysis are expensive, quite laborious and require skilled personnel. The present work deals with feasibility study of potentiometric multisensor system of 18 ion-selective and cross-sensitive sensors as an analytical tool for determination of urine ionic composition. In total 136 samples from patients of Urolithiasis Laboratory and healthy people were analyzed by the multisensor system as well as by capillary electrophoresis as a reference method. Various chemometric approaches were implemented to relate the data from electrochemical measurements with the reference data. Logistic regression (LR) was applied for classification of samples into healthy and unhealthy producing reasonable misclassification rates. Projection on Latent Structures (PLS) regression was applied for quantitative analysis of ionic composition from potentiometric data. Mean relative errors of simultaneous prediction of sodium, potassium, ammonium, calcium, magnesium, chloride, sulfate, phosphate, urate and creatinine from multisensor system response were in the range 3-13% for independent test sets. This shows a good promise for development of a fast and inexpensive alternative method for urine analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling change from large-scale high-dimensional spatio-temporal array data

NASA Astrophysics Data System (ADS)

Lu, Meng; Pebesma, Edzer

2014-05-01

The massive data that come from Earth observation satellite and other sensors provide significant information for modeling global change. At the same time, the high dimensionality of the data has brought challenges in data acquisition, management, effective querying and processing. In addition, the output of earth system modeling tends to be data intensive and needs methodologies for storing, validation, analyzing and visualization, e.g. as maps. An important proportion of earth system observations and simulated data can be represented as multi-dimensional array data, which has received increasingly attention in big data management and spatial-temporal analysis. Study cases will be developed in natural science such as climate change, hydrological modeling, sediment dynamics, from which the addressing of big data problems is necessary. Multi-dimensional array-based database management and analytics system such as Rasdaman, SciDB, and R will be applied to these cases. From these studies will hope to learn the strengths and weaknesses of these systems, how they might work together or how semantics of array operations differ, through addressing the problems associated with big data. Research questions include: • How can we reduce dimensions spatially and temporally, or thematically? • How can we extend existing GIS functions to work on multidimensional arrays? • How can we combine data sets of different dimensionality or different resolutions? • Can map algebra be extended to an intelligible array algebra? • What are effective semantics for array programming of dynamic data driven applications? • In which sense are space and time special, as dimensions, compared to other properties? • How can we make the analysis of multi-spectral, multi-temporal and multi-sensor earth observation data easy?

ATR architecture for multisensor fusion

NASA Astrophysics Data System (ADS)

Hamilton, Mark K.; Kipp, Teresa A.

1996-06-01

The work of the U.S. Army Research Laboratory (ARL) in the area of algorithms for the identification of static military targets in single-frame electro-optical (EO) imagery has demonstrated great potential in platform-based automatic target identification (ATI). In this case, the term identification is used to mean being able to tell the difference between two military vehicles -- e.g., the M60 from the T72. ARL's work includes not only single-sensor forward-looking infrared (FLIR) ATI algorithms, but also multi-sensor ATI algorithms. We briefly discuss ARL's hybrid model-based/data-learning strategy for ATI, which represents a significant step forward in ATI algorithm design. For example, in the case of single sensor FLIR it allows the human algorithm designer to build directly into the algorithm knowledge that can be adequately modeled at this time, such as the target geometry which directly translates into the target silhouette in the FLIR realm. In addition, it allows structure that is not currently well understood (i.e., adequately modeled) to be incorporated through automated data-learning algorithms, which in a FLIR directly translates into an internal thermal target structure signature. This paper shows the direct applicability of this strategy to both the single-sensor FLIR as well as the multi-sensor FLIR and laser radar.

Multi-Sensor Registration of Earth Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Cole-Rhodes, Arlene; Eastman, Roger; Johnson, Kisha; Morisette, Jeffrey; Netanyahu, Nathan S.; Stone, Harold S.; Zavorin, Ilya; Zukor, Dorothy (Technical Monitor)

2001-01-01

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

NASA Technical Reports Server (NTRS)

Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.;

Geocoding and stereo display of tropical forest multisensor datasets

NASA Technical Reports Server (NTRS)

Welch, R.; Jordan, T. R.; Luvall, J. C.

1990-01-01

Concern about the future of tropical forests has led to a demand for geocoded multisensor databases that can be used to assess forest structure, deforestation, thermal response, evapotranspiration, and other parameters linked to climate change. In response to studies being conducted at the Braulino Carrillo National Park, Costa Rica, digital satellite and aircraft images recorded by Landsat TM, SPOT HRV, Thermal Infrared Multispectral Scanner, and Calibrated Airborne Multispectral Scanner sensors were placed in register using the Landsat TM image as the reference map. Despite problems caused by relief, multitemporal datasets, and geometric distortions in the aircraft images, registration was accomplished to within + or - 20 m (+ or - 1 data pixel). A digital elevation model constructed from a multisensor Landsat TM/SPOT stereopair proved useful for generating perspective views of the rugged, forested terrain.

Multi-sensor image registration based on algebraic projective invariants.

PubMed

Li, Bin; Wang, Wei; Ye, Hao

2013-04-22

A new automatic feature-based registration algorithm is presented for multi-sensor images with projective deformation. Contours are firstly extracted from both reference and sensed images as basic features in the proposed method. Since it is difficult to design a projective-invariant descriptor from the contour information directly, a new feature named Five Sequential Corners (FSC) is constructed based on the corners detected from the extracted contours. By introducing algebraic projective invariants, we design a descriptor for each FSC that is ensured to be robust against projective deformation. Further, no gray scale related information is required in calculating the descriptor, thus it is also robust against the gray scale discrepancy between the multi-sensor image pairs. Experimental results utilizing real image pairs are presented to show the merits of the proposed registration method.

Multisensor data fusion for physical activity assessment.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John W; Freedson, Patty S

2012-03-01

This paper presents a sensor fusion method for assessing physical activity (PA) of human subjects, based on support vector machines (SVMs). Specifically, acceleration and ventilation measured by a wearable multisensor device on 50 test subjects performing 13 types of activities of varying intensities are analyzed, from which activity type and energy expenditure are derived. The results show that the method correctly recognized the 13 activity types 88.1% of the time, which is 12.3% higher than using a hip accelerometer alone. Also, the method predicted energy expenditure with a root mean square error of 0.42 METs, 22.2% lower than using a hip accelerometer alone. Furthermore, the fusion method was effective in reducing the subject-to-subject variability (standard deviation of recognition accuracies across subjects) in activity recognition, especially when data from the ventilation sensor were added to the fusion model. These results demonstrate that the multisensor fusion technique presented is more effective in identifying activity type and energy expenditure than the traditional accelerometer-alone-based methods.

A model for the distributed storage and processing of large arrays

NASA Technical Reports Server (NTRS)

Mehrota, P.; Pratt, T. W.

1983-01-01

A conceptual model for parallel computations on large arrays is developed. The model provides a set of language concepts appropriate for processing arrays which are generally too large to fit in the primary memories of a multiprocessor system. The semantic model is used to represent arrays on a concurrent architecture in such a way that the performance realities inherent in the distributed storage and processing can be adequately represented. An implementation of the large array concept as an Ada package is also described.

Multisensor fusion for 3-D defect characterization using wavelet basis function neural networks

NASA Astrophysics Data System (ADS)

Lim, Jaein; Udpa, Satish S.; Udpa, Lalita; Afzal, Muhammad

2001-04-01

The primary objective of multi-sensor data fusion, which offers both quantitative and qualitative benefits, has the ability to draw inferences that may not be feasible with data from a single sensor alone. In this paper, data from two sets of sensors are fused to estimate the defect profile from magnetic flux leakage (MFL) inspection data. The two sensors measure the axial and circumferential components of the MFL. Data is fused at the signal level. If the flux is oriented axially, the samples of the axial signal are measured along a direction parallel to the flaw, while the circumferential signal is measured in a direction that is perpendicular to the flaw. The two signals are combined as the real and imaginary components of a complex valued signal. Signals from an array of sensors are arranged in contiguous rows to obtain a complex valued image. A boundary extraction algorithm is used to extract the defect areas in the image. Signals from the defect regions are then processed to minimize noise and the effects of lift-off. Finally, a wavelet basis function (WBF) neural network is employed to map the complex valued image appropriately to obtain the geometrical profile of the defect. The feasibility of the approach was evaluated using the data obtained from the MFL inspection of natural gas transmission pipelines. Results show the effectiveness of the approach.

An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph

PubMed Central

Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe

2017-01-01

An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method. PMID:28335570

Array signal processing in the NASA Deep Space Network

NASA Technical Reports Server (NTRS)

Pham, Timothy T.; Jongeling, Andre P.

2004-01-01

In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

Multisensor Parallel Largest Ellipsoid Distributed Data Fusion with Unknown Cross-Covariances

PubMed Central

Liu, Baoyu; Zhan, Xingqun; Zhu, Zheng H.

2017-01-01

As the largest ellipsoid (LE) data fusion algorithm can only be applied to two-sensor system, in this contribution, parallel fusion structure is proposed to introduce the LE algorithm into a multisensor system with unknown cross-covariances, and three parallel fusion structures based on different estimate pairing methods are presented and analyzed. In order to assess the influence of fusion structure on fusion performance, two fusion performance assessment parameters are defined as Fusion Distance and Fusion Index. Moreover, the formula for calculating the upper bounds of actual fused error covariances of the presented multisensor LE fusers is also provided. Demonstrated with simulation examples, the Fusion Index indicates fuser’s actual fused accuracy and its sensitivity to the sensor orders, as well as its robustness to the accuracy of newly added sensors. Compared to the LE fuser with sequential structure, the LE fusers with proposed parallel structures not only significantly improve their properties in these aspects, but also embrace better performances in consistency and computation efficiency. The presented multisensor LE fusers generally have better accuracies than covariance intersection (CI) fusion algorithm and are consistent when the local estimates are weakly correlated. PMID:28661442

Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.

RadMAP: The Radiological Multi-sensor Analysis Platform

NASA Astrophysics Data System (ADS)

Bandstra, Mark S.; Aucott, Timothy J.; Brubaker, Erik; Chivers, Daniel H.; Cooper, Reynold J.; Curtis, Joseph C.; Davis, John R.; Joshi, Tenzing H.; Kua, John; Meyer, Ross; Negut, Victor; Quinlan, Michael; Quiter, Brian J.; Srinivasan, Shreyas; Zakhor, Avideh; Zhang, Richard; Vetter, Kai

2016-12-01

The variability of gamma-ray and neutron background during the operation of a mobile detector system greatly limits the ability of the system to detect weak radiological and nuclear threats. The natural radiation background measured by a mobile detector system is the result of many factors, including the radioactivity of nearby materials, the geometric configuration of those materials and the system, the presence of absorbing materials, and atmospheric conditions. Background variations tend to be highly non-Poissonian, making it difficult to set robust detection thresholds using knowledge of the mean background rate alone. The Radiological Multi-sensor Analysis Platform (RadMAP) system is designed to allow the systematic study of natural radiological background variations and to serve as a development platform for emerging concepts in mobile radiation detection and imaging. To do this, RadMAP has been used to acquire extensive, systematic background measurements and correlated contextual data that can be used to test algorithms and detector modalities at low false alarm rates. By combining gamma-ray and neutron detector systems with data from contextual sensors, the system enables the fusion of data from multiple sensors into novel data products. The data are curated in a common format that allows for rapid querying across all sensors, creating detailed multi-sensor datasets that are used to study correlations between radiological and contextual data, and develop and test novel techniques in mobile detection and imaging. In this paper we will describe the instruments that comprise the RadMAP system, the effort to curate and provide access to multi-sensor data, and some initial results on the fusion of contextual and radiological data.

Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

PubMed Central

Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng

2015-01-01

Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384

Expanding Coherent Array Processing to Larger Apertures Using Empirical Matched Field Processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ringdal, F; Harris, D B; Kvaerna, T

2009-07-23

We have adapted matched field processing, a method developed in underwater acoustics to detect and locate targets, to classify transient seismic signals arising from mining explosions. Matched field processing, as we apply it, is an empirical technique, using observations of historic events to calibrate the amplitude and phase structure of wavefields incident upon an array aperture for particular repeating sources. The objective of this project is to determine how broadly applicable the method is and to understand the phenomena that control its performance. We obtained our original results in distinguishing events from ten mines in the Khibiny and Olenegorsk miningmore » districts of the Kola Peninsula, for which we had exceptional ground truth information. In a cross-validation test, some 98.2% of 549 explosions were correctly classified by originating mine using just the Pn observations (2.5-12.5 Hz) on the ARCES array at ranges from 350-410 kilometers. These results were achieved despite the fact that the mines are as closely spaced as 3 kilometers. Such classification performance is significantly better than predicted by the Rayleigh limit. Scattering phenomena account for the increased resolution, as we make clear in an analysis of the information carrying capacity of Pn under two alternative propagation scenarios: free-space propagation and propagation with realistic (actually measured) spatial covariance structure. The increase in information capacity over a wide band is captured by the matched field calibrations and used to separate explosions from very closely-spaced sources. In part, the improvement occurs because the calibrations enable coherent processing at frequencies above those normally considered coherent. We are investigating whether similar results can be expected in different regions, with apertures of increasing scale and for diffuse seismicity. We verified similar performance with the closely-spaced Zapolyarni mines, though discovered that

Urban structure analysis of mega city Mexico City using multisensoral remote sensing data

NASA Astrophysics Data System (ADS)

Taubenböck, H.; Esch, T.; Wurm, M.; Thiel, M.; Ullmann, T.; Roth, A.; Schmidt, M.; Mehl, H.; Dech, S.

2008-10-01

Mega city Mexico City is ranked the third largest urban agglomeration to date around the globe. The large extension as well as dynamic urban transformation and sprawl processes lead to a lack of up-to-date and area-wide data and information to measure, monitor, and understand the urban situation. This paper focuses on the capabilities of multisensoral remotely sensed data to provide a broad range of products derived from one scientific field - remote sensing - to support urban managing and planning. Therefore optical data sets from the Landsat and Quickbird sensors as well as radar data from the Shuttle Radar Topography Mission (SRTM) and the TerraSAR-X sensor are utilised. Using the multi-sensoral data sets the analysis are scale-dependent. On the one hand change detection on city level utilising the derived urban footprints enables to monitor and to assess spatiotemporal urban transformation, areal dimension of urban sprawl, its direction, and the built-up density distribution over time. On the other hand, structural characteristics of an urban landscape - the alignment and types of buildings, streets and open spaces - provide insight in the very detailed physical pattern of urban morphology on higher scale. The results show high accuracies of the derived multi-scale products. The multi-scale analysis allows quantifying urban processes and thus leading to an assessment and interpretation of urban trends.

Design of a multisensor data fusion system for target detection

NASA Astrophysics Data System (ADS)

Thomopoulos, Stelios C.; Okello, Nickens N.; Kadar, Ivan; Lovas, Louis A.

1993-09-01

The objective of this paper is to discuss the issues that are involved in the design of a multisensor fusion system and provide a systematic analysis and synthesis methodology for the design of the fusion system. The system under consideration consists of multifrequency (similar) radar sensors. However, the fusion design must be flexible to accommodate additional dissimilar sensors such as IR, EO, ESM, and Ladar. The motivation for the system design is the proof of the fusion concept for enhancing the detectability of small targets in clutter. In the context of down-selecting the proper configuration for multisensor (similar and dissimilar, and centralized vs. distributed) data fusion, the issues of data modeling, fusion approaches, and fusion architectures need to be addressed for the particular application being considered. Although the study of different approaches may proceed in parallel, the interplay among them is crucial in selecting a fusion configuration for a given application. The natural sequence for addressing the three different issues is to begin from the data modeling, in order to determine the information content of the data. This information will dictate the appropriate fusion approach. This, in turn, will lead to a global fusion architecture. Both distributed and centralized fusion architectures are used to illustrate the design issues along with Monte-Carlo simulation performance comparison of a single sensor versus a multisensor centrally fused system.

Regional Mapping of Plantation Extent Using Multisensor Imagery

NASA Astrophysics Data System (ADS)

Torbick, N.; Ledoux, L.; Hagen, S.; Salas, W.

2016-12-01

Industrial forest plantations are expanding rapidly across the tropics and monitoring extent is critical for understanding environmental and socioeconomic impacts. In this study, new, multisensor imagery were evaluated and integrated to extract the strengths of each sensor for mapping plantation extent at regional scales. Three distinctly different landscapes with multiple plantation types were chosen to consider scalability and transferability. These were Tanintharyi, Myanmar, West Kalimantan, Indonesia, and southern Ghana. Landsat-8 Operational Land Imager (OLI), Phased Array L-band Synthetic Aperture Radar-2 (PALSAR-2), and Sentinel-1A images were fused within a Classification and Regression Tree (CART) framework using random forest and high-resolution surveys. Multi-criteria evaluations showed both L-and C-band gamma nought γ° backscatter decibel (dB), Landsat reflectance ρλ, and texture indices were useful for distinguishing oil palm and rubber plantations from other land types. The classification approach identified 750,822 ha or 23% of the Taninathryi, Myanmar, and 216,086 ha or 25% of western West Kalimantan as plantation with very high cross validation accuracy. The mapping approach was scalable and transferred well across the different geographies and plantation types. As archives for Sentinel-1, Landsat-8, and PALSAR-2 continue to grow, mapping plantation extent and dynamics at moderate resolution over large regions should be feasible.

Nonlinear Blind Compensation for Array Signal Processing Application

PubMed Central

Ma, Hong; Jin, Jiang; Zhang, Hua

2018-01-01

Recently, nonlinear blind compensation technique has attracted growing attention in array signal processing application. However, due to the nonlinear distortion stemming from array receiver which consists of multi-channel radio frequency (RF) front-ends, it is too difficult to estimate the parameters of array signal accurately. A novel nonlinear blind compensation algorithm aims at the nonlinearity mitigation of array receiver and its spurious-free dynamic range (SFDR) improvement, which will be more precise to estimate the parameters of target signals such as their two-dimensional directions of arrival (2-D DOAs). Herein, the suggested method is designed as follows: the nonlinear model parameters of any channel of RF front-end are extracted to synchronously compensate the nonlinear distortion of the entire receiver. Furthermore, a verification experiment on the array signal from a uniform circular array (UCA) is adopted to testify the validity of our approach. The real-world experimental results show that the SFDR of the receiver is enhanced, leading to a significant improvement of the 2-D DOAs estimation performance for weak target signals. And these results demonstrate that our nonlinear blind compensation algorithm is effective to estimate the parameters of weak array signal in concomitance with strong jammers. PMID:29690571

A Versatile Multichannel Digital Signal Processing Module for Microcalorimeter Arrays

NASA Astrophysics Data System (ADS)

Tan, H.; Collins, J. W.; Walby, M.; Hennig, W.; Warburton, W. K.; Grudberg, P.

2012-06-01

Different techniques have been developed for reading out microcalorimeter sensor arrays: individual outputs for small arrays, and time-division or frequency-division or code-division multiplexing for large arrays. Typically, raw waveform data are first read out from the arrays using one of these techniques and then stored on computer hard drives for offline optimum filtering, leading not only to requirements for large storage space but also limitations on achievable count rate. Thus, a read-out module that is capable of processing microcalorimeter signals in real time will be highly desirable. We have developed multichannel digital signal processing electronics that are capable of on-board, real time processing of microcalorimeter sensor signals from multiplexed or individual pixel arrays. It is a 3U PXI module consisting of a standardized core processor board and a set of daughter boards. Each daughter board is designed to interface a specific type of microcalorimeter array to the core processor. The combination of the standardized core plus this set of easily designed and modified daughter boards results in a versatile data acquisition module that not only can easily expand to future detector systems, but is also low cost. In this paper, we first present the core processor/daughter board architecture, and then report the performance of an 8-channel daughter board, which digitizes individual pixel outputs at 1 MSPS with 16-bit precision. We will also introduce a time-division multiplexing type daughter board, which takes in time-division multiplexing signals through fiber-optic cables and then processes the digital signals to generate energy spectra in real time.

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

NASA Technical Reports Server (NTRS)

Masunaga, Hirohiko; Matsui, Toshihisa; Tao, Wei-Kuo; Hou, Arthur Y.; Kummerow, Christian D.; Nakajima, Teruyuki; Bauer, Peter; Olson, William S.; Sekiguchi, Miho; Nakajima, Teruyuki

2010-01-01

Several multisensor simulator packages are being developed by different research groups across the world. Such simulator packages [e.g., COSP , CRTM, ECSIM, RTTO, ISSARS (under development), and SDSU (this article), among others] share overall aims, although some are targeted more on particular satellite programs or specific applications (for research purposes or for operational use) than others. The SDSU or Satellite Data Simulator Unit is a general-purpose simulator composed of Fortran 90 codes and applicable to spaceborne microwave radiometer, radar, and visible/infrared imagers including, but not limited to, the sensors listed in a table. That shows satellite programs particularly suitable for multisensor data analysis: some are single satellite missions carrying two or more instruments, while others are constellations of satellites flying in formation. The TRMM and A-Train are ongoing satellite missions carrying diverse sensors that observe clouds and precipitation, and will be continued or augmented within the decade to come by future multisensor missions such as the GPM and Earth-CARE. The ultimate goals of these present and proposed satellite programs are not restricted to clouds and precipitation but are to better understand their interactions with atmospheric dynamics/chemistry and feedback to climate. The SDSU's applicability is not technically limited to hydrometeor measurements either, but may be extended to air temperature and humidity observations by tuning the SDSU to sounding channels. As such, the SDSU and other multisensor simulators would potentially contribute to a broad area of climate and atmospheric sciences. The SDSU is not optimized to any particular orbital geometry of satellites. The SDSU is applicable not only to low-Earth orbiting platforms as listed in Table 1, but also to geostationary meteorological satellites. Although no geosynchronous satellite carries microwave instruments at present or in the near future, the SDSU would be

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

Multisensor signal denoising based on matching synchrosqueezing wavelet transform for mechanical fault condition assessment

NASA Astrophysics Data System (ADS)

Yi, Cancan; Lv, Yong; Xiao, Han; Huang, Tao; You, Guanghui

2018-04-01

Since it is difficult to obtain the accurate running status of mechanical equipment with only one sensor, multisensor measurement technology has attracted extensive attention. In the field of mechanical fault diagnosis and condition assessment based on vibration signal analysis, multisensor signal denoising has emerged as an important tool to improve the reliability of the measurement result. A reassignment technique termed the synchrosqueezing wavelet transform (SWT) has obvious superiority in slow time-varying signal representation and denoising for fault diagnosis applications. The SWT uses the time-frequency reassignment scheme, which can provide signal properties in 2D domains (time and frequency). However, when the measured signal contains strong noise components and fast varying instantaneous frequency, the performance of SWT-based analysis still depends on the accuracy of instantaneous frequency estimation. In this paper, a matching synchrosqueezing wavelet transform (MSWT) is investigated as a potential candidate to replace the conventional synchrosqueezing transform for the applications of denoising and fault feature extraction. The improved technology utilizes the comprehensive instantaneous frequency estimation by chirp rate estimation to achieve a highly concentrated time-frequency representation so that the signal resolution can be significantly improved. To exploit inter-channel dependencies, the multisensor denoising strategy is performed by using a modulated multivariate oscillation model to partition the time-frequency domain; then, the common characteristics of the multivariate data can be effectively identified. Furthermore, a modified universal threshold is utilized to remove noise components, while the signal components of interest can be retained. Thus, a novel MSWT-based multisensor signal denoising algorithm is proposed in this paper. The validity of this method is verified by numerical simulation, and experiments including a rolling

A Low Power, Parallel Wearable Multi-Sensor System for Human Activity Evaluation.

PubMed

Li, Yuecheng; Jia, Wenyan; Yu, Tianjian; Luan, Bo; Mao, Zhi-Hong; Zhang, Hong; Sun, Mingui

2015-04-01

In this paper, the design of a low power heterogeneous wearable multi-sensor system, built with Zynq System-on-Chip (SoC), for human activity evaluation is presented. The powerful data processing capability and flexibility of this SoC represent significant improvements over our previous ARM based system designs. The new system captures and compresses multiple color images and sensor data simultaneously. Several strategies are adopted to minimize power consumption. Our wearable system provides a new tool for the evaluation of human activity, including diet, physical activity and lifestyle.

Performance of A Compact Multi-crystal High-purity Germanium Detector Array for Measuring Coincident Gamma-ray Emissions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Howard, Chris; Daigle, Stephen; Buckner, Matt

2015-02-18

The Multi-sensor Airborne Radiation Survey (MARS) detector is a 14-crystal array of high-purity germanium (HPGe) detectors housed in a single cryostat. The array was used to measure the astrophysical S-factor for the 14N(p,γ) 15O* reaction for several transition energies at an effective center of mass energy of 163 keV. Owing to the segmented nature of the MARS detector, the effect of gamma-ray summing was greatly reduced in comparison to past experiments which utilized large, single-crystal detectors. The new S-factor values agree within the uncertainties with the past measurements. Details of the analysis and detector performance will be presented.

Radar Array Processing of Experimental Data Via the Scan-MUSIC Algorithm

DTIC Science & Technology

2004-06-01

Radar Array Processing of Experimental Data Via the Scan- MUSIC Algorithm by Canh Ly ARL-TR-3135 June 2004...Processing of Experimental Data Via the Scan- MUSIC Algorithm Canh Ly Sensors and Electron Devices Directorate, ARL...NUMBER 5b. GRANT NUMBER 4. TITLE AND SUBTITLE Radar Array Processing of Experimental Data Via the Scan- MUSIC Algorithm 5c. PROGRAM ELEMENT NUMBER 5d

50 years of progress in microphone arrays for speech processing

NASA Astrophysics Data System (ADS)

Elko, Gary W.; Frisk, George V.

2004-10-01

In the early 1980s, Jim Flanagan had a dream of covering the walls of a room with microphones. He occasionally referred to this concept as acoustic wallpaper. Being a new graduate in the field of acoustics and signal processing, it was fortunate that Bell Labs was looking for someone to investigate this area of microphone arrays for telecommunication. The job interview was exciting, with all of the big names in speech signal processing and acoustics sitting in the audience, many of whom were the authors of books and articles that were seminal contributions to the fields of acoustics and signal processing. If there ever was an opportunity of a lifetime, this was it. Fortunately, some of the work had already begun, and Sessler and West had already laid the groundwork for directional electret microphones. This talk will describe some of the very early work done at Bell Labs on microphone arrays and reflect on some of the many systems, from large 400-element arrays, to small two-microphone arrays. These microphone array systems were built under Jim Flanagan's leadership in an attempt to realize his vision of seamless hands-free speech communication between people and the communication of people with machines.

Multi-Sensor Characterization of the Boreal Forest: Initial Findings

NASA Technical Reports Server (NTRS)

Reith, Ernest; Roberts, Dar A.; Prentiss, Dylan

2001-01-01

Results are presented in an initial apriori knowledge approach toward using complementary multi-sensor multi-temporal imagery in characterizing vegetated landscapes over a site in the Boreal Ecosystem-Atmosphere Study (BOREAS). Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data were segmented using multiple endmember spectral mixture analysis and binary decision tree approaches. Individual date/sensor land cover maps had overall accuracies between 55.0% - 69.8%. The best eight land cover layers from all dates and sensors correctly characterized 79.3% of the cover types. An overlay approach was used to create a final land cover map. An overall accuracy of 71.3% was achieved in this multi-sensor approach, a 1.5% improvement over our most accurate single scene technique, but 8% less than the original input. Black spruce was evaluated to be particularly undermapped in the final map possibly because it was also contained within jack pine and muskeg land coverages.

Frequency-wavenumber processing for infrasound distributed arrays.

PubMed

Costley, R Daniel; Frazier, W Garth; Dillion, Kevin; Picucci, Jennifer R; Williams, Jay E; McKenna, Mihan H

2013-10-01

The work described herein discusses the application of a frequency-wavenumber signal processing technique to signals from rectangular infrasound arrays for detection and estimation of the direction of travel of infrasound. Arrays of 100 sensors were arranged in square configurations with sensor spacing of 2 m. Wind noise data were collected at one site. Synthetic infrasound signals were superposed on top of the wind noise to determine the accuracy and sensitivity of the technique with respect to signal-to-noise ratio. The technique was then applied to an impulsive event recorded at a different site. Preliminary results demonstrated the feasibility of this approach.

Effective World Modeling: Multisensor Data Fusion Methodology for Automated Driving

PubMed Central

Elfring, Jos; Appeldoorn, Rein; van den Dries, Sjoerd; Kwakkernaat, Maurice

2016-01-01

The number of perception sensors on automated vehicles increases due to the increasing number of advanced driver assistance system functions and their increasing complexity. Furthermore, fail-safe systems require redundancy, thereby increasing the number of sensors even further. A one-size-fits-all multisensor data fusion architecture is not realistic due to the enormous diversity in vehicles, sensors and applications. As an alternative, this work presents a methodology that can be used to effectively come up with an implementation to build a consistent model of a vehicle’s surroundings. The methodology is accompanied by a software architecture. This combination minimizes the effort required to update the multisensor data fusion system whenever sensors or applications are added or replaced. A series of real-world experiments involving different sensors and algorithms demonstrates the methodology and the software architecture. PMID:27727171

Evaluation of a novel chemical sensor system to detect clinical mastitis in bovine milk.

PubMed

Mottram, Toby; Rudnitskaya, Alisa; Legin, Andrey; Fitzpatrick, Julie L; Eckersall, P David

2007-05-15

Automatic detection of clinical mastitis is an essential part of high performance and robotic milking. Currently available technology (conductivity monitoring) is unable to achieve acceptable specificity or sensitivity of detection of clinical mastitis or other clinical diseases. Arrays of sensors with high cross-sensitivity have been successfully applied for recognition and quantitative analysis of other multicomponent liquids. An experiment was conducted to determine whether a multisensor system ("electronic tongue") based on an array of chemical sensors and suitable data processing could be used to discriminate between milk secretions from infected and healthy glands. Measurements were made with a multisensor system of milk samples from two different farms in two experiments. A total of 67 samples of milk from both mastitic and healthy glands were in two sets. It was demonstrated that the multisensor system could distinguish between control and clinically mastitic milk samples (p=0.05). The sensitivity and specificity of the sensor system (93 and 96% correspondingly) showed an improvement over conductivity (56 and 82% correspondingly). The multisensor system offers a novel method of improving mastitis detection.

Reliability measurement during software development. [for a multisensor tracking system

NASA Technical Reports Server (NTRS)

Hecht, H.; Sturm, W. A.; Trattner, S.

1977-01-01

During the development of data base software for a multi-sensor tracking system, reliability was measured. The failure ratio and failure rate were found to be consistent measures. Trend lines were established from these measurements that provided good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the individual run submission rather than with the code proper. Possible application of these findings for line management, project managers, functional management, and regulatory agencies is discussed. Steps for simplifying the measurement process and for use of these data in predicting operational software reliability are outlined.

A parallel implementation of a multisensor feature-based range-estimation method

NASA Technical Reports Server (NTRS)

Suorsa, Raymond E.; Sridhar, Banavar

1993-01-01

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Barrow real-time sea ice mass balance data: ingestion, processing, dissemination and archival of multi-sensor data

NASA Astrophysics Data System (ADS)

Grimes, J.; Mahoney, A. R.; Heinrichs, T. A.; Eicken, H.

2012-12-01

Sensor data can be highly variable in nature and also varied depending on the physical quantity being observed, sensor hardware and sampling parameters. The sea ice mass balance site (MBS) operated in Barrow by the University of Alaska Fairbanks (http://seaice.alaska.edu/gi/observatories/barrow_sealevel) is a multisensor platform consisting of a thermistor string, air and water temperature sensors, acoustic altimeters above and below the ice and a humidity sensor. Each sensor has a unique specification and configuration. The data from multiple sensors are combined to generate sea ice data products. For example, ice thickness is calculated from the positions of the upper and lower ice surfaces, which are determined using data from downward-looking and upward-looking acoustic altimeters above and below the ice, respectively. As a data clearinghouse, the Geographic Information Network of Alaska (GINA) processes real time data from many sources, including the Barrow MBS. Doing so requires a system that is easy to use, yet also offers the flexibility to handle data from multisensor observing platforms. In the case of the Barrow MBS, the metadata system needs to accommodate the addition of new and retirement of old sensors from year to year as well as instrument configuration changes caused by, for example, spring melt or inquisitive polar bears. We also require ease of use for both administrators and end users. Here we present the data and processing steps of using sensor data system powered by the NoSQL storage engine, MongoDB. The system has been developed to ingest, process, disseminate and archive data from the Barrow MBS. Storing sensor data in a generalized format, from many different sources, is a challenging task, especially for traditional SQL databases with a set schema. MongoDB is a NoSQL (not only SQL) database that does not require a fixed schema. There are several advantages using this model over the traditional relational database management system (RDBMS

Redundant Disk Arrays in Transaction Processing Systems. Ph.D. Thesis, 1993

NASA Technical Reports Server (NTRS)

Mourad, Antoine Nagib

1994-01-01

We address various issues dealing with the use of disk arrays in transaction processing environments. We look at the problem of transaction undo recovery and propose a scheme for using the redundancy in disk arrays to support undo recovery. The scheme uses twin page storage for the parity information in the array. It speeds up transaction processing by eliminating the need for undo logging for most transactions. The use of redundant arrays of distributed disks to provide recovery from disasters as well as temporary site failures and disk crashes is also studied. We investigate the problem of assigning the sites of a distributed storage system to redundant arrays in such a way that a cost of maintaining the redundant parity information is minimized. Heuristic algorithms for solving the site partitioning problem are proposed and their performance is evaluated using simulation. We also develop a heuristic for which an upper bound on the deviation from the optimal solution can be established.

MATSurv: multisensor air traffic surveillance system

NASA Astrophysics Data System (ADS)

Yeddanapudi, Murali; Bar-Shalom, Yaakov; Pattipati, Krishna R.; Gassner, Richard R.

1995-09-01

This paper deals with the design and implementation of MATSurv 1--an experimental Multisensor Air Traffic Surveillance system. The proposed system consists of a Kalman filter based state estimator used in conjunction with a 2D sliding window assignment algorithm. Real data from two FAA radars is used to evaluate the performance of this algorithm. The results indicate that the proposed algorithm provides a superior classification of the measurements into tracks (i.e., the most likely aircraft trajectories) when compared to the aircraft trajectories obtained using the measurement IDs (squawk or IFF code).

Parallel Processing of Large Scale Microphone Arrays for Sound Capture

NASA Astrophysics Data System (ADS)

Jan, Ea-Ee.

1995-01-01

Performance of microphone sound pick up is degraded by deleterious properties of the acoustic environment, such as multipath distortion (reverberation) and ambient noise. The degradation becomes more prominent in a teleconferencing environment in which the microphone is positioned far away from the speaker. Besides, the ideal teleconference should feel as easy and natural as face-to-face communication with another person. This suggests hands-free sound capture with no tether or encumbrance by hand-held or body-worn sound equipment. Microphone arrays for this application represent an appropriate approach. This research develops new microphone array and signal processing techniques for high quality hands-free sound capture in noisy, reverberant enclosures. The new techniques combine matched-filtering of individual sensors and parallel processing to provide acute spatial volume selectivity which is capable of mitigating the deleterious effects of noise interference and multipath distortion. The new method outperforms traditional delay-and-sum beamformers which provide only directional spatial selectivity. The research additionally explores truncated matched-filtering and random distribution of transducers to reduce complexity and improve sound capture quality. All designs are first established by computer simulation of array performance in reverberant enclosures. The simulation is achieved by a room model which can efficiently calculate the acoustic multipath in a rectangular enclosure up to a prescribed order of images. It also calculates the incident angle of the arriving signal. Experimental arrays were constructed and their performance was measured in real rooms. Real room data were collected in a hard-walled laboratory and a controllable variable acoustics enclosure of similar size, approximately 6 x 6 x 3 m. An extensive speech database was also collected in these two enclosures for future research on microphone arrays. The simulation results are shown to be

SBIR Phase II Final Report: Low cost Autonomous NMR and Multi-sensor Soil Monitoring Instrument

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, David O.

In this 32-month SBIR Phase 2 program, Vista Clara designed, assembled and successfully tested four new NMR instruments for soil moisture measurement and monitoring: An enhanced performance man-portable Dart NMR logging probe and control unit for rapid, mobile measurement in core holes and 2” PVC access wells; A prototype 4-level Dart NMR monitoring probe and prototype multi-sensor soil monitoring control unit for long-term unattended monitoring of soil moisture and other measurements in-situ; A non-invasive 1m x 1m Discus NMR soil moisture sensor with surface based magnet/coil array for rapid measurement of soil moisture in the top 50 cm of themore » subsurface; A non-invasive, ultra-lightweight Earth’s field surface NMR instrument for non-invasive measurement and mapping of soil moisture in the top 3 meters of the subsurface. The Phase 2 research and development achieved most, but not all of our technical objectives. The single-coil Dart in-situ sensor and control unit were fully developed, demonstrated and successfully commercialized within the Phase 2 period of performance. The multi-level version of the Dart probe was designed, assembled and demonstrated in Phase 2, but its final assembly and testing were delayed until close to the end of the Phase 2 performance period, which limited our opportunities for demonstration in field settings. Likewise, the multi-sensor version of the Dart control unit was designed and assembled, but not in time for it to be deployed for any long-term monitoring demonstrations. The prototype ultra-lightweight surface NMR instrument was developed and demonstrated, and this result will be carried forward into the development of a new flexible surface NMR instrument and commercial product in 2018.« less

Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays.

PubMed

Gehring, Tiago V; Vasilaki, Eleni; Giugliano, Michele

2015-01-01

Technological advances of Multielectrode Arrays (MEAs) used for multisite, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable.

NeuroSeek dual-color image processing infrared focal plane array

NASA Astrophysics Data System (ADS)

McCarley, Paul L.; Massie, Mark A.; Baxter, Christopher R.; Huynh, Buu L.

1998-09-01

Several technologies have been developed in recent years to advance the state of the art of IR sensor systems including dual color affordable focal planes, on-focal plane array biologically inspired image and signal processing techniques and spectral sensing techniques. Pacific Advanced Technology (PAT) and the Air Force Research Lab Munitions Directorate have developed a system which incorporates the best of these capabilities into a single device. The 'NeuroSeek' device integrates these technologies into an IR focal plane array (FPA) which combines multicolor Midwave IR/Longwave IR radiometric response with on-focal plane 'smart' neuromorphic analog image processing. The readout and processing integrated circuit very large scale integration chip which was developed under this effort will be hybridized to a dual color detector array to produce the NeuroSeek FPA, which will have the capability to fuse multiple pixel-based sensor inputs directly on the focal plane. Great advantages are afforded by application of massively parallel processing algorithms to image data in the analog domain; the high speed and low power consumption of this device mimic operations performed in the human retina.

Limited Scope Design Study for Multi-Sensor Towbody

DTIC Science & Technology

2016-06-01

FINAL REPORT Limited Scope Design Study for Multi-Sensor Towbody SERDP Project MR-2501 JUNE 2016 Dr. Kevin Williams Tim McGinnis...prepared under contract to the Department of Defense Strategic Environmental Research and Development Program (SERDP). The publication of this...Left Blank REPORT DOCUMENTATION PAGE Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 Form Approved OMB No. 0704-0188 The public

Metal oxide based multisensor array and portable database for field analysis of antioxidants

PubMed Central

Sharpe, Erica; Bradley, Ryan; Frasco, Thalia; Jayathilaka, Dilhani; Marsh, Amanda; Andreescu, Silvana

2014-01-01

We report a novel chemical sensing array based on metal oxide nanoparticles as a portable and inexpensive paper-based colorimetric method for polyphenol detection and field characterization of antioxidant containing samples. Multiple metal oxide nanoparticles with various polyphenol binding properties were used as active sensing materials to develop the sensor array and establish a database of polyphenol standards that include epigallocatechin gallate, gallic acid, resveratrol, and Trolox among others. Unique charge-transfer complexes are formed between each polyphenol and each metal oxide on the surface of individual sensors in the array, creating distinct optically detectable signals which have been quantified and logged into a reference database for polyphenol identification. The field-portable Pantone/X-Rite© CapSure® color reader was used to create this database and to facilitate rapid colorimetric analysis. The use of multiple metal-oxide sensors allows for cross-validation of results and increases accuracy of analysis. The database has enabled successful identification and quantification of antioxidant constituents within real botanical extractions including green tea. Formation of charge-transfer complexes is also correlated with antioxidant activity exhibiting electron transfer capabilities of each polyphenol. The antioxidant activity of each sample was calculated and validated against the oxygen radical absorbance capacity (ORAC) assay showing good comparability. The results indicate that this method can be successfully used for a more comprehensive analysis of antioxidant containing samples as compared to conventional methods. This technology can greatly simplify investigations into plant phenolics and make possible the on-site determination of antioxidant composition and activity in remote locations. PMID:24610993

NASA 1990 Multisensor Airborne Campaigns (MACs) for ecosystem and watershed studies

NASA Technical Reports Server (NTRS)

Wickland, Diane E.; Asrar, Ghassem; Murphy, Robert E.

1991-01-01

The Multisensor Airborne Campaign (MAC) focus within NASA's former Land Processes research program was conceived to achieve the following objectives: to acquire relatively complete, multisensor data sets for well-studied field sites, to add a strong remote sensing science component to ecology-, hydrology-, and geology-oriented field projects, to create a research environment that promotes strong interactions among scientists within the program, and to more efficiently utilize and compete for the NASA fleet of remote sensing aircraft. Four new MAC's were conducted in 1990: the Oregon Transect Ecosystem Research (OTTER) project along an east-west transect through central Oregon, the Forest Ecosystem Dynamics (FED) project at the Northern Experimental Forest in Howland, Maine, the MACHYDRO project in the Mahantango Creek watershed in central Pennsylvania, and the Walnut Gulch project near Tombstone, Arizona. The OTTER project is testing a model that estimates the major fluxes of carbon, nitrogen, and water through temperate coniferous forest ecosystems. The focus in the project is on short time-scale (days-year) variations in ecosystem function. The FED project is concerned with modeling vegetation changes of forest ecosystems using remotely sensed observations to extract biophysical properties of forest canopies. The focus in this project is on long time-scale (decades to millenia) changes in ecosystem structure. The MACHYDRO project is studying the role of soil moisture and its regulating effects on hydrologic processes. The focus of the study is to delineate soil moisture differences within a basin and their changes with respect to evapotranspiration, rainfall, and streamflow. The Walnut Gulch project is focused on the effects of soil moisture in the energy and water balance of arid and semiarid ecosystems and their feedbacks to the atmosphere via thermal forcing.

A Vision for an International Multi-Sensor Snow Observing Mission

NASA Technical Reports Server (NTRS)

Kim, Edward

2015-01-01

Discussions within the international snow remote sensing community over the past two years have led to encouraging consensus regarding the broad outlines of a dedicated snow observing mission. The primary consensus - that since no single sensor type is satisfactory across all snow types and across all confounding factors, a multi-sensor approach is required - naturally leads to questions about the exact mix of sensors, required accuracies, and so on. In short, the natural next step is to collect such multi-sensor snow observations (with detailed ground truth) to enable trade studies of various possible mission concepts. Such trade studies must assess the strengths and limitations of heritage as well as newer measurement techniques with an eye toward natural sensitivity to desired parameters such as snow depth and/or snow water equivalent (SWE) in spite of confounding factors like clouds, lack of solar illumination, forest cover, and topography, measurement accuracy, temporal and spatial coverage, technological maturity, and cost.

Total focusing method with correlation processing of antenna array signals

NASA Astrophysics Data System (ADS)

Kozhemyak, O. A.; Bortalevich, S. I.; Loginov, E. L.; Shinyakov, Y. A.; Sukhorukov, M. P.

2018-03-01

The article proposes a method of preliminary correlation processing of a complete set of antenna array signals used in the image reconstruction algorithm. The results of experimental studies of 3D reconstruction of various reflectors using and without correlation processing are presented in the article. Software ‘IDealSystem3D’ by IDeal-Technologies was used for experiments. Copper wires of different diameters located in a water bath were used as a reflector. The use of correlation processing makes it possible to obtain more accurate reconstruction of the image of the reflectors and to increase the signal-to-noise ratio. The experimental results were processed using an original program. This program allows varying the parameters of the antenna array and sampling frequency.

A Method for Improving the Pose Accuracy of a Robot Manipulator Based on Multi-Sensor Combined Measurement and Data Fusion

PubMed Central

Liu, Bailing; Zhang, Fumin; Qu, Xinghua

2015-01-01

An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%∼78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 × 0.8 × 1 ∼ 2 × 0.8 × 1 m in the field of view (FOV) is indicated by the experimental results. PMID:25850067

An enhanced data visualization method for diesel engine malfunction classification using multi-sensor signals.

PubMed

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-10-21

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine.

An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals

PubMed Central

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-01-01

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine. PMID:26506347

Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network

NASA Technical Reports Server (NTRS)

Navarro, Robert

2006-01-01

The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..

Array Processing in the Cloud: the rasdaman Approach

NASA Astrophysics Data System (ADS)

Merticariu, Vlad; Dumitru, Alex

2015-04-01

The multi-dimensional array data model is gaining more and more attention when dealing with Big Data challenges in a variety of domains such as climate simulations, geographic information systems, medical imaging or astronomical observations. Solutions provided by classical Big Data tools such as Key-Value Stores and MapReduce, as well as traditional relational databases, proved to be limited in domains associated with multi-dimensional data. This problem has been addressed by the field of array databases, in which systems provide database services for raster data, without imposing limitations on the number of dimensions that a dataset can have. Examples of datasets commonly handled by array databases include 1-dimensional sensor data, 2-D satellite imagery, 3-D x/y/t image time series as well as x/y/z geophysical voxel data, and 4-D x/y/z/t weather data. And this can grow as large as simulations of the whole universe when it comes to astrophysics. rasdaman is a well established array database, which implements many optimizations for dealing with large data volumes and operation complexity. Among those, the latest one is intra-query parallelization support: a network of machines collaborate for answering a single array database query, by dividing it into independent sub-queries sent to different servers. This enables massive processing speed-ups, which promise solutions to research challenges on multi-Petabyte data cubes. There are several correlated factors which influence the speedup that intra-query parallelisation brings: the number of servers, the capabilities of each server, the quality of the network, the availability of the data to the server that needs it in order to compute the result and many more. In the effort of adapting the engine to cloud processing patterns, two main components have been identified: one that handles communication and gathers information about the arrays sitting on every server, and a processing unit responsible with dividing work

A novel scalable manufacturing process for the production of hydrogel-forming microneedle arrays

PubMed Central

Lutton, Rebecca E.M.; Larrañeta, Eneko; Kearney, Mary-Carmel; Boyd, Peter; Woolfson, A.David; Donnelly, Ryan F.

2015-01-01

A novel manufacturing process for fabricating microneedle arrays (MN) has been designed and evaluated. The prototype is able to successfully produce 14 × 14 MN arrays and is easily capable of scale-up, enabling the transition from laboratory to industry and subsequent commercialisation. The method requires the custom design of metal MN master templates to produce silicone MN moulds using an injection moulding process. The MN arrays produced using this novel method was compared with centrifugation, the traditional method of producing aqueous hydrogel-forming MN arrays. The results proved that there was negligible difference between either methods, with each producing MN arrays with comparable quality. Both types of MN arrays can be successfully inserted in a skin simulant. In both cases the insertion depth was approximately 60% of the needle length and the height reduction after insertion was in both cases approximately 3%. PMID:26302858

Matched Field Processing Based on Least Squares with a Small Aperture Hydrophone Array.

PubMed

Wang, Qi; Wang, Yingmin; Zhu, Guolei

2016-12-30

The receiver hydrophone array is the signal front-end and plays an important role in matched field processing, which usually covers the whole water column from the sea surface to the bottom. Such a large aperture array is very difficult to realize. To solve this problem, an approach called matched field processing based on least squares with a small aperture hydrophone array is proposed, which decomposes the received acoustic fields into depth function matrix and amplitudes of the normal modes at the beginning. Then all the mode amplitudes are estimated using the least squares in the sense of minimum norm, and the amplitudes estimated are used to recalculate the received acoustic fields of the small aperture array, which means the recalculated ones contain more environmental information. In the end, lots of numerical experiments with three small aperture arrays are processed in the classical shallow water, and the performance of matched field passive localization is evaluated. The results show that the proposed method can make the recalculated fields contain more acoustic information of the source, and the performance of matched field passive localization with small aperture array is improved, so the proposed algorithm is proved to be effective.

Matched Field Processing Based on Least Squares with a Small Aperture Hydrophone Array

PubMed Central

Wang, Qi; Wang, Yingmin; Zhu, Guolei

2016-01-01

The receiver hydrophone array is the signal front-end and plays an important role in matched field processing, which usually covers the whole water column from the sea surface to the bottom. Such a large aperture array is very difficult to realize. To solve this problem, an approach called matched field processing based on least squares with a small aperture hydrophone array is proposed, which decomposes the received acoustic fields into depth function matrix and amplitudes of the normal modes at the beginning. Then all the mode amplitudes are estimated using the least squares in the sense of minimum norm, and the amplitudes estimated are used to recalculate the received acoustic fields of the small aperture array, which means the recalculated ones contain more environmental information. In the end, lots of numerical experiments with three small aperture arrays are processed in the classical shallow water, and the performance of matched field passive localization is evaluated. The results show that the proposed method can make the recalculated fields contain more acoustic information of the source, and the performance of matched field passive localization with small aperture array is improved, so the proposed algorithm is proved to be effective. PMID:28042828

Statistical generation of training sets for measuring NO3(-), NH4(+) and major ions in natural waters using an ion selective electrode array.

PubMed

Mueller, Amy V; Hemond, Harold F

2016-05-18

Knowledge of ionic concentrations in natural waters is essential to understand watershed processes. Inorganic nitrogen, in the form of nitrate and ammonium ions, is a key nutrient as well as a participant in redox, acid-base, and photochemical processes of natural waters, leading to spatiotemporal patterns of ion concentrations at scales as small as meters or hours. Current options for measurement in situ are costly, relying primarily on instruments adapted from laboratory methods (e.g., colorimetric, UV absorption); free-standing and inexpensive ISE sensors for NO3(-) and NH4(+) could be attractive alternatives if interferences from other constituents were overcome. Multi-sensor arrays, coupled with appropriate non-linear signal processing, offer promise in this capacity but have not yet successfully achieved signal separation for NO3(-) and NH4(+)in situ at naturally occurring levels in unprocessed water samples. A novel signal processor, underpinned by an appropriate sensor array, is proposed that overcomes previous limitations by explicitly integrating basic chemical constraints (e.g., charge balance). This work further presents a rationalized process for the development of such in situ instrumentation for NO3(-) and NH4(+), including a statistical-modeling strategy for instrument design, training/calibration, and validation. Statistical analysis reveals that historical concentrations of major ionic constituents in natural waters across New England strongly covary and are multi-modal. This informs the design of a statistically appropriate training set, suggesting that the strong covariance of constituents across environmental samples can be exploited through appropriate signal processing mechanisms to further improve estimates of minor constituents. Two artificial neural network architectures, one expanded to incorporate knowledge of basic chemical constraints, were tested to process outputs of a multi-sensor array, trained using datasets of varying degrees of

Research on a Defects Detection Method in the Ferrite Phase Shifter Cementing Process Based on a Multi-Sensor Prognostic and Health Management (PHM) System.

PubMed

Wan, Bo; Fu, Guicui; Li, Yanruoyue; Zhao, Youhu

2016-08-10

The cementing manufacturing process of ferrite phase shifters has the defect that cementing strength is insufficient and fractures always appear. A detection method of these defects was studied utilizing the multi-sensors Prognostic and Health Management (PHM) theory. Aiming at these process defects, the reasons that lead to defects are analyzed in this paper. In the meanwhile, the key process parameters were determined and Differential Scanning Calorimetry (DSC) tests during the cure process of resin cementing were carried out. At the same time, in order to get data on changing cementing strength, multiple-group cementing process tests of different key process parameters were designed and conducted. A relational model of cementing strength and cure temperature, time and pressure was established, by combining data of DSC and process tests as well as based on the Avrami formula. Through sensitivity analysis for three process parameters, the on-line detection decision criterion and the process parameters which have obvious impact on cementing strength were determined. A PHM system with multiple temperature and pressure sensors was established on this basis, and then, on-line detection, diagnosis and control for ferrite phase shifter cementing process defects were realized. It was verified by subsequent process that the on-line detection system improved the reliability of the ferrite phase shifter cementing process and reduced the incidence of insufficient cementing strength defects.

Solution-processed single-wall carbon nanotube transistor arrays for wearable display backplanes

NASA Astrophysics Data System (ADS)

Kang, Byeong-Cheol; Ha, Tae-Jun

2018-01-01

In this paper, we demonstrate solution-processed single-wall carbon nanotube thin-film transistor (SWCNT-TFT) arrays with polymeric gate dielectrics on the polymeric substrates for wearable display backplanes, which can be directly attached to the human body. The optimized SWCNT-TFTs without any buffer layer on flexible substrates exhibit a linear field-effect mobility of 1.5cm2/V-s and a threshold voltage of around 0V. The statistical plot of the key device metrics extracted from 35 SWCNT-TFTs which were fabricated in different batches at different times conclusively support that we successfully demonstrated high-performance solution-processed SWCNT-TFT arrays which demand excellent uniformity in the device performance. We also investigate the operational stability of wearable SWCNT-TFT arrays against an applied strain of up to 40%, which is the essential for a harsh degree of strain on human body. We believe that the demonstration of flexible SWCNT-TFT arrays which were fabricated by all solution-process except the deposition of metal electrodes at process temperature below 130oC can open up new routes for wearable display backplanes.

A novel scalable manufacturing process for the production of hydrogel-forming microneedle arrays.

PubMed

Lutton, Rebecca E M; Larrañeta, Eneko; Kearney, Mary-Carmel; Boyd, Peter; Woolfson, A David; Donnelly, Ryan F

2015-10-15

A novel manufacturing process for fabricating microneedle arrays (MN) has been designed and evaluated. The prototype is able to successfully produce 14×14 MN arrays and is easily capable of scale-up, enabling the transition from laboratory to industry and subsequent commercialisation. The method requires the custom design of metal MN master templates to produce silicone MN moulds using an injection moulding process. The MN arrays produced using this novel method was compared with centrifugation, the traditional method of producing aqueous hydrogel-forming MN arrays. The results proved that there was negligible difference between either methods, with each producing MN arrays with comparable quality. Both types of MN arrays can be successfully inserted in a skin simulant. In both cases the insertion depth was approximately 60% of the needle length and the height reduction after insertion was in both cases approximately 3%. Copyright © 2015 Elsevier B.V. All rights reserved.

Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics.

PubMed

Herrero, Héctor; Outón, Jose Luis; Puerto, Mildred; Sallé, Damien; López de Ipiña, Karmele

2017-05-31

This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques.

Signal Processing for a Lunar Array: Minimizing Power Consumption

NASA Technical Reports Server (NTRS)

D'Addario, Larry; Simmons, Samuel

2011-01-01

Motivation for the study is: (1) Lunar Radio Array for low frequency, high redshift Dark Ages/Epoch of Reionization observations (z =6-50, f=30-200 MHz) (2) High precision cosmological measurements of 21 cm H I line fluctuations (3) Probe universe before first star formation and provide information about the Intergalactic Medium and evolution of large scale structures (5) Does the current cosmological model accurately describe the Universe before reionization? Lunar Radio Array is for (1) Radio interferometer based on the far side of the moon (1a) Necessary for precision measurements, (1b) Shielding from earth-based and solar RFI (12) No permanent ionosphere, (2) Minimum collecting area of approximately 1 square km and brightness sensitivity 10 mK (3)Several technologies must be developed before deployment The power needed to process signals from a large array of nonsteerable elements is not prohibitive, even for the Moon, and even in current technology. Two different concepts have been proposed: (1) Dark Ages Radio Interferometer (DALI) (2)( Lunar Array for Radio Cosmology (LARC)

Multisensor System for Isotemporal Measurements to Assess Indoor Climatic Conditions in Poultry Farms

PubMed Central

Bustamante, Eliseo; Guijarro, Enrique; García-Diego, Fernando-Juan; Balasch, Sebastián; Hospitaler, Antonio; Torres, Antonio G.

2012-01-01

The rearing of poultry for meat production (broilers) is an agricultural food industry with high relevance to the economy and development of some countries. Periodic episodes of extreme climatic conditions during the summer season can cause high mortality among birds, resulting in economic losses. In this context, ventilation systems within poultry houses play a critical role to ensure appropriate indoor climatic conditions. The objective of this study was to develop a multisensor system to evaluate the design of the ventilation system in broiler houses. A measurement system equipped with three types of sensors: air velocity, temperature and differential pressure was designed and built. The system consisted in a laptop, a data acquisition card, a multiplexor module and a set of 24 air temperature, 24 air velocity and two differential pressure sensors. The system was able to acquire up to a maximum of 128 signals simultaneously at 5 second intervals. The multisensor system was calibrated under laboratory conditions and it was then tested in field tests. Field tests were conducted in a commercial broiler farm under four different pressure and ventilation scenarios in two sections within the building. The calibration curves obtained under laboratory conditions showed similar regression coefficients among temperature, air velocity and pressure sensors and a high goodness fit (R2 = 0.99) with the reference. Under field test conditions, the multisensor system showed a high number of input signals from different locations with minimum internal delay in acquiring signals. The variation among air velocity sensors was not significant. The developed multisensor system was able to integrate calibrated sensors of temperature, air velocity and differential pressure and operated succesfully under different conditions in a mechanically-ventilated broiler farm. This system can be used to obtain quasi-instantaneous fields of the air velocity and temperature, as well as differential

Parallel processing in a host plus multiple array processor system for radar

NASA Technical Reports Server (NTRS)

Barkan, B. Z.

1983-01-01

Host plus multiple array processor architecture is demonstrated to yield a modular, fast, and cost-effective system for radar processing. Software methodology for programming such a system is developed. Parallel processing with pipelined data flow among the host, array processors, and discs is implemented. Theoretical analysis of performance is made and experimentally verified. The broad class of problems to which the architecture and methodology can be applied is indicated.

Multi-Sensor Data Fusion Project

DTIC Science & Technology

2000-02-28

seismic network by detecting T phases generated by underground events ( generally earthquakes ) and associating these phases to seismic events. The...between underwater explosions (H), underground sources, mostly earthquake - generated (7), and noise detections (N). The phases classified as H are the only...processing for infrasound sensors is most similar to seismic array processing with the exception that the detections are based on a more sophisticated

Hypothesis Testing Using Spatially Dependent Heavy Tailed Multisensor Data

DTIC Science & Technology

2014-12-01

Office of Research 113 Bowne Hall Syracuse, NY 13244 -1200 ABSTRACT HYPOTHESIS TESTING USING SPATIALLY DEPENDENT HEAVY-TAILED MULTISENSOR DATA Report...consistent with the null hypothesis of linearity and can be used to estimate the distribution of a test statistic that can discrimi- nate between the null... Test for nonlinearity. Histogram is generated using the surrogate data. The statistic of the original time series is represented by the solid line

The Use of a Microcomputer Based Array Processor for Real Time Laser Velocimeter Data Processing

NASA Technical Reports Server (NTRS)

Meyers, James F.

1990-01-01

The application of an array processor to laser velocimeter data processing is presented. The hardware is described along with the method of parallel programming required by the array processor. A portion of the data processing program is described in detail. The increase in computational speed of a microcomputer equipped with an array processor is illustrated by comparative testing with a minicomputer.

Optical implementation of systolic array processing

NASA Technical Reports Server (NTRS)

Caulfield, H. J.; Rhodes, W. T.; Foster, M. J.; Horvitz, S.

1981-01-01

Algorithms for matrix vector multiplication are implemented using acousto-optic cells for multiplication and input data transfer and using charge coupled devices detector arrays for accumulation and output of the results. No two dimensional matrix mask is required; matrix changes are implemented electronically. A system for multiplying a 50 component nonnegative real vector by a 50 by 50 nonnegative real matrix is described. Modifications for bipolar real and complex valued processing are possible, as are extensions to matrix-matrix multiplication and multiplication of a vector by multiple matrices.

A Novel Energy-Efficient Multi-Sensor Fusion Wake-Up Control Strategy Based on a Biomimetic Infectious-Immune Mechanism for Target Tracking.

PubMed

Zhou, Jie; Liang, Yan; Shen, Qiang; Feng, Xiaoxue; Pan, Quan

2018-04-18

A biomimetic distributed infection-immunity model (BDIIM), inspired by the immune mechanism of an infected organism, is proposed in order to achieve a high-efficiency wake-up control strategy based on multi-sensor fusion for target tracking. The resultant BDIIM consists of six sub-processes reflecting the infection-immunity mechanism: occurrence probabilities of direct-infection (DI) and cross-infection (CI), immunity/immune-deficiency of DI and CI, pathogen amount of DI and CI, immune cell production, immune memory, and pathogen accumulation under immunity state. Furthermore, a corresponding relationship between the BDIIM and sensor wake-up control is established to form the collaborative wake-up method. Finally, joint surveillance and target tracking are formulated in the simulation, in which we show that the energy cost and position tracking error are reduced to 50.8% and 78.9%, respectively. Effectiveness of the proposed BDIIM algorithm is shown, and this model is expected to have a significant role in guiding the performance improvement of multi-sensor networks.

Subspace Dimensionality: A Tool for Automated QC in Seismic Array Processing

NASA Astrophysics Data System (ADS)

Rowe, C. A.; Stead, R. J.; Begnaud, M. L.

2013-12-01

Because of the great resolving power of seismic arrays, the application of automated processing to array data is critically important in treaty verification work. A significant problem in array analysis is the inclusion of bad sensor channels in the beamforming process. We are testing an approach to automated, on-the-fly quality control (QC) to aid in the identification of poorly performing sensor channels prior to beam-forming in routine event detection or location processing. The idea stems from methods used for large computer servers, when monitoring traffic at enormous numbers of nodes is impractical on a node-by node basis, so the dimensionality of the node traffic is instead monitoried for anomalies that could represent malware, cyber-attacks or other problems. The technique relies upon the use of subspace dimensionality or principal components of the overall system traffic. The subspace technique is not new to seismology, but its most common application has been limited to comparing waveforms to an a priori collection of templates for detecting highly similar events in a swarm or seismic cluster. In the established template application, a detector functions in a manner analogous to waveform cross-correlation, applying a statistical test to assess the similarity of the incoming data stream to known templates for events of interest. In our approach, we seek not to detect matching signals, but instead, we examine the signal subspace dimensionality in much the same way that the method addresses node traffic anomalies in large computer systems. Signal anomalies recorded on seismic arrays affect the dimensional structure of the array-wide time-series. We have shown previously that this observation is useful in identifying real seismic events, either by looking at the raw signal or derivatives thereof (entropy, kurtosis), but here we explore the effects of malfunctioning channels on the dimension of the data and its derivatives, and how to leverage this effect for

Medical decision-making inspired from aerospace multisensor data fusion concepts.

PubMed

Pombo, Nuno; Bousson, Kouamana; Araújo, Pedro; Viana, Joaquim

2015-01-01

In recent years, Internet-delivered treatments have been largely used for pain monitoring, offering healthcare professionals and patients the ability to interact anywhere and at any time. Electronic diaries have been increasingly adopted as the preferred methodology to collect data related to pain intensity and symptoms, replacing traditional pen-and-paper diaries. This article presents a multisensor data fusion methodology based on the capabilities provided by aerospace systems to evaluate the effects of electronic and pen-and-paper diaries on pain. We examined English-language studies of randomized controlled trials that use computerized systems and the Internet to collect data about chronic pain complaints. These studies were obtained from three data sources: BioMed Central, PubMed Central and ScienceDirect from the year 2000 until 30 June 2012. Based on comparisons of the reported pain intensity collected during pre- and post-treatment in both the control and intervention groups, the proposed multisensor data fusion model revealed that the benefits of technology and pen-and-paper are qualitatively equivalent [Formula: see text]. We conclude that the proposed model is suitable, intelligible, easy to implement, time efficient and resource efficient.

Monolithic optical phased-array transceiver in a standard SOI CMOS process.

PubMed

Abediasl, Hooman; Hashemi, Hossein

2015-03-09

Monolithic microwave phased arrays are turning mainstream in automotive radars and high-speed wireless communications fulfilling Gordon Moores 1965 prophecy to this effect. Optical phased arrays enable imaging, lidar, display, sensing, and holography. Advancements in fabrication technology has led to monolithic nanophotonic phased arrays, albeit without independent phase and amplitude control ability, integration with electronic circuitry, or including receive and transmit functions. We report the first monolithic optical phased array transceiver with independent control of amplitude and phase for each element using electronic circuitry that is tightly integrated with the nanophotonic components on one substrate using a commercial foundry CMOS SOI process. The 8 × 8 phased array chip includes thermo-optical tunable phase shifters and attenuators, nano-photonic antennas, and dedicated control electronics realized using CMOS transistors. The complex chip includes over 300 distinct optical components and over 74,000 distinct electrical components achieving the highest level of integration for any electronic-photonic system.

Gallium arsenide processing for gate array logic

NASA Technical Reports Server (NTRS)

Cole, Eric D.

1989-01-01

The development of a reliable and reproducible GaAs process was initiated for applications in gate array logic. Gallium Arsenide is an extremely important material for high speed electronic applications in both digital and analog circuits since its electron mobility is 3 to 5 times that of silicon, this allows for faster switching times for devices fabricated with it. Unfortunately GaAs is an extremely difficult material to process with respect to silicon and since it includes the arsenic component GaAs can be quite dangerous (toxic) especially during some heating steps. The first stage of the research was directed at developing a simple process to produce GaAs MESFETs. The MESFET (MEtal Semiconductor Field Effect Transistor) is the most useful, practical and simple active device which can be fabricated in GaAs. It utilizes an ohmic source and drain contact separated by a Schottky gate. The gate width is typically a few microns. Several process steps were required to produce a good working device including ion implantation, photolithography, thermal annealing, and metal deposition. A process was designed to reduce the total number of steps to a minimum so as to reduce possible errors. The first run produced no good devices. The problem occurred during an aluminum etch step while defining the gate contacts. It was found that the chemical etchant attacked the GaAs causing trenching and subsequent severing of the active gate region from the rest of the device. Thus all devices appeared as open circuits. This problem is being corrected and since it was the last step in the process correction should be successful. The second planned stage involves the circuit assembly of the discrete MESFETs into logic gates for test and analysis. Finally the third stage is to incorporate the designed process with the tested circuit in a layout that would produce the gate array as a GaAs integrated circuit.

SVM-based multi-sensor fusion for free-living physical activity assessment.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty S

2011-01-01

This paper presents a sensor fusion method for assessing physical activity (PA) of human subjects, based on the support vector machines (SVMs). Specifically, acceleration and ventilation measured by a wearable multi-sensor device on 50 test subjects performing 13 types of activities of varying intensities are analyzed, from which the activity types and related energy expenditures are derived. The result shows that the method correctly recognized the 13 activity types 84.7% of the time, which is 26% higher than using a hip accelerometer alone. Also, the method predicted the associated energy expenditure with a root mean square error of 0.43 METs, 43% lower than using a hip accelerometer alone. Furthermore, the fusion method was effective in reducing the subject-to-subject variability (standard deviation of recognition accuracies across subjects) in activity recognition, especially when data from the ventilation sensor was added to the fusion model. These results demonstrate that the multi-sensor fusion technique presented is more effective in assessing activities of varying intensities than the traditional accelerometer-alone based methods.

MR 201104: Evaluation of Discrimination Technologies and Classification Results and MR 201157: Demonstration of MetalMapper Static Data Acquisition and Data Analysis

DTIC Science & Technology

2016-09-23

Acquisition and Data Analysis). EMI sensors, MetalMapper, man-portable Time-domain Electromagnetic Multi-sensor Towed Array Detection System (TEMTADS...California Department of Toxic Substances Control EM61 EM61-MK2 EMI electromagnetic induction ESTCP Environmental Security Technology Certification...SOP Standard Operating Procedure v TEMTADS Time-domain Electromagnetic Multi-sensor Towed Array Detection System man-portable 2x2 TOI target(s

Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics

PubMed Central

Herrero, Héctor; Outón, Jose Luis; Puerto, Mildred; Sallé, Damien; López de Ipiña, Karmele

2017-01-01

This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques. PMID:28561750

Multisensor Fire Observations

NASA Technical Reports Server (NTRS)

Boquist, C.

2004-01-01

This DVD includes animations of multisensor fire observations from the following satellite sources: Landsat, GOES, TOMS, Terra, QuikSCAT, and TRMM. Some of the animations are included in multiple versions of a short video presentation on the DVD which focuses on the Hayman, Rodeo-Chediski, and Biscuit fires during the 2002 North American fire season. In one version of the presentation, MODIS, TRMM, GOES, and QuikSCAT data are incorporated into the animations of these wildfires. These data products provided rain, wind, cloud, and aerosol data on the fires, and monitored the smoke and destruction created by them. Another presentation on the DVD consists of a panel discussion, in which experts from academia, NASA, and the U.S. Forest Service answer questions on the role of NASA in fighting forest fires, the role of the Terra satellite and its instruments, including the Moderate Resolution Imaging Spectroradiometer (MODIS), in fire fighting decision making, and the role of fire in the Earth's climate. The third section of the DVD features several animations of fires over the years 2001-2003, including animations of global and North American fires, and specific fires from 2003 in California, Washington, Montana, and Arizona.

A Multitemporal, Multisensor Approach to Mapping the Canadian Boreal Forest

NASA Astrophysics Data System (ADS)

Reith, Ernest

The main anthropogenic source of CO2 emissions is the combustion of fossil fuels, while the clearing and burning of forests contribute significant amounts as well. Vegetation represents a major reservoir for terrestrial carbon stocks, and improving our ability to inventory vegetation will enhance our understanding of the impacts of land cover and climate change on carbon stocks and fluxes. These relationships may be an indication of a series of troubling biosphere-atmospheric feedback mechanisms that need to be better understood and modeled. Valuable land cover information can be provided to the global climate change modeling community using advanced remote sensing capabilities such as Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR). Individually and synergistically, data were successfully used to characterize the complex nature of the Canadian boreal forest land cover types. The multiple endmember spectral mixture analysis process was applied against seasonal AVIRIS data to produce species-level vegetated land cover maps of two study sites in the Canadian boreal forest: Old Black Spruce (OBS) and Old Jack Pine (OJP). The highest overall accuracy was assessed to be at least 66% accurate to the available reference map, providing evidence that high-quality, species-level land cover mapping of the Canadian boreal forest is achievable at accuracy levels greater than other previous research efforts in the region. Backscatter information from multichannel, polarimetric SAR utilizing a binary decision tree-based classification technique methodology was moderately successfully applied to AIRSAR to produce maps of the boreal land cover types at both sites, with overall accuracies at least 59%. A process, centered around noise whitening and principal component analysis features of the minimum noise fraction transform, was implemented to leverage synergies contained within spatially coregistered multitemporal and

SenseCube--A Novel Inexpensive Wireless Multisensor for Physics Lab Experimentations

ERIC Educational Resources Information Center

Mehta, Vedant; Lane, Charles D.

2018-01-01

SenseCube is a multisensor capable of measuring many different real-time events and changes in environment. Most conventional sensors used in introductory-physics labs use their own software and have wires that must be attached to a computer or an alternate device to analyze the data. This makes the standard sensors time consuming, tedious, and…

High resolution beamforming on large aperture vertical line arrays: Processing synthetic data

NASA Astrophysics Data System (ADS)

Tran, Jean-Marie Q.; Hodgkiss, William S.

1990-09-01

This technical memorandum studies the beamforming of large aperture line arrays deployed vertically in the water column. The work concentrates on the use of high resolution techniques. Two processing strategies are envisioned: (1) full aperture coherent processing which offers in theory the best processing gain; and (2) subaperture processing which consists in extracting subapertures from the array and recombining the angular spectra estimated from these subarrays. The conventional beamformer, the minimum variance distortionless response (MVDR) processor, the multiple signal classification (MUSIC) algorithm and the minimum norm method are used in this study. To validate the various processing techniques, the ATLAS normal mode program is used to generate synthetic data which constitute a realistic signals environment. A deep-water, range-independent sound velocity profile environment, characteristic of the North-East Pacific, is being studied for two different 128 sensor arrays: a very long one cut for 30 Hz and operating at 20 Hz; and a shorter one cut for 107 Hz and operating at 100 Hz. The simulated sound source is 5 m deep. The full aperture and subaperture processing are being implemented with curved and plane wavefront replica vectors. The beamforming results are examined and compared to the ray-theory results produced by the generic sonar model.

Systolic array processing of the sequential decoding algorithm

NASA Technical Reports Server (NTRS)

Chang, C. Y.; Yao, K.

1989-01-01

A systolic array processing technique is applied to implementing the stack algorithm form of the sequential decoding algorithm. It is shown that sorting, a key function in the stack algorithm, can be efficiently realized by a special type of systolic arrays known as systolic priority queues. Compared to the stack-bucket algorithm, this approach is shown to have the advantages that the decoding always moves along the optimal path, that it has a fast and constant decoding speed and that its simple and regular hardware architecture is suitable for VLSI implementation. Three types of systolic priority queues are discussed: random access scheme, shift register scheme and ripple register scheme. The property of the entries stored in the systolic priority queue is also investigated. The results are applicable to many other basic sorting type problems.

The Very Large Array Data Processing Pipeline

NASA Astrophysics Data System (ADS)

Kent, Brian R.; Masters, Joseph S.; Chandler, Claire J.; Davis, Lindsey E.; Kern, Jeffrey S.; Ott, Juergen; Schinzel, Frank K.; Medlin, Drew; Muders, Dirk; Williams, Stewart; Geers, Vincent C.; Momjian, Emmanuel; Butler, Bryan J.; Nakazato, Takeshi; Sugimoto, Kanako

2018-01-01

We present the VLA Pipeline, software that is part of the larger pipeline processing framework used for the Karl G. Jansky Very Large Array (VLA), and Atacama Large Millimeter/sub-millimeter Array (ALMA) for both interferometric and single dish observations.Through a collection of base code jointly used by the VLA and ALMA, the pipeline builds a hierarchy of classes to execute individual atomic pipeline tasks within the Common Astronomy Software Applications (CASA) package. Each pipeline task contains heuristics designed by the team to actively decide the best processing path and execution parameters for calibration and imaging. The pipeline code is developed and written in Python and uses a "context" structure for tracking the heuristic decisions and processing results. The pipeline "weblog" acts as the user interface in verifying the quality assurance of each calibration and imaging stage. The majority of VLA scheduling blocks above 1 GHz are now processed with the standard continuum recipe of the pipeline and offer a calibrated measurement set as a basic data product to observatory users. In addition, the pipeline is used for processing data from the VLA Sky Survey (VLASS), a seven year community-driven endeavor started in September 2017 to survey the entire sky down to a declination of -40 degrees at S-band (2-4 GHz). This 5500 hour next-generation large radio survey will explore the time and spectral domains, relying on pipeline processing to generate calibrated measurement sets, polarimetry, and imaging data products that are available to the astronomical community with no proprietary period. Here we present an overview of the pipeline design philosophy, heuristics, and calibration and imaging results produced by the pipeline. Future development will include the testing of spectral line recipes, low signal-to-noise heuristics, and serving as a testing platform for science ready data products.The pipeline is developed as part of the CASA software package by an

Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources.

PubMed

Gao, Xiang; Acar, Levent

2016-07-04

This paper addresses the problem of mapping odor distribution derived from a chemical source using multi-sensor integration and reasoning system design. Odor localization is the problem of finding the source of an odor or other volatile chemical. Most localization methods require a mobile vehicle to follow an odor plume along its entire path, which is time consuming and may be especially difficult in a cluttered environment. To solve both of the above challenges, this paper proposes a novel algorithm that combines data from odor and anemometer sensors, and combine sensors' data at different positions. Initially, a multi-sensor integration method, together with the path of airflow was used to map the pattern of odor particle movement. Then, more sensors are introduced at specific regions to determine the probable location of the odor source. Finally, the results of odor source location simulation and a real experiment are presented.

Acoustic Vector-Sensor Array Processing

DTIC Science & Technology

2010-06-01

NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS( ES ) Massachusetts Institute...ADDRESS( ES ) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public...section shows, vector-sensor arrays are more versatile than arrays of only pressure-sensors. Exploiting this versatility raises a number of ques

Microphone Array

NASA Astrophysics Data System (ADS)

Bader, Rolf

This chapter deals with microphone arrays. It is arranged according to the different methods available to proceed through the different problems and through the different mathematical methods. After discussing general properties of different array types, such as plane arrays, spherical arrays, or scanning arrays, it proceeds to the signal processing tools that are most used in speech processing. In the third section, backpropagating methods based on the Helmholtz-Kirchhoff integral are discussed, which result in spatial radiation patterns of vibrating bodies or air.

Multispectral multisensor image fusion using wavelet transforms

USGS Publications Warehouse

Lemeshewsky, George P.

1999-01-01

Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.

Dimpled ball grid array process development for space flight applications

NASA Technical Reports Server (NTRS)

Barr, S. L.; Mehta, A.

2000-01-01

A 472 dimpled ball grid array (D-BGA) package has not been used in past space flight environments, therefore it was necessary to develop a process that would yield robust and reliable solder joints. The process developing assembly, inspection and rework techniques, were verified by conducting environmental tests. Since the 472 D-BGA packages passed the above environmental tests within the specifications, the process was successfully developed for space flight electronics.

Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation

NASA Astrophysics Data System (ADS)

Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.

2018-01-01

A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.

Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system

USGS Publications Warehouse

Bera, Maitreyee; Ortel, Terry W.

2018-01-12

The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.

Monitoring and Evaluation of Alcoholic Fermentation Processes Using a Chemocapacitor Sensor Array

PubMed Central

Oikonomou, Petros; Raptis, Ioannis; Sanopoulou, Merope

2014-01-01

The alcoholic fermentation of Savatiano must variety was initiated under laboratory conditions and monitored daily with a gas sensor array without any pre-treatment steps. The sensor array consisted of eight interdigitated chemocapacitors (IDCs) coated with specific polymers. Two batches of fermented must were tested and also subjected daily to standard chemical analysis. The chemical composition of the two fermenting musts differed from day one of laboratory monitoring (due to different storage conditions of the musts) and due to a deliberate increase of the acetic acid content of one of the musts, during the course of the process, in an effort to spoil the fermenting medium. Sensor array responses to the headspace of the fermenting medium were compared with those obtained either for pure or contaminated samples with controlled concentrations of standard ethanol solutions of impurities. Results of data processing with Principal Component Analysis (PCA), demonstrate that this sensing system could discriminate between a normal and a potential spoiled grape must fermentation process, so this gas sensing system could be potentially applied during wine production as an auxiliary qualitative control instrument. PMID:25184490

Stochastic model for threat assessment in multi-sensor defense system

NASA Astrophysics Data System (ADS)

Wang, Yongcheng; Wang, Hongfei; Jiang, Changsheng

2007-11-01

This paper puts forward a stochastic model for target detecting and tracking in multi-sensor defense systems and applies the Lanchester differential equations to threat assessment in combat. The two different modes of targets tracking and their respective Lanchester differential equations are analyzed and established. By use of these equations, we could briefly estimate the loss of each combat side and accordingly get the threat estimation results, given the situation analysis is accomplished.

Microphone Array Phased Processing System (MAPPS): Version 4.0 Manual

NASA Technical Reports Server (NTRS)

Watts, Michael E.; Mosher, Marianne; Barnes, Michael; Bardina, Jorge

1999-01-01

A processing system has been developed to meet increasing demands for detailed noise measurement of individual model components. The Microphone Array Phased Processing System (MAPPS) uses graphical user interfaces to control all aspects of data processing and visualization. The system uses networked parallel computers to provide noise maps at selected frequencies in a near real-time testing environment. The system has been successfully used in the NASA Ames 7- by 10-Foot Wind Tunnel.

Transform-Based Wideband Array Processing

DTIC Science & Technology

1992-01-31

Breusch and Pagan [2], it is possible to test which model, M,€, 0 AR or random coefficient, will better fit typical array data. Li The test indicates that...bearing estimation problems," Proc. IEEE, vol. 70, no. 9, pp. 1018-1028, 1982. (2] T. S. Breusch and A. R. Pagan , "A simple test for het...cor- relations do not obey an AR relationship across the array; relations in the observations. Through the use of a binary hypothesis test , it is

Effects of process parameters on the molding quality of the micro-needle array

NASA Astrophysics Data System (ADS)

Qiu, Z. J.; Ma, Z.; Gao, S.

2016-07-01

Micro-needle array, which is used in medical applications, is a kind of typical injection molded products with microstructures. Due to its tiny micro-features size and high aspect ratios, it is more likely to produce short shots defects, leading to poor molding quality. The injection molding process of the micro-needle array was studied in this paper to find the effects of the process parameters on the molding quality of the micro-needle array and to provide theoretical guidance for practical production of high-quality products. With the shrinkage ratio and warpage of micro needles as the evaluation indices of the molding quality, the orthogonal experiment was conducted and the analysis of variance was carried out. According to the results, the contribution rates were calculated to determine the influence of various process parameters on molding quality. The single parameter method was used to analyse the main process parameter. It was found that the contribution rate of the holding pressure on shrinkage ratio and warpage reached 83.55% and 94.71% respectively, far higher than that of the other parameters. The study revealed that the holding pressure is the main factor which affects the molding quality of micro-needle array so that it should be focused on in order to obtain plastic parts with high quality in the practical production.

Multi-sensor data processing method for improved satellite retrievals

NASA Astrophysics Data System (ADS)

Fan, Xingwang

2017-04-01

calibration and its comparison with regression approaches. IEEE Transactions on Geoscience and Remote Sensing, 55(3), doi: 10.1109/TGRS.2016.2635802.]. These studies demonstrate the success of multi-sensor data and novel methods in the research domain of geoscience. These data will benefit remote sensing of terrestrial parameters in decadal timescales, such as soil salinity content in Fan et al. (2016) [Fan, X., Weng, Y., and Tao, J. (2016). Towards decadal soil salinity mapping using Landsat time series data. International Journal of Applied Earth Observation and Geoinformation, 52, 32-41.].

Laboratory evaluation of dual-frequency multisensor capacitance probes to monitor soil water and salinity

USDA-ARS?s Scientific Manuscript database

Real-time information on salinity levels and transport of fertilizers are generally missing from soil profile knowledge bases. A dual-frequency multisensor capacitance probe (MCP) is now commercially available for sandy soils that simultaneously monitor volumetric soil water content (VWC, ') and sa...

Flat-plate solar array project. Volume 5: Process development

NASA Technical Reports Server (NTRS)

Gallagher, B.; Alexander, P.; Burger, D.

1986-01-01

The goal of the Process Development Area, as part of the Flat-Plate Solar Array (FSA) Project, was to develop and demonstrate solar cell fabrication and module assembly process technologies required to meet the cost, lifetime, production capacity, and performance goals of the FSA Project. R&D efforts expended by Government, Industry, and Universities in developing processes capable of meeting the projects goals during volume production conditions are summarized. The cost goals allocated for processing were demonstrated by small volume quantities that were extrapolated by cost analysis to large volume production. To provide proper focus and coverage of the process development effort, four separate technology sections are discussed: surface preparation, junction formation, metallization, and module assembly.

High density processing electronics for superconducting tunnel junction x-ray detector arrays

NASA Astrophysics Data System (ADS)

Warburton, W. K.; Harris, J. T.; Friedrich, S.

2015-06-01

Superconducting tunnel junctions (STJs) are excellent soft x-ray (100-2000 eV) detectors, particularly for synchrotron applications, because of their ability to obtain energy resolutions below 10 eV at count rates approaching 10 kcps. In order to achieve useful solid detection angles with these very small detectors, they are typically deployed in large arrays - currently with 100+ elements, but with 1000 elements being contemplated. In this paper we review a 5-year effort to develop compact, computer controlled low-noise processing electronics for STJ detector arrays, focusing on the major issues encountered and our solutions to them. Of particular interest are our preamplifier design, which can set the STJ operating points under computer control and achieve 2.7 eV energy resolution; our low noise power supply, which produces only 2 nV/√Hz noise at the preamplifier's critical cascode node; our digital processing card that digitizes and digitally processes 32 channels; and an STJ I-V curve scanning algorithm that computes noise as a function of offset voltage, allowing an optimum operating point to be easily selected. With 32 preamplifiers laid out on a custom 3U EuroCard, and the 32 channel digital card in a 3U PXI card format, electronics for a 128 channel array occupy only two small chassis, each the size of a National Instruments 5-slot PXI crate, and allow full array control with simple extensions of existing beam line data collection packages.

Assessment of low-cost manufacturing process sequences. [photovoltaic solar arrays

NASA Technical Reports Server (NTRS)

Chamberlain, R. G.

1979-01-01

An extensive research and development activity to reduce the cost of manufacturing photovoltaic solar arrays by a factor of approximately one hundred is discussed. Proposed and actual manufacturing process descriptions were compared to manufacturing costs. An overview of this methodology is presented.

The use of multisensor images for Earth Science applications

NASA Technical Reports Server (NTRS)

Evans, D.; Stromberg, B.

1983-01-01

The use of more than one remote sensing technique is particularly important for Earth Science applications because of the compositional and textural information derivable from the images. The ability to simultaneously analyze images acquired by different sensors requires coregistration of the multisensor image data sets. In order to insure pixel to pixel registration in areas of high relief, images must be rectified to eliminate topographic distortions. Coregistered images can be analyzed using a variety of multidimensional techniques and the acquired knowledge of topographic effects in the images can be used in photogeologic interpretations.

Development of a Multi-Sensor Cancer Detection Probe Final Report CRADA No. TC-2026-01

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marion, J.; Hular, R.

This collaboration continued work started under a previous CRADA (TSB-2023-00) to take a detailed concept specification for a multi-sensor needle/probe suitable for breast cancer analysis and produce a prototype system suitable for human FDA trials.

A miniature electronic nose system based on an MWNT-polymer microsensor array and a low-power signal-processing chip.

PubMed

Chiu, Shih-Wen; Wu, Hsiang-Chiu; Chou, Ting-I; Chen, Hsin; Tang, Kea-Tiong

2014-06-01

This article introduces a power-efficient, miniature electronic nose (e-nose) system. The e-nose system primarily comprises two self-developed chips, a multiple-walled carbon nanotube (MWNT)-polymer based microsensor array, and a low-power signal-processing chip. The microsensor array was fabricated on a silicon wafer by using standard photolithography technology. The microsensor array comprised eight interdigitated electrodes surrounded by SU-8 "walls," which restrained the material-solvent liquid in a defined area of 650 × 760 μm(2). To achieve a reliable sensor-manufacturing process, we used a two-layer deposition method, coating the MWNTs and polymer film as the first and second layers, respectively. The low-power signal-processing chip included array data acquisition circuits and a signal-processing core. The MWNT-polymer microsensor array can directly connect with array data acquisition circuits, which comprise sensor interface circuitry and an analog-to-digital converter; the signal-processing core consists of memory and a microprocessor. The core executes the program, classifying the odor data received from the array data acquisition circuits. The low-power signal-processing chip was designed and fabricated using the Taiwan Semiconductor Manufacturing Company 0.18-μm 1P6M standard complementary metal oxide semiconductor process. The chip consumes only 1.05 mW of power at supply voltages of 1 and 1.8 V for the array data acquisition circuits and the signal-processing core, respectively. The miniature e-nose system, which used a microsensor array, a low-power signal-processing chip, and an embedded k-nearest-neighbor-based pattern recognition algorithm, was developed as a prototype that successfully recognized the complex odors of tincture, sorghum wine, sake, whisky, and vodka.

Frequency-Wavenumber (F-K) Processing for Infrasound Distributed Arrays

DTIC Science & Technology

2012-10-01

UNCLASSIFIED Approved for public release; distribution is unlimited (U) Frequency-Wavenumber (F-K) Processing for Infrasound Distributed...have conventionally been used to detect infrasound . Pipe arrays, used in conjunction with microbarometers, provide noise reduction by averaging wind...signals. This is especially true for infrasound and low-frequency acoustic sources of tactical interest in the 1 to 100 Hz range. The work described

Multisensor data fusion for enhanced respiratory rate estimation in thermal videos.

PubMed

Pereira, Carina B; Xinchi Yu; Blazek, Vladimir; Venema, Boudewijn; Leonhardt, Steffen

2016-08-01

Scientific studies have demonstrated that an atypical respiratory rate (RR) is frequently one of the earliest and major indicators of physiological distress. However, it is also described in the literature as "the neglected vital parameter", mainly due to shortcomings of clinical available monitoring techniques, which require attachment of sensors to the patient's body. The current paper introduces a novel approach that uses multisensor data fusion for an enhanced RR estimation in thermal videos. It considers not only the temperature variation around nostrils and mouth, but the upward and downward movement of both shoulders. In order to analyze the performance of our approach, two experiments were carried out on five healthy candidates. While during phase A, the subjects breathed normally, during phase B they simulated different breathing patterns. Thoracic effort was the gold standard elected to validate our algorithm. Our results show an excellent agreement between infrared thermography (IRT) and ground truth. While in phase A a mean correlation of 0.983 and a root-mean-square error of 0.240 bpm (breaths per minute) was obtained, in phase B they hovered around 0.995 and 0.890 bpm, respectively. In sum, IRT may be a promising clinical alternative to conventional sensors. Additionally, multisensor data fusion contributes to an enhancement of RR estimation and robustness.

Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles.

PubMed

Zhu, Qingyuan; Xiao, Chunsheng; Hu, Huosheng; Liu, Yuanhui; Wu, Jinjin

2018-01-13

Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy.

Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles

PubMed Central

Xiao, Chunsheng; Liu, Yuanhui; Wu, Jinjin

2018-01-01

Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy. PMID:29342850

Integrated multi-sensor package (IMSP) for unmanned vehicle operations

NASA Astrophysics Data System (ADS)

Crow, Eddie C.; Reichard, Karl; Rogan, Chris; Callen, Jeff; Seifert, Elwood

2007-10-01

This paper describes recent efforts to develop integrated multi-sensor payloads for small robotic platforms for improved operator situational awareness and ultimately for greater robot autonomy. The focus is on enhancements to perception through integration of electro-optic, acoustic, and other sensors for navigation and inspection. The goals are to provide easier control and operation of the robot through fusion of multiple sensor outputs, to improve interoperability of the sensor payload package across multiple platforms through the use of open standards and architectures, and to reduce integration costs by embedded sensor data processing and fusion within the sensor payload package. The solutions investigated in this project to be discussed include: improved capture, processing and display of sensor data from multiple, non-commensurate sensors; an extensible architecture to support plug and play of integrated sensor packages; built-in health, power and system status monitoring using embedded diagnostics/prognostics; sensor payload integration into standard product forms for optimized size, weight and power; and the use of the open Joint Architecture for Unmanned Systems (JAUS)/ Society of Automotive Engineers (SAE) AS-4 interoperability standard. This project is in its first of three years. This paper will discuss the applicability of each of the solutions in terms of its projected impact to reducing operational time for the robot and teleoperator.

Sound Is Sound: Film Sound Techniques and Infrasound Data Array Processing

NASA Astrophysics Data System (ADS)

Perttu, A. B.; Williams, R.; Taisne, B.; Tailpied, D.

2017-12-01

A multidisciplinary collaboration between earth scientists and a sound designer/composer was established to explore the possibilities of audification analysis of infrasound array data. Through the process of audification of the infrasound we began to experiment with techniques and processes borrowed from cinema to manipulate the noise content of the signal. The results of this posed the question: "Would the accuracy of infrasound data array processing be enhanced by employing these techniques?". So a new area of research was born from this collaboration and highlights the value of these interactions and the unintended paths that can occur from them. Using a reference event database, infrasound data were processed using these new techniques and the results were compared with existing techniques to asses if there was any improvement to detection capability for the array. With just under one thousand volcanoes, and a high probability of eruption, Southeast Asia offers a unique opportunity to develop and test techniques for regional monitoring of volcanoes with different technologies. While these volcanoes are monitored locally (e.g. seismometer, infrasound, geodetic and geochemistry networks) and remotely (e.g. satellite and infrasound), there are challenges and limitations to the current monitoring capability. Not only is there a high fraction of cloud cover in the region, making plume observation more difficult via satellite, there have been examples of local monitoring networks and telemetry being destroyed early in the eruptive sequence. The success of local infrasound studies to identify explosions at volcanoes, and calculate plume heights from these signals, has led to an interest in retrieving source parameters for the purpose of ash modeling with a regional network independent of cloud cover.

Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

2014-05-01

Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety

An adaptive Hidden Markov Model for activity recognition based on a wearable multi-sensor device

USDA-ARS?s Scientific Manuscript database

Human activity recognition is important in the study of personal health, wellness and lifestyle. In order to acquire human activity information from the personal space, many wearable multi-sensor devices have been developed. In this paper, a novel technique for automatic activity recognition based o...

DAMAS Processing for a Phased Array Study in the NASA Langley Jet Noise Laboratory

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.; Humphreys, William M.; Plassman, Gerald e.

2010-01-01

A jet noise measurement study was conducted using a phased microphone array system for a range of jet nozzle configurations and flow conditions. The test effort included convergent and convergent/divergent single flow nozzles, as well as conventional and chevron dual-flow core and fan configurations. Cold jets were tested with and without wind tunnel co-flow, whereas, hot jets were tested only with co-flow. The intent of the measurement effort was to allow evaluation of new phased array technologies for their ability to separate and quantify distributions of jet noise sources. In the present paper, the array post-processing method focused upon is DAMAS (Deconvolution Approach for the Mapping of Acoustic Sources) for the quantitative determination of spatial distributions of noise sources. Jet noise is highly complex with stationary and convecting noise sources, convecting flows that are the sources themselves, and shock-related and screech noise for supersonic flow. The analysis presented in this paper addresses some processing details with DAMAS, for the array positioned at 90 (normal) to the jet. The paper demonstrates the applicability of DAMAS and how it indicates when strong coherence is present. Also, a new approach to calibrating the array focus and position is introduced and demonstrated.

Multi-Sensor Distributive On-line Processing, Visualization, and Analysis Infrastructure for an Agricultural Information System at the NASA Goddard Earth Sciences DAAC

NASA Astrophysics Data System (ADS)

Teng, W.; Berrick, S.; Leptoukh, G.; Liu, Z.; Rui, H.; Pham, L.; Shen, S.; Zhu, T.

2004-12-01

The Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Distributed Active Archive Center (DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide precipitation and other satellite data products and services. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as that of the U.N. World Food Program. The ability to use the raw data stored in the GES DAAC archives is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. To gain this understanding is a time-consuming process and not a productive investment of the user's time. This is an especially difficult challenge when users need to deal with multi-sensor data that usually are of different structures and resolutions. The AIS has taken a major step towards meeting this challenge by incorporating an underlying infrastructure, called the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni," that integrates various components to support web interfaces that allow users to perform interactive analysis on-line without downloading any data. Several instances of the Giovanni-based interface have been or are being created to serve users of TRMM precipitation, MODIS aerosol, and SeaWiFS ocean color data, as well as agricultural applications users. Giovanni-based interfaces are simple to use but powerful. The user selects geophysical parameters, area of interest, and time period; and the system generates an output on screen in a matter of seconds. The currently available output options are (1) area plot - averaged or accumulated over any available data period for any rectangular area; (2) time plot - time series averaged over any rectangular area; (3) Hovmoller plots - longitude-time and latitude-time plots; (4) ASCII

Automatic parameter selection for feature-based multi-sensor image registration

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Tom, Victor; Webb, Helen; Chao, Alan

2006-05-01

Accurate image registration is critical for applications such as precision targeting, geo-location, change-detection, surveillance, and remote sensing. However, the increasing volume of image data is exceeding the current capacity of human analysts to perform manual registration. This image data glut necessitates the development of automated approaches to image registration, including algorithm parameter value selection. Proper parameter value selection is crucial to the success of registration techniques. The appropriate algorithm parameters can be highly scene and sensor dependent. Therefore, robust algorithm parameter value selection approaches are a critical component of an end-to-end image registration algorithm. In previous work, we developed a general framework for multisensor image registration which includes feature-based registration approaches. In this work we examine the problem of automated parameter selection. We apply the automated parameter selection approach of Yitzhaky and Peli to select parameters for feature-based registration of multisensor image data. The approach consists of generating multiple feature-detected images by sweeping over parameter combinations and using these images to generate estimated ground truth. The feature-detected images are compared to the estimated ground truth images to generate ROC points associated with each parameter combination. We develop a strategy for selecting the optimal parameter set by choosing the parameter combination corresponding to the optimal ROC point. We present numerical results showing the effectiveness of the approach using registration of collected SAR data to reference EO data.

Comparison of X-ray Radiation Process in Single and Nested Wire Array Implosions

NASA Astrophysics Data System (ADS)

Li, Z. H.; Xu, Z. P.; Yang, J. L.; Xu, R. K.; Guo, C.; Grabovsky, E. V.; Oleynic, G. M.; Smirnov, V. P.

2006-01-01

In order to understanding the difference between tungsten single-wire-array and tungsten nested-wire-array Z-pinches, we have measured the x-ray power, the temporal-spatial distributions of x-ray radiation from each of the two loads. The measurements were performed with 0.1mm spatial and 1 ns temporal resolutions at 2.5- and 3.5-MA currents. The experimental conditions, including wire material, number of wires, wire-array length, electrode design, and implosion time, remained unchanged from shot to shot. Analysis of the radiation power profiles suggests that the nested-wire-array radiate slightly less x-ray energy in relatively shorter time interval than the single wire-array, leading to a much greater x-ray power in nested-wire-array implosion. The temporal-spatial distributions of x-ray power show that in both cases, plasmas formed by wire-array ablation radiate not simultaneously along load axis. For nested-wire-array Z-pinch, plasmas near the anode begin to radiate in 2ns later than that near the cathode. As a contrast, the temporal divergence of radiation among different plasma zones of single-wire-array Z-pinch along Z-axis is more than 6ns. Measurements of the x-ray emissions from small segments of pinch (2mm length along axis) indicate that local radiation power profiles almost do not vary for the two loads. Photographs taken by X-ray framing camera give a same description about the radiation process of pinch. One may expect that, as a result of this study, if the single-wire-array can be redesigned so ingeniously that the x-rays are emitted at the same time all over the pinch zone, the radiation power of single wire array Z-pinch may be much greater than what have been achieved.

Multisensor data fusion for IED threat detection

NASA Astrophysics Data System (ADS)

Mees, Wim; Heremans, Roel

2012-10-01

In this paper we present the multi-sensor registration and fusion algorithms that were developed for a force protection research project in order to detect threats against military patrol vehicles. The fusion is performed at object level, using a hierarchical evidence aggregation approach. It first uses expert domain knowledge about the features used to characterize the detected threats, that is implemented in the form of a fuzzy expert system. The next level consists in fusing intra-sensor and inter-sensor information. Here an ordered weighted averaging operator is used. The object level fusion between candidate threats that are detected asynchronously on a moving vehicle by sensors with different imaging geometries, requires an accurate sensor to world coordinate transformation. This image registration will also be discussed in this paper.

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.

2012-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Hua, H.

2012-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

Observability considerations for multi-sensor and product fusion: Bias, information content, and validation (Invited)

NASA Astrophysics Data System (ADS)

Reid, J. S.; Zhang, J.; Hyer, E. J.; Campbell, J. R.; Christopher, S. A.; Ferrare, R. A.; Leptoukh, G. G.; Stackhouse, P. W.

2009-12-01

With the successful development of many aerosol products from the NASA A-train as well as new operational geostationary and polar orbiting sensors, the scientific community now has a host of new parameters to use in their analyses. The variety and quality of products has reached a point where the community has moved from basic observation-based science to sophisticated multi-component research that addresses the complex atmospheric environment. In order for these satellite data contribute to the science their uncertainty levels must move from semi-quantitative to quantitative. Initial attempts to quantify uncertainties have led to some recent debate in the community as to the efficacy of aerosol products from current and future NASA satellite sensors. In an effort to understand the state of satellite product fidelity, the Naval Research Laboratory and a newly reformed Global Energy and Water Cycle Experiment (GEWEX) aerosol panel have both initiated assessments of the nature of aerosol remote sensing uncertainty and bias. In this talk we go over areas of specific concern based on the authors’ experiences with the data, emphasizing the multi-sensor problem. We first enumerate potential biases, including retrieval, sampling/contextual, and cognitive bias. We show examples of how these biases can subsequently lead to the pitfalls of correlated/compensating errors, tautology, and confounding. The nature of bias is closely related to the information content of the sensor signal and its subsequent application to the derived aerosol quantity of interest (e.g., optical depth, flux, index of refraction, etc.). Consequently, purpose-specific validation methods must be employed, especially when generating multi-sensor products. Indeed, cloud and lower boundary condition biases in particular complicate the more typical methods of regressional bias elimination and histogram matching. We close with a discussion of sequestration of uncertainty in multi-sensor applications of

Integration of Multi-sensor Data for Desertification Monitoring

NASA Astrophysics Data System (ADS)

Lin, S.; Kim, J.

2010-12-01

dune activities can be clearly revealed. For the very detailed measurement, a terrestrial system applying close range photogrammetry will be set up in the test sites to acquire sequential images and used to generate 4D model of the dunes in future. Finally, all the outputs from the multi-sensor data will be crossly verified and compiled to model the desertification process and the consequences. A desertification combating activity which is performed by Korea-China NGO alliance has been conducted in Qubuqi desert in Nei Mongol, China. The method and system proposed above will be established and applied to monitor the dune mobility occurring in this area. The results are expected to be of great value to demonstrate the first case of remote sensing monitoring over the combat desertification activities.

Extended Kalman Doppler tracking and model determination for multi-sensor short-range radar

NASA Astrophysics Data System (ADS)

Mittermaier, Thomas J.; Siart, Uwe; Eibert, Thomas F.; Bonerz, Stefan

2016-09-01

A tracking solution for collision avoidance in industrial machine tools based on short-range millimeter-wave radar Doppler observations is presented. At the core of the tracking algorithm there is an Extended Kalman Filter (EKF) that provides dynamic estimation and localization in real-time. The underlying sensor platform consists of several homodyne continuous wave (CW) radar modules. Based on In-phase-Quadrature (IQ) processing and down-conversion, they provide only Doppler shift information about the observed target. Localization with Doppler shift estimates is a nonlinear problem that needs to be linearized before the linear KF can be applied. The accuracy of state estimation depends highly on the introduced linearization errors, the initialization and the models that represent the true physics as well as the stochastic properties. The important issue of filter consistency is addressed and an initialization procedure based on data fitting and maximum likelihood estimation is suggested. Models for both, measurement and process noise are developed. Tracking results from typical three-dimensional courses of movement at short distances in front of a multi-sensor radar platform are presented.

Optimum Array Processing for Detecting Binary Signals Corrupted by Directional Interference.

DTIC Science & Technology

1972-12-01

specific cases. Two different series representations of a vector random process are discussed in Van Trees [3]. These two methods both require the... spaci ~ng d, etc.) its detection error represents a lower bound for the performance that might be obtained with other types of array processing (such...Middleton, Introduction to Statistical Communication Theory, New York: McGraw-Hill, 1960. 3. H.L. Van Trees , Detection, Estimation, and Modulation Theory

An array processing system for lunar geochemical and geophysical data

NASA Technical Reports Server (NTRS)

Eliason, E. M.; Soderblom, L. A.

1977-01-01

A computerized array processing system has been developed to reduce, analyze, display, and correlate a large number of orbital and earth-based geochemical, geophysical, and geological measurements of the moon on a global scale. The system supports the activities of a consortium of about 30 lunar scientists involved in data synthesis studies. The system was modeled after standard digital image-processing techniques but differs in that processing is performed with floating point precision rather than integer precision. Because of flexibility in floating-point image processing, a series of techniques that are impossible or cumbersome in conventional integer processing were developed to perform optimum interpolation and smoothing of data. Recently color maps of about 25 lunar geophysical and geochemical variables have been generated.

Solid-contact potentiometric sensors and multisensors based on polyaniline and thiacalixarene receptors for the analysis of some beverages and alcoholic drinks

NASA Astrophysics Data System (ADS)

Sorvin, Michail; Belyakova, Svetlana; Stoikov, Ivan; Shamagsumova, Rezeda; Evtugyn, Gennady

2018-04-01

Electronic tongue is a sensor array that aims to discriminate and analyze complex media like food and beverages on the base of chemometrics approaches for data mining and pattern recognition. In this review, the concept of electronic tongue comprising of solid-contact potentiometric sensors with polyaniline and thacalix[4]arene derivatives is described. The electrochemical reactions of polyaniline as a background of solid-contact sensors and the characteristics of thiacalixarenes and pillararenes as neutral ionophores are briefly considered. The electronic tongue systems described were successfully applied for assessment of fruit juices, green tea, beer and alcoholic drinks They were classified in accordance with the origination, brands and styles. Variation of the sensor response resulted from the reactions between Fe(III) ions added and sample components, i.e., antioxidants and complexing agents. The use of principal component analysis and discriminant analysis is shown for multisensor signal treatment and visualization. The discrimination conditions can be optimized by variation of the ionophores, Fe(III) concentration and sample dilution. The results obtained were compared with other electronic tongue systems reported for the same subjects.

Solid-Contact Potentiometric Sensors and Multisensors Based on Polyaniline and Thiacalixarene Receptors for the Analysis of Some Beverages and Alcoholic Drinks.

PubMed

Sorvin, Michail; Belyakova, Svetlana; Stoikov, Ivan; Shamagsumova, Rezeda; Evtugyn, Gennady

2018-01-01

Electronic tongue is a sensor array that aims to discriminate and analyze complex media like food and beverages on the base of chemometrics approaches for data mining and pattern recognition. In this review, the concept of electronic tongue comprising of solid-contact potentiometric sensors with polyaniline and thacalix[4]arene derivatives is described. The electrochemical reactions of polyaniline as a background of solid-contact sensors and the characteristics of thiacalixarenes and pillararenes as neutral ionophores are briefly considered. The electronic tongue systems described were successfully applied for assessment of fruit juices, green tea, beer, and alcoholic drinks They were classified in accordance with the origination, brands and styles. Variation of the sensor response resulted from the reactions between Fe(III) ions added and sample components, i.e., antioxidants and complexing agents. The use of principal component analysis and discriminant analysis is shown for multisensor signal treatment and visualization. The discrimination conditions can be optimized by variation of the ionophores, Fe(III) concentration, and sample dilution. The results obtained were compared with other electronic tongue systems reported for the same subjects.

Solid-Contact Potentiometric Sensors and Multisensors Based on Polyaniline and Thiacalixarene Receptors for the Analysis of Some Beverages and Alcoholic Drinks

PubMed Central

Sorvin, Michail; Belyakova, Svetlana; Stoikov, Ivan; Shamagsumova, Rezeda; Evtugyn, Gennady

2018-01-01

Electronic tongue is a sensor array that aims to discriminate and analyze complex media like food and beverages on the base of chemometrics approaches for data mining and pattern recognition. In this review, the concept of electronic tongue comprising of solid-contact potentiometric sensors with polyaniline and thacalix[4]arene derivatives is described. The electrochemical reactions of polyaniline as a background of solid-contact sensors and the characteristics of thiacalixarenes and pillararenes as neutral ionophores are briefly considered. The electronic tongue systems described were successfully applied for assessment of fruit juices, green tea, beer, and alcoholic drinks They were classified in accordance with the origination, brands and styles. Variation of the sensor response resulted from the reactions between Fe(III) ions added and sample components, i.e., antioxidants and complexing agents. The use of principal component analysis and discriminant analysis is shown for multisensor signal treatment and visualization. The discrimination conditions can be optimized by variation of the ionophores, Fe(III) concentration, and sample dilution. The results obtained were compared with other electronic tongue systems reported for the same subjects. PMID:29740577

Physics-based signal processing algorithms for micromachined cantilever arrays

DOEpatents

Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W

2013-11-19

A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.

BreedVision--a multi-sensor platform for non-destructive field-based phenotyping in plant breeding.

PubMed

Busemeyer, Lucas; Mentrup, Daniel; Möller, Kim; Wunder, Erik; Alheit, Katharina; Hahn, Volker; Maurer, Hans Peter; Reif, Jochen C; Würschum, Tobias; Müller, Joachim; Rahe, Florian; Ruckelshausen, Arno

2013-02-27

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies.

Assesment on the performance of electrode arrays using image processing technique

NASA Astrophysics Data System (ADS)

Usman, N.; Khiruddin, A.; Nawawi, Mohd

2017-08-01

Interpreting inverted resistivity section is time consuming, tedious and requires other sources of information to be relevant geologically. Image processing technique was used in order to perform post inversion processing which make geophysical data interpretation easier. The inverted data sets were imported into the PCI Geomatica 9.0.1 for further processing. The data sets were clipped and merged together in order to match the coordinates of the three layers and permit pixel to pixel analysis. Dipole-dipole array is more sensitive to resistivity variation with depth in comparison with Werner-Schlumberger and pole-dipole. Image processing serves as good post-inversion tool in geophysical data processing.

Multisensor Fusion for Change Detection

NASA Astrophysics Data System (ADS)

Schenk, T.; Csatho, B.

2005-12-01

Combining sensors that record different properties of a 3-D scene leads to complementary and redundant information. If fused properly, a more robust and complete scene description becomes available. Moreover, fusion facilitates automatic procedures for object reconstruction and modeling. For example, aerial imaging sensors, hyperspectral scanning systems, and airborne laser scanning systems generate complementary data. We describe how data from these sensors can be fused for such diverse applications as mapping surface erosion and landslides, reconstructing urban scenes, monitoring urban land use and urban sprawl, and deriving velocities and surface changes of glaciers and ice sheets. An absolute prerequisite for successful fusion is a rigorous co-registration of the sensors involved. We establish a common 3-D reference frame by using sensor invariant features. Such features are caused by the same object space phenomena and are extracted in multiple steps from the individual sensors. After extracting, segmenting and grouping the features into more abstract entities, we discuss ways on how to automatically establish correspondences. This is followed by a brief description of rigorous mathematical models suitable to deal with linear and area features. In contrast to traditional, point-based registration methods, lineal and areal features lend themselves to a more robust and more accurate registration. More important, the chances to automate the registration process increases significantly. The result of the co-registration of the sensors is a unique transformation between the individual sensors and the object space. This makes spatial reasoning of extracted information more versatile; reasoning can be performed in sensor space or in 3-D space where domain knowledge about features and objects constrains reasoning processes, reduces the search space, and helps to make the problem well-posed. We demonstrate the feasibility of the proposed multisensor fusion approach

Integrated multisensor perimeter detection systems

NASA Astrophysics Data System (ADS)

Kent, P. J.; Fretwell, P.; Barrett, D. J.; Faulkner, D. A.

2007-10-01

The report describes the results of a multi-year programme of research aimed at the development of an integrated multi-sensor perimeter detection system capable of being deployed at an operational site. The research was driven by end user requirements in protective security, particularly in threat detection and assessment, where effective capability was either not available or prohibitively expensive. Novel video analytics have been designed to provide robust detection of pedestrians in clutter while new radar detection and tracking algorithms provide wide area day/night surveillance. A modular integrated architecture based on commercially available components has been developed. A graphical user interface allows intuitive interaction and visualisation with the sensors. The fusion of video, radar and other sensor data provides the basis of a threat detection capability for real life conditions. The system was designed to be modular and extendable in order to accommodate future and legacy surveillance sensors. The current sensor mix includes stereoscopic video cameras, mmWave ground movement radar, CCTV and a commercially available perimeter detection cable. The paper outlines the development of the system and describes the lessons learnt after deployment in a pilot trial.

Implementation of a Digital Signal Processing Subsystem for a Long Wavelength Array Station

NASA Technical Reports Server (NTRS)

Soriano, Melissa; Navarro, Robert; D'Addario, Larry; Sigman, Elliott; Wang, Douglas

2011-01-01

This paper describes the implementation of a Digital Signal Processing (DP) subsystem for a single Long Wavelength Array (LWA) station.12 The LWA is a radio telescope that will consist of many phased array stations. Each LWA station consists of 256 pairs of dipole-like antennas operating over the 10-88 MHz frequency range. The Digital Signal Processing subsystem digitizes up to 260 dual-polarization signals at 196 MHz from the LWA Analog Receiver, adjusts the delay and amplitude of each signal, and forms four independent beams. Coarse delay is implemented using a first-in-first-out buffer and fine delay is implemented using a finite impulse response filter. Amplitude adjustment and polarization corrections are implemented using a 2x2 matrix multiplication

Real Time Assessment of Potable Water Quality in Distribution Network based on Low Cost Multi-Sensor Array

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Khatri, Punit

2018-03-01

New concepts and techniques are replacing traditional methods of water quality parameters measurement systems. This paper proposed a new way of potable water quality assessment in distribution network using Multi Sensor Array (MSA). Extensive research suggests that following parameters i.e. pH, Dissolved Oxygen (D.O.), Conductivity, Oxygen Reduction Potential (ORP), Temperature and Salinity are most suitable to detect overall quality of potable water. Commonly MSA is not an integrated sensor array on some substrate, but rather comprises a set of individual sensors measuring simultaneously different water parameters all together. Based on research, a MSA has been developed followed by signal conditioning unit and finally, an algorithm for easy user interfacing. A dedicated part of this paper also discusses the platform design and significant results. The Objective of this proposed research is to provide simple, efficient, cost effective and socially acceptable means to detect and analyse water bodies regularly and automatically.

Seismic &Infrasound Integrated Array "Apatity". Techniques, data processing, first results of observations.

NASA Astrophysics Data System (ADS)

Vinogradov, Y.; Baryshnikov, A.

2003-04-01

Since September 2001 3 infrasound membrane type sensors "K-304 AM" have been installed on the territory seismic array "Apatity" near the lake Imandra. A seismic array comprising 11 short-period sensors (type "Geotech S-500"), disposed on small and large circle (0.4 and 1 km diameter). Infrasound sensors located on small circle near the seismograths. All data are digitized at the array site and transmitted in real time to a processing center in Apatity to the Kola Regional Seismological Centre (KRSC). Common complex we are called - Seismic &Infrasound Integrated Array (SISIA) "Apatity". To support temporary storage the transmitting data in a disk loop and access to the data "NEWNORAC" program was created. This program replaced "NORAC" system developed by Norwegian Institute NORSAR, which was in use in KRSC before. A program package EL (event locator) for display and processing of the data has been modified. Now it includes the following : - quick access to the data stored in the disk loop (last two weeks); - data convertation from disk loop format to CSS 3.0 format; - data filtering using bandpass, highpass, lowpass, adaptive or rejector filters; - calculation of spectra and sonograms (spectral diagrams); - seismic events location with plotting on a map; - calculation of backazimuth and apparent velocity of acoustic wave by similar parts of wave recordings; - loading and processing CSS 3.0 seismic and acoustic data from KRSC archive. To store the acoustic data permanently the program BARCSS was made. It rewrites the data from the disk loop to KRSC archive in CSS 3.0 format. For comparison of acoustic noise level with wind we use data from meteorological station in Kandalaksha city, sampling rate is 3 hours. During the period from October 2001 to October 2002 more than 745 seismic events, which basically connected with mine technical activity of the large mining enterprises at the Kola Peninsula, were registered. The most part of events, caused by ground explosions

Fully Solution-Processed Flexible Organic Thin Film Transistor Arrays with High Mobility and Exceptional Uniformity

PubMed Central

Fukuda, Kenjiro; Takeda, Yasunori; Mizukami, Makoto; Kumaki, Daisuke; Tokito, Shizuo

2014-01-01

Printing fully solution-processed organic electronic devices may potentially revolutionize production of flexible electronics for various applications. However, difficulties in forming thin, flat, uniform films through printing techniques have been responsible for poor device performance and low yields. Here, we report on fully solution-processed organic thin-film transistor (TFT) arrays with greatly improved performance and yields, achieved by layering solution-processable materials such as silver nanoparticle inks, organic semiconductors, and insulating polymers on thin plastic films. A treatment layer improves carrier injection between the source/drain electrodes and the semiconducting layer and dramatically reduces contact resistance. Furthermore, an organic semiconductor with large-crystal grains results in TFT devices with shorter channel lengths and higher field-effect mobilities. We obtained mobilities of over 1.2 cm2 V−1 s−1 in TFT devices with channel lengths shorter than 20 μm. By combining these fabrication techniques, we built highly uniform organic TFT arrays with average mobility levels as high as 0.80 cm2 V−1 s−1 and ideal threshold voltages of 0 V. These results represent major progress in the fabrication of fully solution-processed organic TFT device arrays. PMID:24492785

Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles.

PubMed

Xing, Boyang; Zhu, Quanmin; Pan, Feng; Feng, Xiaoxue

2018-05-25

A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids the map distortion due to lack of correction. Based on the conception of multi-sensor information fusion, the federated Kalman filter is utilized to synthesize the multi-source information from markers, optical flow, ultrasonic and the inertial sensor, which can obtain a continuous localization result and effectively reduce the position drift due to the long-term loss of markers in pure marker localization. The proposed algorithm can be easily implemented in a hardware of one Raspberry Pi Zero and two STM32 micro controllers produced by STMicroelectronics (Geneva, Switzerland). Thus, a small-size and low-cost marker-based localization system is presented. The experimental results show that the speed estimation result of the proposed system is better than Px4flow, and it has the centimeter accuracy of mapping and positioning. The presented system not only gives satisfying localization precision, but also has the potential to expand other sensors (such as visual odometry, ultra wideband (UWB) beacon and lidar) to further improve the localization performance. The proposed system can be reliably employed in Micro Aerial Vehicle (MAV) visual localization and robotics control.

Multi-sensor electrometer

NASA Technical Reports Server (NTRS)

Gompf, Raymond (Inventor); Buehler, Martin C. (Inventor)

2003-01-01

An array of triboelectric sensors is used for testing the electrostatic properties of a remote environment. The sensors may be mounted in the heel of a robot arm scoop. To determine the triboelectric properties of a planet surface, the robot arm scoop may be rubbed on the soil of the planet and the triboelectrically developed charge measured. By having an array of sensors, different insulating materials may be measured simultaneously. The insulating materials may be selected so their triboelectric properties cover a desired range. By mounting the sensor on a robot arm scoop, the measurements can be obtained during an unmanned mission.

Novel Multisensor Probe for Monitoring Bladder Temperature During Locoregional Chemohyperthermia for Nonmuscle-Invasive Bladder Cancer: Technical Feasibility Study

PubMed Central

Geijsen, Debby E.; Zum Vörde Sive Vörding, Paul J.; Schooneveldt, Gerben; Sijbrands, Jan; Hulshof, Maarten C.; de la Rosette, Jean; de Reijke, Theo M.; Crezee, Hans

2013-01-01

Abstract Background and Purpose: The effectiveness of locoregional hyperthermia combined with intravesical instillation of mitomycin C to reduce the risk of recurrence and progression of intermediate- and high-risk nonmuscle-invasive bladder cancer is currently investigated in clinical trials. Clinically effective locoregional hyperthermia delivery necessitates adequate thermal dosimetry; thus, optimal thermometry methods are needed to monitor accurately the temperature distribution throughout the bladder wall. The aim of the study was to evaluate the technical feasibility of a novel intravesical device (multi-sensor probe) developed to monitor the local bladder wall temperatures during loco-regional C-HT. Materials and Methods: A multisensor thermocouple probe was designed for deployment in the human bladder, using special sensors to cover the bladder wall in different directions. The deployment of the thermocouples against the bladder wall was evaluated with visual, endoscopic, and CT imaging in bladder phantoms, porcine models, and human bladders obtained from obduction for bladder volumes and different deployment sizes of the probe. Finally, porcine bladders were embedded in a phantom and subjected to locoregional heating to compare probe temperatures with additional thermometry inside and outside the bladder wall. Results: The 7.5 cm thermocouple probe yielded optimal bladder wall contact, adapting to different bladder volumes. Temperature monitoring was shown to be accurate and representative for the actual bladder wall temperature. Conclusions: Use of this novel multisensor probe could yield a more accurate monitoring of the bladder wall temperature during locoregional chemohyperthermia. PMID:24112045

TRIGA: Telecommunications Protocol Processing Subsystem Using Reconfigurable Interoperable Gate Arrays

NASA Technical Reports Server (NTRS)

Pang, Jackson; Pingree, Paula J.; Torgerson, J. Leigh

2006-01-01

We present the Telecommunications protocol processing subsystem using Reconfigurable Interoperable Gate Arrays (TRIGA), a novel approach that unifies fault tolerance, error correction coding and interplanetary communication protocol off-loading to implement CCSDS File Delivery Protocol and Datalink layers. The new reconfigurable architecture offers more than one order of magnitude throughput increase while reducing footprint requirements in memory, command and data handling processor utilization, communication system interconnects and power consumption.

Multi-Sensor Testing for Automated Rendezvous and Docking Sensor Testing at the Flight Robotics Laboratory

NASA Technical Reports Server (NTRS)

Brewster, L.; Johnston, A.; Howard, R.; Mitchell, J.; Cryan, S.

2007-01-01

The Exploration Systems Architecture defines missions that require rendezvous, proximity operations, and docking (RPOD) of two spacecraft both in Low Earth Orbit (LEO) and in Low Lunar Orbit (LLO). Uncrewed spacecraft must perform automated and/or autonomous rendezvous, proximity operations and docking operations (commonly known as AR&D). The crewed missions may also perform rendezvous and docking operations and may require different levels of automation and/or autonomy, and must provide the crew with relative navigation information for manual piloting. The capabilities of the RPOD sensors are critical to the success of the Exploration Program. NASA has the responsibility to determine whether the Crew Exploration Vehicle (CEV) contractor proposed relative navigation sensor suite will meet the requirements. The relatively low technology readiness level of AR&D relative navigation sensors has been carried as one of the CEV Project's top risks. The AR&D Sensor Technology Project seeks to reduce the risk by the testing and analysis of selected relative navigation sensor technologies through hardware-in-the-loop testing and simulation. These activities will provide the CEV Project information to assess the relative navigation sensors maturity as well as demonstrate test methods and capabilities. The first year of this project focused on a series of"pathfinder" testing tasks to develop the test plans, test facility requirements, trajectories, math model architecture, simulation platform, and processes that will be used to evaluate the Contractor-proposed sensors. Four candidate sensors were used in the first phase of the testing. The second phase of testing used four sensors simultaneously: two Marshall Space Flight Center (MSFC) Advanced Video Guidance Sensors (AVGS), a laser-based video sensor that uses retroreflectors attached to the target vehicle, and two commercial laser range finders. The multi-sensor testing was conducted at MSFC's Flight Robotics Laboratory (FRL

Multi-Sensor Testing for Automated Rendezvous and Docking Sensor Testing at the Flight Robotics Lab

NASA Technical Reports Server (NTRS)

Brewster, Linda L.; Howard, Richard T.; Johnston, A. S.; Carrington, Connie; Mitchell, Jennifer D.; Cryan, Scott P.

2008-01-01

The Exploration Systems Architecture defines missions that require rendezvous, proximity operations, and docking (RPOD) of two spacecraft both in Low Earth Orbit (LEO) and in Low Lunar Orbit (LLO). Uncrewed spacecraft must perform automated and/or autonomous rendezvous, proximity operations and docking operations (commonly known as AR&D). The crewed missions may also perform rendezvous and docking operations and may require different levels of automation and/or autonomy, and must provide the crew with relative navigation information for manual piloting. The capabilities of the RPOD sensors are critical to the success ofthe Exploration Program. NASA has the responsibility to determine whether the Crew Exploration Vehicle (CEV) contractor-proposed relative navigation sensor suite will meet the requirements. The relatively low technology readiness level of AR&D relative navigation sensors has been carried as one of the CEV Project's top risks. The AR&D Sensor Technology Project seeks to reduce the risk by the testing and analysis of selected relative navigation sensor technologies through hardware-in-the-Ioop testing and simulation. These activities will provide the CEV Project information to assess the relative navigation sensors maturity as well as demonstrate test methods and capabilities. The first year of this project focused on a series of "pathfinder" testing tasks to develop the test plans, test facility requirements, trajectories, math model architecture, simulation platform, and processes that will be used to evaluate the Contractor-proposed sensors. Four candidate sensors were used in the first phase of the testing. The second phase of testing used four sensors simultaneously: two Marshall Space Flight Center (MSFC) Advanced Video Guidance Sensors (AVGS), a laser-based video sensor that uses retroreflectors attached to the target vehicle, and two commercial laser range finders. The multi-sensor testing was conducted at MSFC's Flight Robotics Laboratory (FRL

Formulating an image matching strategy for terrestrial stem data collection using a multisensor video system

Treesearch

Neil A. Clark

2001-01-01

A multisensor video system has been developed incorporating a CCD video camera, a 3-axis magnetometer, and a laser-rangefinding device, for the purpose of measuring individual tree stems. While preliminary results show promise, some changes are needed to improve the accuracy and efficiency of the system. Image matching is needed to improve the accuracy of length...

Structural control of ultra-fine CoPt nanodot arrays via electrodeposition process

NASA Astrophysics Data System (ADS)

Wodarz, Siggi; Hasegawa, Takashi; Ishio, Shunji; Homma, Takayuki

2017-05-01

CoPt nanodot arrays were fabricated by combining electrodeposition and electron beam lithography (EBL) for the use of bit-patterned media (BPM). To achieve precise control of deposition uniformity and coercivity of the CoPt nanodot arrays, their crystal structure and magnetic properties were controlled by controlling the diffusion state of metal ions from the initial deposition stage with the application of bath agitation. Following bath agitation, the composition gradient of the CoPt alloy with thickness was mitigated to have a near-ideal alloy composition of Co:Pt =80:20, which induces epitaxial-like growth from Ru substrate, thus resulting in the improvement of the crystal orientation of the hcp (002) structure from its initial deposition stages. Furthermore, the cross-sectional transmission electron microscope (TEM) analysis of the nanodots deposited with bath agitation showed CoPt growth along its c-axis oriented in the perpendicular direction, having uniform lattice fringes on the hcp (002) plane from the Ru underlayer interface, which is a significant factor to induce perpendicular magnetic anisotropy. Magnetic characterization of the CoPt nanodot arrays showed increase in the perpendicular coercivity and squareness of the hysteresis loops from 2.0 kOe and 0.64 (without agitation) to 4.0 kOe and 0.87 with bath agitation. Based on the detailed characterization of nanodot arrays, the precise crystal structure control of the nanodot arrays with ultra-high recording density by electrochemical process was successfully demonstrated.

Batch-processed semiconductor gas sensor array for the selective detection of NOx in automotive exhaust gas

NASA Astrophysics Data System (ADS)

Jang, Hani; Kim, Minki; Kim, Yongjun

2016-12-01

This paper reports on a semiconductor gas sensor array to detect nitrogen oxides (NOx) in automotive exhaust gas. The proposed semiconductor gas sensor array consisted of one common electrode and three individual electrodes to minimize the size of the sensor array, and three sensing layers [TiO2 + SnO2 (15 wt%), SnO2, and Ga2O3] were deposited using screen printing. In addition, sensing materials were sintered under the same conditions in order to take advantage of batch processing. The sensing properties of the proposed sensor array were verified by experimental measurements, and the selectivity improved by using pattern recognition.

Co-Prime Frequency and Aperture Design for HF Surveillance, Wideband Radar Imaging, and Nonstationary Array Processing

DTIC Science & Technology

2018-03-01

offset designs . Particularly, the proposed CA-CFO is compared with uniform linear array and uniform frequency offset (ULA-UFO). Uniform linear array...and Aperture Design for HF Surveillance, Wideband Radar Imaging, and Nonstationary Array Processing (Grant No. N00014-13-1-0061) Submitted to...Contents 1. Executive Summary …………………………………………………………………………. 1 1.1. Generalized Co-Prime Array Design ………………………………………………… 1 1.2. Wideband

Multisensor fusion with non-optimal decision rules: the challenges of open world sensing

NASA Astrophysics Data System (ADS)

Minor, Christian; Johnson, Kevin

2014-05-01

In this work, simple, generic models of chemical sensing are used to simulate sensor array data and to illustrate the impact on overall system performance that specific design choices impart. The ability of multisensor systems to perform multianalyte detection (i.e., distinguish multiple targets) is explored by examining the distinction between fundamental design-related limitations stemming from mismatching of mixture composition to fused sensor measurement spaces, and limitations that arise from measurement uncertainty. Insight on the limits and potential of sensor fusion to robustly address detection tasks in realistic field conditions can be gained through an examination of a) the underlying geometry of both the composition space of sources one hopes to elucidate and the measurement space a fused sensor system is capable of generating, and b) the informational impact of uncertainty on both of these spaces. For instance, what is the potential impact on sensor fusion in an open world scenario where unknown interferants may contaminate target signals? Under complex and dynamic backgrounds, decision rules may implicitly become non-optimal and adding sensors may increase the amount of conflicting information observed. This suggests that the manner in which a decision rule handles sensor conflict can be critical in leveraging sensor fusion for effective open world sensing, and becomes exponentially more important as more sensors are added. Results and design considerations for handling conflicting evidence in Bayes and Dempster-Shafer fusion frameworks are presented. Bayesian decision theory is used to provide an upper limit on detector performance of simulated sensor systems.

Using surface lattice resonances to engineer nonlinear optical processes in metal nanoparticle arrays

NASA Astrophysics Data System (ADS)

Huttunen, Mikko J.; Rasekh, Payman; Boyd, Robert W.; Dolgaleva, Ksenia

2018-05-01

Collective responses of localized surface plasmon resonances, known as surface lattice resonances (SLRs) in metal nanoparticle arrays, can lead to high quality factors (˜100 ), large local-field enhancements, and strong light-matter interactions. SLRs have found many applications in linear optics, but little work of the influence of SLRs on nonlinear optics has been reported. Here we show how SLRs could be utilized to enhance nonlinear optical interactions. We devote special attention to the sum-frequency, difference-frequency, and third-harmonic generation processes because of their potential for the realization of novel sources of light. We also demonstrate how such arrays could be engineered to enhance higher-order nonlinear optical interactions through cascaded nonlinear processes. In particular, we demonstrate how the efficiency of third-harmonic generation could be engineered via cascaded second-order responses.

Seismic array processing and computational infrastructure for improved monitoring of Alaskan and Aleutian seismicity and volcanoes

NASA Astrophysics Data System (ADS)

Lindquist, Kent Gordon

We constructed a near-real-time system, called Iceworm, to automate seismic data collection, processing, storage, and distribution at the Alaska Earthquake Information Center (AEIC). Phase-picking, phase association, and interprocess communication components come from Earthworm (U.S. Geological Survey). A new generic, internal format for digital data supports unified handling of data from diverse sources. A new infrastructure for applying processing algorithms to near-real-time data streams supports automated information extraction from seismic wavefields. Integration of Datascope (U. of Colorado) provides relational database management of all automated measurements, parametric information for located hypocenters, and waveform data from Iceworm. Data from 1997 yield 329 earthquakes located by both Iceworm and the AEIC. Of these, 203 have location residuals under 22 km, sufficient for hazard response. Regionalized inversions for local magnitude in Alaska yield Msb{L} calibration curves (logAsb0) that differ from the Californian Richter magnitude. The new curve is 0.2\\ Msb{L} units more attenuative than the Californian curve at 400 km for earthquakes north of the Denali fault. South of the fault, and for a region north of Cook Inlet, the difference is 0.4\\ Msb{L}. A curve for deep events differs by 0.6\\ Msb{L} at 650 km. We expand geographic coverage of Alaskan regional seismic monitoring to the Aleutians, the Bering Sea, and the entire Arctic by initiating the processing of four short-period, Alaskan seismic arrays. To show the array stations' sensitivity, we detect and locate two microearthquakes that were missed by the AEIC. An empirical study of the location sensitivity of the arrays predicts improvements over the Alaskan regional network that are shown as map-view contour plots. We verify these predictions by detecting an Msb{L} 3.2 event near Unimak Island with one array. The detection and location of four representative earthquakes illustrates the expansion

BreedVision — A Multi-Sensor Platform for Non-Destructive Field-Based Phenotyping in Plant Breeding

PubMed Central

Busemeyer, Lucas; Mentrup, Daniel; Möller, Kim; Wunder, Erik; Alheit, Katharina; Hahn, Volker; Maurer, Hans Peter; Reif, Jochen C.; Würschum, Tobias; Müller, Joachim; Rahe, Florian; Ruckelshausen, Arno

2013-01-01

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies. PMID:23447014

Downsampling Photodetector Array with Windowing

NASA Technical Reports Server (NTRS)

Patawaran, Ferze D.; Farr, William H.; Nguyen, Danh H.; Quirk, Kevin J.; Sahasrabudhe, Adit

2012-01-01

In a photon counting detector array, each pixel in the array produces an electrical pulse when an incident photon on that pixel is detected. Detection and demodulation of an optical communication signal that modulated the intensity of the optical signal requires counting the number of photon arrivals over a given interval. As the size of photon counting photodetector arrays increases, parallel processing of all the pixels exceeds the resources available in current application-specific integrated circuit (ASIC) and gate array (GA) technology; the desire for a high fill factor in avalanche photodiode (APD) detector arrays also precludes this. Through the use of downsampling and windowing portions of the detector array, the processing is distributed between the ASIC and GA. This allows demodulation of the optical communication signal incident on a large photon counting detector array, as well as providing architecture amenable to algorithmic changes. The detector array readout ASIC functions as a parallel-to-serial converter, serializing the photodetector array output for subsequent processing. Additional downsampling functionality for each pixel is added to this ASIC. Due to the large number of pixels in the array, the readout time of the entire photodetector is greater than the time between photon arrivals; therefore, a downsampling pre-processing step is done in order to increase the time allowed for the readout to occur. Each pixel drives a small counter that is incremented at every detected photon arrival or, equivalently, the charge in a storage capacitor is incremented. At the end of a user-configurable counting period (calculated independently from the ASIC), the counters are sampled and cleared. This downsampled photon count information is then sent one counter word at a time to the GA. For a large array, processing even the downsampled pixel counts exceeds the capabilities of the GA. Windowing of the array, whereby several subsets of pixels are designated

R-process experiments with the Advanced Implantation Detector Array

NASA Astrophysics Data System (ADS)

Estrade, Alfredo; Griffin, Chris; Davinson, Tom; Bruno, Carlo; Hall, Oscar; Liu, Zhong; Woods, Phil; Coleman-Smith, Patrick; Labiche, Marc; Lazarus, Ian; Pucknell, Victor; Simpson, John; Harkness-Brennan, Laura; Page, Robert; Kiss, Gabor; Liu, Jiajiang; Matsui, Keishi; Nishimura, Shunji; Phong, Vi; Lorusso, Giuseppe; Montes, Fernando; Nepal, Neerajan; Briken Collaboration; Ribf106 Experiment Team

2017-09-01

Decay properties of neutron rich isotopes, such as half-lives and β-delayed neutron emission probabilities, are an important input for astrophysical models of the r-process. A new generation of fragmentation beam facilities has made it possible to access large regions of the nuclear chart that are close to the path of the r-process for some astrophysical models. The Advanced Implantation Detector Array (AIDA) is a segmented active-stopper detector designed for decay experiments with fast ion beams, which was recently commissioned at the Radioactive Ion Beam Factory in RIKEN, Japan. In this presentation we describe the main characteristics of AIDA, and present preliminary results of the first experiments in the region of neutron-rich selenium isotopes and along the N=82 shell closure.

Integrated LTCC pressure/flow/temperature multisensor for compressed air diagnostics.

PubMed

Fournier, Yannick; Maeder, Thomas; Boutinard-Rouelle, Grégoire; Barras, Aurélie; Craquelin, Nicolas; Ryser, Peter

2010-01-01

We present a multisensor designed for industrial compressed air diagnostics and combining the measurement of pressure, flow, and temperature, integrated with the corresponding signal conditioning electronics in a single low-temperature co-fired ceramic (LTCC) package. The developed sensor may be soldered onto an integrated electro-fluidic platform by using standard surface mount device (SMD) technology, e.g., as a standard electronic component would be on a printed circuit board, obviating the need for both wires and tubes and thus paving the road towards low-cost integrated electro-fluidic systems. Several performance aspects of this device are presented and discussed, together with electronics design issues.

Integrated LTCC Pressure/Flow/Temperature Multisensor for Compressed Air Diagnostics†

PubMed Central

Fournier, Yannick; Maeder, Thomas; Boutinard-Rouelle, Grégoire; Barras, Aurélie; Craquelin, Nicolas; Ryser, Peter

2010-01-01

We present a multisensor designed for industrial compressed air diagnostics and combining the measurement of pressure, flow, and temperature, integrated with the corresponding signal conditioning electronics in a single low-temperature co-fired ceramic (LTCC) package. The developed sensor may be soldered onto an integrated electro-fluidic platform by using standard surface mount device (SMD) technology, e.g., as a standard electronic component would be on a printed circuit board, obviating the need for both wires and tubes and thus paving the road towards low-cost integrated electro-fluidic systems. Several performance aspects of this device are presented and discussed, together with electronics design issues. PMID:22163518

Solid-State Multi-Sensor Array System for Real Time Imaging of Magnetic Fields and Ferrous Objects

NASA Astrophysics Data System (ADS)

Benitez, D.; Gaydecki, P.; Quek, S.; Torres, V.

2008-02-01

In this paper the development of a solid-state sensors based system for real-time imaging of magnetic fields and ferrous objects is described. The system comprises 1089 magneto inductive solid state sensors arranged in a 2D array matrix of 33×33 files and columns, equally spaced in order to cover an approximate area of 300 by 300 mm. The sensor array is located within a large current-carrying coil. Data is sampled from the sensors by several DSP controlling units and finally streamed to a host computer via a USB 2.0 interface and the image generated and displayed at a rate of 20 frames per minute. The development of the instrumentation has been complemented by extensive numerical modeling of field distribution patterns using boundary element methods. The system was originally intended for deployment in the non-destructive evaluation (NDE) of reinforced concrete. Nevertheless, the system is not only capable of producing real-time, live video images of the metal target embedded within any opaque medium, it also allows the real-time visualization and determination of the magnetic field distribution emitted by either permanent magnets or geometries carrying current. Although this system was initially developed for the NDE arena, it could also have many potential applications in many other fields, including medicine, security, manufacturing, quality assurance and design involving magnetic fields.

A multi-sensor remote sensing approach for measuring primary production from space

NASA Technical Reports Server (NTRS)

Gautier, Catherine

1989-01-01

It is proposed to develop a multi-sensor remote sensing method for computing marine primary productivity from space, based on the capability to measure the primary ocean variables which regulate photosynthesis. The three variables and the sensors which measure them are: (1) downwelling photosynthetically available irradiance, measured by the VISSR sensor on the GOES satellite, (2) sea-surface temperature from AVHRR on NOAA series satellites, and (3) chlorophyll-like pigment concentration from the Nimbus-7/CZCS sensor. These and other measured variables would be combined within empirical or analytical models to compute primary productivity. With this proposed capability of mapping primary productivity on a regional scale, we could begin realizing a more precise and accurate global assessment of its magnitude and variability. Applications would include supplementation and expansion on the horizontal scale of ship-acquired biological data, which is more accurate and which supplies the vertical components of the field, monitoring oceanic response to increased atmospheric carbon dioxide levels, correlation with observed sedimentation patterns and processes, and fisheries management.

Status report on the land processes aircraft science management operations working group

NASA Technical Reports Server (NTRS)

Lawless, James G.; Mann, Lisa J.

1991-01-01

Since its inception three years ago, the Land Processes Aircraft Science Management Operations Working Group (MOWG) provided recommendations on the optimal use of the Agency's aircraft in support of the Land Processes Science Program. Recommendations covered topics such as aircraft and sensor usage, development of long-range plans, Multisensor Airborne Campaigns (MAC), program balance, aircraft sensor databases, new technology and sensor development, and increased University scientist participation in the program. Impacts of these recommendations improved the efficiency of various procedures including the flight request process, tracking of flight hours, and aircraft usage. The group also created a bibliography focused on publications produced by Land Processes scientists from the use of the aircraft program, surveyed NASA funded PI's on their participation in the aircraft program, and developed a planning template for multi-sensor airborne campaigns. Benefits from these activities are summarized.

Square Kilometre Array Science Data Processing

NASA Astrophysics Data System (ADS)

Nikolic, Bojan; SDP Consortium, SKA

2014-04-01

The Square Kilometre Array (SKA) is planned to be, by a large factor, the largest and most sensitive radio telescope ever constructed. The first phase of the telescope (SKA1), now in the design phase, will in itself represent a major leap in capabilities compared to current facilities. These advances are to a large extent being made possible by advances in available computer processing power so that that larger numbers of smaller, simpler and cheaper receptors can be used. As a result of greater reliance and demands on computing, ICT is becoming an ever more integral part of the telescope. The Science Data Processor is the part of the SKA system responsible for imaging, calibration, pulsar timing, confirmation of pulsar candidates, derivation of some further derived data products, archiving and providing the data to the users. It will accept visibilities at data rates at several TB/s and require processing power for imaging in range 100 petaFLOPS -- ~1 ExaFLOPS, putting SKA1 into the regime of exascale radio astronomy. In my talk I will present the overall SKA system requirements and how they drive these high data throughput and processing requirements. Some of the key challenges for the design of SDP are: - Identifying sufficient parallelism to utilise very large numbers of separate compute cores that will be required to provide exascale computing throughput - Managing efficiently the high internal data flow rates - A conceptual architecture and software engineering approach that will allow adaptation of the algorithms as we learn about the telescope and the atmosphere during the commissioning and operational phases - System management that will deal gracefully with (inevitably frequent) failures of individual units of the processing system In my talk I will present possible initial architectures for the SDP system that attempt to address these and other challenges.

The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System.

PubMed

Caduff, Andreas; Zanon, Mattia; Mueller, Martin; Zakharov, Pavel; Feldman, Yuri; De Feo, Oscar; Donath, Marc; Stahel, Werner A; Talary, Mark S

2015-07-01

We study here the influence of different patients and the influence of different devices with the same patients on the signals and modeling of data from measurements from a noninvasive Multisensor glucose monitoring system in patients with type 1 diabetes. The Multisensor includes several sensors for biophysical monitoring of skin and underlying tissue integrated on a single substrate. Two Multisensors were worn simultaneously, 1 on the upper left and 1 on the upper right arm by 4 patients during 16 study visits. Glucose was administered orally to induce 2 consecutive hyperglycemic excursions. For the analysis, global (valid for a population of patients), personal (tailored to a specific patient), and device-specific multiple linear regression models were derived. We find that adjustments of the model to the patients improves the performance of the glucose estimation with an MARD of 17.8% for personalized model versus a MARD of 21.1% for the global model. At the same time the effect of the measurement side is negligible. The device can equally well measure on the left or right arm. We also see that devices are equal in the linear modeling. Thus hardware calibration of the sensors is seen to be sufficient to eliminate interdevice differences in the measured signals. We demonstrate that the hardware of the 2 devices worn on the left and right arms are consistent yielding similar measured signals and thus glucose estimation results with a global model. The 2 devices also return similar values of glucose errors. These errors are mainly due to nonstationarities in the measured signals that are not solved by the linear model, thus suggesting for more sophisticated modeling approaches. © 2015 Diabetes Technology Society.

Performance of redundant disk array organizations in transaction processing environments

NASA Technical Reports Server (NTRS)

Mourad, Antoine N.; Fuchs, W. K.; Saab, Daniel G.

1993-01-01

A performance evaluation is conducted for two redundant disk-array organizations in a transaction-processing environment, relative to the performance of both mirrored disk organizations and organizations using neither striping nor redundancy. The proposed parity-striping alternative to striping with rotated parity is shown to furnish rapid recovery from failure at the same low storage cost without interleaving the data over multiple disks. Both noncached systems and systems using a nonvolatile cache as the controller are considered.

Acetylcholine molecular arrays enable quantum information processing

NASA Astrophysics Data System (ADS)

Tamulis, Arvydas; Majauskaite, Kristina; Talaikis, Martynas; Zborowski, Krzysztof; Kairys, Visvaldas

2017-09-01

We have found self-assembly of four neurotransmitter acetylcholine (ACh) molecular complexes in a water molecules environment by using geometry optimization with DFT B97d method. These complexes organizes to regular arrays of ACh molecules possessing electronic spins, i.e. quantum information bits. These spin arrays could potentially be controlled by the application of a non-uniform external magnetic field. The proper sequence of resonant electromagnetic pulses would then drive all the spin groups into the 3-spin entangled state and proceed large scale quantum information bits.

Air Enquirer's multi-sensor boxes as a tool for High School Education and Atmospheric Research

NASA Astrophysics Data System (ADS)

Morguí, Josep-Anton; Font, Anna; Cañas, Lidia; Vázquez-García, Eusebi; Gini, Andrea; Corominas, Ariadna; Àgueda, Alba; Lobo, Agustin; Ferraz, Carlos; Nofuentes, Manel; Ulldemolins, Delmir; Roca, Alex; Kamnang, Armand; Grossi, Claudia; Curcoll, Roger; Batet, Oscar; Borràs, Silvia; Occhipinti, Paola; Rodó, Xavier

2016-04-01

An educational tool was designed with the aim of making more comprehensive the research done on Greenhouse Gases (GHGs) in the ClimaDat Spanish network of atmospheric observation stations (www.climadat.es). This tool is called Air Enquirer and it consist of a multi-sensor box. It is envisaged to build more than two hundred boxes to yield them to the Spanish High Schools through the Education department (www.educaixa.com) of the "Obra Social 'La Caixa'", who funds this research. The starting point for the development of the Air Enquirers was the experience at IC3 (www.ic3.cat) in the CarboSchools+ FP7 project (www.carboschools.cat, www.carboschools.eu). The Air Enquirer's multi-sensor box is based in Arduino's architecture and contains sensors for CO2, temperature, relative humidity, pressure, and both infrared and visible luminance. The Air Enquirer is designed for taking continuous measurements. Every Air Enquirer ensemble of measurements is used to convert values to standard units (water content in ppmv, and CO2 in ppmv_dry). These values are referred to a calibration made with Cavity Ring Down Spectrometry (Picarro®) under different temperature, pressure, humidity and CO2 concentrations. Multiple sets of Air Enquirers are intercalibrated for its use in parallel during the experiments. The different experiments proposed to the students will be outdoor (observational) or indoor (experimental, in the lab) focusing on understanding the biogeochemistry of GHGs in the ecosystems (mainly CO2), the exchange (flux) of gases, the organic matter production, respiration and decomposition processes, the influence of the anthropogenic activities on the gases (and particles) exchanges, and their interaction with the structure and composition of the atmosphere (temperature, water content, cooling and warming processes, radiative forcing, vertical gradients and horizontal patterns). In order to ensure Air Enquirers a high-profile research performance the experimental designs

The Canadian Forces ILDS: a militarily fielded multisensor vehicle-mounted teleoperated landmine detection system

NASA Astrophysics Data System (ADS)

McFee, John E.; Russell, Kevin L.; Chesney, Robert H.; Faust, Anthony A.; Das, Yogadhish

2006-05-01

The Improved Landmine Detection System (ILDS) is intended to meet Canadian military mine clearance requirements in rear area combat situations and peacekeeping on roads and tracks. The system consists of two teleoperated vehicles and a command vehicle. The teleoperated protection vehicle precedes, clearing antipersonnel mines and magnetic and tilt rod-fuzed antitank mines. It consists of an armoured personnel carrier with a forward looking infrared imager, a finger plow or roller and a magnetic signature duplicator. The teleoperated detection vehicle follows to detect antitank mines. The purpose-built vehicle carries forward looking infrared and visible imagers, a 3 m wide, down-looking sensitive electromagnetic induction detector array and a 3 m wide down-looking ground probing radar, which scan the ground in front of the vehicle. Sensor information is combined using navigation sensors and custom navigation, registration, spatial correspondence and data fusion algorithms. Suspicious targets are then confirmed by a thermal neutron activation detector. The prototype, designed and built by Defence R&D Canada, was completed in October 1997. General Dynamics Canada delivered four production units, based on the prototype concept and technologies, to the Canadian Forces (CF) in 2002. ILDS was deployed in Afghanistan in 2003, making the system the first militarily fielded, teleoperated, multi-sensor vehicle-mounted mine detector and the first with a fielded confirmation sensor. Performance of the prototype in Canadian and independent US trials is summarized and recent results from the production version of the confirmation sensor are discussed. CF operations with ILDS in Afghanistan are described.

In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis

PubMed Central

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-01-01

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image. PMID:20057957

In-TFT-array-process micro defect inspection using nonlinear principal component analysis.

PubMed

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-11-20

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image.

Fabrication of Aligned Polyaniline Nanofiber Array via a Facile Wet Chemical Process.

PubMed

Sun, Qunhui; Bi, Wu; Fuller, Thomas F; Ding, Yong; Deng, Yulin

2009-06-17

In this work, we demonstrate for the first time a template free approach to synthesize aligned polyaniline nanofiber (PN) array on a passivated gold (Au) substrate via a facile wet chemical process. The Au surface was first modified using 4-aminothiophenol (4-ATP) to afford the surface functionality, followed subsequently by an oxidation polymerization of aniline (AN) monomer in an aqueous medium using ammonium persulfate as the oxidant and tartaric acid as the doping agent. The results show that a vertically aligned PANI nanofiber array with individual fiber diameters of ca. 100 nm, heights of ca. 600 nm and a packing density of ca. 40 pieces·µm(-2) , was synthesized. Copyright © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Close-in detection system for the Mine Hunter/Killer program

NASA Astrophysics Data System (ADS)

Bishop, Steven S.; Campana, Stephen B.; Lang, David A.; Wiggins, Carl M.

2000-08-01

The Close-in Detection (CID) System is the vehicle-mounted multisensor landmine detection system for the Army CECOM Night Vision Electronic Sensors Directorate (NVESD) Mine Hunter/Killer (MH/K) Program. The CID System is being developed by BAE Systems in San Diego, CA. TRW Systems and Information Technology Group in Arlington, VA and a team of specialists for ERIM, E-OIR, SNL, and APL/JHU support NVESD in the development, analysis and testing of the CID and associated signal and data processing. The CID System includes tow down-looking sensor arrays: a ground- penetrating radar (GPR) array, and a set of Electro-Magnetic Induction (EMI) coils for metal detection. These arrays span a 3-meter wide swath in front of a high mobility, multipurpose wheeled vehicle. The system also includes a forward looking IR imaging system mounted on the roof of the vehicle and covering a swath of the road ahead of the vehicle. Signals from each sensor are processed separately to detect and localize objects of interest. Features of candidate objects are integrated in a processor that uses them to discriminates between anti-tank miens and clutter. Mine locations are passed to the neutralization subsystem of MH/K. This paper reviews the design of the sensors and signal processing of the CID system and gives examples and analysis of recent test results at the NVESD mine lanes. The strengths and weaknesses of each sensor are discussed, and the application of multisensor fusion is illustrated.

Geophysical Inversion with Adaptive Array Processing of Ambient Noise

NASA Astrophysics Data System (ADS)

Traer, James

2011-12-01

Land-based seismic observations of microseisms generated during Tropical Storms Ernesto and Florence are dominated by signals in the 0.15--0.5Hz band. Data from seafloor hydrophones in shallow water (70m depth, 130 km off the New Jersey coast) show dominant signals in the gravity-wave frequency band, 0.02--0.18Hz and low amplitudes from 0.18--0.3Hz, suggesting significant opposing wave components necessary for DF microseism generation were negligible at the site. Both storms produced similar spectra, despite differing sizes, suggesting near-coastal shallow water as the dominant region for observed microseism generation. A mathematical explanation for a sign-inversion induced to the passive fathometer response by minimum variance distortionless response (MVDR) beamforming is presented. This shows that, in the region containing the bottom reflection, the MVDR fathometer response is identical to that obtained with conventional processing multiplied by a negative factor. A model is presented for the complete passive fathometer response to ocean surface noise, interfering discrete noise sources, and locally uncorrelated noise in an ideal waveguide. The leading order term of the ocean surface noise produces the cross-correlation of vertical multipaths and yields the depth of sub-bottom reflectors. Discrete noise incident on the array via multipaths give multiple peaks in the fathometer response. These peaks may obscure the sub-bottom reflections but can be attenuated with use of Minimum Variance Distortionless Response (MVDR) steering vectors. A theory is presented for the Signal-to-Noise-Ratio (SNR) for the seabed reflection peak in the passive fathometer response as a function of seabed depth, seabed reflection coefficient, averaging time, bandwidth and spatial directivity of the noise field. The passive fathometer algorithm was applied to data from two drifting array experiments in the Mediterranean, Boundary 2003 and 2004, with 0.34s of averaging time. In the 2004

Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors.

PubMed

Chowdhury, Enhad A; Western, Max J; Nightingale, Thomas E; Peacock, Oliver J; Thompson, Dylan

2017-01-01

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices

Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors

PubMed Central

Chowdhury, Enhad A.; Western, Max J.; Nightingale, Thomas E.; Peacock, Oliver J.; Thompson, Dylan

2017-01-01

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices

Improving GPR Surveys Productivity by Array Technology and Fully Automated Processing

NASA Astrophysics Data System (ADS)

Morello, Marco; Ercoli, Emanuele; Mazzucchelli, Paolo; Cottino, Edoardo

2016-04-01

The realization of network infrastructures with lower environmental impact and the tendency to use digging technologies less invasive in terms of time and space of road occupation and restoration play a key-role in the development of communication networks. However, pre-existing buried utilities must be detected and located in the subsurface, to exploit the high productivity of modern digging apparatus. According to SUE quality level B+ both position and depth of subsurface utilities must be accurately estimated, demanding for 3D GPR surveys. In fact, the advantages of 3D GPR acquisitions (obtained either by multiple 2D recordings or by an antenna array) versus 2D acquisitions are well-known. Nonetheless, the amount of acquired data for such 3D acquisitions does not usually allow to complete processing and interpretation directly in field and in real-time, thus limiting the overall efficiency of the GPR acquisition. As an example, the "low impact mini-trench "technique (addressed in ITU - International Telecommunication Union - L.83 recommendation) requires that non-destructive mapping of buried services enhances its productivity to match the improvements of new digging equipment. Nowadays multi-antenna and multi-pass GPR acquisitions demand for new processing techniques that can obtain high quality subsurface images, taking full advantage of 3D data: the development of a fully automated and real-time 3D GPR processing system plays a key-role in overall optical network deployment profitability. Furthermore, currently available computing power suggests the feasibility of processing schemes that incorporate better focusing algorithms. A novel processing scheme, whose goal is the automated processing and detection of buried targets that can be applied in real-time to 3D GPR array systems, has been developed and fruitfully tested with two different GPR arrays (16 antennas, 900 MHz central frequency, and 34 antennas, 600 MHz central frequency). The proposed processing

Assembly and Integration Process of the First High Density Detector Array for the Atacama Cosmology Telescope

NASA Technical Reports Server (NTRS)

Li, Yaqiong; Choi, Steve; Ho, Shuay-Pwu; Crowley, Kevin T.; Salatino, Maria; Simon, Sara M.; Staggs, Suzanne T.; Nati, Federico; Wollack, Edward J.

2016-01-01

The Advanced ACTPol (AdvACT) upgrade on the Atacama Cosmology Telescope (ACT) consists of multichroicTransition Edge Sensor (TES) detector arrays to measure the Cosmic Microwave Background (CMB) polarization anisotropies in multiple frequency bands. The first AdvACT detector array, sensitive to both 150 and 230 GHz, is fabricated on a 150 mm diameter wafer and read out with a completely different scheme compared to ACTPol. Approximately 2000 TES bolometers are packed into the wafer leading to both a much denser detector density and readout circuitry. The demonstration of the assembly and integration of the AdvACT arrays is important for the next generation CMB experiments, which will continue to increase the pixel number and density. We present the detailed assembly process of the first AdvACT detector array.

Controllable 3D architectures of aligned carbon nanotube arrays by multi-step processes

NASA Astrophysics Data System (ADS)

Huang, Shaoming

2003-06-01

An effective way to fabricate large area three-dimensional (3D) aligned CNTs pattern based on pyrolysis of iron(II) phthalocyanine (FePc) by two-step processes is reported. The controllable generation of different lengths and selective growth of the aligned CNT arrays on metal-patterned (e.g., Ag and Au) substrate are the bases for generating such 3D aligned CNTs architectures. By controlling experimental conditions 3D aligned CNT arrays with different lengths/densities and morphologies/structures as well as multi-layered architectures can be fabricated in large scale by multi-step pyrolysis of FePc. These 3D architectures could have interesting properties and be applied for developing novel nanotube-based devices.

Astronomical Data Processing Using SciQL, an SQL Based Query Language for Array Data

NASA Astrophysics Data System (ADS)

Zhang, Y.; Scheers, B.; Kersten, M.; Ivanova, M.; Nes, N.

2012-09-01

SciQL (pronounced as ‘cycle’) is a novel SQL-based array query language for scientific applications with both tables and arrays as first class citizens. SciQL lowers the entrance fee of adopting relational DBMS (RDBMS) in scientific domains, because it includes functionality often only found in mathematics software packages. In this paper, we demonstrate the usefulness of SciQL for astronomical data processing using examples from the Transient Key Project of the LOFAR radio telescope. In particular, how the LOFAR light-curve database of all detected sources can be constructed, by correlating sources across the spatial, frequency, time and polarisation domains.

Solution-Processed Organic Thin-Film Transistor Array for Active-Matrix Organic Light-Emitting Diode

NASA Astrophysics Data System (ADS)

Harada, Chihiro; Hata, Takuya; Chuman, Takashi; Ishizuka, Shinichi; Yoshizawa, Atsushi

2013-05-01

We developed a 3-in. organic thin-film transistor (OTFT) array with an ink-jetted organic semiconductor. All layers except electrodes were fabricated by solution processes. The OTFT performed well without hysteresis, and the field-effect mobility in the saturation region was 0.45 cm2 V-1 s-1, the threshold voltage was 3.3 V, and the on/off current ratio was more than 106. We demonstrated a 3-in. active-matrix organic light-emitting diode (AMOLED) display driven by the OTFT array. The display could provide clear moving images. The peak luminance of the display was 170 cd/m2.

Principles of Adaptive Array Processing

DTIC Science & Technology

2006-09-01

ACE with and without tapering (homogeneous case). These analytical results are less suited to predict the detection performance of a real system ...Nickel: Adaptive Beamforming for Phased Array Radars. Proc. Int. Radar Symposium IRS’98 (Munich, Sept. 1998), DGON and VDE /ITG, pp. 897-906.(Reprint also...strategies for airborne radar. Asilomar Conf. on Signals, Systems and Computers, Pacific Grove, CA, 1998, IEEE Cat.Nr. 0-7803-5148-7/98, pp. 1327-1331. [17

Numerical Simulation of the Diffusion Processes in Nanoelectrode Arrays Using an Axial Neighbor Symmetry Approximation.

PubMed

Peinetti, Ana Sol; Gilardoni, Rodrigo S; Mizrahi, Martín; Requejo, Felix G; González, Graciela A; Battaglini, Fernando

2016-06-07

Nanoelectrode arrays have introduced a complete new battery of devices with fascinating electrocatalytic, sensitivity, and selectivity properties. To understand and predict the electrochemical response of these arrays, a theoretical framework is needed. Cyclic voltammetry is a well-fitted experimental technique to understand the undergoing diffusion and kinetics processes. Previous works describing microelectrode arrays have exploited the interelectrode distance to simulate its behavior as the summation of individual electrodes. This approach becomes limited when the size of the electrodes decreases to the nanometer scale due to their strong radial effect with the consequent overlapping of the diffusional fields. In this work, we present a computational model able to simulate the electrochemical behavior of arrays working either as the summation of individual electrodes or being affected by the overlapping of the diffusional fields without previous considerations. Our computational model relays in dividing a regular electrode array in cells. In each of them, there is a central electrode surrounded by neighbor electrodes; these neighbor electrodes are transformed in a ring maintaining the same active electrode area than the summation of the closest neighbor electrodes. Using this axial neighbor symmetry approximation, the problem acquires a cylindrical symmetry, being applicable to any diffusion pattern. The model is validated against micro- and nanoelectrode arrays showing its ability to predict their behavior and therefore to be used as a designing tool.

Dynamic array processing for computationally intensive expert systems in CLIPS

NASA Technical Reports Server (NTRS)

Athavale, N. N.; Ragade, R. K.; Fenske, T. E.; Cassaro, M. A.

1990-01-01

This paper puts forth an architecture for implementing a loop for advanced data structure of arrays in CLIPS. An attempt is made to use multi-field variables in such an architecture to process a set of data during the decision making cycle. Also, current limitations on the expert system shells are discussed in brief in this paper. The resulting architecture is designed to circumvent the current limitations set by the expert system shell and also by the operating environment. Such advanced data structures are needed for tightly coupling symbolic and numeric computation modules.

Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery.

PubMed

Sarkar, Anjan; Banerjee, Anjan; Banerjee, Nilanjan; Brahma, Siddhartha; Kartikeyan, B; Chakraborty, Manab; Majumder, K L

2005-05-01

This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data.

Direct Growth of Crystalline Tungsten Oxide Nanorod Arrays by a Hydrothermal Process and Their Electrochromic Properties

NASA Astrophysics Data System (ADS)

Lu, Chih-Hao; Hon, Min Hsiung; Leu, Ing-Chi

2017-04-01

Transparent crystalline tungsten oxide nanorod arrays for use as an electrochromic layer have been directly prepared on fluorine-doped tin oxide-coated glass via a facile tungsten film-assisted hydrothermal process using aqueous tungsten hexachloride solution. X-ray diffraction analysis and field-emission scanning electron microscopy were used to characterize the phase and morphology of the grown nanostructures. Arrays of tungsten oxide nanorods with diameter of ˜22 nm and length of ˜240 nm were obtained at 200°C after 8 h of hydrothermal reaction. We propose a growth mechanism for the deposition of the monoclinic tungsten oxide phase in the hydrothermal environment. The tungsten film was first oxidized to tungsten oxide to provide seed sites for crystal growth and address the poor connection between the growing tungsten oxide and substrate. Aligned tungsten oxide nanorod arrays can be grown by a W thin film-assisted heterogeneous nucleation process with NaCl as a structure-directing agent. The fabricated electrochromic device demonstrated optical modulation (coloration/bleaching) at 632.8 nm of ˜41.2% after applying a low voltage of 0.1 V for 10 s, indicating the potential of such nanorod array films for use in energy-saving smart windows.

Validation of a multi-sensor hotwire probe for boundary layer enstrophy measurements

NASA Astrophysics Data System (ADS)

Zimmerman, Spencer; Morrill-Winter, Caleb; Klewicki, Joseph

2016-11-01

A multi-sensor hotwire probe capable of measuring the velocity and vorticity vectors has been designed and implemented in a turbulent boundary layer with the goal of educing the means by which the associated momentum transport is maintained under increasing scale separation between the velocity and vorticity fields with increasing Reynolds number. The capacity of this sensor to accurately measure each component of velocity and vorticity is first evaluated via synthetic experiment. The three-dimensional velocity field from the DNS of Sillero et al. is used to compute effective cooling for each sensor element, and the resulting signals are interpreted via two-dimensional calibration surfaces such as would be used to process physical experimental data. Results from this virtual validation experiment are presented and suggest the sensor is capable of resolving key features of the velocity and vorticity fields at physically achievable spatial resolutions. Results from measurements collected at the Flow Physics Facility (FPF) at the University of New Hampshire are presented alongside these projections and exhibit very good agreement in trend, but with some differences in magnitude. The support of the Australian Research Council and the National Science Foundation is gratefully acknowledged.

Lightweight solar array blanket tooling, laser welding and cover process technology

NASA Technical Reports Server (NTRS)

Dillard, P. A.

1983-01-01

A two phase technology investigation was performed to demonstrate effective methods for integrating 50 micrometer thin solar cells into ultralightweight module designs. During the first phase, innovative tooling was developed which allows lightweight blankets to be fabricated in a manufacturing environment with acceptable yields. During the second phase, the tooling was improved and the feasibility of laser processing of lightweight arrays was confirmed. The development of the cell/interconnect registration tool and interconnect bonding by laser welding is described.

Low cost, multiscale and multi-sensor application for flooded area mapping

NASA Astrophysics Data System (ADS)

Giordan, Daniele; Notti, Davide; Villa, Alfredo; Zucca, Francesco; Calò, Fabiana; Pepe, Antonio; Dutto, Furio; Pari, Paolo; Baldo, Marco; Allasia, Paolo

2018-05-01

Flood mapping and estimation of the maximum water depth are essential elements for the first damage evaluation, civil protection intervention planning and detection of areas where remediation is needed. In this work, we present and discuss a methodology for mapping and quantifying flood severity over floodplains. The proposed methodology considers a multiscale and multi-sensor approach using free or low-cost data and sensors. We applied this method to the November 2016 Piedmont (northwestern Italy) flood. We first mapped the flooded areas at the basin scale using free satellite data from low- to medium-high-resolution from both the SAR (Sentinel-1, COSMO-Skymed) and multispectral sensors (MODIS, Sentinel-2). Using very- and ultra-high-resolution images from the low-cost aerial platform and remotely piloted aerial system, we refined the flooded zone and detected the most damaged sector. The presented method considers both urbanised and non-urbanised areas. Nadiral images have several limitations, in particular in urbanised areas, where the use of terrestrial images solved this limitation. Very- and ultra-high-resolution images were processed with structure from motion (SfM) for the realisation of 3-D models. These data, combined with an available digital terrain model, allowed us to obtain maps of the flooded area, maximum high water area and damaged infrastructures.

Advanced ACTPol Multichroic Polarimeter Array Fabrication Process for 150 mm Wafers

NASA Astrophysics Data System (ADS)

Duff, S. M.; Austermann, J.; Beall, J. A.; Becker, D.; Datta, R.; Gallardo, P. A.; Henderson, S. W.; Hilton, G. C.; Ho, S. P.; Hubmayr, J.; Koopman, B. J.; Li, D.; McMahon, J.; Nati, F.; Niemack, M. D.; Pappas, C. G.; Salatino, M.; Schmitt, B. L.; Simon, S. M.; Staggs, S. T.; Stevens, J. R.; Van Lanen, J.; Vavagiakis, E. M.; Ward, J. T.; Wollack, E. J.

2016-08-01

Advanced ACTPol (AdvACT) is a third-generation cosmic microwave background receiver to be deployed in 2016 on the Atacama Cosmology Telescope (ACT). Spanning five frequency bands from 25 to 280 GHz and having just over 5600 transition-edge sensor (TES) bolometers, this receiver will exhibit increased sensitivity and mapping speed compared to previously fielded ACT instruments. This paper presents the fabrication processes developed by NIST to scale to large arrays of feedhorn-coupled multichroic AlMn-based TES polarimeters on 150-mm diameter wafers. In addition to describing the streamlined fabrication process which enables high yields of densely packed detectors across larger wafers, we report the details of process improvements for sensor (AlMn) and insulator (SiN_x) materials and microwave structures, and the resulting performance improvements.

Advanced ACTPol Multichroic Polarimeter Array Fabrication Process for 150 mm Wafers

NASA Technical Reports Server (NTRS)

Duff, S. M.; Austermann, J.; Beall, J. A.; Becker, D.; Datta, R.; Gallardo, P. A.; Henderson, S. W.; Hilton, G. C.; Ho, S. P.; Hubmayr, J.;

Multi-Sensor Documentation of Metric and Qualitative Information of Historic Stone Structures

NASA Astrophysics Data System (ADS)

Adamopoulos, E.; Tsilimantou, E.; Keramidas, V.; Apostolopoulou, M.; Karoglou, M.; Tapinaki, S.; Ioannidis, C.; Georgopoulos, A.; Moropoulou, A.

2017-08-01

This paper focuses on the integration of multi-sensor techniques regarding the acquisition, processing, visualisation and management of data regarding historic stone structures. The interdisciplinary methodology that is carried out here comprises of two parts. In the first part, the acquisition of qualitative and quantitative data concerning the geometry, the materials and the degradation of the tangible heritage asset each time, is discussed. The second part, refers to the analysis, management and visualization of the interrelated data by using spatial information technologies. Through the paradigm of the surveying of the ancient temple of Pythian Apollo at Acropolis of Rhodes, Rhodes Island, Greece, it is aimed to highlight the issues deriving from the separate application of documentation procedures and how the fusion of these methods can contribute effectively to ensure the completeness of the measurements for complex structures. The surveying results are further processed to be compatible and integrated with GIS. Also, the geometric documentation derivatives are combined with environmental data and the results of the application of non-destructive testing and evaluation techniques in situ and analytical techniques in lab after sampling. GIS operations are utilized to document the building materials but also to model and to analyse the decay extent and patterns. Detailed surface measurements and geo-processing analysis are executed. This integrated approach, helps the assessment of past interventions on the monument, identify main causes of damage and decay, and finally assist the decision making on the most compatible materials and techniques for protection and restoration works.

Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar

Free-running ADC- and FPGA-based signal processing method for brain PET using GAPD arrays

NASA Astrophysics Data System (ADS)

Hu, Wei; Choi, Yong; Hong, Key Jo; Kang, Jihoon; Jung, Jin Ho; Huh, Youn Suk; Lim, Hyun Keong; Kim, Sang Su; Kim, Byung-Tae; Chung, Yonghyun

2012-02-01

Currently, for most photomultiplier tube (PMT)-based PET systems, constant fraction discriminators (CFD) and time to digital converters (TDC) have been employed to detect gamma ray signal arrival time, whereas anger logic circuits and peak detection analog-to-digital converters (ADCs) have been implemented to acquire position and energy information of detected events. As compared to PMT the Geiger-mode avalanche photodiodes (GAPDs) have a variety of advantages, such as compactness, low bias voltage requirement and MRI compatibility. Furthermore, the individual read-out method using a GAPD array coupled 1:1 with an array scintillator can provide better image uniformity than can be achieved using PMT and anger logic circuits. Recently, a brain PET using 72 GAPD arrays (4×4 array, pixel size: 3 mm×3 mm) coupled 1:1 with LYSO scintillators (4×4 array, pixel size: 3 mm×3 mm×20 mm) has been developed for simultaneous PET/MRI imaging in our laboratory. Eighteen 64:1 position decoder circuits (PDCs) were used to reduce GAPD channel number and three off-the-shelf free-running ADC and field programmable gate array (FPGA) combined data acquisition (DAQ) cards were used for data acquisition and processing. In this study, a free-running ADC- and FPGA-based signal processing method was developed for the detection of gamma ray signal arrival time, energy and position information all together for each GAPD channel. For the method developed herein, three DAQ cards continuously acquired 18 channels of pre-amplified analog gamma ray signals and 108-bit digital addresses from 18 PDCs. In the FPGA, the digitized gamma ray pulses and digital addresses were processed to generate data packages containing pulse arrival time, baseline value, energy value and GAPD channel ID. Finally, these data packages were saved to a 128 Mbyte on-board synchronous dynamic random access memory (SDRAM) and then transferred to a host computer for coincidence sorting and image reconstruction. In order to

Information integration and diagnosis analysis of equipment status and production quality for machining process

NASA Astrophysics Data System (ADS)

Zan, Tao; Wang, Min; Hu, Jianzhong

2010-12-01

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

Micromachined Thermoelectric Sensors and Arrays and Process for Producing

NASA Technical Reports Server (NTRS)

Foote, Marc C. (Inventor); Jones, Eric W. (Inventor); Caillat, Thierry (Inventor)

2000-01-01

Linear arrays with up to 63 micromachined thermopile infrared detectors on silicon substrates have been constructed and tested. Each detector consists of a suspended silicon nitride membrane with 11 thermocouples of sputtered Bi-Te and Bi-Sb-Te thermoelectric elements films. At room temperature and under vacuum these detectors exhibit response times of 99 ms, zero frequency D* values of 1.4 x 10(exp 9) cmHz(exp 1/2)/W and responsivity values of 1100 V/W when viewing a 1000 K blackbody source. The only measured source of noise above 20 mHz is Johnson noise from the detector resistance. These results represent the best performance reported to date for an array of thermopile detectors. The arrays are well suited for uncooled dispersive point spectrometers. In another embodiment, also with Bi-Te and Bi-Sb-Te thermoelectric materials on micromachined silicon nitride membranes, detector arrays have been produced with D* values as high as 2.2 x 10(exp 9) cm Hz(exp 1/2)/W for 83 ms response times.

Physical assessment of coastal vulnerability under enhanced land subsidence in Semarang, Indonesia, using multi-sensor satellite data

NASA Astrophysics Data System (ADS)

Husnayaen; Rimba, A. Besse; Osawa, Takahiro; Parwata, I. Nyoman Sudi; As-syakur, Abd. Rahman; Kasim, Faizal; Astarini, Ida Ayu

2018-04-01

Research has been conducted in Semarang, Indonesia, to assess coastal vulnerability under enhanced land subsidence using multi-sensor satellite data, including the Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR), Landsat TM, IKONOS, and TOPEX/Poseidon. A coastal vulnerability index (CVI) was constructed to estimate the level of vulnerability of a coastline approximately 48.68 km in length using seven physical variables, namely, land subsidence, relative sea level change, coastal geomorphology, coastal slope, shoreline change, mean tidal range, and significant wave height. A comparison was also performed between a CVI calculated using seven parameters and a CVI using six parameters, the latter of which excludes the land subsidence parameter, to determine the effects of land subsidence during the coastal vulnerability assessment. This study showed that the accuracy of coastal vulnerability was increased 40% by adding the land subsidence factor (i.e., CVI 6 parameters = 53%, CVI 7 parameters = 93%). Moreover, Kappa coefficient indicated very good agreement (0.90) for CVI 7 parameters and fair agreement (0.3) for CVI 6 parameters. The results indicate that the area of very high vulnerability increased by 7% when land subsidence was added. Hence, using the CVI calculation including land subsidence parameters, the very high vulnerability area is determined to be 20% of the total coastline or 9.7 km of the total 48.7 km of coastline. This study proved that land subsidence has significant influence on coastal vulnerability in Semarang.

Conversion of electromagnetic energy in Z-pinch process of single planar wire arrays at 1.5 MA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liangping, Wang; Mo, Li; Juanjuan, Han

The electromagnetic energy conversion in the Z-pinch process of single planar wire arrays was studied on Qiangguang generator (1.5 MA, 100 ns). Electrical diagnostics were established to monitor the voltage of the cathode-anode gap and the load current for calculating the electromagnetic energy. Lumped-element circuit model of wire arrays was employed to analyze the electromagnetic energy conversion. Inductance as well as resistance of a wire array during the Z-pinch process was also investigated. Experimental data indicate that the electromagnetic energy is mainly converted to magnetic energy and kinetic energy and ohmic heating energy can be neglected before the final stagnation. Themore » kinetic energy can be responsible for the x-ray radiation before the peak power. After the stagnation, the electromagnetic energy coupled by the load continues increasing and the resistance of the load achieves its maximum of 0.6–1.0 Ω in about 10–20 ns.« less

Multi-Sensor Distributive On-Line Processing, Visualization, and Analysis Infrastructure for an Agricultural Information System at the NASA Goddard Earth Sciences DAAC

NASA Technical Reports Server (NTRS)

Teng, William; Berrick, Steve; Leptuokh, Gregory; Liu, Zhong; Rui, Hualan; Pham, Long; Shen, Suhung; Zhu, Tong

2004-01-01

The Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Distributed Active Center (DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM On-line Visualization and Analysis System precipitation and other satellite data products and services. AIS outputs will be ,integrated into existing operational decision support system for global crop monitoring, such as that of the U.N. World Food Program. The ability to use the raw data stored in the GES DAAC archives is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. To gain this understanding is a time-consuming process and not a productive investment of the user's time. This is an especially difficult challenge when users need to deal with multi-sensor data that usually are of different structures and resolutions. The AIS has taken a major step towards meeting this challenge by incorporating an underlying infrastructure, called the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni," that integrates various components to support web interfaces that ,allow users to perform interactive analysis on-line without downloading any data. Several instances of the Giovanni-based interface have been or are being created to serve users of TRMM precipitation, MODIS aerosol, and SeaWiFS ocean color data, as well as agricultural applications users. Giovanni-based interfaces are simple to use but powerful. The user selects geophysical ,parameters, area of interest, and time period; and the system generates an output ,on screen in a matter of seconds.

Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions

NASA Astrophysics Data System (ADS)

Marchesotti, Luca; Piva, Stefano; Turolla, Andrea; Minetti, Deborah; Regazzoni, Carlo S.

2005-03-01

The presented work describes an innovative architecture for multi-sensor distributed video surveillance applications. The aim of the system is to track moving objects in outdoor environments with a cooperative strategy exploiting two video cameras. The system also exhibits the capacity of focusing its attention on the faces of detected pedestrians collecting snapshot frames of face images, by segmenting and tracking them over time at different resolution. The system is designed to employ two video cameras in a cooperative client/server structure: the first camera monitors the entire area of interest and detects the moving objects using change detection techniques. The detected objects are tracked over time and their position is indicated on a map representing the monitored area. The objects" coordinates are sent to the server sensor in order to point its zooming optics towards the moving object. The second camera tracks the objects at high resolution. As well as the client camera, this sensor is calibrated and the position of the object detected on the image plane reference system is translated in its coordinates referred to the same area map. In the map common reference system, data fusion techniques are applied to achieve a more precise and robust estimation of the objects" track and to perform face detection and tracking. The work novelties and strength reside in the cooperative multi-sensor approach, in the high resolution long distance tracking and in the automatic collection of biometric data such as a person face clip for recognition purposes.

Array processor architecture

NASA Technical Reports Server (NTRS)

Barnes, George H. (Inventor); Lundstrom, Stephen F. (Inventor); Shafer, Philip E. (Inventor)

1983-01-01

A high speed parallel array data processing architecture fashioned under a computational envelope approach includes a data base memory for secondary storage of programs and data, and a plurality of memory modules interconnected to a plurality of processing modules by a connection network of the Omega gender. Programs and data are fed from the data base memory to the plurality of memory modules and from hence the programs are fed through the connection network to the array of processors (one copy of each program for each processor). Execution of the programs occur with the processors operating normally quite independently of each other in a multiprocessing fashion. For data dependent operations and other suitable operations, all processors are instructed to finish one given task or program branch before all are instructed to proceed in parallel processing fashion on the next instruction. Even when functioning in the parallel processing mode however, the processors are not locked-step but execute their own copy of the program individually unless or until another overall processor array synchronization instruction is issued.

Modeling Array Stations in SIG-VISA

NASA Astrophysics Data System (ADS)

Ding, N.; Moore, D.; Russell, S.

2013-12-01

We add support for array stations to SIG-VISA, a system for nuclear monitoring using probabilistic inference on seismic signals. Array stations comprise a large portion of the IMS network; they can provide increased sensitivity and more accurate directional information compared to single-component stations. Our existing model assumed that signals were independent at each station, which is false when lots of stations are close together, as in an array. The new model removes that assumption by jointly modeling signals across array elements. This is done by extending our existing Gaussian process (GP) regression models, also known as kriging, from a 3-dimensional single-component space of events to a 6-dimensional space of station-event pairs. For each array and each event attribute (including coda decay, coda height, amplitude transfer and travel time), we model the joint distribution across array elements using a Gaussian process that learns the correlation lengthscale across the array, thereby incorporating information of array stations into the probabilistic inference framework. To evaluate the effectiveness of our model, we perform ';probabilistic beamforming' on new events using our GP model, i.e., we compute the event azimuth having highest posterior probability under the model, conditioned on the signals at array elements. We compare the results from our probabilistic inference model to the beamforming currently performed by IMS station processing.

Process development for automated solar cell and module production. Task 4: Automated array assembly

NASA Technical Reports Server (NTRS)

1980-01-01

A process sequence which can be used in conjunction with automated equipment for the mass production of solar cell modules for terrestrial use was developed. The process sequence was then critically analyzed from a technical and economic standpoint to determine the technological readiness of certain process steps for implementation. The steps receiving analysis were: back contact metallization, automated cell array layup/interconnect, and module edge sealing. For automated layup/interconnect, both hard automation and programmable automation (using an industrial robot) were studied. The programmable automation system was then selected for actual hardware development.

An Undergraduate Course and Laboratory in Digital Signal Processing with Field Programmable Gate Arrays

ERIC Educational Resources Information Center

Meyer-Base, U.; Vera, A.; Meyer-Base, A.; Pattichis, M. S.; Perry, R. J.

2010-01-01

In this paper, an innovative educational approach to introducing undergraduates to both digital signal processing (DSP) and field programmable gate array (FPGA)-based design in a one-semester course and laboratory is described. While both DSP and FPGA-based courses are currently present in different curricula, this integrated approach reduces the…

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method.

PubMed

Deng, Xinyang; Jiang, Wen

2017-09-12

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model.

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method

PubMed Central

Deng, Xinyang

2017-01-01

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model. PMID:28895905

Similar Tensor Arrays - A Framework for Storage of Tensor Array Data

NASA Astrophysics Data System (ADS)

Brun, Anders; Martin-Fernandez, Marcos; Acar, Burak; Munoz-Moreno, Emma; Cammoun, Leila; Sigfridsson, Andreas; Sosa-Cabrera, Dario; Svensson, Björn; Herberthson, Magnus; Knutsson, Hans

This chapter describes a framework for storage of tensor array data, useful to describe regularly sampled tensor fields. The main component of the framework, called Similar Tensor Array Core (STAC), is the result of a collaboration between research groups within the SIMILAR network of excellence. It aims to capture the essence of regularly sampled tensor fields using a minimal set of attributes and can therefore be used as a “greatest common divisor” and interface between tensor array processing algorithms. This is potentially useful in applied fields like medical image analysis, in particular in Diffusion Tensor MRI, where misinterpretation of tensor array data is a common source of errors. By promoting a strictly geometric perspective on tensor arrays, with a close resemblance to the terminology used in differential geometry, (STAC) removes ambiguities and guides the user to define all necessary information. In contrast to existing tensor array file formats, it is minimalistic and based on an intrinsic and geometric interpretation of the array itself, without references to other coordinate systems.

Design of diffractive microlens array integration with focal plane arrays

NASA Astrophysics Data System (ADS)

Chen, Sihai; Yi, Xinjian; Li, Yi; He, Miao; Chen, Sixiang; Kong, Lingbin

2000-10-01

The IR spectrum from 3 to 5micrometers has numerous applications in both military and civil industries. High performance at high operating temperature is often important in these applications. Conventional Focal Plane Arrays (FPAs) without integration with concentrator such as microlens have poor sensitivity and low signal-to-noise ratio because of their lower fill factor. The binary optics microlens arrays reported in this paper are designed for integration with FPAs. Thus, the FPAs' fill factor, sensitivity, and signal- to-noise ratio can be improved while retaining a given image resolution and optical collection area. In the paper, we discussed the 256(Horizontal)x290(Vertical) microlens arrays designed for a center wavelength of 4micrometers , with 50micrometers (Horizontalx33micrometers (Vertical) quadrate pixel dimension and a speed (F number) of F/1.96. PtSi FPAs were fabricated on the front side of a 400-micrometers -thick Si substrate. The designed diffractive microlens arrays will be etched on the back side of the same wafer in a register fashion and it will be reported in other paper. Considering the diffraction efficiency, 8-phase-level approximation is enough. For the diffraction efficiency of 8-phase-level diffractive microlens reaches 95%. The process only need three mask-level, so we designed and fabricated three masks with the same dimension 4'x4'. Also, a set of fine verniers was designed and fabricated on each mask to allow accurate alignment during the fabrication process. Through a computer simulation, the microlens arrays are nearly diffraction limited, with the diffraction efficiency of 93%, a bit lower than the theoretical value of 95%. Introduction of microlens arrays has the ability to increase the FPAs' fill factor to 100%, while it is only about 21.6% without microlens. To our knowledge, this is the first trial of integration large area microlens arrays with FPAs at home.

Characterizing the Propagation of Uterine Electrophysiological Signals Recorded with a Multi-Sensor Abdominal Array in Term Pregnancies.

PubMed

Escalona-Vargas, Diana; Govindan, Rathinaswamy B; Furdea, Adrian; Murphy, Pam; Lowery, Curtis L; Eswaran, Hari

2015-01-01

The objective of this study was to quantify the number of segments that have contractile activity and determine the propagation speed from uterine electrophysiological signals recorded over the abdomen. The uterine magnetomyographic (MMG) signals were recorded with a 151 channel SARA (SQUID Array for Reproductive Assessment) system from 36 pregnant women between 37 and 40 weeks of gestational age. The MMG signals were scored and segments were classified based on presence of uterine contractile burst activity. The sensor space was then split into four quadrants and in each quadrant signal strength at each sample was calculated using center-of-gravity (COG). To this end, the cross-correlation analysis of the COG was performed to calculate the delay between pairwise combinations of quadrants. The relationship in propagation across the quadrants was quantified and propagation speeds were calculated from the delays. MMG recordings were successfully processed from 25 subjects and the average values of propagation speeds ranged from 1.3-9.5 cm/s, which was within the physiological range. The propagation was observed between both vertical and horizontal quadrants confirming multidirectional propagation. After the multiple pairwise test (99% CI), significant differences in speeds can be observed between certain vertical or horizontal combinations and the crossed pair combinations. The number of segments containing contractile activity in any given quadrant pair with a detectable delay was significantly higher in the lower abdominal pairwise combination as compared to all others. The quadrant-based approach using MMG signals provided us with high spatial-temporal information of the uterine contractile activity and will help us in the future to optimize abdominal electromyographic (EMG) recordings that are practical in a clinical setting.

Characterizing the Propagation of Uterine Electrophysiological Signals Recorded with a Multi-Sensor Abdominal Array in Term Pregnancies

PubMed Central

Escalona-Vargas, Diana; Govindan, Rathinaswamy B.; Furdea, Adrian; Murphy, Pam; Lowery, Curtis L.; Eswaran, Hari

2015-01-01

The objective of this study was to quantify the number of segments that have contractile activity and determine the propagation speed from uterine electrophysiological signals recorded over the abdomen. The uterine magnetomyographic (MMG) signals were recorded with a 151 channel SARA (SQUID Array for Reproductive Assessment) system from 36 pregnant women between 37 and 40 weeks of gestational age. The MMG signals were scored and segments were classified based on presence of uterine contractile burst activity. The sensor space was then split into four quadrants and in each quadrant signal strength at each sample was calculated using center-of-gravity (COG). To this end, the cross-correlation analysis of the COG was performed to calculate the delay between pairwise combinations of quadrants. The relationship in propagation across the quadrants was quantified and propagation speeds were calculated from the delays. MMG recordings were successfully processed from 25 subjects and the average values of propagation speeds ranged from 1.3–9.5 cm/s, which was within the physiological range. The propagation was observed between both vertical and horizontal quadrants confirming multidirectional propagation. After the multiple pairwise test (99% CI), significant differences in speeds can be observed between certain vertical or horizontal combinations and the crossed pair combinations. The number of segments containing contractile activity in any given quadrant pair with a detectable delay was significantly higher in the lower abdominal pairwise combination as compared to all others. The quadrant-based approach using MMG signals provided us with high spatial-temporal information of the uterine contractile activity and will help us in the future to optimize abdominal electromyographic (EMG) recordings that are practical in a clinical setting. PMID:26505624

Multi-Sensor Aerosol Products Sampling System

NASA Technical Reports Server (NTRS)

Petrenko, M.; Ichoku, C.; Leptoukh, G.

2011-01-01

Global and local properties of atmospheric aerosols have been extensively observed and measured using both spaceborne and ground-based instruments, especially during the last decade. Unique properties retrieved by the different instruments contribute to an unprecedented availability of the most complete set of complimentary aerosol measurements ever acquired. However, some of these measurements remain underutilized, largely due to the complexities involved in analyzing them synergistically. To characterize the inconsistencies and bridge the gap that exists between the sensors, we have established a Multi-sensor Aerosol Products Sampling System (MAPSS), which consistently samples and generates the spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of aerosol products from multiple spacebome sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Samples of satellite aerosol products are extracted over Aerosol Robotic Network (AERONET) locations as well as over other locations of interest such as those with available ground-based aerosol observations. In this way, MAPSS enables a direct cross-characterization and data integration between Level-2 aerosol observations from multiple sensors. In addition, the available well-characterized co-located ground-based data provides the basis for the integrated validation of these products. This paper explains the sampling methodology and concepts used in MAPSS, and demonstrates specific examples of using MAPSS for an integrated analysis of multiple aerosol products.

Application specific serial arithmetic arrays

NASA Technical Reports Server (NTRS)

Winters, K.; Mathews, D.; Thompson, T.

1990-01-01

High performance systolic arrays of serial-parallel multiplier elements may be rapidly constructed for specific applications by applying hardware description language techniques to a library of full-custom CMOS building blocks. Single clock pre-charged circuits have been implemented for these arrays at clock rates in excess of 100 Mhz using economical 2-micron (minimum feature size) CMOS processes, which may be quickly configured for a variety of applications. A number of application-specific arrays are presented, including a 2-D convolver for image processing, an integer polynomial solver, and a finite-field polynomial solver.

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

NASA Astrophysics Data System (ADS)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

NASA Technical Reports Server (NTRS)

Li, Zhenlong; Hu, Fei; Schnase, John L.; Duffy, Daniel Q.; Lee, Tsengdar; Bowen, Michael K.; Yang, Chaowei

2016-01-01

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

Advantages and Challenges in using Multi-Sensor Data for Studying Aerosols from Space

NASA Astrophysics Data System (ADS)

Leptoukh, Gregory

We are living now in the golden era of numerous sensors measuring aerosols from space, e.g., MODIS, MISR, MERIS, OMI, POLDER, etc. Data from multiple sensors provide a more complete coverage of physical phenomena than data from a single sensor. These sensors are rather different from each other, are sensitive to various parts of the atmosphere, use different aerosol models and treat surface differently when retrieving aerosols. However, they complement each other thus providing more information about spatial, vertical and temporal distribution of aerosols. In addition to differences in instrumentation, retrieval algorithms and calibration, there are quite substantial differences in processing algorithms from Level 0 up to Level 3 and 4. Some of these differences in processing steps, at times not well documented and not widely known by users, can lead to quite significant differences in final products. Without documenting all the steps leading to the final product, data users will not trust the data and/or may use data incorrectly. Data by themselves without quality assessment and provenance are not sufficient to make accurate scientific conclusions. In this paper we provide examples of striking differences between aerosol optical depth data from MODIS, MISR, and MERIS that can be attributed to differences in a certain threshold, aggregation methods, and the dataday definition. We talk about challenges in developing processing provenance. Also, we address issues of harmonization of data, quality and provenance that is needed to guide the multi-sensor data usage and avoid apples-to-oranges comparison and fusion.

A Comparison of Multisensor Precipitation Estimation Methods in Complex Terrain for Flash Flood Warning and Mitigation

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Chandrasekar, C. V.; Willie, D.; Reynolds, D.; Campbell, C.; Zhang, Y.; Sukovich, E.

2012-12-01

Investigating the uncertainties and improving the accuracy of quantitative precipitation estimation (QPE) is a critical mission of the National Oceanic and Atmospheric Administration (NOAA). QPE is extremely challenging in regions of complex terrain like the western U.S. because of the sparse coverage of ground-based radar, complex orographic precipitation processes, and the effects of beam blockages (e.g., Westrick et al. 1999). In addition, the rain gauge density in complex terrain is often inadequate to capture spatial variability in the precipitation patterns. The NOAA Hydrometeorology Testbed (HMT) conducts research on precipitation and weather conditions that can lead to flooding, and fosters transition of scientific advances and new tools into forecasting operations (see hmt.noaa.gov). The HMT program consists of a series of demonstration projects in different geographical regions to enhance understanding of region specific processes related to precipitation, including QPE. There are a number of QPE systems that are widely used across NOAA for precipitation estimation (e.g., Cifelli et al. 2011; Chandrasekar et al. 2012). Two of these systems have been installed at the NOAA Earth System Research Laboratory: Multisensor Precipitation Estimator (MPE) and National Mosaic and Multi-sensor QPE (NMQ) developed by NWS and NSSL, respectively. Both provide gridded QPE products that include radar-only, gauge-only and gauge-radar-merged, etc; however, these systems often provide large differences in QPE (in terms of amounts and spatial patterns) due to differences in Z-R selection, vertical profile of reflectivity correction, and gauge interpolation procedures. Determining the appropriate QPE product and quantification of QPE uncertainty is critical for operational applications, including water management decisions and flood warnings. For example, hourly QPE is used to correct radar based rain rates used by the Flash Flood Monitoring and Prediction (FFMP) package in

Non-invasive glucose monitoring in patients with Type 1 diabetes: a Multisensor system combining sensors for dielectric and optical characterisation of skin.

PubMed

Caduff, Andreas; Talary, Mark S; Mueller, Martin; Dewarrat, Francois; Klisic, Jelena; Donath, Marc; Heinemann, Lutz; Stahel, Werner A

2009-05-15

In vivo variations of blood glucose (BG) are affecting the biophysical characteristics (e.g. dielectric and optical) of skin and underlying tissue (SAUT) at various frequencies. However, the skin impedance spectra for instance can also be affected by other factors, perturbing the glucose related information, factors such as temperature, skin moisture and sweat, blood perfusion as well as body movements affecting the sensor-skin contact. In order to be able to correct for such perturbing factors, a Multisensor system was developed including sensors to measure the identified factors. To evaluate the quality of glucose monitoring, the Multisensor was applied in 10 patients with Type 1 diabetes. Glucose was administered orally to induce hyperglycaemic excursions at two different study visits. For analysis of the sensor signals, a global multiple linear regression model was derived. The respective coefficients of the variables were determined from the sensor signals of this first study visit (R(2)=0.74, MARD=18.0%--mean absolute relative difference). The identical set of modelling coefficients of the first study visit was re-applied to the test data of the second study visit to evaluate the predictive power of the model (R(2)=0.68, MARD=27.3%). It appears as if the Multisensor together with the global linear regression model applied, allows for tracking glucose changes non-invasively in patients with diabetes without requiring new model coefficients for each visit. Confirmation of these findings in a larger study group and under less experimentally controlled conditions is required for understanding whether a global parameterisation routine is feasible.

Optimum Sensors Integration for Multi-Sensor Multi-Target Environment for Ballistic Missile Defense Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Neena; Barhen, Jacob; Glover, Charles Wayne

2012-01-01

Multi-sensor networks may face resource limitations in a dynamically evolving multiple target tracking scenario. It is necessary to task the sensors efficiently so that the overall system performance is maximized within the system constraints. The central sensor resource manager may control the sensors to meet objective functions that are formulated to meet system goals such as minimization of track loss, maximization of probability of target detection, and minimization of track error. This paper discusses the variety of techniques that may be utilized to optimize sensor performance for either near term gain or future reward over a longer time horizon.

Development of a monolithic ferrite memory array

NASA Technical Reports Server (NTRS)

Heckler, C. H., Jr.; Bhiwandker, N. C.

1972-01-01

The results of the development and testing of ferrite monolithic memory arrays are presented. This development required the synthesis of ferrite materials having special magnetic and physical characteristics and the development of special processes; (1) for making flexible sheets (laminae) of the ferrite composition, (2) for embedding conductors in ferrite, and (3) bonding ferrite laminae together to form a monolithic structure. Major problems encountered in each of these areas and their solutions are discussed. Twenty-two full-size arrays were fabricated and fired during the development of these processes. The majority of these arrays were tested for their memory characteristics as well as for their physical characteristics and the results are presented. The arrays produced during this program meet the essential goals and demonstrate the feasibility of fabricating monolithic ferrite memory arrays by the processes developed.

The New Pelagic Operational Observatory of the Catalan Sea (OOCS) for the Multisensor Coordinated Measurement of Atmospheric and Oceanographic Conditions

PubMed Central

Bahamon, Nixon; Aguzzi, Jacopo; Bernardello, Raffaele; Ahumada-Sempoal, Miguel-Angel; Puigdefabregas, Joan; Cateura, Jordi; Muñoz, Eduardo; Velásquez, Zoila; Cruzado, Antonio

2011-01-01

The new pelagic Operational Observatory of the Catalan Sea (OOCS) for the coordinated multisensor measurement of atmospheric and oceanographic conditions has been recently installed (2009) in the Catalan Sea (41°39′N, 2°54′E; Western Mediterranean) and continuously operated (with minor maintenance gaps) until today. This multiparametric platform is moored at 192 m depth, 9.3 km off Blanes harbour (Girona, Spain). It is composed of a buoy holding atmospheric sensors and a set of oceanographic sensors measuring the water conditions over the upper 100 m depth. The station is located close to the head of the Blanes submarine canyon where an important multispecies pelagic and demersal fishery gives the station ecological and economic relevance. The OOCS provides important records on atmospheric and oceanographic conditions, the latter through the measurement of hydrological and biogeochemical parameters, at depths with a time resolution never attained before for this area of the Mediterranean. Twenty four moored sensors and probes operating in a coordinated fashion provide important data on Essential Ocean Variables (EOVs; UNESCO) such as temperature, salinity, pressure, dissolved oxygen, chlorophyll fluorescence, and turbidity. In comparison with other pelagic observatories presently operating in other world areas, OOCS also measures photosynthetic available radiation (PAR) from above the sea surface and at different depths in the upper 50 m. Data are recorded each 30 min and transmitted in real-time to a ground station via GPRS. This time series is published and automatically updated at the frequency of data collection on the official OOCS website (http://www.ceab.csic.es/~oceans). Under development are embedded automated routines for the in situ data treatment and assimilation into numerical models, in order to provide a reliable local marine processing forecast. In this work, our goal is to detail the OOCS multisensor architecture in relation to the

β-Decay Studies of r-Process Nuclei Using the Advanced Implantation Detector Array (AIDA)

NASA Astrophysics Data System (ADS)

Griffin, C. J.; Davinson, T.; Estrade, A.; Braga, D.; Burrows, I.; Coleman-Smith, P. J.; Grahn, T.; Grant, A.; Harkness-Brennan, L. J.; Kiss, G.; Kogimtzis, M.; Lazarus, I. H.; Letts, S. C.; Liu, Z.; Lorusso, G.; Matsui, K.; Nishimura, S.; Page, R. D.; Prydderch, M.; Phong, V. H.; Pucknell, V. F. E.; Rinta-Antila, S.; Roberts, O. J.; Seddon, D. A.; Simpson, J.; Thomas, S. L.; Woods, P. J.

Thought to produce around half of all isotopes heavier than iron, the r-process is a key mechanism for nucleosynthesis. However, a complete description of the r-process is still lacking and many unknowns remain. Experimental determination of β-decay half-lives and β-delayed neutron emission probabilities along the r-process path would help to facilitate a greater understanding of this process. The Advanced Implantation Detector Array (AIDA) represents the latest generation of silicon implantation detectors for β-decay studies with fast radioactive ion beams. Preliminary results from commissioning experiments demonstrate successful operation of AIDA and analysis of the data obtained during the first official AIDA experiments is now under-way.

High density pixel array and laser micro-milling method for fabricating array

NASA Technical Reports Server (NTRS)

McFall, James Earl (Inventor); Wiener-Avnear, Eliezer (Inventor)

2003-01-01

A pixel array device is fabricated by a laser micro-milling method under strict process control conditions. The device has an array of pixels bonded together with an adhesive filling the grooves between adjacent pixels. The array is fabricated by moving a substrate relative to a laser beam of predetermined intensity at a controlled, constant velocity along a predetermined path defining a set of grooves between adjacent pixels so that a predetermined laser flux per unit area is applied to the material, and repeating the movement for a plurality of passes of the laser beam until the grooves are ablated to a desired depth. The substrate is of an ultrasonic transducer material in one example for fabrication of a 2D ultrasonic phase array transducer. A substrate of phosphor material is used to fabricate an X-ray focal plane array detector.

Can single empirical algorithms accurately predict inland shallow water quality status from high resolution, multi-sensor, multi-temporal satellite data?

NASA Astrophysics Data System (ADS)

Theologou, I.; Patelaki, M.; Karantzalos, K.

2015-04-01

Assessing and monitoring water quality status through timely, cost effective and accurate manner is of fundamental importance for numerous environmental management and policy making purposes. Therefore, there is a current need for validated methodologies which can effectively exploit, in an unsupervised way, the enormous amount of earth observation imaging datasets from various high-resolution satellite multispectral sensors. To this end, many research efforts are based on building concrete relationships and empirical algorithms from concurrent satellite and in-situ data collection campaigns. We have experimented with Landsat 7 and Landsat 8 multi-temporal satellite data, coupled with hyperspectral data from a field spectroradiometer and in-situ ground truth data with several physico-chemical and other key monitoring indicators. All available datasets, covering a 4 years period, in our case study Lake Karla in Greece, were processed and fused under a quantitative evaluation framework. The performed comprehensive analysis posed certain questions regarding the applicability of single empirical models across multi-temporal, multi-sensor datasets towards the accurate prediction of key water quality indicators for shallow inland systems. Single linear regression models didn't establish concrete relations across multi-temporal, multi-sensor observations. Moreover, the shallower parts of the inland system followed, in accordance with the literature, different regression patterns. Landsat 7 and 8 resulted in quite promising results indicating that from the recreation of the lake and onward consistent per-sensor, per-depth prediction models can be successfully established. The highest rates were for chl-a (r2=89.80%), dissolved oxygen (r2=88.53%), conductivity (r2=88.18%), ammonium (r2=87.2%) and pH (r2=86.35%), while the total phosphorus (r2=70.55%) and nitrates (r2=55.50%) resulted in lower correlation rates.

From GaN to ZnGa(2)O(4) through a low-temperature process: nanotube and heterostructure arrays.

PubMed

Lu, Ming-Yen; Zhou, Xiang; Chiu, Cheng-Yao; Crawford, Samuel; Gradečak, Silvija

2014-01-22

We demonstrate a method to synthesize GaN-ZnGa2O4 core-shell nanowire and ZnGa2O4 nanotube arrays by a low-temperature hydrothermal process using GaN nanowires as templates. Transmission electron microscopy and X-ray photoelectron spectroscopy results show that a ZnGa2O4 shell forms on the surface of GaN nanowires and that the shell thickness is controlled by the time of the hydrothermal process and thus the concentration of Zn ions in the solution. Furthermore, ZnGa2O4 nanotube arrays were obtained by depleting the GaN core from GaN-ZnGa2O4 core-shell nanowire arrays during the reaction and subsequent etching with HCl. The GaN-ZnGa2O4 core-shell nanowires exhibit photoluminescence peaks centered at 2.60 and 2.90 eV attributed to the ZnGa2O4 shell, as well as peaks centered at 3.35 and 3.50 eV corresponding to the GaN core. We also demonstrate the synthesis of GaN-ZnGa2O4 heterojunction nanowires by a selective formation process as a simple route toward development of heterojunction nanodevices for optoelectronic applications.

Target-type probability combining algorithms for multisensor tracking

NASA Astrophysics Data System (ADS)

Wigren, Torbjorn

2001-08-01

Algorithms for the handing of target type information in an operational multi-sensor tracking system are presented. The paper discusses recursive target type estimation, computation of crosses from passive data (strobe track triangulation), as well as the computation of the quality of the crosses for deghosting purposes. The focus is on Bayesian algorithms that operate in the discrete target type probability space, and on the approximations introduced for computational complexity reduction. The centralized algorithms are able to fuse discrete data from a variety of sensors and information sources, including IFF equipment, ESM's, IRST's as well as flight envelopes estimated from track data. All algorithms are asynchronous and can be tuned to handle clutter, erroneous associations as well as missed and erroneous detections. A key to obtain this ability is the inclusion of data forgetting by a procedure for propagation of target type probability states between measurement time instances. Other important properties of the algorithms are their abilities to handle ambiguous data and scenarios. The above aspects are illustrated in a simulations study. The simulation setup includes 46 air targets of 6 different types that are tracked by 5 airborne sensor platforms using ESM's and IRST's as data sources.

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

PubMed

Hsu, Yu-Liang; Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

2017-07-15

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents' wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident's feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment.

Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter.

PubMed

Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei

2016-11-02

Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system's error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the

Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter

PubMed Central

Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei

2016-01-01

Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system’s error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the

Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

PubMed

Eide, Ingvar; Westad, Frank

2018-01-01

A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors), salinity (calculated from temperature and conductivity), biomass at three different depth intervals (5-50, 50-120, 120-250 m), and current speed measured in two directions (east and north) using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA). Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology

PubMed Central

Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

2017-01-01

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents’ wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident’s feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment. PMID:28714884

The Role of Water Vapor and Dissociative Recombination Processes in Solar Array Arc Initiation

NASA Technical Reports Server (NTRS)

Galofar, J.; Vayner, B.; Degroot, W.; Ferguson, D.

2002-01-01

Experimental plasma arc investigations involving the onset of arc initiation for a negatively biased solar array immersed in low-density plasma have been performed. Previous studies into the arc initiation process have shown that the most probable arcing sites tend to occur at the triple junction involving the conductor, dielectric and plasma. More recently our own experiments have led us to believe that water vapor is the main causal factor behind the arc initiation process. Assuming the main component of the expelled plasma cloud by weight is water, the fastest process available is dissociative recombination (H2O(+) + e(-) (goes to) H* + OH*). A model that agrees with the observed dependency of arc current pulse width on the square root of capacitance is presented. A 400 MHz digital storage scope and current probe was used to detect arcs at the triple junction of a solar array. Simultaneous measurements of the arc trigger pulse, the gate pulse, the arc current and the arc voltage were then obtained. Finally, a large number of measurements of individual arc spectra were obtained in very short time intervals, ranging from 10 to 30 microseconds, using a 1/4 a spectrometer coupled with a gated intensified CCD. The spectrometer was systematically tuned to obtain optical arc spectra over the entire wavelength range of 260 to 680 nanometers. All relevant atomic lines and molecular bands were then identified.

Breath alcohol, multisensor arrays, and electronic noses

NASA Astrophysics Data System (ADS)

Paulsson, Nils; Winquist, Fredrik

1997-01-01

The concept behind a volatile compound mapper, or electronic nose, is to use the combination of multiple gas sensors and pattern recognition techniques to detect and quantify substances in gas mixtures. There are several different kinds of sensors which have been developed during recent years of which the base techniques are conducting polymers, piezo electrical crystals and solid state devices. In this work we have used a combination of gas sensitive field effect devices and semiconducting metal oxides. The most useful pattern recognition routine was found to be ANNs, which is a mathematical approximation of the human neural network. The aim of this work is to evaluate the possibility of using electronic noses in field instruments to detect drugs, arson residues, explosives etc. As a test application we have chosen breath alcohol measurements. There are several reasons for this. Breath samples are a quite complex mixture contains between 200 and 300 substances at trace levels. The alcohol level is low but still possible to handle. There are needs for replacing large and heavy mobile instruments with smaller devices. Current instrumentation is rather sensitive to interfering substances. The work so far has dealt with sampling, how to introduce ethanol and other substances in the breath, correlation measurements between the electronic nose and headspace GC, and how to evaluate the sensor signals.

Mapping Palm Swamp Wetland Ecosystems in the Peruvian Amazon: a Multi-Sensor Remote Sensing Approach

NASA Astrophysics Data System (ADS)

Podest, E.; McDonald, K. C.; Schroeder, R.; Pinto, N.; Zimmerman, R.; Horna, V.

2012-12-01

Wetland ecosystems are prevalent in the Amazon basin, especially in northern Peru. Of specific interest are palm swamp wetlands because they are characterized by constant surface inundation and moderate seasonal water level variation. This combination of constantly saturated soils and warm temperatures year-round can lead to considerable methane release to the atmosphere. Because of the widespread occurrence and expected sensitivity of these ecosystems to climate change, it is critical to develop methods to quantify their spatial extent and inundation state in order to assess their carbon dynamics. Spatio-temporal information on palm swamps is difficult to gather because of their remoteness and difficult accessibility. Spaceborne microwave remote sensing is an effective tool for characterizing these ecosystems since it is sensitive to surface water and vegetation structure and allows monitoring large inaccessible areas on a temporal basis regardless of atmospheric conditions or solar illumination. We developed a remote sensing methodology using multi-sensor remote sensing data from the Advanced Land Observing Satellite (ALOS) Phased Array L-Band Synthetic Aperture Radar (PALSAR), Shuttle Radar Topography Mission (SRTM) DEM, and Landsat to derive maps at 100 meter resolution of palm swamp extent and inundation based on ground data collections; and combined active and passive microwave data from AMSR-E and QuikSCAT to derive inundation extent at 25 kilometer resolution on a weekly basis. We then compared information content and accuracy of the coarse resolution products relative to the high-resolution datasets. The synergistic combination of high and low resolution datasets allowed for characterization of palm swamps and assessment of their flooding status. This work has been undertaken partly within the framework of the JAXA ALOS Kyoto & Carbon Initiative. PALSAR data have been provided by JAXA. Portions of this work were carried out at the Jet Propulsion Laboratory

ASIC Readout Circuit Architecture for Large Geiger Photodiode Arrays

NASA Technical Reports Server (NTRS)

Vasile, Stefan; Lipson, Jerold

2012-01-01

The objective of this work was to develop a new class of readout integrated circuit (ROIC) arrays to be operated with Geiger avalanche photodiode (GPD) arrays, by integrating multiple functions at the pixel level (smart-pixel or active pixel technology) in 250-nm CMOS (complementary metal oxide semiconductor) processes. In order to pack a maximum of functions within a minimum pixel size, the ROIC array is a full, custom application-specific integrated circuit (ASIC) design using a mixed-signal CMOS process with compact primitive layout cells. The ROIC array was processed to allow assembly in bump-bonding technology with photon-counting infrared detector arrays into 3-D imaging cameras (LADAR). The ROIC architecture was designed to work with either common- anode Si GPD arrays or common-cathode InGaAs GPD arrays. The current ROIC pixel design is hardwired prior to processing one of the two GPD array configurations, and it has the provision to allow soft reconfiguration to either array (to be implemented into the next ROIC array generation). The ROIC pixel architecture implements the Geiger avalanche quenching, bias, reset, and time to digital conversion (TDC) functions in full-digital design, and uses time domain over-sampling (vernier) to allow high temporal resolution at low clock rates, increased data yield, and improved utilization of the laser beam.

Multi-sensor millimeter-wave system for hidden objects detection by non-collaborative screening

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Czarny, Romain; Diaz, Frédéric; Khy, Antoine; Lamarque, Thierry

2011-05-01

In this work, we present the development of a multi-sensor system for the detection of objects concealed under clothes using passive and active millimeter-wave (mmW) technologies. This study concerns both the optimization of a commercial passive mmW imager at 94 GHz using a phase mask and the development of an active mmW detector at 77 GHz based on synthetic aperture radar (SAR). A first wide-field inspection is done by the passive imager while the person is walking. If a suspicious area is detected, the active imager is switched-on and focused on this area in order to obtain more accurate data (shape of the object, nature of the material ...).

SAMuS: Service-Oriented Architecture for Multisensor Surveillance in Smart Homes

PubMed Central

Van de Walle, Rik

2014-01-01

The design of a service-oriented architecture for multisensor surveillance in smart homes is presented as an integrated solution enabling automatic deployment, dynamic selection, and composition of sensors. Sensors are implemented as Web-connected devices, with a uniform Web API. RESTdesc is used to describe the sensors and a novel solution is presented to automatically compose Web APIs that can be applied with existing Semantic Web reasoners. We evaluated the solution by building a smart Kinect sensor that is able to dynamically switch between IR and RGB and optimizing person detection by incorporating feedback from pressure sensors, as such demonstrating the collaboration among sensors to enhance detection of complex events. The performance results show that the platform scales for many Web APIs as composition time remains limited to a few hundred milliseconds in almost all cases. PMID:24778579

High density pixel array

NASA Technical Reports Server (NTRS)

McFall, James Earl (Inventor); Wiener-Avnear, Eliezer (Inventor)

2004-01-01

A pixel array device is fabricated by a laser micro-milling method under strict process control conditions. The device has an array of pixels bonded together with an adhesive filling the grooves between adjacent pixels. The array is fabricated by moving a substrate relative to a laser beam of predetermined intensity at a controlled, constant velocity along a predetermined path defining a set of grooves between adjacent pixels so that a predetermined laser flux per unit area is applied to the material, and repeating the movement for a plurality of passes of the laser beam until the grooves are ablated to a desired depth. The substrate is of an ultrasonic transducer material in one example for fabrication of a 2D ultrasonic phase array transducer. A substrate of phosphor material is used to fabricate an X-ray focal plane array detector.

Multi-Sensor Data Integration Using Deep Learning for Characterization of Defects in Steel Elements †

PubMed Central

2018-01-01

Nowadays, there is a strong demand for inspection systems integrating both high sensitivity under various testing conditions and advanced processing allowing automatic identification of the examined object state and detection of threats. This paper presents the possibility of utilization of a magnetic multi-sensor matrix transducer for characterization of defected areas in steel elements and a deep learning based algorithm for integration of data and final identification of the object state. The transducer allows sensing of a magnetic vector in a single location in different directions. Thus, it enables detecting and characterizing any material changes that affect magnetic properties regardless of their orientation in reference to the scanning direction. To assess the general application capability of the system, steel elements with rectangular-shaped artificial defects were used. First, a database was constructed considering numerical and measurements results. A finite element method was used to run a simulation process and provide transducer signal patterns for different defect arrangements. Next, the algorithm integrating responses of the transducer collected in a single position was applied, and a convolutional neural network was used for implementation of the material state evaluation model. Then, validation of the obtained model was carried out. In this paper, the procedure for updating the evaluated local state, referring to the neighboring area results, is presented. Finally, the results and future perspective are discussed. PMID:29351215

Correlation of lattice defects and thermal processing in the crystallization of titania nanotube arrays

NASA Astrophysics Data System (ADS)

Hosseinpour, Pegah M.; Yung, Daniel; Panaitescu, Eugen; Heiman, Don; Menon, Latika; Budil, David; Lewis, Laura H.

2014-12-01

Titania nanotubes have the potential to be employed in a wide range of energy-related applications such as solar energy-harvesting devices and hydrogen production. As the functionality of titania nanostructures is critically affected by their morphology and crystallinity, it is necessary to understand and control these factors in order to engineer useful materials for green applications. In this study, electrochemically-synthesized titania nanotube arrays were thermally processed in inert and reducing environments to isolate the role of post-synthesis processing conditions on the crystallization behavior, electronic structure and morphology development in titania nanotubes, correlated with the nanotube functionality. Structural and calorimetric studies revealed that as-synthesized amorphous nanotubes crystallize to form the anatase structure in a three-stage process that is facilitated by the creation of structural defects. It is concluded that processing in a reducing gas atmosphere versus in an inert environment provides a larger unit cell volume and a higher concentration of Ti3+ associated with oxygen vacancies, thereby reducing the activation energy of crystallization. Further, post-synthesis annealing in either reducing or inert atmospheres produces pronounced morphological changes, confirming that the nanotube arrays thermally transform into a porous morphology consisting of a fragmented tubular architecture surrounded by a network of connected nanoparticles. This study links explicit data concerning morphology, crystallization and defects, and shows that the annealing gas environment determines the details of the crystal structure, the electronic structure and the morphology of titania nanotubes. These factors, in turn, impact the charge transport and consequently the functionality of these nanotubes as photocatalysts.

Maskless wafer-level microfabrication of optical penetrating neural arrays out of soda-lime glass: Utah Optrode Array.

PubMed

Boutte, Ronald W; Blair, Steve

2016-12-01

Borrowing from the wafer-level fabrication techniques of the Utah Electrode Array, an optical array capable of delivering light for neural optogenetic studies is presented in this paper: the Utah Optrode Array. Utah Optrode Arrays are micromachined out of sheet soda-lime-silica glass using standard backend processes of the semiconductor and microelectronics packaging industries such as precision diamond grinding and wet etching. 9 × 9 arrays with 1100μ m × 100μ m optrodes and a 500μ m back-plane are repeatably reproduced on 2i n wafers 169 arrays at a time. This paper describes the steps and some of the common errors of optrode fabrication.

Advances in Mixed Signal Processing for Regional and Teleseismic Arrays

DTIC Science & Technology

2006-08-15

1: Mixture of signals from two earthquakes from south of Africa and the Philippines observed at USAEDS long-period seismic array in Korea. Correct...window where the detector will miss valid signals . 2 Approaches to detecting signals on arrays all focus on the basic model that expresses the observed...possible use in detecting infrasound signals . The approach is based on orthogonal- ity properties of the eigen vectors of the spectral matrix under a

Application of adaptive optics in complicated and integrated spatial multisensor system and its measurement analysis

NASA Astrophysics Data System (ADS)

Ding, Quanxin; Guo, Chunjie; Cai, Meng; Liu, Hua

2007-12-01

Adaptive Optics Expand System is a kind of new concept spatial equipment, which concerns system, cybernetics and informatics deeply, and is key way to improve advanced sensors ability. Traditional Zernike Phase Contrast Method is developed, and Accelerated High-level Phase Contrast Theory is established. Integration theory and mathematical simulation is achieved. Such Equipment, which is based on some crucial components, such as, core optical system, multi mode wavefront sensor and so on, is established for AOES advantageous configuration and global design. Studies on Complicated Spatial Multisensor System Integratation and measurement Analysis including error analysis are carried out.

Integrated residential photovoltaic array development

NASA Astrophysics Data System (ADS)

Shepard, N. F., Jr.

1981-12-01

An advanced, universally-mountable, integrated residential photovoltaic array concept was defined based upon an in-depth formulation and evaluation of three candidate approaches which were synthesized from existing or proposed residential array concepts. The impact of module circuitry and process sequence is considered and technology gaps and performance drivers associated with residential photovoltaic array concepts are identified. The actual learning experience gained from the comparison of the problem areas of the hexagonal shingle design with the rectangular module design led to what is considered an advanced array concept. Building the laboratory mockup provided actual experience and the opportunity to uncover additional technology gaps.

Integrated residential photovoltaic array development

NASA Technical Reports Server (NTRS)

Shepard, N. F., Jr.

1981-01-01

An advanced, universally-mountable, integrated residential photovoltaic array concept was defined based upon an in-depth formulation and evaluation of three candidate approaches which were synthesized from existing or proposed residential array concepts. The impact of module circuitry and process sequence is considered and technology gaps and performance drivers associated with residential photovoltaic array concepts are identified. The actual learning experience gained from the comparison of the problem areas of the hexagonal shingle design with the rectangular module design led to what is considered an advanced array concept. Building the laboratory mockup provided actual experience and the opportunity to uncover additional technology gaps.

Aided target recognition processing of MUDSS sonar data

NASA Astrophysics Data System (ADS)

Lau, Brian; Chao, Tien-Hsin

1998-09-01

The Mobile Underwater Debris Survey System (MUDSS) is a collaborative effort by the Navy and the Jet Propulsion Lab to demonstrate multi-sensor, real-time, survey of underwater sites for ordnance and explosive waste (OEW). We describe the sonar processing algorithm, a novel target recognition algorithm incorporating wavelets, morphological image processing, expansion by Hermite polynomials, and neural networks. This algorithm has found all planted targets in MUDSS tests and has achieved spectacular success upon another Coastal Systems Station (CSS) sonar image database.

Solar array flight dynamic experiment

NASA Technical Reports Server (NTRS)

Schock, R. W.

1986-01-01

The purpose of the Solar Array Flight Dynamic Experiment (SAFDE) is to demonstrate the feasibility of on-orbit measurement and ground processing of large space structures dynamic characteristics. Test definition or verification provides the dynamic characteristic accuracy required for control systems use. An illumination/measurement system was developed to fly on space shuttle flight STS-31D. The system was designed to dynamically evaluate a large solar array called the Solar Array Flight Experiment (SAFE) that had been scheduled for this flight. The SAFDE system consisted of a set of laser diode illuminators, retroreflective targets, an intelligent star tracker receiver and the associated equipment to power, condition, and record the results. In six tests on STS-41D, data was successfully acquired from 18 retroreflector targets and ground processed, post flight, to define the solar array's dynamic characteristic. The flight experiment proved the viability of on-orbit test definition of large space structures dynamic characteristics. Future large space structures controllability should be greatly enhanced by this capability.

Solar array flight dynamic experiment

NASA Technical Reports Server (NTRS)

Schock, Richard W.

1986-01-01

The purpose of the Solar Array Flight Dynamic Experiment (SAFDE) is to demonstrate the feasibility of on-orbit measurement and ground processing of large space structures dynamic characteristics. Test definition or verification provides the dynamic characteristic accuracy required for control systems use. An illumination/measurement system was developed to fly on Space Shuttle flight STS-31D. The system was designed to dynamically evaluate a large solar array called the Solar Array Flight Experiment (SAFE) that had been scheduled for this flight. The SAFDE system consisted of a set of laser diode illuminators, retroreflective targets, an intelligent star tracker receiver and the associated equipment to power, condition, and record the results. In six tests on STS-41D, data was successfully acquired from 18 retroreflector targets and ground processed, post flight, to define the solar array's dynamic characteristic. The flight experiment proved the viability of on-orbit test definition of large space structures dynamic characteristics. Future large space structures controllability should be greatly enhanced by this capability.

Solar array flight dynamic experiment

NASA Technical Reports Server (NTRS)

Schock, Richard W.

1987-01-01

The purpose of the Solar Array Flight Dynamic Experiment (SAFDE) is to demonstrate the feasibility of on-orbit measurement and ground processing of large space structures' dynamic characteristics. Test definition or verification provides the dynamic characteristic accuracy required for control systems use. An illumination/measurement system was developed to fly on space shuttle flight STS-41D. The system was designed to dynamically evaluate a large solar array called the Solar Array Flight Experiment (SAFE) that had been scheduled for this flight. The SAFDE system consisted of a set of laser diode illuminators, retroreflective targets, an intelligent star tracker receiver and the associated equipment to power, condition, and record the results. In six tests on STS-41D, data was successfully acquired from 18 retroreflector targets and ground processed, post flight, to define the solar array's dynamic characteristic. The flight experiment proved the viability of on-orbit test definition of large space structures dynamic characteristics. Future large space structures controllability should be greatly enhanced by this capability.

Evaluation of the Telecommunications Protocol Processing Subsystem Using Reconfigurable Interoperable Gate Array

NASA Technical Reports Server (NTRS)

Pang, Jackson; Liddicoat, Albert; Ralston, Jesse; Pingree, Paula

2006-01-01

The current implementation of the Telecommunications Protocol Processing Subsystem Using Reconfigurable Interoperable Gate Arrays (TRIGA) is equipped with CFDP protocol and CCSDS Telemetry and Telecommand framing schemes to replace the CPU intensive software counterpart implementation for reliable deep space communication. We present the hardware/software co-design methodology used to accomplish high data rate throughput. The hardware CFDP protocol stack implementation is then compared against the two recent flight implementations. The results from our experiments show that TRIGA offers more than 3 orders of magnitude throughput improvement with less than one-tenth of the power consumption.

Principles and practical implementation for high resolution multi-sensor QPE

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Lim, S.; Cifelli, R.

2011-12-01

The multi-sensor Quantitative Precipitation Estimation (MPE) is a principle and a practical concept and is becoming a well-known term in the scientific circles of hydrology and atmospheric science. The main challenge in QPE is that precipitation is a highly variable quantity with extensive spatial and temporal variability at multiple scales. There are MPE products produced from satellites, radars, models and ground sensors. There are MPE products at global scale (Heinemann et al. 2002), continental scale (Seo et al. 2010; Zhang et al. 2011) and regional scale (Kitzmiller et al. 2011). Lots of the MPE products are used to alleviate the problems of one type of sensor by another. Some multi-sensor products are used to move across scales. This paper looks at a comprehensive view of the "concept of multi sensor precipitation estimate", from different perspectives. This paper delineates the MPE problem into three categories namely, a) Scale based MPE, b) MPE for accuracy enhancement and coverage and c) Integrative across scales. For example, by introducing dual polarization radar data to the MPE system, QPE can be improved significantly. In last decade, dual polarization radars are becoming an important tool for QPE in operational networks. Dual polarization radars offer an advantage to interpret more accurate physical models by providing information of the size, shape, phase and orientation of hydrometers (Bringi and Chandrasekar 2001). In addition, these systems have the ability to provide measurements that are immune to absolute radar calibration and partial beam blockage as well as help in data quality enhancement. By integrating these characteristics of dual polarization radar, QPE performance can be improved in comparison of single polarization radar based QPE (Cifelli and Chandrasekar 2010). Dual-polarization techniques have been applied to S and C band radar systems for several decades and higher frequency system such as X band are now widely available to the

Characterizing land processes in the biosphere

NASA Technical Reports Server (NTRS)

Erickson, J. D.; Tuyahov, A. J.

1984-01-01

NASA long-term planning for the satellite remote sensing of land areas is discussed from the perspective of a holistic interdisciplinary approach to the study of the biosphere. The earth is characterized as a biogeochemical system; the impact of human activity on this system is considered; and the primary scientific goals for their study are defined. Remote-sensing programs are seen as essential in gaining an improved understanding of energy budgets, the hydrological cycle, other biogeological cycles, and the coupling between these cycles, with the construction of a global data base and eventually the development of predictive simulation models which can be used to assess the impact of planned human activities. Current sensor development at NASA includes a multilinear array for the visible and IR and the L-band Shuttle Imaging Radar B, both to be flown on Shuttle missions in the near future; for the 1990s, a large essentially permanent man-tended interdisciplinary multisensor platform connected to an advanced data network is being planned.

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

PubMed Central

Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

2017-01-01

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

Optimized micromirror arrays for adaptive optics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michalicek, M. Adrian

This paper describes the design, layout, fabrication, and surface characterization of highly optimized surface micromachined micromirror devices. Design considerations and fabrication capabilities are presented. These devices are fabricated in the state-of-the-art, four-level, planarized, ultra-low-stress polysilicon process available at Sandia National Laboratories known as the Sandia Ultra-planar Multi-level MEMS Technology (SUMMiT). This enabling process permits the development of micromirror devices with near-ideal characteristics that have previously been unrealizable in standard three-layer polysilicon processes. The reduced 1 {mu}m minimum feature sizes and 0.1 {mu}m mask resolution make it possible to produce dense wiring patterns and irregularly shaped flexures. Likewise, mirror surfaces canmore » be uniquely distributed and segmented in advanced patterns and often irregular shapes in order to minimize wavefront error across the pupil. The ultra-low-stress polysilicon and planarized upper layer allow designers to make larger and more complex micromirrors of varying shape and surface area within an array while maintaining uniform performance of optical surfaces. Powerful layout functions of the AutoCAD editor simplify the design of advanced micromirror arrays and make it possible to optimize devices according to the capabilities of the fabrication process. Micromirrors fabricated in this process have demonstrated a surface variance across the array from only 2{endash}3 nm to a worst case of roughly 25 nm while boasting active surface areas of 98{percent} or better. Combining the process planarization with a {open_quotes}planarized-by-design{close_quotes} approach will produce micromirror array surfaces that are limited in flatness only by the surface deposition roughness of the structural material. Ultimately, the combination of advanced process and layout capabilities have permitted the fabrication of highly optimized micromirror arrays for adaptive

Fill-factor improvement of Si CMOS single-photon avalanche diode detector arrays by integration of diffractive microlens arrays.

PubMed

Intermite, Giuseppe; McCarthy, Aongus; Warburton, Ryan E; Ren, Ximing; Villa, Federica; Lussana, Rudi; Waddie, Andrew J; Taghizadeh, Mohammad R; Tosi, Alberto; Zappa, Franco; Buller, Gerald S

2015-12-28

Single-photon avalanche diode (SPAD) detector arrays generally suffer from having a low fill-factor, in which the photo-sensitive area of each pixel is small compared to the overall area of the pixel. This paper describes the integration of different configurations of high efficiency diffractive optical microlens arrays onto a 32 × 32 SPAD array, fabricated using a 0.35 µm CMOS technology process. The characterization of SPAD arrays with integrated microlens arrays is reported over the spectral range of 500-900 nm, and a range of f-numbers from f/2 to f/22. We report an average concentration factor of 15 measured for the entire SPAD array with integrated microlens array. The integrated SPAD and microlens array demonstrated a very high uniformity in overall efficiency.

Silicon ball grid array chip carrier

DOEpatents

Palmer, David W.; Gassman, Richard A.; Chu, Dahwey

2000-01-01

A ball-grid-array integrated circuit (IC) chip carrier formed from a silicon substrate is disclosed. The silicon ball-grid-array chip carrier is of particular use with ICs having peripheral bond pads which can be reconfigured to a ball-grid-array. The use of a semiconductor substrate such as silicon for forming the ball-grid-array chip carrier allows the chip carrier to be fabricated on an IC process line with, at least in part, standard IC processes. Additionally, the silicon chip carrier can include components such as transistors, resistors, capacitors, inductors and sensors to form a "smart" chip carrier which can provide added functionality and testability to one or more ICs mounted on the chip carrier. Types of functionality that can be provided on the "smart" chip carrier include boundary-scan cells, built-in test structures, signal conditioning circuitry, power conditioning circuitry, and a reconfiguration capability. The "smart" chip carrier can also be used to form specialized or application-specific ICs (ASICs) from conventional ICs. Types of sensors that can be included on the silicon ball-grid-array chip carrier include temperature sensors, pressure sensors, stress sensors, inertia or acceleration sensors, and/or chemical sensors. These sensors can be fabricated by IC processes and can include microelectromechanical (MEM) devices.

Irma 5.2 multi-sensor signature prediction model

NASA Astrophysics Data System (ADS)

Savage, James; Coker, Charles; Thai, Bea; Aboutalib, Omar; Chow, Anthony; Yamaoka, Neil; Kim, Charles

2007-04-01

The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN) to facilitate the research and development of multi-sensor systems. There are over 130 users within the Department of Defense, NASA, Department of Transportation, academia, and industry. Irma began as a high-resolution, physics-based Infrared (IR) target and background signature model for tactical weapon applications and has grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame imagery (1992), and passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model (1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was released after an extensive verification and validation of an upgraded and reengineered active channel. Since 2005, the reengineering effort has focused on the Irma passive channel. Field measurements for the validation effort include the unpolarized data collection. Irma 5.2 is scheduled for release in the summer of 2007. This paper will report the validation test results of the Irma passive models and discuss the new features in Irma 5.2.

In situ synthesis of protein arrays.

PubMed

He, Mingyue; Stoevesandt, Oda; Taussig, Michael J

2008-02-01

In situ or on-chip protein array methods use cell free expression systems to produce proteins directly onto an immobilising surface from co-distributed or pre-arrayed DNA or RNA, enabling protein arrays to be created on demand. These methods address three issues in protein array technology: (i) efficient protein expression and availability, (ii) functional protein immobilisation and purification in a single step and (iii) protein on-chip stability over time. By simultaneously expressing and immobilising many proteins in parallel on the chip surface, the laborious and often costly processes of DNA cloning, expression and separate protein purification are avoided. Recently employed methods reviewed are PISA (protein in situ array) and NAPPA (nucleic acid programmable protein array) from DNA and puromycin-mediated immobilisation from mRNA.

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

NASA Astrophysics Data System (ADS)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was

Multisensor Retrieval of Atmospheric Properties.

NASA Astrophysics Data System (ADS)

Boba Stankov, B.

1998-09-01

A new method, Multisensor Retrieval of Atmospheric Properties (MRAP), is presented for deriving vertical profiles of atmospheric parameters throughout the troposphere. MRAP integrates measurements from multiple, diverse, remote sensing, and in situ instruments, the combination of which provides better capabilities than any instrument alone. Since remote sensors can deliver measurements automatically and continuously with high time resolution, MRAP provides better coverage than traditional rawinsondes. MRAP's design is flexible, being capable of incorporating measurements from different instruments in order to take advantage of new or developing advanced sensor technology. Furthermore, new or alternative atmospheric parameters for a variety of applications may be easily added as products of MRAP.A combination of passive radiometric, active radar, and in situ observations provide the best temperature and humidity profile measurements. Therefore, MRAP starts with a traditional, radiometer-based, physical retrieval algorithm provided by the International TOVS (TIROS-N Operational Vertical Sounder) Processing Package (ITPP) that constrains the retrieved profiles to agree with brightness temperature measurements. The first-guess profiles required by the ITPP's iterative retrieval algorithm are obtained by using a statistical inversion technique and ground-based remote sensing measurements. Because the individual ground-based remote sensing measurements are usually of sufficiently high quality, the first-guess profiles by themselves provide a satisfactory solution to establish the atmospheric water vapor and temperature state, and the TOVS data are included to provide profiles with better accuracy at higher levels, MRAP provides a physically consistent mechanism for combining the ground- and space-based humidity and temperature profiles.Data that have been used successfully to retrieve humidity and temperature profiles with MRAP are the following: temperature profiles in

Automatic Defect Detection for TFT-LCD Array Process Using Quasiconformal Kernel Support Vector Data Description

PubMed Central

Liu, Yi-Hung; Chen, Yan-Jen

2011-01-01

Defect detection has been considered an efficient way to increase the yield rate of panels in thin film transistor liquid crystal display (TFT-LCD) manufacturing. In this study we focus on the array process since it is the first and key process in TFT-LCD manufacturing. Various defects occur in the array process, and some of them could cause great damage to the LCD panels. Thus, how to design a method that can robustly detect defects from the images captured from the surface of LCD panels has become crucial. Previously, support vector data description (SVDD) has been successfully applied to LCD defect detection. However, its generalization performance is limited. In this paper, we propose a novel one-class machine learning method, called quasiconformal kernel SVDD (QK-SVDD) to address this issue. The QK-SVDD can significantly improve generalization performance of the traditional SVDD by introducing the quasiconformal transformation into a predefined kernel. Experimental results, carried out on real LCD images provided by an LCD manufacturer in Taiwan, indicate that the proposed QK-SVDD not only obtains a high defect detection rate of 96%, but also greatly improves generalization performance of SVDD. The improvement has shown to be over 30%. In addition, results also show that the QK-SVDD defect detector is able to accomplish the task of defect detection on an LCD image within 60 ms. PMID:22016625

Automatic defect detection for TFT-LCD array process using quasiconformal kernel support vector data description.

PubMed

Liu, Yi-Hung; Chen, Yan-Jen

2011-01-01

Defect detection has been considered an efficient way to increase the yield rate of panels in thin film transistor liquid crystal display (TFT-LCD) manufacturing. In this study we focus on the array process since it is the first and key process in TFT-LCD manufacturing. Various defects occur in the array process, and some of them could cause great damage to the LCD panels. Thus, how to design a method that can robustly detect defects from the images captured from the surface of LCD panels has become crucial. Previously, support vector data description (SVDD) has been successfully applied to LCD defect detection. However, its generalization performance is limited. In this paper, we propose a novel one-class machine learning method, called quasiconformal kernel SVDD (QK-SVDD) to address this issue. The QK-SVDD can significantly improve generalization performance of the traditional SVDD by introducing the quasiconformal transformation into a predefined kernel. Experimental results, carried out on real LCD images provided by an LCD manufacturer in Taiwan, indicate that the proposed QK-SVDD not only obtains a high defect detection rate of 96%, but also greatly improves generalization performance of SVDD. The improvement has shown to be over 30%. In addition, results also show that the QK-SVDD defect detector is able to accomplish the task of defect detection on an LCD image within 60 ms.

Multi-Sensors Observations of Pre-Earthquake Signals. What We Learned from the Great Tohoku Earthquake?

NASA Technical Reports Server (NTRS)

Ouzonounov, D.; Pulinets, S.; Papadopoulos, G.; Kunitsyn, V.; Nesterov, I.; Hattori, K.; Kafatos, M.; Taylor, P.

2012-01-01

The lessons learned from the Great Tohoku EQ (Japan, 2011) will affect our future observations and an analysis is the main focus of this presentation. Multi-sensors observations and multidisciplinary research is presented in our study of the phenomena preceding major earthquakes Our approach is based on a systematic analysis of several physical and environmental parameters, which been reported by others in connections with earthquake processes: thermal infrared radiation; temperature; concentration of electrons in the ionosphere; radon/ion activities; and atmospheric temperature/humidity [Ouzounov et al, 2011]. We used the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model, one of several possible paradigms [Pulinets and Ouzounov, 2011] to interpret our observations. We retrospectively analyzed the temporal and spatial variations of three different physical parameters characterizing the state of the atmosphere, ionosphere the ground surface several days before the March 11, 2011 M9 Tohoku earthquake Namely: (i) Outgoing Long wave Radiation (OLR) measured at the top of the atmosphere; (ii) Anomalous variations of ionospheric parameters revealed by multi-sensors observations; and (iii) The change in the foreshock sequence (rate, space and time); Our results show that on March 8th, 2011 a rapid increase of emitted infrared radiation was observed and an anomaly developed near the epicenter with largest value occurring on March 11 at 07.30 LT. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. Starting from this day in the lower ionosphere there was also observed an abnormal TEC variation over the epicenter. From March 3 to 11 a large increase in electron concentration was recorded at all four Japanese ground-based ionosondes, which returned to normal after the main earthquake. We use the Japanese GPS network stations and method of Radio Tomography to study the spatiotemporal structure of ionospheric

Integrated multi-sensor fusion for mapping and localization in outdoor environments for mobile robots

NASA Astrophysics Data System (ADS)

Emter, Thomas; Petereit, Janko

2014-05-01

An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

Development of a common biosensor format for an enzyme based biosensor array to monitor fruit quality.

PubMed

Jawaheer, Shobha; White, S F; Rughooputh, S D D V; Cullen, David C

2003-10-15

Individual enzyme-based biosensors involving three-electrode systems were developed for the detection of analytes comprising markers of the stage of maturity and quality in selected fruits of economic importance to tropical countries. Importantly, a common fabrication format has been developed to simplify manufacture and allow future integration of the individual sensors into a single multi-sensor array. Specifically, sensors for beta-D-glucose, total D-glucose, sucrose and ascorbic acid have been developed. Pectin, a natural polysaccharide present in plant cells, was used as a novel matrix to enhance enzyme entrapment and stabilisation in the sensors. Except for ascorbic acid, all the sensors function via the detection of enzymatically generated H2O2 at rhodinised carbon electrodes. Since ascorbic acid is electrochemically active at the working potential chosen (+350 mV vs. Ag/AgCl), it was measured directly. Enzyme sensors demonstrated expected response with respect to their substrates, typically 0-0.8 microA/20 mm2 electrode area response over analyte ranges of 0-7 mM. Interferences related to electrochemically active compounds present in fruits under study were significantly reduced by inclusion of a suitable cellulose acetate (CA) membrane or by enzymatic inactivation with ascorbate oxidase. Initial development was carried out into production of biosensor arrays. CA membranes were used to improve the linear range of the sensors, producing up to a fivefold improvement in the detection range compared to sensors without an additional diffusion barrier.

Spiked Models of Large Dimensional Random Matrices Applied to Wireless Communications and Array Signal Processing

DTIC Science & Technology

2013-12-14

population covariance matrix with application to array signal processing; and 5) a sample covariance matrix for which a CLT is studied on linear...Applications , (01 2012): 1150004. doi: Walid Hachem, Malika Kharouf, Jamal Najim, Jack W. Silverstein. A CLT FOR INFORMATION- THEORETIC STATISTICS...for Multi-source Power Estimation, (04 2010) Malika Kharouf, Jamal Najim, Jack W. Silverstein, Walid Hachem. A CLT FOR INFORMATION- THEORETIC

Flat-plate solar array progress and plans

NASA Technical Reports Server (NTRS)

Callaghan, W. T.

1984-01-01

The results of research into the technology of flat-plate solar arrays undertaken in the Flat-Plate Solar Array Project under the sponsorship of the U.S. Department of Energy are surveyed. Topics examined include Si refinement, ribbon-sheet substrate formation, module process sequences, environmental isolation, module engineering and testing, and photovoltaic-array economics.

Solution-Processed Wide-Bandgap Organic Semiconductor Nanostructures Arrays for Nonvolatile Organic Field-Effect Transistor Memory.

PubMed

Li, Wen; Guo, Fengning; Ling, Haifeng; Liu, Hui; Yi, Mingdong; Zhang, Peng; Wang, Wenjun; Xie, Linghai; Huang, Wei

2018-01-01

In this paper, the development of organic field-effect transistor (OFET) memory device based on isolated and ordered nanostructures (NSs) arrays of wide-bandgap (WBG) small-molecule organic semiconductor material [2-(9-(4-(octyloxy)phenyl)-9H-fluoren-2-yl)thiophene]3 (WG 3 ) is reported. The WG 3 NSs are prepared from phase separation by spin-coating blend solutions of WG 3 /trimethylolpropane (TMP), and then introduced as charge storage elements for nonvolatile OFET memory devices. Compared to the OFET memory device with smooth WG 3 film, the device based on WG 3 NSs arrays exhibits significant improvements in memory performance including larger memory window (≈45 V), faster switching speed (≈1 s), stable retention capability (>10 4 s), and reliable switching properties. A quantitative study of the WG 3 NSs morphology reveals that enhanced memory performance is attributed to the improved charge trapping/charge-exciton annihilation efficiency induced by increased contact area between the WG 3 NSs and pentacene layer. This versatile solution-processing approach to preparing WG 3 NSs arrays as charge trapping sites allows for fabrication of high-performance nonvolatile OFET memory devices, which could be applicable to a wide range of WBG organic semiconductor materials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SenseCube—a novel inexpensive wireless multisensor for physics lab experimentations

NASA Astrophysics Data System (ADS)

Mehta, Vedant; Lane, Charles D.

2018-07-01

SenseCube is a multisensor capable of measuring many different real-time events and changes in environment. Most conventional sensors used in introductory-physics labs use their own software and have wires that must be attached to a computer or an alternate device to analyze the data. This makes the standard sensors time consuming, tedious, and space-constricted. SenseCube was developed to overcome these limitations. This research was focused on developing a device that is all-encompassing, cost-effective, wireless, and compact, yet can perform the same tasks as the multiple standard sensors normally used in physics labs. It measures more than twenty distinct types of real-time events and transfers the data via Bluetooth. Both Windows and Mac software were developed so that the data from this device can be retrieved and/or saved on either platform. This paper describes the sensor itself, its development, its capabilities, and its cost comparison with standard sensors.

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Zubko, V.; Gopalan, A.

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

Multisensor-based human detection and tracking for mobile service robots.

PubMed

Bellotto, Nicola; Hu, Huosheng

2009-02-01

One of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In this paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based leg detection using the onboard laser range finder (LRF). The approach is based on the recognition of typical leg patterns extracted from laser scans, which are shown to also be very discriminative in cluttered environments. These patterns can be used to localize both static and walking persons, even when the robot moves. Furthermore, faces are detected using the robot's camera, and the information is fused to the legs' position using a sequential implementation of unscented Kalman filter. The proposed solution is feasible for service robots with a similar device configuration and has been successfully implemented on two different mobile platforms. Several experiments illustrate the effectiveness of our approach, showing that robust human tracking can be performed within complex indoor environments.

Adaptive Multi-sensor Data Fusion Model for In-situ Exploration of Mars

NASA Astrophysics Data System (ADS)

Schneiderman, T.; Sobron, P.

2014-12-01

Laser Raman spectroscopy (LRS) and laser-induced breakdown spectroscopy (LIBS) can be used synergistically to characterize the geochemistry and mineralogy of potential microbial habitats and biosignatures. The value of LRS and LIBS has been recognized by the planetary science community: (i) NASA's Mars2020 mission features a combined LRS-LIBS instrument, SuperCam, and an LRS instrument, SHERLOC; (ii) an LRS instrument, RLS, will fly on ESA's 2018 ExoMars mission. The advantages of combining LRS and LIBS are evident: (1) LRS/LIBS can share hardware components; (2) LIBS reveals the relative concentration of major (and often trace) elements present in a sample; and (3) LRS yields information on the individual mineral species and their chemical/structural nature. Combining data from LRS and LIBS enables definitive mineral phase identification with precise chemical characterization of major, minor, and trace mineral species. New approaches to data processing are needed to analyze large amounts of LRS+LIBS data efficiently and maximize the scientific return of integrated measurements. Multi-sensor data fusion (MSDF) is a method that allows for robust sample identification through automated acquisition, processing, and combination of data. It optimizes information usage, yielding a more robust characterization of a target than could be acquired through single sensor use. We have developed a prototype fuzzy logic adaptive MSDF model aimed towards the unsupervised characterization of Martian habitats and their biosignatures using LRS and LIBS datasets. Our model also incorporates fusion of microimaging (MI) data - critical for placing analyses in geological and spatial context. Here, we discuss the performance of our novel MSDF model and demonstrate that automated quantification of the salt abundance in sulfate/clay/phyllosilicate mixtures is possible through data fusion of collocated LRS, LIBS, and MI data.

Optimization of processing parameters on the controlled growth of ZnO nanorod arrays for the performance improvement of solid-state dye-sensitized solar cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Yi-Mu, E-mail: ymlee@nuu.edu.t; Yang, Hsi-Wen

2011-03-15

High-transparency and high quality ZnO nanorod arrays were grown on the ITO substrates by a two-step chemical bath deposition (CBD) method. The effects of processing parameters including reaction temperature (25-95 {sup o}C) and solution concentration (0.01-0.1 M) on the crystal growth, alignment, optical and electrical properties were systematically investigated. It has been found that these process parameters are critical for the growth, orientation and aspect ratio of the nanorod arrays, showing different structural and optical properties. Experimental results reveal that the hexagonal ZnO nanorod arrays prepared under reaction temperature of 95 {sup o}C and solution concentration of 0.03 M possessmore » highest aspect ratio of {approx}21, and show the well-aligned orientation and optimum optical properties. Moreover the ZnO nanorod arrays based heterojunction electrodes and the solid-state dye-sensitized solar cells (SS-DSSCs) were fabricated with an improved optoelectrical performance. -- Graphical abstract: The ZnO nanorod arrays demonstrate well-alignment, high aspect ratio (L/D{approx}21) and excellent optical transmittance by low-temperature chemical bath deposition (CBD). Display Omitted Research highlights: > Investigate the processing parameters of CBD on the growth of ZnO nanorod arrays. > Optimization of CBD process parameters: 0.03 M solution concentration and reaction temperature of 95 {sup o}C. > The prepared ZnO samples possess well-alignment and high aspect ratio (L/D{approx}21). > An n-ZnO/p-NiO heterojunction: great rectifying behavior and low leakage current. > SS-DSSC has J{sub SC} of 0.31 mA/cm{sup 2} and V{sub OC} of 590 mV, and an improved {eta} of 0.059%.« less

Application of Seismic Array Processing to Tsunami Early Warning

NASA Astrophysics Data System (ADS)

An, C.; Meng, L.

2015-12-01

Tsunami wave predictions of the current tsunami warning systems rely on accurate earthquake source inversions of wave height data. They are of limited effectiveness for the near-field areas since the tsunami waves arrive before data are collected. Recent seismic and tsunami disasters have revealed the need for early warning to protect near-source coastal populations. In this work we developed the basis for a tsunami warning system based on rapid earthquake source characterisation through regional seismic array back-projections. We explored rapid earthquake source imaging using onshore dense seismic arrays located at regional distances on the order of 1000 km, which provides faster source images than conventional teleseismic back-projections. We implement this method in a simulated real-time environment, and analysed the 2011 Tohoku earthquake rupture with two clusters of Hi-net stations in Kyushu and Northern Hokkaido, and the 2014 Iquique event with the Earthscope USArray Transportable Array. The results yield reasonable estimates of rupture area, which is approximated by an ellipse and leads to the construction of simple slip models based on empirical scaling of the rupture area, seismic moment and average slip. The slip model is then used as the input of the tsunami simulation package COMCOT to predict the tsunami waves. In the example of the Tohoku event, the earthquake source model can be acquired within 6 minutes from the start of rupture and the simulation of tsunami waves takes less than 2 min, which could facilitate a timely tsunami warning. The predicted arrival time and wave amplitude reasonably fit observations. Based on this method, we propose to develop an automatic warning mechanism that provides rapid near-field warning for areas of high tsunami risk. The initial focus will be Japan, Pacific Northwest and Alaska, where dense seismic networks with the capability of real-time data telemetry and open data accessibility, such as the Japanese HiNet (>800

Cas4-Dependent Prespacer Processing Ensures High-Fidelity Programming of CRISPR Arrays.

PubMed

Lee, Hayun; Zhou, Yi; Taylor, David W; Sashital, Dipali G

2018-04-05

CRISPR-Cas immune systems integrate short segments of foreign DNA as spacers into the host CRISPR locus to provide molecular memory of infection. Cas4 proteins are widespread in CRISPR-Cas systems and are thought to participate in spacer acquisition, although their exact function remains unknown. Here we show that Bacillus halodurans type I-C Cas4 is required for efficient prespacer processing prior to Cas1-Cas2-mediated integration. Cas4 interacts tightly with the Cas1 integrase, forming a heterohexameric complex containing two Cas1 dimers and two Cas4 subunits. In the presence of Cas1 and Cas2, Cas4 processes double-stranded substrates with long 3' overhangs through site-specific endonucleolytic cleavage. Cas4 recognizes PAM sequences within the prespacer and prevents integration of unprocessed prespacers, ensuring that only functional spacers will be integrated into the CRISPR array. Our results reveal the critical role of Cas4 in maintaining fidelity during CRISPR adaptation, providing a structural and mechanistic model for prespacer processing and integration. Copyright © 2018 Elsevier Inc. All rights reserved.

Advanced Microscopic Integrated Thermocouple Arrays

NASA Technical Reports Server (NTRS)

Pettigrew, Penny J.

1999-01-01

The purpose of this research is to develop and refine a technique for making microscopic thermocouple arrays for use in measuring the temperature gradient across a solid-liquid interface during the solidification process. Current thermocouple technology does not allow for real-time measurements across the interface due to the prohibitive size of available thermocouples. Microscopic thermocouple arrays will offer a much greater accuracy and resolution of temperature measurements across the solid-liquid interface which will lead to a better characterization of the solidification process and interface reaction which affect the properties of the resulting material.

Automated Array Assembly, Phase 2

NASA Technical Reports Server (NTRS)

Carbajal, B. G.

1979-01-01

The Automated Array Assembly Task, Phase 2 of the Low Cost Silicon Solar Array Project is a process development task. The contract provides for the fabrication of modules from large area tandem junction cells (TJC). During this quarter, effort was focused on the design of a large area, approximately 36 sq cm, TJC and process verification runs. The large area TJC design was optimized for minimum I squared R power losses. In the TJM activity, the cell-module interfaces were defined, module substrates were formed and heat treated and clad metal interconnect strips were fabricated.

Fully Integrated Linear Single Photon Avalanche Diode (SPAD) Array with Parallel Readout Circuit in a Standard 180 nm CMOS Process

NASA Astrophysics Data System (ADS)

Isaak, S.; Bull, S.; Pitter, M. C.; Harrison, Ian.

2011-05-01

This paper reports on the development of a SPAD device and its subsequent use in an actively quenched single photon counting imaging system, and was fabricated in a UMC 0.18 μm CMOS process. A low-doped p- guard ring (t-well layer) encircling the active area to prevent the premature reverse breakdown. The array is a 16×1 parallel output SPAD array, which comprises of an active quenched SPAD circuit in each pixel with the current value being set by an external resistor RRef = 300 kΩ. The SPAD I-V response, ID was found to slowly increase until VBD was reached at excess bias voltage, Ve = 11.03 V, and then rapidly increase due to avalanche multiplication. Digital circuitry to control the SPAD array and perform the necessary data processing was designed in VHDL and implemented on a FPGA chip. At room temperature, the dark count was found to be approximately 13 KHz for most of the 16 SPAD pixels and the dead time was estimated to be 40 ns.

Two-Dimensional Si-Nanodisk Array Fabricated Using Bio-Nano-Process and Neutral Beam Etching for Realistic Quantum Effect Devices

NASA Astrophysics Data System (ADS)

Huang, Chi-Hsien; Igarashi, Makoto; Woné, Michel; Uraoka, Yukiharu; Fuyuki, Takashi; Takeguchi, Masaki; Yamashita, Ichiro; Samukawa, Seiji

2009-04-01

A high-density, large-area, and uniform two-dimensional (2D) Si-nanodisk array was successfully fabricated using the bio-nano-process, advanced etching techniques, including a treatment using nitrogen trifluoride and hydrogen radical (NF3 treatment) and a damage-free chlorine neutral beam (NB). By using the surface oxide formed by neutral beam oxidation (NBO) for the preparation of a 2D nanometer-sized iron core array as an etching mask, a well-ordered 2D Si-nanodisk array was obtained owing to the dangling bonds of the surface oxide. By changing the NF3 treatment time without changing the quantum effect of each nanodisk, we could control the gap between adjacent nanodisks. A device with two electrodes was fabricated to investigate the electron transport in a 2D Si-nanodisk array. Current fluctuation and time-dependent currents were clearly observed owing to the charging-discharging of the nanodisks adjacent to the current percolation path. The new structure may have great potential for future novel quantum effect devices.

Integration of Si-CMOS embedded photo detector array and mixed signal processing system with embedded optical waveguide input

NASA Astrophysics Data System (ADS)

Kim, Daeik D.; Thomas, Mikkel A.; Brooke, Martin A.; Jokerst, Nan M.

2004-06-01

Arrays of embedded bipolar junction transistor (BJT) photo detectors (PD) and a parallel mixed-signal processing system were fabricated as a silicon complementary metal oxide semiconductor (Si-CMOS) circuit for the integration optical sensors on the surface of the chip. The circuit was fabricated with AMI 1.5um n-well CMOS process and the embedded PNP BJT PD has a pixel size of 8um by 8um. BJT PD was chosen to take advantage of its higher gain amplification of photo current than that of PiN type detectors since the target application is a low-speed and high-sensitivity sensor. The photo current generated by BJT PD is manipulated by mixed-signal processing system, which consists of parallel first order low-pass delta-sigma oversampling analog-to-digital converters (ADC). There are 8 parallel ADCs on the chip and a group of 8 BJT PDs are selected with CMOS switches. An array of PD is composed of three or six groups of PDs depending on the number of rows.

The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

NASA Astrophysics Data System (ADS)

Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

2010-12-01

Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential

Alternative Post-Processing on a CMOS Chip to Fabricate a Planar Microelectrode Array

PubMed Central

López-Huerta, Francisco; Herrera-May, Agustín L.; Estrada-López, Johan J.; Zuñiga-Islas, Carlos; Cervantes-Sanchez, Blanca; Soto, Enrique; Soto-Cruz, Blanca S.

2011-01-01

We present an alternative post-processing on a CMOS chip to release a planar microelectrode array (pMEA) integrated with its signal readout circuit, which can be used for monitoring the neuronal activity of vestibular ganglion neurons in newborn Wistar strain rats. This chip is fabricated through a 0.6 μm CMOS standard process and it has 12 pMEA through a 4 × 3 electrodes matrix. The alternative CMOS post-process includes the development of masks to protect the readout circuit and the power supply pads. A wet etching process eliminates the aluminum located on the surface of the p+-type silicon. This silicon is used as transducer for recording the neuronal activity and as interface between the readout circuit and neurons. The readout circuit is composed of an amplifier and tunable bandpass filter, which is placed on a 0.015 mm2 silicon area. The tunable bandpass filter has a bandwidth of 98 kHz and a common mode rejection ratio (CMRR) of 87 dB. These characteristics of the readout circuit are appropriate for neuronal recording applications. PMID:22346681

Alternative post-processing on a CMOS chip to fabricate a planar microelectrode array.

PubMed

López-Huerta, Francisco; Herrera-May, Agustín L; Estrada-López, Johan J; Zuñiga-Islas, Carlos; Cervantes-Sanchez, Blanca; Soto, Enrique; Soto-Cruz, Blanca S

2011-01-01

We present an alternative post-processing on a CMOS chip to release a planar microelectrode array (pMEA) integrated with its signal readout circuit, which can be used for monitoring the neuronal activity of vestibular ganglion neurons in newborn Wistar strain rats. This chip is fabricated through a 0.6 μm CMOS standard process and it has 12 pMEA through a 4 × 3 electrodes matrix. The alternative CMOS post-process includes the development of masks to protect the readout circuit and the power supply pads. A wet etching process eliminates the aluminum located on the surface of the p+ -type silicon. This silicon is used as transducer for recording the neuronal activity and as interface between the readout circuit and neurons. The readout circuit is composed of an amplifier and tunable bandpass filter, which is placed on a 0.015 mm2 silicon area. The tunable bandpass filter has a bandwidth of 98 kHz and a common mode rejection ratio (CMRR) of 87 dB. These characteristics of the readout circuit are appropriate for neuronal recording applications.

Continuous catchment-scale monitoring of geomorphic processes with a 2-D seismological array

NASA Astrophysics Data System (ADS)

Burtin, A.; Hovius, N.; Milodowski, D.; Chen, Y.-G.; Wu, Y.-M.; Lin, C.-W.; Chen, H.

2012-04-01

The monitoring of geomorphic processes during extreme climatic events is of a primary interest to estimate their impact on the landscape dynamics. However, available techniques to survey the surface activity do not provide a relevant time and/or space resolution. Furthermore, these methods hardly investigate the dynamics of the events since their detection are made a posteriori. To increase our knowledge of the landscape evolution and the influence of extreme climatic events on a catchment dynamics, we need to develop new tools and procedures. In many past works, it has been shown that seismic signals are relevant to detect and locate surface processes (landslides, debris flows). During the 2010 typhoon season, we deployed a network of 12 seismometers dedicated to monitor the surface processes of the Chenyoulan catchment in Taiwan. We test the ability of a two dimensional array and small inter-stations distances (~ 11 km) to map in continuous and at a catchment-scale the geomorphic activity. The spectral analysis of continuous records shows a high-frequency (> 1 Hz) seismic energy that is coherent with the occurrence of hillslope and river processes. Using a basic detection algorithm and a location approach running on the analysis of seismic amplitudes, we manage to locate the catchment activity. We mainly observe short-time events (> 300 occurrences) associated with debris falls and bank collapses during daily convective storms, where 69% of occurrences are coherent with the time distribution of precipitations. We also identify a couple of debris flows during a large tropical storm. In contrast, the FORMOSAT imagery does not detect any activity, which somehow reflects the lack of extreme climatic conditions during the experiment. However, high resolution pictures confirm the existence of links between most of geomorphic events and existing structures (landslide scars, gullies...). We thus conclude to an activity that is dominated by reactivation processes. It

NEWTON - NEW portable multi-sensor scienTific instrument for non-invasive ON-site characterization of rock from planetary surface and sub-surfaces

NASA Astrophysics Data System (ADS)

Díaz-Michelena, M.; de Frutos, J.; Ordóñez, A. A.; Rivero, M. A.; Mesa, J. L.; González, L.; Lavín, C.; Aroca, C.; Sanz, M.; Maicas, M.; Prieto, J. L.; Cobos, P.; Pérez, M.; Kilian, R.; Baeza, O.; Langlais, B.; Thébault, E.; Grösser, J.; Pappusch, M.

2017-09-01

In space instrumentation, there is currently no instrument dedicated to susceptibly or complete magnetization measurements of rocks. Magnetic field instrument suites are generally vector (or scalar) magnetometers, which locally measure the magnetic field. When mounted on board rovers, the electromagnetic perturbations associated with motors and other elements make it difficult to reap the benefits from the inclusion of such instruments. However, magnetic characterization is essential to understand key aspects of the present and past history of planetary objects. The work presented here overcomes the limitations currently existing in space instrumentation by developing a new portable and compact multi-sensor instrument for ground breaking high-resolution magnetic characterization of planetary surfaces and sub-surfaces. This new technology introduces for the first time magnetic susceptometry (real and imaginary parts) as a complement to existing compact vector magnetometers for planetary exploration. This work aims to solve the limitations currently existing in space instrumentation by means of providing a new portable and compact multi-sensor instrument for use in space, science and planetary exploration to solve some of the open questions on the crustal and more generally planetary evolution within the Solar System.

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Brightness field distributions of microlens arrays using micro molding.

PubMed

Cheng, Hsin-Chung; Huang, Chiung-Fang; Lin, Yi; Shen, Yung-Kang

2010-12-20

This study describes the brightness field distributions of microlens arrays fabricated by micro injection molding (μIM) and micro injection-compression molding (μICM). The process for fabricating microlens arrays used room-temperature imprint lithography, photoresist reflow, electroforming, μIM, μICM, and optical properties measurement. Analytical results indicate that the brightness field distribution of the molded microlens arrays generated by μICM is better than those made using μIM. Our results further demonstrate that mold temperature is the most important processing parameter for brightness field distribution of molded microlens arrays made by μIM or μICM.

Modelling spatiotemporal change using multidimensional arrays Meng

NASA Astrophysics Data System (ADS)

Lu, Meng; Appel, Marius; Pebesma, Edzer

2017-04-01

The large variety of remote sensors, model simulations, and in-situ records provide great opportunities to model environmental change. The massive amount of high-dimensional data calls for methods to integrate data from various sources and to analyse spatiotemporal and thematic information jointly. An array is a collection of elements ordered and indexed in arbitrary dimensions, which naturally represent spatiotemporal phenomena that are identified by their geographic locations and recording time. In addition, array regridding (e.g., resampling, down-/up-scaling), dimension reduction, and spatiotemporal statistical algorithms are readily applicable to arrays. However, the role of arrays in big geoscientific data analysis has not been systematically studied: How can arrays discretise continuous spatiotemporal phenomena? How can arrays facilitate the extraction of multidimensional information? How can arrays provide a clean, scalable and reproducible change modelling process that is communicable between mathematicians, computer scientist, Earth system scientist and stakeholders? This study emphasises on detecting spatiotemporal change using satellite image time series. Current change detection methods using satellite image time series commonly analyse data in separate steps: 1) forming a vegetation index, 2) conducting time series analysis on each pixel, and 3) post-processing and mapping time series analysis results, which does not consider spatiotemporal correlations and ignores much of the spectral information. Multidimensional information can be better extracted by jointly considering spatial, spectral, and temporal information. To approach this goal, we use principal component analysis to extract multispectral information and spatial autoregressive models to account for spatial correlation in residual based time series structural change modelling. We also discuss the potential of multivariate non-parametric time series structural change methods, hierarchical

Arraying proteins by cell-free synthesis.

PubMed

He, Mingyue; Wang, Ming-Wei

2007-10-01

Recent advances in life science have led to great motivation for the development of protein arrays to study functions of genome-encoded proteins. While traditional cell-based methods have been commonly used for generating protein arrays, they are usually a time-consuming process with a number of technical challenges. Cell-free protein synthesis offers an attractive system for making protein arrays, not only does it rapidly converts the genetic information into functional proteins without the need for DNA cloning, but also presents a flexible environment amenable to production of folded proteins or proteins with defined modifications. Recent advancements have made it possible to rapidly generate protein arrays from PCR DNA templates through parallel on-chip protein synthesis. This article reviews current cell-free protein array technologies and their proteomic applications.

Analyzing CMOS/SOS fabrication for LSI arrays

NASA Technical Reports Server (NTRS)

Ipri, A. C.

1978-01-01

Report discusses set of design rules that have been developed as result of work with test arrays. Set of optimum dimensions is given that would maximize process output and would correspondingly minimize costs in fabrication of large-scale integration (LSI) arrays.

Infrared-Bolometer Arrays with Reflective Backshorts

NASA Technical Reports Server (NTRS)

Miller, Timothy M.; Abrahams, John; Allen, Christine A.

2011-01-01

Integrated circuits that incorporate square arrays of superconducting-transition- edge bolometers with optically reflective backshorts are being developed for use in image sensors in the spectral range from far infrared to millimeter wavelengths. To maximize the optical efficiency (and, thus, sensitivity) of such a sensor at a specific wavelength, resonant optical structures are created by placing the backshorts at a quarter wavelength behind the bolometer plane. The bolometer and backshort arrays are fabricated separately, then integrated to form a single unit denoted a backshort-under-grid (BUG) bolometer array. In a subsequent fabrication step, the BUG bolometer array is connected, by use of single-sided indium bump bonding, to a readout device that comprises mostly a superconducting quantum interference device (SQUID) multiplexer circuit. The resulting sensor unit comprising the BUG bolometer array and the readout device is operated at a temperature below 1 K. The concept of increasing optical efficiency by use of backshorts at a quarter wavelength behind the bolometers is not new. Instead, the novelty of the present development lies mainly in several features of the design of the BUG bolometer array and the fabrication sequence used to implement the design. Prior to joining with the backshort array, the bolometer array comprises, more specifically, a square grid of free-standing molybdenum/gold superconducting-transition-edge bolometer elements on a 1.4- m-thick top layer of silicon that is part of a silicon support frame made from a silicon-on-insulator wafer. The backshort array is fabricated separately as a frame structure that includes support beams and contains a correspond - ing grid of optically reflective patches on a single-crystal silicon substrate. The process used to fabricate the bolometer array includes standard patterning and etching steps that result in the formation of deep notches in the silicon support frame. These notches are designed to

Multi-Sensor Observations of Earthquake Related Atmospheric Signals over Major Geohazard Validation Sites

NASA Technical Reports Server (NTRS)

Ouzounov, D.; Pulinets, S.; Davindenko, D.; Hattori, K.; Kafatos, M.; Taylor, P.

2012-01-01

We are conducting a scientific validation study involving multi-sensor observations in our investigation of phenomena preceding major earthquakes. Our approach is based on a systematic analysis of several atmospheric and environmental parameters, which we found, are associated with the earthquakes, namely: thermal infrared radiation, outgoing long-wavelength radiation, ionospheric electron density, and atmospheric temperature and humidity. For first time we applied this approach to selected GEOSS sites prone to earthquakes or volcanoes. This provides a new opportunity to cross validate our results with the dense networks of in-situ and space measurements. We investigated two different seismic aspects, first the sites with recent large earthquakes, viz.- Tohoku-oki (M9, 2011, Japan) and Emilia region (M5.9, 2012,N. Italy). Our retrospective analysis of satellite data has shown the presence of anomalies in the atmosphere. Second, we did a retrospective analysis to check the re-occurrence of similar anomalous behavior in atmosphere/ionosphere over three regions with distinct geological settings and high seismicity: Taiwan, Japan and Kamchatka, which include 40 major earthquakes (M>5.9) for the period of 2005-2009. We found anomalous behavior before all of these events with no false negatives; false positives were less then 10%. Our initial results suggest that multi-instrument space-borne and ground observations show a systematic appearance of atmospheric anomalies near the epicentral area that could be explained by a coupling between the observed physical parameters and earthquake preparation processes.

Self-assembled three-dimensional nanocrown array.

PubMed

Hong, Soongweon; Kang, Taewook; Choi, Dukhyun; Choi, Yeonho; Lee, Luke P

2012-07-24

Although an ordered nanoplasmonic probe array will have a huge impact on light harvesting, selective frequency response (i.e., nanoantenna), and quantitative molecular/cellular imaging, the realization of such an array is still limited by conventional techniques due to the serial processing or resolution limit by light diffraction. Here, we demonstrate a thermodynamically driven, self-assembled three-dimensional nanocrown array that consists of a core and six satellite gold nanoparticles (GNPs). Our ordered nanoprobe array is fabricated over a large area by thermal dewetting of thin gold film on hexagonally ordered porous anodic alumina (PAA). During thermal dewetting, the structural order of the PAA template dictates the periodic arrangement of gold nanoparticles, rendering the array of gold nanocrown. Because of its tunable size (i.e., 50 nm core and 20 nm satellite GNPs), arrangement, and periodicity, the nanocrown array shows multiple optical resonance frequencies at visible wavelengths as well as angle-dependent optical properties.

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

DOE PAGES

Meng, Ran; Wu, Jin; Zhao, Feng; ...

2018-06-01

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Measuring short-term post-fire forest recovery across a burn severity gradient in a mixed pine-oak forest using multi-sensor remote sensing techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meng, Ran; Wu, Jin; Zhao, Feng

Understanding post-fire forest recovery is pivotal to the study of forest dynamics and global carbon cycle. Field-based studies indicated a convex response of forest recovery rate to burn severity at the individual tree level, related with fire-induced tree mortality; however, these findings were constrained in spatial/temporal extents, while not detectable by traditional optical remote sensing studies, largely attributing to the contaminated effect from understory recovery. For this work, we examined whether the combined use of multi-sensor remote sensing techniques (i.e., 1m simultaneous airborne imaging spectroscopy and LiDAR and 2m satellite multi-spectral imagery) to separate canopy recovery from understory recovery wouldmore » enable to quantify post-fire forest recovery rate spanning a large gradient in burn severity over large-scales. Our study was conducted in a mixed pine-oak forest in Long Island, NY, three years after a top-killing fire. Our studies remotely detected an initial increase and then decline of forest recovery rate to burn severity across the burned area, with a maximum canopy area-based recovery rate of 10% per year at moderate forest burn severity class. More intriguingly, such remotely detected convex relationships also held at species level, with pine trees being more resilient to high burn severity and having a higher maximum recovery rate (12% per year) than oak trees (4% per year). These results are one of the first quantitative evidences showing the effects of fire adaptive strategies on post-fire forest recovery, derived from relatively large spatial-temporal domains. Our study thus provides the methodological advance to link multi-sensor remote sensing techniques to monitor forest dynamics in a spatially explicit manner over large-scales, with important implications for fire-related forest management, and for constraining/benchmarking fire effect schemes in ecological process models.« less

Surface-Micromachined Planar Arrays of Thermopiles

NASA Technical Reports Server (NTRS)

Foote, Marc C.

2003-01-01

Planar two-dimensional arrays of thermopiles intended for use as thermal-imaging detectors are to be fabricated by a process that includes surface micromachining. These thermopile arrays are designed to perform better than do prior two-dimensional thermopile arrays. The lower performance of prior two-dimensional thermopile arrays is attributed to the following causes: The thermopiles are made from low-performance thermoelectric materials. The devices contain dielectric supporting structures, the thermal conductances of which give rise to parasitic losses of heat from detectors to substrates. The bulk-micromachining processes sometimes used to remove substrate material under the pixels, making it difficult to incorporate low-noise readout electronic circuitry. The thermoelectric lines are on the same level as the infrared absorbers, thereby reducing fill factor. The improved pixel design of a thermopile array of the type under development is expected to afford enhanced performance by virtue of the following combination of features: Surface-micromachined detectors are thermally isolated through suspension above readout circuitry. The thermopiles are made of such high-performance thermoelectric materials as Bi-Te and Bi-Sb-Te alloys. Pixel structures are supported only by the thermoelectric materials: there are no supporting dielectric structures that could leak heat by conduction to the substrate.

From Multi-Sensors Observations Towards Cross-Disciplinary Study of Pre-Earthquake Signals. What have We Learned from the Tohoku Earthquake?

NASA Technical Reports Server (NTRS)

Ouzounov, D.; Pulinets, S.; Papadopoulos, G.; Kunitsyn, V.; Nesterov, I.; Hayakawa, M.; Mogi, K.; Hattori, K.; Kafatos, M.; Taylor, P.

2012-01-01

The lessons we have learned from the Great Tohoku EQ (Japan, 2011) how this knowledge will affect our future observation and analysis is the main focus of this presentation.We present multi-sensors observations and multidisciplinary research in our investigation of phenomena preceding major earthquakes. These observations revealed the existence of atmospheric and ionospheric phenomena occurring prior to theM9.0 Tohoku earthquake of March 11, 2011, which indicates s new evidence of a distinct coupling between the lithosphere and atmosphere/ionosphere, as related to underlying tectonic activity. Similar results have been reported before the catastrophic events in Chile (M8.8, 2010), Italy (M6.3, 2009) and Sumatra (M9.3, 2004). For the Tohoku earthquake, our analysis shows a synergy between several independent observations characterizing the state of the lithosphere /atmosphere coupling several days before the onset of the earthquakes, namely: (i) Foreshock sequence change (rate, space and time); (ii) Outgoing Long wave Radiation (OLR) measured at the top of the atmosphere; and (iii) Anomalous variations of ionospheric parameters revealed by multi-sensors observations. We are presenting a cross-disciplinary analysis of the observed pre-earthquake anomalies and will discuss current research in the detection of these signals in Japan. We expect that our analysis will shed light on the underlying physics of pre-earthquake signals associated with some of the largest earthquake events

Breadboard linear array scan imager using LSI solid-state technology

NASA Technical Reports Server (NTRS)

Tracy, R. A.; Brennan, J. A.; Frankel, D. G.; Noll, R. E.

1976-01-01

The performance of large scale integration photodiode arrays in a linear array scan (pushbroom) breadboard was evaluated for application to multispectral remote sensing of the earth's resources. The technical approach, implementation, and test results of the program are described. Several self scanned linear array visible photodetector focal plane arrays were fabricated and evaluated in an optical bench configuration. A 1728-detector array operating in four bands (0.5 - 1.1 micrometer) was evaluated for noise, spectral response, dynamic range, crosstalk, MTF, noise equivalent irradiance, linearity, and image quality. Other results include image artifact data, temporal characteristics, radiometric accuracy, calibration experience, chip alignment, and array fabrication experience. Special studies and experimentation were included in long array fabrication and real-time image processing for low-cost ground stations, including the use of computer image processing. High quality images were produced and all objectives of the program were attained.

Design and testing of a multi-sensor pedestrian location and navigation platform.

PubMed

Morrison, Aiden; Renaudin, Valérie; Bancroft, Jared B; Lachapelle, Gérard

2012-01-01

Navigation and location technologies are continually advancing, allowing ever higher accuracies and operation under ever more challenging conditions. The development of such technologies requires the rapid evaluation of a large number of sensors and related utilization strategies. The integration of Global Navigation Satellite Systems (GNSSs) such as the Global Positioning System (GPS) with accelerometers, gyros, barometers, magnetometers and other sensors is allowing for novel applications, but is hindered by the difficulties to test and compare integrated solutions using multiple sensor sets. In order to achieve compatibility and flexibility in terms of multiple sensors, an advanced adaptable platform is required. This paper describes the design and testing of the NavCube, a multi-sensor navigation, location and timing platform. The system provides a research tool for pedestrian navigation, location and body motion analysis in an unobtrusive form factor that enables in situ data collections with minimal gait and posture impact. Testing and examples of applications of the NavCube are provided.

A Locomotion Intent Prediction System Based on Multi-Sensor Fusion

PubMed Central

Chen, Baojun; Zheng, Enhao; Wang, Qining

2014-01-01

Locomotion intent prediction is essential for the control of powered lower-limb prostheses to realize smooth locomotion transitions. In this research, we develop a multi-sensor fusion based locomotion intent prediction system, which can recognize current locomotion mode and detect locomotion transitions in advance. Seven able-bodied subjects were recruited for this research. Signals from two foot pressure insoles and three inertial measurement units (one on the thigh, one on the shank and the other on the foot) are measured. A two-level recognition strategy is used for the recognition with linear discriminate classifier. Six kinds of locomotion modes and ten kinds of locomotion transitions are tested in this study. Recognition accuracy during steady locomotion periods (i.e., no locomotion transitions) is 99.71% ± 0.05% for seven able-bodied subjects. During locomotion transition periods, all the transitions are correctly detected and most of them can be detected before transiting to new locomotion modes. No significant deterioration in recognition performance is observed in the following five hours after the system is trained, and small number of experiment trials are required to train reliable classifiers. PMID:25014097

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

NASA Technical Reports Server (NTRS)

Ransom, K. J.; Sun, G.; Kharuk, V. I.; Howl, J.

2011-01-01

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

A locomotion intent prediction system based on multi-sensor fusion.

PubMed

Chen, Baojun; Zheng, Enhao; Wang, Qining

2014-07-10

Locomotion intent prediction is essential for the control of powered lower-limb prostheses to realize smooth locomotion transitions. In this research, we develop a multi-sensor fusion based locomotion intent prediction system, which can recognize current locomotion mode and detect locomotion transitions in advance. Seven able-bodied subjects were recruited for this research. Signals from two foot pressure insoles and three inertial measurement units (one on the thigh, one on the shank and the other on the foot) are measured. A two-level recognition strategy is used for the recognition with linear discriminate classifier. Six kinds of locomotion modes and ten kinds of locomotion transitions are tested in this study. Recognition accuracy during steady locomotion periods (i.e., no locomotion transitions) is 99.71% ± 0.05% for seven able-bodied subjects. During locomotion transition periods, all the transitions are correctly detected and most of them can be detected before transiting to new locomotion modes. No significant deterioration in recognition performance is observed in the following five hours after the system is trained, and small number of experiment trials are required to train reliable classifiers.

Big Data Challenges for Large Radio Arrays

NASA Technical Reports Server (NTRS)

Jones, Dayton L.; Wagstaff, Kiri; Thompson, David; D'Addario, Larry; Navarro, Robert; Mattmann, Chris; Majid, Walid; Lazio, Joseph; Preston, Robert; Rebbapragada, Umaa

2012-01-01

Future large radio astronomy arrays, particularly the Square Kilometre Array (SKA), will be able to generate data at rates far higher than can be analyzed or stored affordably with current practices. This is, by definition, a "big data" problem, and requires an end-to-end solution if future radio arrays are to reach their full scientific potential. Similar data processing, transport, storage, and management challenges face next-generation facilities in many other fields.

Performance Assessment of Multi-Array Processing with Ground Truth for Infrasonic, Seismic and Seismo-Acoustic Events

DTIC Science & Technology

2012-07-03

of white noise vectors with square sumable coefficients and components with finite fourth order moments (Shumway et al., 1999). Here, the infrasonic...center in a star -like configuration for reducing the background noise from wind activity along the boundary layer. Sensor data is recorded by 24-bit...the PMCC Algorithm In Figure 19, under the assumption that the source (red star ) is far from the arrays, PMCC starts coherence processing using

Array servo scanning micro EDM of 3D micro cavities

NASA Astrophysics Data System (ADS)

Tong, Hao; Li, Yong; Yi, Futing

2011-05-01

Micro electro discharge machining (Micro EDM) is a non-traditional processing technology with the special advantages of low set-up cost and few cutting force in machining any conductive materials regardless of their hardness. As well known, die-sinking EDM is unsuitable for machining the complex 3D micro cavity less than 1mm due to the high-priced fabrication of 3D microelectrode itself and its serous wear during EDM process. In our former study, a servo scanning 3D micro-EDM (3D SSMEDM) method was put forward, and our experiments showed it was available to fabricate complex 3D micro-cavities. In this study, in order to improve machining efficiency and consistency accuracy for array 3D micro-cavities, an array-servo-scanning 3D micro EDM (3D ASSMEDM) method is presented considering the complementary advantages of the 3D SSMEDM and the array micro electrodes with simple cross-section. During 3D ASSMEDM process, the array cavities designed by CAD / CAM system can be batch-manufactured by servo scanning layer by layer using array-rod-like micro tool electrodes, and the axial wear of the array electrodes is compensated in real time by keeping discharge gap. To verify the effectiveness of the 3D ASSMEDM, the array-triangle-micro cavities (side length 630 μm) are batch-manufactured on P-doped silicon by applying the array-micro-electrodes with square-cross-section fabricated by LIGA process. Our exploratory experiment shows that the 3D ASSMEDM provides a feasible approach for the batch-manufacture of 3D array-micro-cavities of conductive materials.

Interferometric side scan sonar and data fusion

NASA Astrophysics Data System (ADS)

Sintes, Christophe R.; Solaiman, Basel

2000-04-01

This paper concerns the possibilities of sea bottom imaging and altitude determining of each imaged point. The performances of new side scan sonars which are able to image the sea bottom with a high definition and are able to evaluate the relief with the same definition derive from an interferometric multisensor system. The drawbacks concern the precision of the numerical altitude model. One way to improve the measurements precision is to merge all the information issued from the multi-sensors system. This leads to increase the Signal to Noise Ratio (SNR) and the robustness of the used method. The aim of this paper is to clearly demonstrate the ability to derive benefits of all information issued from the three arrays side scan sonar by merging: (1) the three phase signals obtained at the output of the sensors, (2) this same set of data after the application of different processing methods, and (3) the a priori relief contextual information. The key idea the proposed fusion technique is to exploit the strength and the weaknesses of each data element in the fusion of process so that the global SNR will be improved as well as the robustness to hostile noisy environments.

Process-morphology scaling relations quantify self-organization in capillary densified nanofiber arrays.

PubMed

Kaiser, Ashley L; Stein, Itai Y; Cui, Kehang; Wardle, Brian L

2018-02-07

Capillary-mediated densification is an inexpensive and versatile approach to tune the application-specific properties and packing morphology of bulk nanofiber (NF) arrays, such as aligned carbon nanotubes. While NF length governs elasto-capillary self-assembly, the geometry of cellular patterns formed by capillary densified NFs cannot be precisely predicted by existing theories. This originates from the recently quantified orders of magnitude lower than expected NF array effective axial elastic modulus (E), and here we show via parametric experimentation and modeling that E determines the width, area, and wall thickness of the resulting cellular pattern. Both experiments and models show that further tuning of the cellular pattern is possible by altering the NF-substrate adhesion strength, which could enable the broad use of this facile approach to predictably pattern NF arrays for high value applications.

Techniques for Sea Ice Characteristics Extraction and Sea Ice Monitoring Using Multi-Sensor Satellite Data in the Bohai Sea-Dragon 3 Programme Final Report (2012-2016)

NASA Astrophysics Data System (ADS)

Zhang, Xi; Zhang, Jie; Meng, Junmin

2016-08-01

The objectives of Dragon-3 programme (ID: 10501) are to develop methods for classification sea ice types and retrieving ice thickness based on multi-sensor data. In this final results paper, we give a briefly introduction for our research work and mainly results. Key words: the Bohai Sea ice, Sea ice, optical and

Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation.

PubMed

Caduff, Andreas; Mueller, Martin; Megej, Alexander; Dewarrat, Francois; Suri, Roland E; Klisic, Jelena; Donath, Marc; Zakharov, Pavel; Schaub, Dominik; Stahel, Werner A; Talary, Mark S

2011-05-15

The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1 kHz-100 MHz, 1 and 2 GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44±16 y; BMI 24.1±1.3 kg/m(2), duration of diabetes 27±12 y; HbA1c 7.3±1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9 mg dL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions. Copyright © 2011 Elsevier B.V. All rights reserved.

Materials Development for Auxiliary Components for Large Compact Mo/Au TES Arrays

NASA Technical Reports Server (NTRS)

Finkbeiner, F. m.; Chervenak, J. A.; Bandler, S. R.; Brekosky, R.; Brown, A. D.; Figueroa-Feliciano, E.; Iyomoto, N.; Kelley, R. L.; Kilbourne, C. A.; Porter, F. S.;

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne

2012-01-01

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

Redundancy Analysis of Capacitance Data of a Coplanar Electrode Array for Fast and Stable Imaging Processing

PubMed Central

Wen, Yintang; Zhang, Zhenda; Zhang, Yuyan; Sun, Dongtao

2017-01-01

A coplanar electrode array sensor is established for the imaging of composite-material adhesive-layer defect detection. The sensor is based on the capacitive edge effect, which leads to capacitance data being considerably weak and susceptible to environmental noise. The inverse problem of coplanar array electrical capacitance tomography (C-ECT) is ill-conditioning, in which a small error of capacitance data can seriously affect the quality of reconstructed images. In order to achieve a stable image reconstruction process, a redundancy analysis method for capacitance data is proposed. The proposed method is based on contribution rate and anti-interference capability. According to the redundancy analysis, the capacitance data are divided into valid and invalid data. When the image is reconstructed by valid data, the sensitivity matrix needs to be changed accordingly. In order to evaluate the effectiveness of the sensitivity map, singular value decomposition (SVD) is used. Finally, the two-dimensional (2D) and three-dimensional (3D) images are reconstructed by the Tikhonov regularization method. Through comparison of the reconstructed images of raw capacitance data, the stability of the image reconstruction process can be improved, and the quality of reconstructed images is not degraded. As a result, much invalid data are not collected, and the data acquisition time can also be reduced. PMID:29295537

Solar array flight experiment

NASA Technical Reports Server (NTRS)

1986-01-01

Emerging satellite designs require increasing amounts of electrical power to operate spacecraft instruments and to provide environments suitable for human habitation. In the past, electrical power was generated by covering rigid honeycomb panels with solar cells. This technology results in unacceptable weight and volume penalties when large amounts of power are required. To fill the need for large-area, lightweight solar arrays, a fabrication technique in which solar cells are attached to a copper printed circuit laminated to a plastic sheet was developed. The result is a flexible solar array with one-tenth the stowed volume and one-third the weight of comparably sized rigid arrays. An automated welding process developed to attack the cells to the printed circuit guarantees repeatable welds that are more tolerant of severe environments than conventional soldered connections. To demonstrate the flight readiness of this technology, the Solar Array Flight Experiment (SAFE) was developed and flown on the space shuttle Discovery in September 1984. The tests showed the modes and frequencies of the array to be very close to preflight predictions. Structural damping, however, was higher than anticipated. Electrical performance of the active solar panel was also tested. The flight performance and postflight data evaluation are described.

Spaceborne Processor Array

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Schatzel, Donald V.; Whitaker, William D.; Sterling, Thomas

2008-01-01

A Spaceborne Processor Array in Multifunctional Structure (SPAMS) can lower the total mass of the electronic and structural overhead of spacecraft, resulting in reduced launch costs, while increasing the science return through dynamic onboard computing. SPAMS integrates the multifunctional structure (MFS) and the Gilgamesh Memory, Intelligence, and Network Device (MIND) multi-core in-memory computer architecture into a single-system super-architecture. This transforms every inch of a spacecraft into a sharable, interconnected, smart computing element to increase computing performance while simultaneously reducing mass. The MIND in-memory architecture provides a foundation for high-performance, low-power, and fault-tolerant computing. The MIND chip has an internal structure that includes memory, processing, and communication functionality. The Gilgamesh is a scalable system comprising multiple MIND chips interconnected to operate as a single, tightly coupled, parallel computer. The array of MIND components shares a global, virtual name space for program variables and tasks that are allocated at run time to the distributed physical memory and processing resources. Individual processor- memory nodes can be activated or powered down at run time to provide active power management and to configure around faults. A SPAMS system is comprised of a distributed Gilgamesh array built into MFS, interfaces into instrument and communication subsystems, a mass storage interface, and a radiation-hardened flight computer.

What can hafnium isotope ratios arrays tell us about orogenic processes? An insight into geodynamic processes operating in the Alpine/Mediterranean region

NASA Astrophysics Data System (ADS)

Henderson, B.; Murphy, J.; Collins, W. J.; Hand, M. P.

2013-12-01

Over the last decade, technological advances in laser-ablation sampling techniques have resulted in an increase in the number of combined U-Pb-Hf zircon isotope studies used to investigate crustal evolution on a local, regional and global scale. Hafnium isotope arrays over large time scales (>500 myr) have been interpreted to track evolving plate tectonic configurations, and the geological outputs associated with changing plate boundaries. We use the Alpine-Mediterranean region as an example of how hafnium isotope arrays record the geodynamic processes associated with the complex geological evolution of a region. The geology of Alpine-Mediterranean region preserves a complex, semi-continuous tectonic history that extends from the Neoproterozoic to the present day. Major components of the Variscan and Alpine orogens are microcontinental ribbons derived from the northern Gondwanan margin, which were transferred to the Eurasian plate during the opening and closing of the Rheic and Paleo-Tethys Oceans. Convergence of the Eurasian and African plates commenced in the Mid-Late Cretaceous, following the destruction of the Alpine-Tethys Ocean during the terminal breakup of Pangea. In general, convergence occurred slowly and is characterised by northward accretion of Gondwanan fragments, interspersed with subduction of African lithosphere and intermittent roll-back events. A consequence of this geodynamic scenario was periods of granite-dominated magmatism in an arc-backarc setting. New Hf isotope data from the peri-Gondwanan terranes (Iberia, Meguma and Avalonia) and a compilation of existing Phanerozoic data from the Alpine-Mediterranean region, indicate ~500 myr (Cambrian-Recent) of reworking of peri-Gondwanan crust. The eHf array follows a typical crustal evolution pattern (Lu/Hf=0.015) and is considered to reflect reworking of juvenile peri-Gondwanan (Neoproterozoic) crust variably mixed with an older (~1.8-2.0 Ga) source component, probably Eburnian crust from the West

Database recovery using redundant disk arrays

NASA Technical Reports Server (NTRS)

Mourad, Antoine N.; Fuchs, W. K.; Saab, Daniel G.

1992-01-01

Redundant disk arrays provide a way for achieving rapid recovery from media failures with a relatively low storage cost for large scale database systems requiring high availability. In this paper a method is proposed for using redundant disk arrays to support rapid-recovery from system crashes and transaction aborts in addition to their role in providing media failure recovery. A twin page scheme is used to store the parity information in the array so that the time for transaction commit processing is not degraded. Using an analytical model, it is shown that the proposed method achieves a significant increase in the throughput of database systems using redundant disk arrays by reducing the number of recovery operations needed to maintain the consistency of the database.

The Atacama Compact Array: An Overview

NASA Astrophysics Data System (ADS)

Iguchi, S.; Wilson, T. L.

2010-01-01

When completed, ALMA will comprise a 12-meter diameter antennas array (12-m Array) of a minimum of fifty antennas, and the ACA (Atacama Compact Array), composed of four 12-meter diameter antennas and twelve 7-meter diameter antennas. Out of the fifty antennas of the 12-m Array, one-half are provided by the North American partners of ALMA, the other half by the European partners. The sixteen antennas that will comprise the ACA are provided by the East Asian Partners of ALMA. In the last issue of the ALMA Science Newsletter, we outlined the testing of the prototype ALMA 12-meter diameter antennas and the procurement process for these antennas. In that article, only a short account was given of the antennas for the Atacama Compact Array (ACA). In the following we give an overview of the ACA, starting with an introduction to imaging using interferometers.

Adding Semantics and OPM Ontology for the Provenance of Multi-sensor Merged Climate Data Records. Now What About Reproducibility?

NASA Astrophysics Data System (ADS)

Hua, H.; Wilson, B. D.; Manipon, G.; Pan, L.; Fetzer, E.

2011-12-01

Multi-decadal climate data records are critical to studying climate variability and change. These often also require merging data from multiple instruments such as those from NASA's A-Train that contain measurements covering a wide range of atmospheric conditions and phenomena. Multi-decadal climate data record of water vapor measurements from sensors on A-Train, operational weather, and other satellites are being assembled from existing data sources, or produced from well-established methods published in peer-reviewed literature. However, the immense volume and inhomogeneity of data often requires an "exploratory computing" approach to product generation where data is processed in a variety of different ways with varying algorithms, parameters, and code changes until an acceptable intermediate product is generated. This process is repeated until a desirable final merged product can be generated. Typically the production legacy is often lost due to the complexity of processing steps that were tried along the way. The data product information associated with source data, processing methods, parameters used, intermediate product outputs, and associated materials are often hidden in each of the trials and scattered throughout the processing system(s). We will discuss methods to help users better capture and explore the production legacy of the data, metadata, ancillary files, code, and computing environment changes used during the production of these merged and multi-sensor data products. By leveraging existing semantic and provenance tools, we can capture sufficient information to enable users to track, perform faceted searches, and visualize the provenance of the products and processing lineage. We will explore if sufficient provenance information can be captured to enable science reproducibility of these climate data records.

Low Cost Multi-Sensor Robot Laser Scanning System and its Accuracy Investigations for Indoor Mapping Application

NASA Astrophysics Data System (ADS)

Chen, C.; Zou, X.; Tian, M.; Li, J.; Wu, W.; Song, Y.; Dai, W.; Yang, B.

2017-11-01

In order to solve the automation of 3D indoor mapping task, a low cost multi-sensor robot laser scanning system is proposed in this paper. The multiple-sensor robot laser scanning system includes a panorama camera, a laser scanner, and an inertial measurement unit and etc., which are calibrated and synchronized together to achieve simultaneously collection of 3D indoor data. Experiments are undertaken in a typical indoor scene and the data generated by the proposed system are compared with ground truth data collected by a TLS scanner showing an accuracy of 99.2% below 0.25 meter, which explains the applicability and precision of the system in indoor mapping applications.

Copper-encapsulated vertically aligned carbon nanotube arrays.

PubMed

Stano, Kelly L; Chapla, Rachel; Carroll, Murphy; Nowak, Joshua; McCord, Marian; Bradford, Philip D

2013-11-13

A new procedure is described for the fabrication of vertically aligned carbon nanotubes (VACNTs) that are decorated, and even completely encapsulated, by a dense network of copper nanoparticles. The process involves the conformal deposition of pyrolytic carbon (Py-C) to stabilize the aligned carbon-nanotube structure during processing. The stabilized arrays are mildly functionalized using oxygen plasma treatment to improve wettability, and they are then infiltrated with an aqueous, supersaturated Cu salt solution. Once dried, the salt forms a stabilizing crystal network throughout the array. After calcination and H2 reduction, Cu nanoparticles are left decorating the CNT surfaces. Studies were carried out to determine the optimal processing parameters to maximize Cu content in the composite. These included the duration of Py-C deposition and system process pressure as well as the implementation of subsequent and multiple Cu salt solution infiltrations. The optimized procedure yielded a nanoscale hybrid material where the anisotropic alignment from the VACNT array was preserved, and the mass of the stabilized arrays was increased by over 24-fold because of the addition of Cu. The procedure has been adapted for other Cu salts and can also be used for other metal salts altogether, including Ni, Co, Fe, and Ag. The resulting composite is ideally suited for application in thermal management devices because of its low density, mechanical integrity, and potentially high thermal conductivity. Additionally, further processing of the material via pressing and sintering can yield consolidated, dense bulk composites.

LSSA (Low-cost Silicon Solar Array) project

NASA Technical Reports Server (NTRS)

1976-01-01

The Photovoltaic Conversion Program was established to find methods of economically generating enough electrical power to meet future requirements. Activities and progress in the following areas are discussed: silicon-refinement processes; silicon-sheet-growth techniques; encapsulants; manufacturing of off-the-shelf solar arrays; and procurement of semistandardized solar arrays.

The Deep Space Network Array

NASA Technical Reports Server (NTRS)

Gatti, Mark S.

2006-01-01

This document is a viewgraph presentation that reviews the costs, and technological processing required to replace the current network of Deep Space Antennas. The concept of using an array for space communications is much less of a concern than the cost of implementing and operating such an array. Within the cost question, the cost uncertainty of the front-end components (repeated n-times) is of most importance. The activities at JPL have focused on both these aspects of the cost. A breadboard array of three antennas at JPL has been the vehicle to perform many investigations into the development of the new DSN. Several pictures of the antennas at JPL are shown.

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification.

PubMed

Zhou, Tao; Li, Zhaofu; Pan, Jianjun

2018-01-27

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively.

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification

PubMed Central

Pan, Jianjun

2018-01-01

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively. PMID:29382073

Field programmable gate array processing of eye-safe all-fiber coherent wind Doppler lidar return signals

NASA Astrophysics Data System (ADS)

Abdelazim, S.; Santoro, D.; Arend, M.; Moshary, F.; Ahmed, S.

2011-11-01

A field deployable all-fiber eye-safe Coherent Doppler LIDAR is being developed at the Optical Remote Sensing Lab at the City College of New York (CCNY) and is designed to monitor wind fields autonomously and continuously in urban settings. Data acquisition is accomplished by sampling lidar return signals at 400 MHz and performing onboard processing using field programmable gate arrays (FPGAs). The FPGA is programmed to accumulate signal information that is used to calculate the power spectrum of the atmospherically back scattered signal. The advantage of using FPGA is that signal processing will be performed at the hardware level, reducing the load on the host computer and allowing for 100% return signal processing. An experimental setup measured wind speeds at ranges of up to 3 km.

Micromirror array nanostructures for anticounterfeiting applications

NASA Astrophysics Data System (ADS)

Lee, Robert A.

2004-06-01

The optical characteristics of pixellated passive micro mirror arrays are derived and applied in the context of their use as reflective optically variable device (OVD) nanostructures for the protection of documents from counterfeiting. The traditional design variables of foil based diffractive OVDs are shown to be able to be mapped to a corresponding set of design parameters for reflective optical micro mirror array (OMMA) devices. The greatly increased depth characteristics of micro mirror array OVDs provides an opportunity for directly printing the OVD microstructure onto the security document in-line with the normal printing process. The micro mirror array OVD architecture therefore eliminates the need for hot stamping foil as the carrier of the OVD information, thereby reducing costs. The origination of micro mirror array devices via a palette based data format and a combination electron beam lithography and photolithography techniques is discussed via an artwork example and experimental tests. Finally the application of the technology to the design of a generic class of devices which have the interesting property of allowing for both application and customer specific OVD image encoding and data encoding at the end user stage of production is described. Because of the end user nature of the image and data encoding process these devices are particularly well suited to ID document applications and for this reason we refer this new OVD concept as biometric OVD technology.

Process Development for Automated Solar Cell and Module Production. Task 4: Automated Array Assembly

NASA Technical Reports Server (NTRS)

1979-01-01

A baseline sequence for the manufacture of solar cell modules was specified. Starting with silicon wafers, the process goes through damage etching, texture etching, junction formation, plasma edge etch, aluminum back surface field formation, and screen printed metallization to produce finished solar cells. The cells were then series connected on a ribbon and bonded into a finished glass tedlar module. A number of steps required additional developmental effort to verify technical and economic feasibility. These steps include texture etching, plasma edge etch, aluminum back surface field formation, array layup and interconnect, and module edge sealing and framing.

Si Wire-Array Solar Cells

NASA Astrophysics Data System (ADS)

Boettcher, Shannon

2010-03-01

Micron-scale Si wire arrays are three-dimensional photovoltaic absorbers that enable orthogonalization of light absorption and carrier collection and hence allow for the utilization of relatively impure Si in efficient solar cell designs. The wire arrays are grown by a vapor-liquid-solid-catalyzed process on a crystalline (111) Si wafer lithographically patterned with an array of metal catalyst particles. Following growth, such arrays can be embedded in polymethyldisiloxane (PDMS) and then peeled from the template growth substrate. The result is an unusual photovoltaic material: a flexible, bendable, wafer-thickness crystalline Si absorber. In this paper I will describe: 1. the growth of high-quality Si wires with controllable doping and the evaluation of their photovoltaic energy-conversion performance using a test electrolyte that forms a rectifying conformal semiconductor-liquid contact 2. the observation of enhanced absorption in wire arrays exceeding the conventional light trapping limits for planar Si cells of equivalent material thickness and 3. single-wire and large-area solid-state Si wire-array solar cell results obtained to date with directions for future cell designs based on optical and device physics. In collaboration with Michael Kelzenberg, Morgan Putnam, Joshua Spurgeon, Daniel Turner-Evans, Emily Warren, Nathan Lewis, and Harry Atwater, California Institute of Technology.

Compressive sensing-based electrostatic sensor array signal processing and exhausted abnormal debris detecting

NASA Astrophysics Data System (ADS)

Tang, Xin; Chen, Zhongsheng; Li, Yue; Yang, Yongmin

2018-05-01

When faults happen at gas path components of gas turbines, some sparsely-distributed and charged debris will be generated and released into the exhaust gas. The debris is called abnormal debris. Electrostatic sensors can detect the debris online and further indicate the faults. It is generally considered that, under a specific working condition, a more serious fault generates more and larger debris, and a piece of larger debris carries more charge. Therefore, the amount and charge of the abnormal debris are important indicators of the fault severity. However, because an electrostatic sensor can only detect the superposed effect on the electrostatic field of all the debris, it can hardly identify the amount and position of the debris. Moreover, because signals of electrostatic sensors depend on not only charge but also position of debris, and the position information is difficult to acquire, measuring debris charge accurately using the electrostatic detecting method is still a technical difficulty. To solve these problems, a hemisphere-shaped electrostatic sensors' circular array (HSESCA) is used, and an array signal processing method based on compressive sensing (CS) is proposed in this paper. To research in a theoretical framework of CS, the measurement model of the HSESCA is discretized into a sparse representation form by meshing. In this way, the amount and charge of the abnormal debris are described as a sparse vector. It is further reconstructed by constraining l1-norm when solving an underdetermined equation. In addition, a pre-processing method based on singular value decomposition and a result calibration method based on weighted-centroid algorithm are applied to ensure the accuracy of the reconstruction. The proposed method is validated by both numerical simulations and experiments. Reconstruction errors, characteristics of the results and some related factors are discussed.

Assessment of Bias in the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Reanalysis Radar-Only Estimate

NASA Astrophysics Data System (ADS)

Nelson, B. R.; Prat, O. P.; Stevens, S. E.; Seo, D. J.; Zhang, J.; Howard, K.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is nearly completed for the period covering from 2001 to 2012. Reanalysis data are available at 1-km and 5-minute resolution. An important step in generating the best possible precipitation data is to assess the bias in the radar-only product. In this work, we use data from a combination of rain gauge networks to assess the bias in the NMQ reanalysis. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network Daily (GHCN-D) are combined for use in the assessment. These rain gauge networks vary in spatial density and temporal resolution. The challenge hence is to optimally utilize them to assess the bias at the finest resolution possible. For initial assessment, we propose to subset the CONUS data in climatologically representative domains, and perform bias assessment using information in the Q2 dataset on precipitation type and phase.

Full image-processing pipeline in field-programmable gate array for a small endoscopic camera

NASA Astrophysics Data System (ADS)

Mostafa, Sheikh Shanawaz; Sousa, L. Natércia; Ferreira, Nuno Fábio; Sousa, Ricardo M.; Santos, Joao; Wäny, Martin; Morgado-Dias, F.

2017-01-01

Endoscopy is an imaging procedure used for diagnosis as well as for some surgical purposes. The camera used for the endoscopy should be small and able to produce a good quality image or video, to reduce discomfort of the patients, and to increase the efficiency of the medical team. To achieve these fundamental goals, a small endoscopy camera with a footprint of 1 mm×1 mm×1.65 mm is used. Due to the physical properties of the sensors and human vision system limitations, different image-processing algorithms, such as noise reduction, demosaicking, and gamma correction, among others, are needed to faithfully reproduce the image or video. A full image-processing pipeline is implemented using a field-programmable gate array (FPGA) to accomplish a high frame rate of 60 fps with minimum processing delay. Along with this, a viewer has also been developed to display and control the image-processing pipeline. The control and data transfer are done by a USB 3.0 end point in the computer. The full developed system achieves real-time processing of the image and fits in a Xilinx Spartan-6LX150 FPGA.

A multi-sensor monitoring system of human physiology and daily activities.

PubMed

Doherty, Sean T; Oh, Paul

2012-04-01

To present the design and pilot test results of a continuous multi-sensor monitoring system of real-world physiological conditions and daily life (activities, travel, exercise, and food consumption), culminating in a Web-based graphical decision-support interface. The system includes a set of wearable sensors wirelessly connected to a "smartphone" with a continuously running software application that compresses and transmits the data to a central server. Sensors include a Global Positioning System (GPS) receiver, electrocardiogram (ECG), three-axis accelerometer, and continuous blood glucose monitor. A food/medicine diary and prompted recall activity diary were also used. The pilot test involved 40 type 2 diabetic patients monitored over a 72-h period. All but three subjects were successfully monitored for the full study period. Smartphones proved to be an effective hub for managing multiple streams of data but required attention to data compression and battery consumption issues. ECG, accelerometer, and blood glucose devices performed adequately as long as subjects wore them. GPS tracking for a full day was feasible, although significant efforts are needed to impute missing data. Activity detection algorithms were successful in identifying activities and trip modes but could benefit by incorporating accelerometer data. The prompted recall diary was an effective tool for augmenting algorithm results, although subjects reported some difficulties with it. The food and medicine diary was completed fully, although end times and medicine dosages were occasionally missing. The unique combination of sensors holds promise for increasing accuracy and reducing burden associated with collecting individual-level activity and physiological data under real-world conditions, but significant data processing issues remain. Such data will provide new opportunities to explore the impacts of human geography and daily lifestyle on health at a fine spatial/temporal scale.

Manufacture of Micromirror Arrays Using a CMOS-MEMS Technique.

PubMed

Kao, Pin-Hsu; Dai, Ching-Liang; Hsu, Cheng-Chih; Wu, Chyan-Chyi

2009-01-01

In this study we used the commercial 0.35 μm CMOS (complementary metal oxide semiconductor) process and simple maskless post-processing to fabricate an array of micromirrors exhibiting high natural frequency. The micromirrors were manufactured from aluminum; the sacrificial layer was silicon dioxide. Because we fabricated the micromirror arrays using the standard CMOS process, they have the potential to be integrated with circuitry on a chip. For post-processing we used an etchant to remove the sacrificial layer and thereby suspend the micromirrors. The micromirror array contained a circular membrane and four fixed beams set symmetrically around and below the circular mirror; these four fan-shaped electrodes controlled the tilting of the micromirror. A MEMS (microelectromechanical system) motion analysis system and a confocal 3D-surface topography were used to characterize the properties and configuration of the micromirror array. Each micromirror could be rotated in four independent directions. Experimentally, we found that the micromirror had a tilting angle of about 2.55° when applying a driving voltage of 40 V. The natural frequency of the micromirrors was 59.1 kHz.

Integrated filter and detector array for spectral imaging

NASA Technical Reports Server (NTRS)

Labaw, Clayton C. (Inventor)

1992-01-01

A spectral imaging system having an integrated filter and photodetector array is disclosed. The filter has narrow transmission bands which vary in frequency along the photodetector array. The frequency variation of the transmission bands is matched to, and aligned with, the frequency variation of a received spectral image. The filter is deposited directly on the photodetector array by a low temperature deposition process. By depositing the filter directly on the photodetector array, permanent alignment is achieved for all temperatures, spectral crosstalk is substantially eliminated, and a high signal to noise ratio is achieved.

DFT algorithms for bit-serial GaAs array processor architectures

NASA Technical Reports Server (NTRS)

Mcmillan, Gary B.

1988-01-01

Systems and Processes Engineering Corporation (SPEC) has developed an innovative array processor architecture for computing Fourier transforms and other commonly used signal processing algorithms. This architecture is designed to extract the highest possible array performance from state-of-the-art GaAs technology. SPEC's architectural design includes a high performance RISC processor implemented in GaAs, along with a Floating Point Coprocessor and a unique Array Communications Coprocessor, also implemented in GaAs technology. Together, these data processors represent the latest in technology, both from an architectural and implementation viewpoint. SPEC has examined numerous algorithms and parallel processing architectures to determine the optimum array processor architecture. SPEC has developed an array processor architecture with integral communications ability to provide maximum node connectivity. The Array Communications Coprocessor embeds communications operations directly in the core of the processor architecture. A Floating Point Coprocessor architecture has been defined that utilizes Bit-Serial arithmetic units, operating at very high frequency, to perform floating point operations. These Bit-Serial devices reduce the device integration level and complexity to a level compatible with state-of-the-art GaAs device technology.

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to

Configuration Considerations for Low Frequency Arrays

NASA Astrophysics Data System (ADS)

Lonsdale, C. J.

2005-12-01

The advance of digital signal processing capabilities has spurred a new effort to exploit the lowest radio frequencies observable from the ground, from ˜10 MHz to a few hundred MHz. Multiple scientifically and technically complementary instruments are planned, including the Mileura Widefield Array (MWA) in the 80-300 MHz range, and the Long Wavelength Array (LWA) in the 20-80 MHz range. The latter instrument will target relatively high angular resolution, and baselines up to a few hundred km. An important practical question for the design of such an array is how to distribute the collecting area on the ground. The answer to this question profoundly affects both cost and performance. In this contribution, the factors which determine the anticipated performance of any such array are examined, paying particular attention to the viability and accuracy of array calibration. It is argued that due to the severity of ionospheric effects in particular, it will be difficult or impossible to achieve routine, high dynamic range imaging with a geographically large low frequency array, unless a large number of physically separate array stations is built. This conclusion is general, is based on the need for adequate sampling of ionospheric irregularities, and is independent of the calibration algorithms and techniques that might be employed. It is further argued that array configuration figures of merit that are traditionally used for higher frequency arrays are inappropriate, and a different set of criteria are proposed.

Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products

NASA Astrophysics Data System (ADS)

Jeong, J.; Baik, J.; Choi, M.

2016-12-01

Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.

Improved chemical identification from sensor arrays using intelligent algorithms

NASA Astrophysics Data System (ADS)

Roppel, Thaddeus A.; Wilson, Denise M.

2001-02-01

Intelligent signal processing algorithms are shown to improve identification rates significantly in chemical sensor arrays. This paper focuses on the use of independently derived sensor status information to modify the processing of sensor array data by using a fast, easily-implemented "best-match" approach to filling in missing sensor data. Most fault conditions of interest (e.g., stuck high, stuck low, sudden jumps, excess noise, etc.) can be detected relatively simply by adjunct data processing, or by on-board circuitry. The objective then is to devise, implement, and test methods for using this information to improve the identification rates in the presence of faulted sensors. In one typical example studied, utilizing separately derived, a-priori knowledge about the health of the sensors in the array improved the chemical identification rate by an artificial neural network from below 10 percent correct to over 99 percent correct. While this study focuses experimentally on chemical sensor arrays, the results are readily extensible to other types of sensor platforms.

Performance comparisons on spatial lattice algorithm and direct matrix inverse method with application to adaptive arrays processing

NASA Technical Reports Server (NTRS)

An, S. H.; Yao, K.

1986-01-01

Lattice algorithm has been employed in numerous adaptive filtering applications such as speech analysis/synthesis, noise canceling, spectral analysis, and channel equalization. In this paper the application to adaptive-array processing is discussed. The advantages are fast convergence rate as well as computational accuracy independent of the noise and interference conditions. The results produced by this technique are compared to those obtained by the direct matrix inverse method.

Next-Generation Microshutter Arrays for Large-Format Imaging and Spectroscopy

NASA Technical Reports Server (NTRS)

Moseley, Samuel; Kutyrev, Alexander; Brown, Ari; Li, Mary

2012-01-01

A next-generation microshutter array, LArge Microshutter Array (LAMA), was developed as a multi-object field selector. LAMA consists of small-scaled microshutter arrays that can be combined to form large-scale microshutter array mosaics. Microshutter actuation is accomplished via electrostatic attraction between the shutter and a counter electrode, and 2D addressing can be accomplished by applying an electrostatic potential between a row of shutters and a column, orthogonal to the row, of counter electrodes. Microelectromechanical system (MEMS) technology is used to fabricate the microshutter arrays. The main feature of the microshutter device is to use a set of standard surface micromachining processes for device fabrication. Electrostatic actuation is used to eliminate the need for macromechanical magnet actuating components. A simplified electrostatic actuation with no macro components (e.g. moving magnets) required for actuation and latching of the shutters will make the microshutter arrays robust and less prone to mechanical failure. Smaller-size individual arrays will help to increase the yield and thus reduce the cost and improve robustness of the fabrication process. Reducing the size of the individual shutter array to about one square inch and building the large-scale mosaics by tiling these smaller-size arrays would further help to reduce the cost of the device due to the higher yield of smaller devices. The LAMA development is based on prior experience acquired while developing microshutter arrays for the James Webb Space Telescope (JWST), but it will have different features. The LAMA modular design permits large-format mosaicking to cover a field of view at least 50 times larger than JWST MSA. The LAMA electrostatic, instead of magnetic, actuation enables operation cycles at least 100 times faster and a mass significantly smaller compared to JWST MSA. Also, standard surface micromachining technology will simplify the fabrication process, increasing

Fabrication and characterization of controllable grain boundary arrays in solution-processed small molecule organic semiconductor films

NASA Astrophysics Data System (ADS)

Wo, Songtao; Headrick, Randall L.; Anthony, John E.

2012-04-01

We have produced solution-processed thin films of 6,13-bis(tri-isopropyl-silylethynyl) pentacene with grain sizes from a few micrometers up to millimeter scale by lateral crystallization from a rectangular stylus. Grains are oriented along the crystallization direction, and the grain size transverse to the crystallization direction depends inversely on the writing speed, hence forming a regular array of oriented grain boundaries with controllable spacing. We utilize these controllable arrays to systematically study the role of large-angle grain boundaries in carrier transport and charge trapping in thin film transistors. The effective mobility scales with the grain size, leading to an estimate of the potential drop at individual large-angle grain boundaries of more than 1 volt. This result indicates that the structure of grain boundaries is not molecularly abrupt, which may be a general feature of solution-processed small molecule organic semiconductor thin films, where relatively high energy grain boundaries are typically formed. Transient measurements after switching from positive to negative gate bias or between large and small negative gate bias reveal reversible charge trapping, with time constants on the order of 10 s and trap densities that are correlated with grain boundary density. We suggest that charge diffusion along grain boundaries and other defects is the rate-determining mechanism of the reversible trapping.

CMOS-micromachined, two-dimenisional transistor arrays for neural recording and stimulation.

PubMed

Lin, J S; Chang, S R; Chang, C H; Lu, S C; Chen, H

2007-01-01

In-plane microelectrode arrays have proven to be useful tools for studying the connectivities and the functions of neural tissues. However, seldom microelectrode arrays are monolithically-integrated with signal-processing circuits, without which the maximum number of electrodes is limited by the compromise with routing complexity and interferences. This paper proposes a CMOS-compatible, two-dimensional array of oxide-semiconductor field-effect transistors(OSFETs), capable of both recording and stimulating neuronal activities. The fabrication of the OSFETs not only requires simply die-level, post-CMOS micromachining process, but also retains metal layers for monolithic integration with signal-processing circuits. A CMOS microsystem containing the OSFET arrays and gain-programmable recording circuits has been fabricated and tested. The preliminary testing results are presented and discussed.

Multi-Sensor Fusion for Enhanced Contextual Awareness of Everyday Activities with Ubiquitous Devices

PubMed Central

Guiry, John J.; van de Ven, Pepijn; Nelson, John

2014-01-01

In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances. PMID:24662406

Multi-sensor fusion for enhanced contextual awareness of everyday activities with ubiquitous devices.

PubMed

Guiry, John J; van de Ven, Pepijn; Nelson, John

2014-03-21

In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances.

Recent progress in the joint multisensor mine-signatures database project

NASA Astrophysics Data System (ADS)

Lewis, Adam M.; Verlinde, Patrick S. A.; Acheroy, Marc P. J.; Sieber, Alois J.

2002-08-01

The MsMs project is a major campaign to collect calibrated and well-documented data, suitable for use by workers developing advanced multisensor algorithms for antipersonnel mine detection. The data, together with a full description of the site layout and measurement protocols, are publicly available via the internet site http://demining.jrc.it/msms. Measurements are made on a test lane consisting of 7 plots of different soils, each 6m by 6m, populated with surrogate mines, calibration objects, simulated clutter and position markers. There are 48 targets in each plot, configured identically for all plots. A first report was presented last year. Since then, laser acoustic vibrometer and magnetometer data have been added and the metal detector and thermal infrared data have been augmented. The database has been reformatted to make it more uniform and user-friendly and to remove typographic mistakes. The test site remains essentially unchanged, apart from some equipment upgrades, and is available for further data collection. In particular, the targets have not been moved, so as to provide stable surrounding soil conditions representative of mines left undisturbed for long periods post-conflict. This presentation will describe the new data and data format, the status of the upgrades and the outlook for the future.

Proposed evaluation framework for assessing operator performance with multisensor displays

NASA Technical Reports Server (NTRS)

Foyle, David C.

1992-01-01

Despite aggressive work on the development of sensor fusion algorithms and techniques, no formal evaluation procedures have been proposed. Based on existing integration models in the literature, an evaluation framework is developed to assess an operator's ability to use multisensor, or sensor fusion, displays. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The operator's performance with the sensor fusion display can be compared to the models' predictions based on the operator's performance when viewing the original sensor displays prior to fusion. This allows for the determination as to when a sensor fusion system leads to: 1) poorer performance than one of the original sensor displays (clearly an undesirable system in which the fused sensor system causes some distortion or interference); 2) better performance than with either single sensor system alone, but at a sub-optimal (compared to the model predictions) level; 3) optimal performance (compared to model predictions); or, 4) super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays. An experiment demonstrating the usefulness of the proposed evaluation framework is discussed.

Automated installation methods for photovoltaic arrays

NASA Astrophysics Data System (ADS)

Briggs, R.; Daniels, A.; Greenaway, R.; Oster, J., Jr.; Racki, D.; Stoeltzing, R.

1982-11-01

Since installation expenses constitute a substantial portion of the cost of a large photovoltaic power system, methods for reduction of these costs were investigated. The installation of the photovoltaic arrays includes all areas, starting with site preparation (i.e., trenching, wiring, drainage, foundation installation, lightning protection, grounding and installation of the panel) and concluding with the termination of the bus at the power conditioner building. To identify the optimum combination of standard installation procedures and automated/mechanized techniques, the installation process was investigated including the equipment and hardware available, the photovoltaic array structure systems and interfaces, and the array field and site characteristics. Preliminary designs of hardware for both the standard installation method, the automated/mechanized method, and a mix of standard installation procedures and mechanized procedures were identified to determine which process effectively reduced installation costs. In addition, costs associated with each type of installation method and with the design, development and fabrication of new installation hardware were generated.

Fabrication of five-level ultraplanar micromirror arrays by flip-chip assembly

NASA Astrophysics Data System (ADS)

Michalicek, M. Adrian; Bright, Victor M.

2001-10-01

This paper reports a detailed study of the fabrication of various piston, torsion, and cantilever style micromirror arrays using a novel, simple, and inexpensive flip-chip assembly technique. Several rectangular and polar arrays were commercially prefabricated in the MUMPs process and then flip-chip bonded to form advanced micromirror arrays where adverse effects typically associated with surface micromachining were removed. These arrays were bonded by directly fusing the MUMPs gold layers with no complex preprocessing. The modules were assembled using a computer-controlled, custom-built flip-chip bonding machine. Topographically opposed bond pads were designed to correct for slight misalignment errors during bonding and typically result in less than 2 micrometers of lateral alignment error. Although flip-chip micromirror performance is briefly discussed, the means used to create these arrays is the focus of the paper. A detailed study of flip-chip process yield is presented which describes the primary failure mechanisms for flip-chip bonding. Studies of alignment tolerance, bonding force, stress concentration, module planarity, bonding machine calibration techniques, prefabrication errors, and release procedures are presented in relation to specific observations in process yield. Ultimately, the standard thermo-compression flip-chip assembly process remains a viable technique to develop highly complex prototypes of advanced micromirror arrays.

Novel fabrication method of microlens arrays with High OLED outcoupling efficiency

NASA Astrophysics Data System (ADS)

Kim, Hyun Soo; Moon, Seong Il; Hwang, Dong Eui; Jeong, Ki Won; Kim, Chang Kyo; Moon, Dae-Gyu; Hong, Chinsoo

2016-03-01

We presented a novel fabrication method of pyramidal and hemispherical polymethylmethacrylate (PMMA) microlens arrays to improve the outcoupling efficiency. Pyramidal microlens arrays were fabricated by replica molding processes using concave-pyramidal silicon molds prepared by the wet etching method. Concave-hemispherical PMMA thin film was used as a template for fabrication of the hemispherical microlens array. The concave-hemispherical PMMA template was prepared by blowing a N2 gas stream onto the thin PMMA film suspended on a silicon pedestal. A PMMA microlens arrays with hemispherical structure were fabricated by a replica molding process. The outcoupling efficiency of the hemispherical microlens array was greater than that of the pyramidal microlens array. The outcoupling efficiency of hemispherical microlens arrays with a higher contact angle was larger than that of those with lower contact angle. This indicates that, for the hemispherical microlens with larger contact angle, more light can be extracted from the OLEDs due to the decrease in the incident angle of the light at the interface between an air and a hemispherical microlens arrays. After attaching a hemispherical microlens array with contact angle of 50.4° onto the OLEDs, the luminance was enhanced by approximately 117%.

Solution-processed, Self-organized Organic Single Crystal Arrays with Controlled Crystal Orientation

PubMed Central

Kumatani, Akichika; Liu, Chuan; Li, Yun; Darmawan, Peter; Takimiya, Kazuo; Minari, Takeo; Tsukagoshi, Kazuhito

2012-01-01

A facile solution process for the fabrication of organic single crystal semiconductor devices which meets the demand for low-cost and large-area fabrication of high performance electronic devices is demonstrated. In this paper, we develop a bottom-up method which enables direct formation of organic semiconductor single crystals at selected locations with desired orientations. Here oriented growth of one-dimensional organic crystals is achieved by using self-assembly of organic molecules as the driving force to align these crystals in patterned regions. Based upon the self-organized organic single crystals, we fabricate organic field effect transistor arrays which exhibit an average field-effect mobility of 1.1 cm2V−1s−1. This method can be carried out under ambient atmosphere at room temperature, thus particularly promising for production of future plastic electronics. PMID:22563523

General MoM Solutions for Large Arrays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fasenfest, B; Capolino, F; Wilton, D R

2003-07-22

This paper focuses on a numerical procedure that addresses the difficulties of dealing with large, finite arrays while preserving the generality and robustness of full-wave methods. We present a fast method based on approximating interactions between sufficiently separated array elements via a relatively coarse interpolation of the Green's function on a uniform grid commensurate with the array's periodicity. The interaction between the basis and testing functions is reduced to a three-stage process. The first stage is a projection of standard (e.g., RWG) subdomain bases onto a set of interpolation functions that interpolate the Green's function on the array face. Thismore » projection, which is used in a matrix/vector product for each array cell in an iterative solution process, need only be carried out once for a single cell and results in a low-rank matrix. An intermediate stage matrix/vector product computation involving the uniformly sampled Green's function is of convolutional form in the lateral (transverse) directions so that a 2D FFT may be used. The final stage is a third matrix/vector product computation involving a matrix resulting from projecting testing functions onto the Green's function interpolation functions; the low-rank matrix is either identical to (using Galerkin's method) or similar to that for the bases projection. An effective MoM solution scheme is developed for large arrays using a modification of the AIM (Adaptive Integral Method) method. The method permits the analysis of arrays with arbitrary contours and nonplanar elements. Both fill and solve times within the MoM method are improved with respect to more standard MoM solvers.« less

A novel multisensor traffic state assessment system based on incomplete data.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

Dynamic multisensor fusion for mobile robot navigation in an indoor environment

NASA Astrophysics Data System (ADS)

Jin, Taeseok; Lee, Jang-Myung; Luk, Bing L.; Tso, Shiu K.

2001-10-01

In this study, as the preliminary step for developing a multi-purpose Autonomous robust carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as sonar, CCD camera dn IR sensor for map-building mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. Smart sensory systems are crucial for successful autonomous systems. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the intelligent service robot project at the Centre of Intelligent Design, Automation & Manufacturing (CIDAM). We will conclude by discussing some possible future extensions of the project. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions recognizing environments updated, obstacle detection and motion assessment, with the first results form the simulations run.

A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system. PMID:25162055

Manufacture of Micromirror Arrays Using a CMOS-MEMS Technique

PubMed Central

Kao, Pin-Hsu; Dai, Ching-Liang; Hsu, Cheng-Chih; Wu, Chyan-Chyi

2009-01-01

In this study we used the commercial 0.35 μm CMOS (complementary metal oxide semiconductor) process and simple maskless post-processing to fabricate an array of micromirrors exhibiting high natural frequency. The micromirrors were manufactured from aluminum; the sacrificial layer was silicon dioxide. Because we fabricated the micromirror arrays using the standard CMOS process, they have the potential to be integrated with circuitry on a chip. For post-processing we used an etchant to remove the sacrificial layer and thereby suspend the micromirrors. The micromirror array contained a circular membrane and four fixed beams set symmetrically around and below the circular mirror; these four fan-shaped electrodes controlled the tilting of the micromirror. A MEMS (microelectromechanical system) motion analysis system and a confocal 3D-surface topography were used to characterize the properties and configuration of the micromirror array. Each micromirror could be rotated in four independent directions. Experimentally, we found that the micromirror had a tilting angle of about 2.55° when applying a driving voltage of 40 V. The natural frequency of the micromirrors was 59.1 kHz. PMID:22454581

Damage Detection in Composite Structures with Wavenumber Array Data Processing

NASA Technical Reports Server (NTRS)

Tian, Zhenhua; Leckey, Cara; Yu, Lingyu

2013-01-01

Guided ultrasonic waves (GUW) have the potential to be an efficient and cost-effective method for rapid damage detection and quantification of large structures. Attractive features include sensitivity to a variety of damage types and the capability of traveling relatively long distances. They have proven to be an efficient approach for crack detection and localization in isotropic materials. However, techniques must be pushed beyond isotropic materials in order to be valid for composite aircraft components. This paper presents our study on GUW propagation and interaction with delamination damage in composite structures using wavenumber array data processing, together with advanced wave propagation simulations. Parallel elastodynamic finite integration technique (EFIT) is used for the example simulations. Multi-dimensional Fourier transform is used to convert time-space wavefield data into frequency-wavenumber domain. Wave propagation in the wavenumber-frequency domain shows clear distinction among the guided wave modes that are present. This allows for extracting a guided wave mode through filtering and reconstruction techniques. Presence of delamination causes spectral change accordingly. Results from 3D CFRP guided wave simulations with delamination damage in flat-plate specimens are used for wave interaction with structural defect study.

Integration of Antibody Array Technology into Drug Discovery and Development.

PubMed

Huang, Wei; Whittaker, Kelly; Zhang, Huihua; Wu, Jian; Zhu, Si-Wei; Huang, Ruo-Pan

Antibody arrays represent a high-throughput technique that enables the parallel detection of multiple proteins with minimal sample volume requirements. In recent years, antibody arrays have been widely used to identify new biomarkers for disease diagnosis or prognosis. Moreover, many academic research laboratories and commercial biotechnology companies are starting to apply antibody arrays in the field of drug discovery. In this review, some technical aspects of antibody array development and the various platforms currently available will be addressed; however, the main focus will be on the discussion of antibody array technologies and their applications in drug discovery. Aspects of the drug discovery process, including target identification, mechanisms of drug resistance, molecular mechanisms of drug action, drug side effects, and the application in clinical trials and in managing patient care, which have been investigated using antibody arrays in recent literature will be examined and the relevance of this technology in progressing this process will be discussed. Protein profiling with antibody array technology, in addition to other applications, has emerged as a successful, novel approach for drug discovery because of the well-known importance of proteins in cell events and disease development.

Backshort-Under-Grid arrays for infrared astronomy

NASA Astrophysics Data System (ADS)

Allen, C. A.; Benford, D. J.; Chervenak, J. A.; Chuss, D. T.; Miller, T. M.; Moseley, S. H.; Staguhn, J. G.; Wollack, E. J.

2006-04-01

We are developing a kilopixel, filled bolometer array for space infrared astronomy. The array consists of three individual components, to be merged into a single, working unit; (1) a transition edge sensor bolometer array, operating in the milliKelvin regime, (2) a quarter-wave backshort grid, and (3) superconducting quantum interference device multiplexer readout. The detector array is designed as a filled, square grid of suspended, silicon bolometers with superconducting sensors. The backshort arrays are fabricated separately and will be positioned in the cavities created behind each detector during fabrication. The grids have a unique interlocking feature machined into the walls for positioning and mechanical stability. The spacing of the backshort beneath the detector grid can be set from ˜30 300 μm, by independently adjusting two process parameters during fabrication. The ultimate goal is to develop a large-format array architecture with background-limited sensitivity, suitable for a wide range of wavelengths and applications, to be directly bump bonded to a multiplexer circuit. We have produced prototype two-dimensional arrays having 8×8 detector elements. We present detector design, fabrication overview, and assembly technologies.

Stretched Lens Array Squarerigger (SLASR) Technology Maturation

NASA Technical Reports Server (NTRS)

O'Neill, Mark; McDanal, A.J.; Howell, Joe; Lollar, Louis; Carrington, Connie; Hoppe, David; Piszczor, Michael; Suszuki, Nantel; Eskenazi, Michael; Aiken, Dan;

2-D Ultrasound Sparse Arrays Multidepth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions.

PubMed

Roux, Emmanuel; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Robini, Marc C; Liebgott, Herve

2016-12-01

Full matrix arrays are excellent tools for 3-D ultrasound imaging, but the required number of active elements is too high to be individually controlled by an equal number of scanner channels. The number of active elements is significantly reduced by the sparse array techniques, but the position of the remaining elements must be carefully optimized. This issue is faced here by introducing novel energy functions in the simulated annealing (SA) algorithm. At each iteration step of the optimization process, one element is freely translated and the associated radiated pattern is simulated. To control the pressure field behavior at multiple depths, three energy functions inspired by the pressure field radiated by a Blackman-tapered spiral array are introduced. Such energy functions aim at limiting the main lobe width while lowering the side lobe and grating lobe levels at multiple depths. Numerical optimization results illustrate the influence of the number of iterations, pressure measurement points, and depths, as well as the influence of the energy function definition on the optimized layout. It is also shown that performance close to or even better than the one provided by a spiral array, here assumed as reference, may be obtained. The finite-time convergence properties of SA allow the duration of the optimization process to be set in advance.

Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

PubMed Central

Kampmann, Peter; Kirchner, Frank

2014-01-01

With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach. PMID:24743158

Optimised 'on demand' protein arraying from DNA by cell free expression with the 'DNA to Protein Array' (DAPA) technology.

PubMed

Schmidt, Ronny; Cook, Elizabeth A; Kastelic, Damjana; Taussig, Michael J; Stoevesandt, Oda

2013-08-02

We have previously described a protein arraying process based on cell free expression from DNA template arrays (DNA Array to Protein Array, DAPA). Here, we have investigated the influence of different array support coatings (Ni-NTA, Epoxy, 3D-Epoxy and Polyethylene glycol methacrylate (PEGMA)). Their optimal combination yields an increased amount of detected protein and an optimised spot morphology on the resulting protein array compared to the previously published protocol. The specificity of protein capture was improved using a tag-specific capture antibody on a protein repellent surface coating. The conditions for protein expression were optimised to yield the maximum amount of protein or the best detection results using specific monoclonal antibodies or a scaffold binder against the expressed targets. The optimised DAPA system was able to increase by threefold the expression of a representative model protein while conserving recognition by a specific antibody. The amount of expressed protein in DAPA was comparable to those of classically spotted protein arrays. Reaction conditions can be tailored to suit the application of interest. DAPA represents a cost effective, easy and convenient way of producing protein arrays on demand. The reported work is expected to facilitate the application of DAPA for personalized medicine and screening purposes. Copyright © 2013 Elsevier B.V. All rights reserved.

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

PubMed

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-08-04

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

Design and Fabrication Highlights Enabling a 2 mm, 128 Element Bolometer Array for GISMO

NASA Technical Reports Server (NTRS)

Allen, Christine; Benford, Dominic; Miller, Timothy; Staguhn, Johannes; Wollack, Edward; Moseley, Harvey

2007-01-01

The Backshort-Under-Grid (BUG) superconducting bolometer array architecture is intended to be highly versatile, operating in a large range of wavelengths and background conditions. We have undertaken a three-year program to develop key technologies and processes required to build kilopixel arrays. To validate the basic array design and to demonstrate its applicability for future kilopixel arrays, we have chosen to demonstrate a 128 element bolometer array optimized for 2 mm wavelength using a newly built Goddard instrument, GISMO (Goddard /RAM Superconducting 2-millimeter Observer). The arrays are fabricated using batch wafer processing developed and optimized for high pixel yield, low noise, and high uniformity. The molybdenum-gold superconducting transition edge sensors are fabricated using batch sputter deposition and are patterned using dry etch techniques developed at Goddard. With a detector pitch of 2 mm 8x16 array for GISMO occupies nearly one half of the processing area of a 100 mm silicon-on-insulator starting wafer. Two such arrays are produced from a single wafer along with witness samples for process characterization. To provide thermal isolation for the detector elements, at the end of the process over 90% of the silicon must be removed using deep reactive ion etching techniques. The electrical connections for each bolometer element are patterned on the top edge of the square grid supporting the array. The design considerations unique to GISMO, key fabrication challenges, and laboratory experimental results will be presented.

rasdaman Array Database: current status

NASA Astrophysics Data System (ADS)

Merticariu, George; Toader, Alexandru

2015-04-01

rasdaman (Raster Data Manager) is a Free Open Source Array Database Management System which provides functionality for storing and processing massive amounts of raster data in the form of multidimensional arrays. The user can access, process and delete the data using SQL. The key features of rasdaman are: flexibility (datasets of any dimensionality can be processed with the help of SQL queries), scalability (rasdaman's distributed architecture enables it to seamlessly run on cloud infrastructures while offering an increase in performance with the increase of computation resources), performance (real-time access, processing, mixing and filtering of arrays of any dimensionality) and reliability (legacy communication protocol replaced with a new one based on cutting edge technology - Google Protocol Buffers and ZeroMQ). Among the data with which the system works, we can count 1D time series, 2D remote sensing imagery, 3D image time series, 3D geophysical data, and 4D atmospheric and climate data. Most of these representations cannot be stored only in the form of raw arrays, as the location information of the contents is also important for having a correct geoposition on Earth. This is defined by ISO 19123 as coverage data. rasdaman provides coverage data support through the Petascope service. Extensions were added on top of rasdaman in order to provide support for the Geoscience community. The following OGC standards are currently supported: Web Map Service (WMS), Web Coverage Service (WCS), and Web Coverage Processing Service (WCPS). The Web Map Service is an extension which provides zoom and pan navigation over images provided by a map server. Starting with version 9.1, rasdaman supports WMS version 1.3. The Web Coverage Service provides capabilities for downloading multi-dimensional coverage data. Support is also provided for several extensions of this service: Subsetting Extension, Scaling Extension, and, starting with version 9.1, Transaction Extension, which

Imaging Arrays With Improved Transmit Power Capability

PubMed Central

Zipparo, Michael J.; Bing, Kristin F.; Nightingale, Kathy R.

2010-01-01

Bonded multilayer ceramics and composites incorporating low-loss piezoceramics have been applied to arrays for ultrasound imaging to improve acoustic transmit power levels and to reduce internal heating. Commercially available hard PZT from multiple vendors has been characterized for microstructure, ability to be processed, and electroacoustic properties. Multilayers using the best materials demonstrate the tradeoffs compared with the softer PZT5-H typically used for imaging arrays. Three-layer PZT4 composites exhibit an effective dielectric constant that is three times that of single layer PZT5H, a 50% higher mechanical Q, a 30% lower acoustic impedance, and only a 10% lower coupling coefficient. Application of low-loss multilayers to linear phased and large curved arrays results in equivalent or better element performance. A 3-layer PZT4 composite array achieved the same transmit intensity at 40% lower transmit voltage and with a 35% lower face temperature increase than the PZT-5 control. Although B-mode images show similar quality, acoustic radiation force impulse (ARFI) images show increased displacement for a given drive voltage. An increased failure rate for the multilayers following extended operation indicates that further development of the bond process will be necessary. In conclusion, bonded multilayer ceramics and composites allow additional design freedom to optimize arrays and improve the overall performance for increased acoustic output while maintaining image quality. PMID:20875996

Magnetic arrays

DOEpatents

Trumper, David L.; Kim, Won-jong; Williams, Mark E.

1997-05-20

Electromagnet arrays which can provide selected field patterns in either two or three dimensions, and in particular, which can provide single-sided field patterns in two or three dimensions. These features are achieved by providing arrays which have current densities that vary in the windings both parallel to the array and in the direction of array thickness.

Parametric study of two planar high power flexible solar array concepts

NASA Technical Reports Server (NTRS)

Garba, J. A.; Kudija, D. A.; Zeldin, B.; Costogue, E. N.

1978-01-01

The design parameters examined were: frequency, aspect ratio, packaging constraints, and array blanket flatness. Specific power-to-mass ratios for both solar arrays as a function of array frequency and array width were developed and plotted. Summaries of the baseline design data, developed equations, the computer program operation, plots of the parameters, and the process for using the information as a design manual are presented.

Big data challenges for large radio arrays

NASA Astrophysics Data System (ADS)

Jones, D. L.; Wagstaff, K.; Thompson, D. R.; D'Addario, L.; Navarro, R.; Mattmann, C.; Majid, W.; Lazio, J.; Preston, J.; Rebbapragada, U.

2012-03-01

Future large radio astronomy arrays, particularly the Square Kilometre Array (SKA), will be able to generate data at rates far higher than can be analyzed or stored affordably with current practices. This is, by definition, a "big data" problem, and requires an end-to-end solution if future radio arrays are to reach their full scientific potential. Similar data processing, transport, storage, and management challenges face next-generation facilities in many other fields. The Jet Propulsion Laboratory is developing technologies to address big data issues, with an emphasis in three areas: 1) Lower-power digital processing architectures to make highvolume data generation operationally affordable, 2) Date-adaptive machine learning algorithms for real-time analysis (or "data triage") of large data volumes, and 3) Scalable data archive systems that allow efficient data mining and remote user code to run locally where the data are stored.

Magnetic arrays

DOEpatents

Trumper, D.L.; Kim, W.; Williams, M.E.

1997-05-20

Electromagnet arrays are disclosed which can provide selected field patterns in either two or three dimensions, and in particular, which can provide single-sided field patterns in two or three dimensions. These features are achieved by providing arrays which have current densities that vary in the windings both parallel to the array and in the direction of array thickness. 12 figs.

CMOS array design automation techniques. [metal oxide semiconductors

NASA Technical Reports Server (NTRS)

Ramondetta, P.; Feller, A.; Noto, R.; Lombardi, T.

1975-01-01

A low cost, quick turnaround technique for generating custom metal oxide semiconductor arrays using the standard cell approach was developed, implemented, tested and validated. Basic cell design topology and guidelines are defined based on an extensive analysis that includes circuit, layout, process, array topology and required performance considerations particularly high circuit speed.

Array Automated Assembly Task Low Cost Silicon Solar Array Project, Phase 2

NASA Technical Reports Server (NTRS)

Rhee, S. S.; Jones, G. T.; Allison, K. L.

1978-01-01

Progress in the development of solar cells and module process steps for low-cost solar arrays is reported. Specific topics covered include: (1) a system to automatically measure solar cell electrical performance parameters; (2) automation of wafer surface preparation, printing, and plating; (3) laser inspection of mechanical defects of solar cells; and (4) a silicon antireflection coating system. Two solar cell process steps, laser trimming and holing automation and spray-on dopant junction formation, are described.

Direct write of microlens array using digital projection photopolymerization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu Yi; Chen Shaochen

Microlens array is a key element in the field of information processing, optoelectronics, and integrated optics. Many existing fabrication processes remain expensive and complicated even though relatively low-cost replication processes have been developed. Here, we demonstrate the fabrication of microlens arrays through projection photopolymerization using a digital micromirror device (DMD) as a dynamic photomask. The DMD projects grayscale images, which are designed in a computer, onto a photocurable resin. The resin is then solidified with its thickness determined by a grayscale ultraviolet light and exposure time. Therefore, various geometries can be formed in a single-step, massively parallel fashion. We presentmore » microlens arrays made of acrylate-based polymer precursor. The physical and optical characteristics of the resulting lenses suggest that this fabrication technique is potentially suitable for applications in integrated optics.« less

A mobile ferromagnetic shape detection sensor using a Hall sensor array and magnetic imaging.

PubMed

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a mobile Hall sensor array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the mobile Hall sensor array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of mobile Hall sensor array system for actual shape detection. The results prove that the mobile Hall sensor array system is able to perform magnetic imaging in identifying various ferromagnetic materials.

A Mobile Ferromagnetic Shape Detection Sensor Using a Hall Sensor Array and Magnetic Imaging

PubMed Central

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a Mobile Hall Sensor Array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the Mobile Hall Sensor Array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of Mobile Hall Sensor Array system for actual shape detection. The results prove that the Mobile Hall Sensor Array system is able to perform magnetic imaging in identifying various ferromagnetic materials. PMID:22346653

Multilevel photonic modules for millimeter-wave phased-array antennas

NASA Astrophysics Data System (ADS)

Paolella, Arthur C.; Bauerle, Athena; Joshi, Abhay M.; Wright, James G.; Coryell, Louis A.

2000-09-01

Millimeter wave phased array systems have antenna element sizes and spacings similar to MMIC chip dimensions by virtue of the operating wavelength. Designing modules in traditional planar packaing techniques are therefore difficult to implement. An advantageous way to maintain a small module footprint compatible with Ka-Band and high frequency systems is to take advantage of two leading edge technologies, opto- electronic integrated circuits (OEICs) and multilevel packaging technology. Under a Phase II SBIR these technologies are combined to form photonic modules for optically controlled millimeter wave phased array antennas. The proposed module, consisting of an OEIC integrated with a planar antenna array will operate on the 40GHz region. The OEIC consists of an InP based dual-depletion PIN photodetector and distributed amplifier. The multi-level module will be fabricated using an enhanced circuit processing thick film process. Since the modules are batch fabricated using an enhanced circuit processing thick film process. Since the modules are batch fabricated, using standard commercial processes, it has the potential to be low cost while maintaining high performance, impacting both military and commercial communications systems.

Optical Design of Segmented Hexagon Array Solar Mirror

NASA Technical Reports Server (NTRS)

Huegele, Vince

2000-01-01

A segmented array of mirrors was designed for a solar concentrator test stand at MSFC for firing solar thermal propulsion engines. The 144 mirrors each have a spherical surface to approximate a parabolic concentrator when combined into the entire 18-foot diameter array. The mirror segments are aluminum hexagons that had the surface diamond turned and quartz coated. The array focuses sunlight reflected from a heliostat to a 4 inch diameter spot containing 10 kw of power at the 15-foot focal point. The derivation of the surface figure for the respective mirror elements is shown. The alignment process of the array is discussed and test results of the system's performance is given.

Optically interconnected phased arrays

NASA Technical Reports Server (NTRS)

Bhasin, Kul B.; Kunath, Richard R.

1988-01-01

Phased-array antennas are required for many future NASA missions. They will provide agile electronic beam forming for communications and tracking in the range of 1 to 100 GHz. Such phased arrays are expected to use several hundred GaAs monolithic integrated circuits (MMICs) as transmitting and receiving elements. However, the interconnections of these elements by conventional coaxial cables and waveguides add weight, reduce flexibility, and increase electrical interference. Alternative interconnections based on optical fibers, optical processing, and holography are under evaluation as possible solutions. In this paper, the current status of these techniques is described. Since high-frequency optical components such as photodetectors, lasers, and modulators are key elements in these interconnections, their performance and limitations are discussed.

Nanocylinder arrays

DOEpatents

Tuominen, Mark; Schotter, Joerg; Thurn-Albrecht, Thomas; Russell, Thomas P.

2007-03-13

Pathways to rapid and reliable fabrication of nanocylinder arrays are provided. Simple methods are described for the production of well-ordered arrays of nanopores, nanowires, and other materials. This is accomplished by orienting copolymer films and removing a component from the film to produce nanopores, that in turn, can be filled with materials to produce the arrays. The resulting arrays can be used to produce nanoscale media, devices, and systems.

Nanocylinder arrays

DOEpatents

Tuominen, Mark [Shutesbury, MA; Schotter, Joerg [Bielefeld, DE; Thurn-Albrecht, Thomas [Freiburg, DE; Russell, Thomas P [Amherst, MA

2009-08-11

Pathways to rapid and reliable fabrication of nanocylinder arrays are provided. Simple methods are described for the production of well-ordered arrays of nanopores, nanowires, and other materials. This is accomplished by orienting copolymer films and removing a component from the film to produce nanopores, that in turn, can be filled with materials to produce the arrays. The resulting arrays can be used to produce nanoscale media, devices, and systems.

Swallow segmentation with artificial neural networks and multi-sensor fusion.

PubMed

Lee, Joon; Steele, Catriona M; Chau, Tom

2009-11-01

Swallow segmentation is a critical precursory step to the analysis of swallowing signal characteristics. In an effort to automatically segment swallows, we investigated artificial neural networks (ANN) with information from cervical dual-axis accelerometry, submental MMG, and nasal airflow. Our objectives were (1) to investigate the relationship between segmentation performance and the number of signal sources and (2) to identify the signals or signal combinations most useful for swallow segmentation. Signals were acquired from 17 healthy adults in both discrete and continuous swallowing tasks using five stimuli. Training and test feature vectors were constructed with variances from single or multiple signals, estimated within 200 ms moving windows with 50% overlap. Corresponding binary target labels (swallow or non-swallow) were derived by manual segmentation. A separate 3-layer ANN was trained for each participant-signal combination, and all possible signal combinations were investigated. As more signal sources were included, segmentation performance improved in terms of sensitivity, specificity, accuracy, and adjusted accuracy. The combination of all four signal sources achieved the highest mean accuracy and adjusted accuracy of 88.5% and 89.6%, respectively. A-P accelerometry proved to be the most discriminatory source, while the inclusion of MMG or nasal airflow resulted in the least performance improvement. These findings suggest that an ANN, multi-sensor fusion approach to segmentation is worthy of further investigation in swallowing studies.

Process Development of Gallium Nitride Phosphide Core-Shell Nanowire Array Solar Cell

NASA Astrophysics Data System (ADS)

Chuang, Chen

Dilute Nitride GaNP is a promising materials for opto-electronic applications due to its band gap tunability. The efficiency of GaNxP1-x /GaNyP1-y core-shell nanowire solar cell (NWSC) is expected to reach as high as 44% by 1% N and 9% N in the core and shell, respectively. By developing such high efficiency NWSCs on silicon substrate, a further reduction of the cost of solar photovoltaic can be further reduced to 61$/MWh, which is competitive to levelized cost of electricity (LCOE) of fossil fuels. Therefore, a suitable NWSC structure and fabrication process need to be developed to achieve this promising NWSC. This thesis is devoted to the study on the development of fabrication process of GaNxP 1-x/GaNyP1-y core-shell Nanowire solar cell. The thesis is divided into two major parts. In the first parts, previously grown GaP/GaNyP1-y core-shell nanowire samples are used to develop the fabrication process of Gallium Nitride Phosphide nanowire solar cell. The design for nanowire arrays, passivation layer, polymeric filler spacer, transparent col- lecting layer and metal contact are discussed and fabricated. The property of these NWSCs are also characterized to point out the future development of Gal- lium Nitride Phosphide NWSC. In the second part, a nano-hole template made by nanosphere lithography is studied for selective area growth of nanowires to improve the structure of core-shell NWSC. The fabrication process of nano-hole templates and the results are presented. To have a consistent features of nano-hole tem- plate, the Taguchi Method is used to optimize the fabrication process of nano-hole templates.

Nonvolatile programmable neural network synaptic array

NASA Technical Reports Server (NTRS)

Tawel, Raoul (Inventor)

1994-01-01

A floating-gate metal oxide semiconductor (MOS) transistor is implemented for use as a nonvolatile analog storage element of a synaptic cell used to implement an array of processing synaptic cells. These cells are based on a four-quadrant analog multiplier requiring both X and Y differential inputs, where one Y input is UV programmable. These nonvolatile synaptic cells are disclosed fully connected in a 32 x 32 synaptic cell array using standard very large scale integration (VLSI) complementary MOS (CMOS) technology.

Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Heymsfield, A.; Newman Frey, K.; Davis, R.; Rapp, J.; Bansemer, A.; Coon, T.; Folsom, R.; Pfeufer, N.; Kalloor, J.

2017-12-01

Cloud radiative feedback mechanisms are one of the largest sources of uncertainty in global climate models. Variations in local 3D cloud structure impact the interpretation of NASA CERES and MODIS data for top-of-atmosphere radiation studies over clouds. Much of this uncertainty results from lack of knowledge of cloud vertical and horizontal structure. Surface-based data on 3-D cloud structure from a multi-sensor array of low-latency ground-based cameras can be used to intercompare radiative transfer models based on MODIS and other satellite data with CERES data to improve the 3-D cloud parameterizations. Closely related, forecasting of solar insolation and associated cloud cover on time scales out to 1 hour and with spatial resolution of 100 meters is valuable for stabilizing power grids with high solar photovoltaic penetrations. Data for cloud-advection based solar insolation forecasting with requisite spatial resolution and latency needed to predict high ramp rate events obtained from a bottom-up perspective is strongly correlated with cloud-induced fluctuations. The development of grid management practices for improved integration of renewable solar energy thus also benefits from a multi-sensor camera array. The data needs for both 3D cloud radiation modelling and solar forecasting are being addressed using a network of low-cost upward-looking visible light CCD sky cameras positioned at 2 km spacing over an area of 30-60 km in size acquiring imagery on 30 second intervals. Such cameras can be manufactured in quantity and deployed by citizen volunteers at a marginal cost of 200-400 and operated unattended using existing communications infrastructure. A trial phase to understand the potential utility of up-looking multi-sensor visible imagery is underway within this NASA Citizen Science project. To develop the initial data sets necessary to optimally design a multi-sensor cloud camera array a team of 100 citizen scientists using self-owned PDA cameras is being

Developing infrared array controller with software real time operating system

NASA Astrophysics Data System (ADS)

Sako, Shigeyuki; Miyata, Takashi; Nakamura, Tomohiko; Motohara, Kentaro; Uchimoto, Yuka Katsuno; Onaka, Takashi; Kataza, Hirokazu

2008-07-01

Real-time capabilities are required for a controller of a large format array to reduce a dead-time attributed by readout and data transfer. The real-time processing has been achieved by dedicated processors including DSP, CPLD, and FPGA devices. However, the dedicated processors have problems with memory resources, inflexibility, and high cost. Meanwhile, a recent PC has sufficient resources of CPUs and memories to control the infrared array and to process a large amount of frame data in real-time. In this study, we have developed an infrared array controller with a software real-time operating system (RTOS) instead of the dedicated processors. A Linux PC equipped with a RTAI extension and a dual-core CPU is used as a main computer, and one of the CPU cores is allocated to the real-time processing. A digital I/O board with DMA functions is used for an I/O interface. The signal-processing cores are integrated in the OS kernel as a real-time driver module, which is composed of two virtual devices of the clock processor and the frame processor tasks. The array controller with the RTOS realizes complicated operations easily, flexibly, and at a low cost.

LSSA (Low-cost Silicon Solar Array) project

NASA Technical Reports Server (NTRS)

1976-01-01

Methods are explored for economically generating electrical power to meet future requirements. The Low-Cost Silicon Solar Array Project (LSSA) was established to reduce the price of solar arrays by improving manufacturing technology, adapting mass production techniques, and promoting user acceptance. The new manufacturing technology includes the consideration of new silicon refinement processes, silicon sheet growth techniques, encapsulants, and automated assembly production being developed under contract by industries and universities.

Multi-sensor fusion of Landsat 8 thermal infrared (TIR) and panchromatic (PAN) images.

PubMed

Jung, Hyung-Sup; Park, Sung-Whan

2014-12-18

Data fusion is defined as the combination of data from multiple sensors such that the resulting information is better than would be possible when the sensors are used individually. The multi-sensor fusion of panchromatic (PAN) and thermal infrared (TIR) images is a good example of this data fusion. While a PAN image has higher spatial resolution, a TIR one has lower spatial resolution. In this study, we have proposed an efficient method to fuse Landsat 8 PAN and TIR images using an optimal scaling factor in order to control the trade-off between the spatial details and the thermal information. We have compared the fused images created from different scaling factors and then tested the performance of the proposed method at urban and rural test areas. The test results show that the proposed method merges the spatial resolution of PAN image and the temperature information of TIR image efficiently. The proposed method may be applied to detect lava flows of volcanic activity, radioactive exposure of nuclear power plants, and surface temperature change with respect to land-use change.

Game Design to Measure Reflexes and Attention Based on Biofeedback Multi-Sensor Interaction

PubMed Central

Ortiz-Vigon Uriarte, Inigo de Loyola; Garcia-Zapirain, Begonya; Garcia-Chimeno, Yolanda

2015-01-01

This paper presents a multi-sensor system for implementing biofeedback as a human-computer interaction technique in a game involving driving cars in risky situations. The sensors used are: Eye Tracker, Kinect, pulsometer, respirometer, electromiography (EMG) and galvanic skin resistance (GSR). An algorithm has been designed which gives rise to an interaction logic with the game according to the set of physiological constants obtained from the sensors. The results reflect a 72.333 response to the System Usability Scale (SUS), a significant difference of p = 0.026 in GSR values in terms of the difference between the start and end of the game, and an r = 0.659 and p = 0.008 correlation while playing with the Kinect between the breathing level and the energy and joy factor. All the sensors used had an impact on the end results, whereby none of them should be disregarded in future lines of research, even though it would be interesting to obtain separate breathing values from that of the cardio. PMID:25789493

Security enhancement of optical encryption based on biometric array keys

NASA Astrophysics Data System (ADS)

Yan, Aimin; Wei, Yang; Zhang, Jingtao

2018-07-01

A novel optical image encryption method is proposed by using Dammann grating and biometric array keys. Dammann grating is utilized to create a 2D finite uniform-intensity spot array. In encryption, a fingerprint array is used as private encryption keys. An original image can be encrypted by a scanning Fresnel zone plate array. Encrypted signals are processed by an optical coherent heterodyne detection system. Biometric array keys and optical scanning cryptography are integrated with each other to enhance information security greatly. Numerical simulations are performed to demonstrate the feasibility and validity of this method. Analyses on key sensitivity and the resistance against to possible attacks are provided.

Noncontact Microembossing Technology for Fabricating Thermoplastic Optical Polymer Microlens Array Sheets

PubMed Central

Chang, Xuefeng; Ge, Xiaohong; Li, Hui

2014-01-01

Thermoplastic optical polymers have replaced traditional optical glass for many applications, due to their superior optical performance, mechanical characteristics, low cost, and efficient production process. This paper investigates noncontact microembossing technology used for producing microlens arrays made out of PMMA (polymethyl methacrylate), PS (polyStyrene), and PC (polycarbonate) from a quartz mold, with microhole arrays. An array of planoconvex microlenses are formed because of surface tension caused by applying pressure to the edge of a hole at a certain glass transition temperature. We studied the principle of noncontact microembossing techniques using finite element analysis, in addition to the thermal and mechanical properties of the three polymers. Then, the independently developed hot-embossing equipment was used to fabricate microlens arrays on PMMA, PS, and PC sheets. This is a promising technique for fabricating diverse thermoplastic optical polymer microlens array sheets, with a simple technological process and low production costs. PMID:25162063

Dynamical analysis of surface-insulated planar wire array Z-pinches

NASA Astrophysics Data System (ADS)

Li, Yang; Sheng, Liang; Hei, Dongwei; Li, Xingwen; Zhang, Jinhai; Li, Mo; Qiu, Aici

2018-05-01

The ablation and implosion dynamics of planar wire array Z-pinches with and without surface insulation are compared and discussed in this paper. This paper first presents a phenomenological model named the ablation and cascade snowplow implosion (ACSI) model, which accounts for the ablation and implosion phases of a planar wire array Z-pinch in a single simulation. The comparison between experimental data and simulation results shows that the ACSI model could give a fairly good description about the dynamical characteristics of planar wire array Z-pinches. Surface insulation introduces notable differences in the ablation phase of planar wire array Z-pinches. The ablation phase is divided into two stages: insulation layer ablation and tungsten wire ablation. The two-stage ablation process of insulated wires is simulated in the ACSI model by updating the formulas describing the ablation process.

Fiber-optic hydrophone array for acoustic surveillance in the littoral

NASA Astrophysics Data System (ADS)

Hill, David; Nash, Phillip

2005-05-01

We describe a fibre-optic hydrophone array system architecture that can be tailored to meet the underwater acoustic surveillance requirements of the military, counter terrorist and customs authorities in protecting ports and harbours, offshore production facilities or coastal approaches. Physically the fibre-optic hydrophone array is in the form of a lightweight cable, enabling rapid deployment from a small vessel. Based upon an optical architecture of time and wavelength multiplexed interferometric hydrophones, the array is comprised of a series of hydrophone sub-arrays. Using multiple sub-arrays, extended perimeters many tens of kilometres in length can be monitored. Interrogated via a long (~50km) optical fibre data link, the acoustic date is processed using the latest open architecture sonar processing platform, ensuring that acoustic targets below, on and above the surface are detected, tracked and classified. Results obtained from an at sea trial of a 96-channel hydrophone array are given, showing the passive detection and tracking of a diver, small surface craft and big ocean going ships beyond the horizon. Furthermore, we describe how the OptaMarine fibre-optic hydrophone array fits into an integrated multi-layered approach to port and harbour security consisting of active sonar for diver detection and hull imaging, as well as thermal imaging and CCTV for surface monitoring. Finally, we briefly describe a complimentary land perimeter intruder detection system consisting of an array of fibre optic accelerometers.

Processing and characterization of high resolution GaN/InGaN LED arrays at 10 micron pitch for micro display applications

NASA Astrophysics Data System (ADS)

Dupré, Ludovic; Marra, Marjorie; Verney, Valentin; Aventurier, Bernard; Henry, Franck; Olivier, François; Tirano, Sauveur; Daami, Anis; Templier, François

2017-02-01

We report the fabrication process and characterization of high resolution 873 x 500 pixels emissive arrays based on blue or green GaN/InGaN light emitting diodes (LEDs) at a reduced pixel pitch of 10 μm. A self-aligned process along with a combination of damascene metallization steps is presented as the key to create a common cathode which is expected to provide good thermal dissipation and prevent voltage drops between center and side of the micro LED matrix. We will discuss the challenges of a self-aligned technology related to the choice of a good P contact metal and will present our solutions for the realization of the metallic interconnections between the GaN contacts and the higher levels of metallization at such a small pixel pitch. Enhanced control of each technological step allows scalability of the process up to 4 inch LED wafers and production of high quality LED arrays. The very high brightness (up to 107 cd.m-2) and good external quantum efficiency (EQE) of the resulting device make these kind of micro displays suitable for augmented reality or head up display applications.

Indoor Multi-Sensor Acquisition System for Projects on Energy Renovation of Buildings.

PubMed

Armesto, Julia; Sánchez-Villanueva, Claudio; Patiño-Cambeiro, Faustino; Patiño-Barbeito, Faustino

2016-05-28

Energy rehabilitation actions in buildings have become a great economic opportunity for the construction sector. They also constitute a strategic goal in the European Union (EU), given the energy dependence and the compromises with climate change of its member states. About 75% of existing buildings in the EU were built when energy efficiency codes had not been developed. Approximately 75% to 90% of those standing buildings are expected to remain in use in 2050. Significant advances have been achieved in energy analysis, simulation tools, and computer fluid dynamics for building energy evaluation. However, the gap between predictions and real savings might still be improved. Geomatics and computer science disciplines can really help in modelling, inspection, and diagnosis procedures. This paper presents a multi-sensor acquisition system capable of automatically and simultaneously capturing the three-dimensional geometric information, thermographic, optical, and panoramic images, ambient temperature map, relative humidity map, and light level map. The system integrates a navigation system based on a Simultaneous Localization and Mapping (SLAM) approach that allows georeferencing every data to its position in the building. The described equipment optimizes the energy inspection and diagnosis steps and facilitates the energy modelling of the building.

Indoor Multi-Sensor Acquisition System for Projects on Energy Renovation of Buildings

PubMed Central

Armesto, Julia; Sánchez-Villanueva, Claudio; Patiño-Cambeiro, Faustino; Patiño-Barbeito, Faustino

2016-01-01

Energy rehabilitation actions in buildings have become a great economic opportunity for the construction sector. They also constitute a strategic goal in the European Union (EU), given the energy dependence and the compromises with climate change of its member states. About 75% of existing buildings in the EU were built when energy efficiency codes had not been developed. Approximately 75% to 90% of those standing buildings are expected to remain in use in 2050. Significant advances have been achieved in energy analysis, simulation tools, and computer fluid dynamics for building energy evaluation. However, the gap between predictions and real savings might still be improved. Geomatics and computer science disciplines can really help in modelling, inspection, and diagnosis procedures. This paper presents a multi-sensor acquisition system capable of automatically and simultaneously capturing the three-dimensional geometric information, thermographic, optical, and panoramic images, ambient temperature map, relative humidity map, and light level map. The system integrates a navigation system based on a Simultaneous Localization and Mapping (SLAM) approach that allows georeferencing every data to its position in the building. The described equipment optimizes the energy inspection and diagnosis steps and facilitates the energy modelling of the building. PMID:27240379

A novel framework for feature extraction in multi-sensor action potential sorting.

PubMed

Wu, Shun-Chi; Swindlehurst, A Lee; Nenadic, Zoran

2015-09-30

Extracellular recordings of multi-unit neural activity have become indispensable in neuroscience research. The analysis of the recordings begins with the detection of the action potentials (APs), followed by a classification step where each AP is associated with a given neural source. A feature extraction step is required prior to classification in order to reduce the dimensionality of the data and the impact of noise, allowing source clustering algorithms to work more efficiently. In this paper, we propose a novel framework for multi-sensor AP feature extraction based on the so-called Matched Subspace Detector (MSD), which is shown to be a natural generalization of standard single-sensor algorithms. Clustering using both simulated data and real AP recordings taken in the locust antennal lobe demonstrates that the proposed approach yields features that are discriminatory and lead to promising results. Unlike existing methods, the proposed algorithm finds joint spatio-temporal feature vectors that match the dominant subspace observed in the two-dimensional data without needs for a forward propagation model and AP templates. The proposed MSD approach provides more discriminatory features for unsupervised AP sorting applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Information-based approach to performance estimation and requirements allocation in multisensor fusion for target recognition

NASA Astrophysics Data System (ADS)

Harney, Robert C.

1997-03-01

A novel methodology offering the potential for resolving two of the significant problems of implementing multisensor target recognition systems, i.e., the rational selection of a specific sensor suite and optimal allocation of requirements among sensors, is presented. Based on a sequence of conjectures (and their supporting arguments) concerning the relationship of extractable information content to recognition performance of a sensor system, a set of heuristics (essentially a reformulation of Johnson's criteria applicable to all sensor and data types) is developed. An approach to quantifying the information content of sensor data is described. Coupling this approach with the widely accepted Johnson's criteria for target recognition capabilities results in a quantitative method for comparing the target recognition ability of diverse sensors (imagers, nonimagers, active, passive, electromagnetic, acoustic, etc.). Extension to describing the performance of multiple sensors is straightforward. The application of the technique to sensor selection and requirements allocation is discussed.

Coherent-subspace array processing based on wavelet covariance: an application to broad-band, seismo-volcanic signals

NASA Astrophysics Data System (ADS)

Saccorotti, G.; Nisii, V.; Del Pezzo, E.

2008-07-01

Long-Period (LP) and Very-Long-Period (VLP) signals are the most characteristic seismic signature of volcano dynamics, and provide important information about the physical processes occurring in magmatic and hydrothermal systems. These events are usually characterized by sharp spectral peaks, which may span several frequency decades, by emergent onsets, and by a lack of clear S-wave arrivals. These two latter features make both signal detection and location a challenging task. In this paper, we propose a processing procedure based on Continuous Wavelet Transform of multichannel, broad-band data to simultaneously solve the signal detection and location problems. Our method consists of two steps. First, we apply a frequency-dependent threshold to the estimates of the array-averaged WCO in order to locate the time-frequency regions spanned by coherent arrivals. For these data, we then use the time-series of the complex wavelet coefficients for deriving the elements of the spatial Cross-Spectral Matrix. From the eigenstructure of this matrix, we eventually estimate the kinematic signals' parameters using the MUltiple SIgnal Characterization (MUSIC) algorithm. The whole procedure greatly facilitates the detection and location of weak, broad-band signals, in turn avoiding the time-frequency resolution trade-off and frequency leakage effects which affect conventional covariance estimates based upon Windowed Fourier Transform. The method is applied to explosion signals recorded at Stromboli volcano by either a short-period, small aperture antenna, or a large-aperture, broad-band network. The LP (0.2 < T < 2s) components of the explosive signals are analysed using data from the small-aperture array and under the plane-wave assumption. In this manner, we obtain a precise time- and frequency-localization of the directional properties for waves impinging at the array. We then extend the wavefield decomposition method using a spherical wave front model, and analyse the VLP

The data array, a tool to interface the user to a large data base

NASA Technical Reports Server (NTRS)

Foster, G. H.

1974-01-01

Aspects of the processing of spacecraft data is considered. Use of the data array in a large address space as an intermediate form in data processing for a large scientific data base is advocated. Techniques for efficient indexing in data arrays are reviewed and the data array method for mapping an arbitrary structure onto linear address space is shown. A compromise between the two forms is given. The impact of the data array on the user interface are considered along with implementation.

A novel 384-multiwell microelectrode array for the impedimetric monitoring of Tau protein induced neurodegenerative processes.

PubMed

Jahnke, Heinz-Georg; Krinke, Dana; Seidel, Diana; Lilienthal, Katharina; Schmidt, Sabine; Azendorf, Ronny; Fischer, Michael; Mack, Till; Striggow, Frank; Althaus, Holger; Schober, Andreas; Robitzki, Andrea A

2017-02-15

Over the last decades, countless bioelectronic monitoring systems were developed for the analysis of cells as well as complex tissues. Most studies addressed the sensitivity and specificity of the bioelectronic detection method in comparison to classical molecular biological assays. In contrast, the up scaling as a prerequisite for the practical application of these novel bioelectronic monitoring systems is mostly only discussed theoretically. In this context, we developed a novel 384-multiwell microelectrode array (MMEA) based measurement system for the sensitive label-free real-time monitoring of neurodegenerative processes by impedance spectroscopy. With respect to the needs of productive screening systems for robust and reproducible measurements on high numbers of plates, we focused on reducing the critical contacting of more than 400 electrodes for a 384-MMEA. Therefore, we introduced an on top array of immersive counter electrodes that are individually addressed by a multiplexer and connected all measurement electrodes on the 384-MMEA to a single contact point. More strikingly, our novel approach provided a comparable signal stability and sensitivity similar to an array with integrated counter electrodes. Next, we optimized a SH-SY5Y cell based tauopathy model by introducing a novel 5-fold Tau mutation eliminating the need of artificial tauopathy induction. In combination with our novel 384-MMEA based measurement system, the concentration and time dependent neuroregenerative effect of the kinase inhibitor SRN-003-556 could be quantitatively monitored. Thus, our novel screening system could be a useful tool to identify and develop potential novel therapeutics in the field of Tau-related neurodegenerative diseases. Copyright © 2016. Published by Elsevier B.V.

Recovery issues in databases using redundant disk arrays

NASA Technical Reports Server (NTRS)

Mourad, Antoine N.; Fuchs, W. K.; Saab, Daniel G.

1993-01-01

Redundant disk arrays provide a way for achieving rapid recovery from media failures with a relatively low storage cost for large scale database systems requiring high availability. In this paper we propose a method for using redundant disk arrays to support rapid recovery from system crashes and transaction aborts in addition to their role in providing media failure recovery. A twin page scheme is used to store the parity information in the array so that the time for transaction commit processing is not degraded. Using an analytical model, we show that the proposed method achieves a significant increase in the throughput of database systems using redundant disk arrays by reducing the number of recovery operations needed to maintain the consistency of the database.

Ghost artifact cancellation using phased array processing.

PubMed

Kellman, P; McVeigh, E R

2001-08-01

In this article, a method for phased array combining is formulated which may be used to cancel ghosts caused by a variety of distortion mechanisms, including space variant distortions such as local flow or off-resonance. This method is based on a constrained optimization, which optimizes SNR subject to the constraint of nulling ghost artifacts at known locations. The resultant technique is similar to the method known as sensitivity encoding (SENSE) used for accelerated imaging; however, in this formulation it is applied to full field-of-view (FOV) images. The method is applied to multishot EPI with noninterleaved phase encode acquisition. A number of benefits, as compared to the conventional interleaved approach, are reduced distortion due to off-resonance, in-plane flow, and EPI delay misalignment, as well as eliminating the need for echo-shifting. Experimental results demonstrate the cancellation for both phantom as well as cardiac imaging examples.

Ghost Artifact Cancellation Using Phased Array Processing

PubMed Central

Kellman, Peter; McVeigh, Elliot R.

2007-01-01

In this article, a method for phased array combining is formulated which may be used to cancel ghosts caused by a variety of distortion mechanisms, including space variant distortions such as local flow or off-resonance. This method is based on a constrained optimization, which optimizes SNR subject to the constraint of nulling ghost artifacts at known locations. The resultant technique is similar to the method known as sensitivity encoding (SENSE) used for accelerated imaging; however, in this formulation it is applied to full field-of-view (FOV) images. The method is applied to multishot EPI with noninterleaved phase encode acquisition. A number of benefits, as compared to the conventional interleaved approach, are reduced distortion due to off-resonance, in-plane flow, and EPI delay misalignment, as well as eliminating the need for echo-shifting. Experimental results demonstrate the cancellation for both phantom as well as cardiac imaging examples. PMID:11477638

An Electrochemical Quartz Crystal Microbalance Multisensor System Based on Phthalocyanine Nanostructured Films: Discrimination of Musts

PubMed Central

Garcia-Hernandez, Celia; Medina-Plaza, Cristina; Garcia-Cabezon, Cristina; Martin-Pedrosa, Fernando; del Valle, Isabel; de Saja, Jose Antonio; Rodríguez-Méndez, Maria Luz

2015-01-01

An array of electrochemical quartz crystal electrodes (EQCM) modified with nanostructured films based on phthalocyanines was developed and used to discriminate musts prepared from different varieties of grapes. Nanostructured films of iron, nickel and copper phthalocyanines were deposited on Pt/quartz crystals through the Layer by Layer technique by alternating layers of the corresponding phthalocyanine and poly-allylamine hydrochloride. Simultaneous electrochemical and mass measurements were used to study the mass changes accompanying the oxidation of electroactive species present in must samples obtained from six Spanish varieties of grapes (Juan García, Prieto Picudo, Mencía Regadío, Cabernet Sauvignon, Garnacha and Tempranillo). The mass and voltammetric outputs were processed using three-way models. Parallel Factor Analysis (PARAFAC) was successfully used to discriminate the must samples according to their variety. Multi-way partial least squares (N-PLS) evidenced the correlations existing between the voltammetric data and the polyphenolic content measured by chemical methods. Similarly, N-PLS showed a correlation between mass outputs and parameters related to the sugar content. These results demonstrated that electronic tongues based on arrays of EQCM sensors can offer advantages over arrays of mass or voltammetric sensors used separately. PMID:26610494

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network

PubMed Central

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-01-01

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO2, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO2 and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO2; smoke and temperature; smoke, CO2 and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%–92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition. PMID:27527175

Localization of multiple defects using the compact phased array (CPA) method

NASA Astrophysics Data System (ADS)

Senyurek, Volkan Y.; Baghalian, Amin; Tashakori, Shervin; McDaniel, Dwayne; Tansel, Ibrahim N.

2018-01-01

Array systems of transducers have found numerous applications in detection and localization of defects in structural health monitoring (SHM) of plate-like structures. Different types of array configurations and analysis algorithms have been used to improve the process of localization of defects. For accurate and reliable monitoring of large structures by array systems, a high number of actuator and sensor elements are often required. In this study, a compact phased array system consisting of only three piezoelectric elements is used in conjunction with an updated total focusing method (TFM) for localization of single and multiple defects in an aluminum plate. The accuracy of the localization process was greatly improved by including wave propagation information in TFM. Results indicated that the proposed CPA approach can locate single and multiple defects with high accuracy while decreasing the processing costs and the number of required transducers. This method can be utilized in critical applications such as aerospace structures where the use of a large number of transducers is not desirable.

Electromagnetically Clean Solar Arrays

NASA Technical Reports Server (NTRS)

Stem, Theodore G.; Kenniston, Anthony E.

2008-01-01

The term 'electromagnetically clean solar array' ('EMCSA') refers to a panel that contains a planar array of solar photovoltaic cells and that, in comparison with a functionally equivalent solar-array panel of a type heretofore used on spacecraft, (1) exhibits less electromagnetic interferences to and from other nearby electrical and electronic equipment and (2) can be manufactured at lower cost. The reduction of electromagnetic interferences is effected through a combination of (1) electrically conductive, electrically grounded shielding and (2) reduction of areas of current loops (in order to reduce magnetic moments). The reduction of cost is effected by designing the array to be fabricated as a more nearly unitary structure, using fewer components and fewer process steps. Although EMCSAs were conceived primarily for use on spacecraft they are also potentially advantageous for terrestrial applications in which there are requirements to limit electromagnetic interference. In a conventional solar panel of the type meant to be supplanted by an EMCSA panel, the wiring is normally located on the back side, separated from the cells, thereby giving rise to current loops having significant areas and, consequently, significant magnetic moments. Current-loop geometries are chosen in an effort to balance opposing magnetic moments to limit far-0field magnetic interactions, but the relatively large distances separating current loops makes full cancellation of magnetic fields problematic. The panel is assembled from bare photovoltaic cells by means of multiple sensitive process steps that contribute significantly to cost, especially if electomagnetic cleanliness is desired. The steps include applying a cover glass and electrical-interconnect-cell (CIC) sub-assemble, connecting the CIC subassemblies into strings of series-connected cells, laying down and adhesively bonding the strings onto a panel structure that has been made in a separate multi-step process, and mounting the

A Self-Sustained Wireless Multi-Sensor Platform Integrated with Printable Organic Sensors for Indoor Environmental Monitoring

PubMed Central

Wu, Chun-Chang; Chuang, Wen-Yu; Wu, Ching-Da; Su, Yu-Cheng; Huang, Yung-Yang; Huang, Yang-Jing; Peng, Sheng-Yu; Yu, Shih-An; Lin, Chih-Ting; Lu, Shey-Shi

2017-01-01

A self-sustained multi-sensor platform for indoor environmental monitoring is proposed in this paper. To reduce the cost and power consumption of the sensing platform, in the developed platform, organic materials of PEDOT:PSS and PEDOT:PSS/EB-PANI are used as the sensing films for humidity and CO2 detection, respectively. Different from traditional gas sensors, these organic sensing films can operate at room temperature without heating processes or infrared transceivers so that the power consumption of the developed humidity and the CO2 sensors can be as low as 10 μW and 5 μW, respectively. To cooperate with these low-power sensors, a Complementary Metal-Oxide-Semiconductor (CMOS) system-on-chip (SoC) is designed to amplify and to read out multiple sensor signals with low power consumption. The developed SoC includes an analog-front-end interface circuit (AFE), an analog-to-digital convertor (ADC), a digital controller and a power management unit (PMU). Scheduled by the digital controller, the sensing circuits are power gated with a small duty-cycle to reduce the average power consumption to 3.2 μW. The designed PMU converts the power scavenged from a dye sensitized solar cell (DSSC) module into required supply voltages for SoC circuits operation under typical indoor illuminance conditions. To our knowledge, this is the first multiple environmental parameters (Temperature/CO2/Humidity) sensing platform that demonstrates a true self-powering functionality for long-term operations. PMID:28353680

A Self-Sustained Wireless Multi-Sensor Platform Integrated with Printable Organic Sensors for Indoor Environmental Monitoring.

PubMed

Wu, Chun-Chang; Chuang, Wen-Yu; Wu, Ching-Da; Su, Yu-Cheng; Huang, Yung-Yang; Huang, Yang-Jing; Peng, Sheng-Yu; Yu, Shih-An; Lin, Chih-Ting; Lu, Shey-Shi

2017-03-29

A self-sustained multi-sensor platform for indoor environmental monitoring is proposed in this paper. To reduce the cost and power consumption of the sensing platform, in the developed platform, organic materials of PEDOT:PSS and PEDOT:PSS/EB-PANI are used as the sensing films for humidity and CO₂ detection, respectively. Different from traditional gas sensors, these organic sensing films can operate at room temperature without heating processes or infrared transceivers so that the power consumption of the developed humidity and the CO₂ sensors can be as low as 10 μW and 5 μW, respectively. To cooperate with these low-power sensors, a Complementary Metal-Oxide-Semiconductor (CMOS) system-on-chip (SoC) is designed to amplify and to read out multiple sensor signals with low power consumption. The developed SoC includes an analog-front-end interface circuit (AFE), an analog-to-digital convertor (ADC), a digital controller and a power management unit (PMU). Scheduled by the digital controller, the sensing circuits are power gated with a small duty-cycle to reduce the average power consumption to 3.2 μW. The designed PMU converts the power scavenged from a dye sensitized solar cell (DSSC) module into required supply voltages for SoC circuits operation under typical indoor illuminance conditions. To our knowledge, this is the first multiple environmental parameters (Temperature/CO₂/Humidity) sensing platform that demonstrates a true self-powering functionality for long-term operations.

Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development