WorldWideScience

Sample records for network sensing system

  1. A Spectrum Sensing Network for Cognitive PMSE Systems

    Science.gov (United States)

    Brendel, Johannes; Riess, Steffen; Stoeckle, Andreas; Rummel, Rafael; Fischer, Georg

    2012-09-01

    This article is about a Spectrum Sensing Network (SSN) which generates an accurate radio environment map (e.g. power over frequency, time, and location) from a given application area. It is intended to be used in combination with cognitive Program Making and Special Events (PMSE) devices (e.g. wireless microphones) to improve their operation reliability. The SSN consists of a distributed network of multiple scanning radio receivers and a central data management and storage unit. The parts of the SSN are presented in detail and the advantages and use cases of such a sensing network structure will be outlined.

  2. Handbook of sensor networks compact wireless and wired sensing systems

    CERN Document Server

    Ilyas, Mohammad

    2004-01-01

    INTRODUCTION Opportunities and Challenges in Wireless Sensor Networks, M. Haenggi, Next Generation Technologies to Enable Sensor Networks, J. I.  Goodman, A. I. Reuther, and D. R. Martinez Sensor Networks Management, L. B. Ruiz, J. M. Nogueira, and A. A. F. Loureiro Models for Programmability in Sensor Networks, A. Boulis Miniaturizing Sensor Networks with MEMS, Brett Warneke A Taxonomy of Routing Techniques in Wireless Sensor Networks, J. N. Al-Karaki and A. E. Kamal Artificial Perceptual Systems, A. Loutfi, M. Lindquist, and P. Wide APPLICATIONS Sensor Network Architecture and Appl

  3. A novel proposal of GPON-oriented fiber grating sensing data digitalization system for remote sensing network

    Science.gov (United States)

    Wang, Yubao; Zhu, Zhaohui; Wang, Lu; Bai, Jian

    2016-05-01

    A novel GPON-oriented sensing data digitalization system is proposed to achieve remote monitoring of fiber grating sensing networks utilizing existing optical communication networks in some harsh environments. In which, Quick digitalization of sensing information obtained from the reflected lightwaves by fiber Bragg grating (FBG) sensor is realized, and a novel frame format of sensor signal is designed to suit for public transport so as to facilitate sensor monitoring center to receive and analyze the sensor data. The delay effect, identification method of the sensor data, and various interference factors which influence the sensor data to be correctly received are analyzed. The system simulation is carried out with OptiSystem/Matlab co-simulation approach. The theoretical analysis and simulation results verify the feasibility of the integration of the sensor network and communication network.

  4. Ocean Networks Canada: Live Sensing of a Dynamic Ocean System

    Science.gov (United States)

    Heesemann, Martin; Juniper, Kim; Hoeberechts, Maia; Matabos, Marjolaine; Mihaly, Steven; Scherwath, Martin; Dewey, Richard

    2013-04-01

    Ocean Networks Canada operates two advanced cabled networks on the west coast of British Columbia. VENUS, the coastal network consisting of two cabled arrays with four Nodes reaching an isolated fjord (Saanich Inlet) and a busy shipping corridor near Vancouver (the Strait of Georgia) went into operation in February 2006. NEPTUNE Canada is the first operational deep-sea regional cabled ocean observatory worldwide. Since the first data began streaming to the public in 2009, instruments on the five active nodes along the 800 km cable loop have gathered a time-series documenting three years in the northeastern Pacific. Observations cover the northern Juan de Fuca tectonic plate from ridge to trench and the continental shelf and slope off Vancouver Island. The cabled systems provide power and high bandwidth communications to a wide range of oceanographic instrument systems which measure the physical, chemical, geological, and biological conditions of the dynamic earth-ocean system. Over the years significant challenges have been overcome and currently we have more than 100 instruments with hundreds of sensors reporting data in real-time. Salient successes are the first open-ocean seafloor to sea-surface vertical profiling system, three years of operation of Wally—a seafloor crawler that explores a hydrate mound, and a proven resilient cable design that can recover from trawler hits and major equipment meltdown with minimal loss of data. A network wide array of bottom mounted pressure recorders and seismometers recorded the passage of three major tsunamis, numerous earthquakes and frequent whale calls. At the Endeavour segment of the Juan de Fuca ridge high temperature and diffuse vent fluids were monitored and sampled using novel equipment, including high resolution active acoustics instrumentation to study plume dynamics at a massive sulfide hydrothermal vent. Also, four deep sea cabled moorings (300 m high) were placed in the precipitous bathymetry of the 2200 m

  5. Network architecture design of an agile sensing system with sandwich wireless sensor nodes

    Science.gov (United States)

    Dorvash, S.; Li, X.; Pakzad, S.; Cheng, L.

    2012-04-01

    Wireless sensor network (WSN) is recently emerged as a powerful tool in the structural health monitoring (SHM). Due to the limitations of wireless channel capacity and the heavy data traffic, the control on the network is usually not real time. On the other hand, many SHM applications require quick response when unexpected events, such as earthquake, happen. Realizing the need to have an agile monitoring system, an approach, called sandwich node, was proposed. Sandwich is a design of complex sensor node where two Imote2 nodes are connected with each other to enhance the capabilities of the sensing units. The extra channel and processing power, added into the nodes, enable agile responses of the sensing network, particularly in interrupting the network and altering the undergoing tasks for burst events. This paper presents the design of a testbed for examination of the performance of wireless sandwich nodes in a network. The designed elements of the network are the software architecture of remote and local nodes, and the triggering strategies for coordinating the sensing units. The performance of the designed network is evaluated through its implementation in a monitoring test in the laboratory. For both original Imote2 and the sandwich node, the response time is estimated. The results show that the sandwich node is an efficient solution to the collision issue in existing interrupt approaches and the latency in dense wireless sensor networks.

  6. Hybrid networking sensing system for structural health monitoring of a concrete cable-stayed bridge

    Science.gov (United States)

    Torbol, Marco; Kim, Sehwan; Chien, Ting-Chou; Shinozuka, Masanobu

    2013-04-01

    The purpose of this study is the remote structural health monitoring to identify the torsional natural frequencies and mode shapes of a concrete cable-stayed bridge using a hybrid networking sensing system. The system consists of one data aggregation unit, which is daisy-chained to one or more sensing nodes. A wireless interface is used between the data aggregation units, whereas a wired interface is used between a data aggregation unit and the sensing nodes. Each sensing node is equipped with high-precision MEMS accelerometers with adjustable sampling frequency from 0.2 Hz to 1.2 kHz. The entire system was installed inside the reinforced concrete box-girder deck of Hwamyung Bridge, which is a cable stayed bridge in Busan, South Korea, to protect the system from the harsh environmental conditions. This deployment makes wireless communication a challenge due to the signal losses and the high levels of attenuation. To address these issues, the concept of hybrid networking system is introduced with the efficient local power distribution technique. The theoretical communication range of Wi-Fi is 100m. However, inside the concrete girder, the peer to peer wireless communication cannot exceed about 20m. The distance is further reduced by the line of sight between the antennas. However, the wired daisy-chained connection between sensing nodes is useful because the data aggregation unit can be placed in the optimal location for transmission. To overcome the limitation of the wireless communication range, we adopt a high-gain antenna that extends the wireless communication distance to 50m. Additional help is given by the multi-hopping data communication protocol. The 4G modem, which allows remote access to the system, is the only component exposed to the external environment.

  7. A Drone Remote Sensing for Virtual Reality Simulation System for Forest Fires: Semantic Neural Network Approach

    Science.gov (United States)

    Narasimha Rao, Gudikandhula; Jagadeeswara Rao, Peddada; Duvvuru, Rajesh

    2016-09-01

    Wild fires have significant impact on atmosphere and lives. The demand of predicting exact fire area in forest may help fire management team by using drone as a robot. These are flexible, inexpensive and elevated-motion remote sensing systems that use drones as platforms are important for substantial data gaps and supplementing the capabilities of manned aircraft and satellite remote sensing systems. In addition, powerful computational tools are essential for predicting certain burned area in the duration of a forest fire. The reason of this study is to built up a smart system based on semantic neural networking for the forecast of burned areas. The usage of virtual reality simulator is used to support the instruction process of fire fighters and all users for saving of surrounded wild lives by using a naive method Semantic Neural Network System (SNNS). Semantics are valuable initially to have a enhanced representation of the burned area prediction and better alteration of simulation situation to the users. In meticulous, consequences obtained with geometric semantic neural networking is extensively superior to other methods. This learning suggests that deeper investigation of neural networking in the field of forest fires prediction could be productive.

  8. Monitoring of Thermal Protection Systems using Robust Self-Organizing Optical Fiber Sensing Networks Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Objectives a) Development, evaluation and demonstration of a dynamically reconfigurable optical fiber sensing network that is interrogated using the optical...

  9. Mobile sensing systems.

    Science.gov (United States)

    Macias, Elsa; Suarez, Alvaro; Lloret, Jaime

    2013-12-16

    Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high.

  10. Mobile Sensing Systems

    Directory of Open Access Journals (Sweden)

    Elsa Macias

    2013-12-01

    Full Text Available Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high.

  11. Mobile Sensing Systems

    Science.gov (United States)

    Macias, Elsa; Suarez, Alvaro; Lloret, Jaime

    2013-01-01

    Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high. PMID:24351637

  12. A WiMAX Networked UAV Telemetry System for Net-Centric Remote Sensing and Range Surveillance Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A WiMAX networked UAV Telemetry System (WNUTS) is designed for net-centric remote sensing and launch range surveillance applications. WNUTS integrates a MIMO powered...

  13. Air-Sense: indoor environment monitoring evaluation system based on ZigBee network

    Science.gov (United States)

    Huang, Yang; Hu, Liang; Yang, Disheng; Liu, Hengchang

    2017-08-01

    In the modern life, people spend most of their time indoors. However, indoor environmental quality problems have always been affecting people’s social activities. In general, indoor environmental quality is also related to our indoor activities. Since most of the organic irritants and volatile gases are colorless, odorless and too tiny to be seen, because we have been unconsciously overlooked indoor environment quality. Consequently, our body suffer a great health problem. In this work, we propose Air-Sense system which utilizes the platform of ZigBee Network to collect and detect the real-time indoor environment quality. What’s more, Air-Sense system can also provide data analysis, and visualizing the results of the indoor environment to the user.

  14. Health Participatory Sensing Networks

    Directory of Open Access Journals (Sweden)

    Andrew Clarke

    2014-01-01

    Full Text Available The use of participatory sensing in relation to the capture of health-related data is rapidly becoming a possibility due to the widespread consumer adoption of emerging mobile computing technologies and sensing platforms. This has the potential to revolutionize data collection for population health, aspects of epidemiology, and health-related e-Science applications and as we will describe, provide new public health intervention capabilities, with the classifications and capabilities of such participatory sensing platforms only just beginning to be explored. Such a development will have important benefits for access to near real-time, large-scale, up to population-scale data collection. However, there are also numerous issues to be addressed first: provision of stringent anonymity and privacy within these methodologies, user interface issues, and the related issue of how to incentivize participants and address barriers/concerns over participation. To provide a step towards describing these aspects, in this paper we present a first classification of health participatory sensing models, a novel contribution to the literature, and provide a conceptual reference architecture for health participatory sensing networks (HPSNs and user interaction example case study.

  15. GPM Ground Validation Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) IFloodS V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS)...

  16. A radial basis function neural network based on artificial immune systems for remote sensing image classification

    Science.gov (United States)

    Yan, Qin; Zhong, Yanfei

    2008-12-01

    The radial basis function (RBF) neural network is a powerful method for remote sensing image classification. It has a simple architecture and the learning algorithm corresponds to the solution of a linear regression problem, resulting in a fast training process. The main drawback of this strategy is the requirement of an efficient algorithm to determine the number, position, and dispersion of the RBF. Traditional methods to determine the centers are: randomly choose input vectors from the training data set; vectors obtained from unsupervised clustering algorithms, such as k-means, applied to the input data. These conduce that traditional RBF neural network is sensitive to the center initialization. In this paper, the artificial immune network (aiNet) model, a new computational intelligence based on artificial immune networks (AIN), is applied to obtain appropriate centers for remote sensing image classification. In the aiNet-RBF algorihtm, each input pattern corresonds to an antigenic stimulus, while each RBF candidate center is considered to be an element, or cell, of the immune network model. The steps are as follows: A set of candidate centers is initialized at random, where the initial number of candidates and their positions is not crucial to the performance. Then, the clonal selection principle will control which candidates will be selected and how they will be upadated. Note that the clonal selection principle will be responsible for how the centers will represent the training data set. Finally, the immune network will identify and eliminate or suppress self-recognizing individuals to control the number of candidate centers. After the above learning phase, the aiNet network centers represent internal images of the inuput patterns presented to it. The algorithm output is taken to be the matrix of memory cells' coordinates that represent the final centers to be adopted by the RBF network. The stopping criterion of the proposed algorithm is given by a pre

  17. Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

    Science.gov (United States)

    Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

    2015-01-01

    Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

  18. Future directions in networked sensing.

    NARCIS (Netherlands)

    Havinga, Paul J.M.; van Dijk, H.W.; Maas, J.W.; van de Schootbrugge, G.A.

    Started one decade ago as a wild academic idea, wireless sensor and actuator networks turned into a vibrant research area with a large R&D community dealing with a commercially highly relevant technology. The new paradigm in networked sensing has received significant attention because of the

  19. Advanced mobile networking, sensing, and controls.

    Energy Technology Data Exchange (ETDEWEB)

    Feddema, John Todd; Kilman, Dominique Marie; Byrne, Raymond Harry; Young, Joseph G.; Lewis, Christopher L.; Van Leeuwen, Brian P.; Robinett, Rush D. III; Harrington, John J.

    2005-03-01

    This report describes an integrated approach for designing communication, sensing, and control systems for mobile distributed systems. Graph theoretic methods are used to analyze the input/output reachability and structural controllability and observability of a decentralized system. Embedded in each network node, this analysis will automatically reconfigure an ad hoc communication network for the sensing and control task at hand. The graph analysis can also be used to create the optimal communication flow control based upon the spatial distribution of the network nodes. Edge coloring algorithms tell us that the minimum number of time slots in a planar network is equal to either the maximum number of adjacent nodes (or degree) of the undirected graph plus some small number. Therefore, the more spread out that the nodes are, the fewer number of time slots are needed for communication, and the smaller the latency between nodes. In a coupled system, this results in a more responsive sensor network and control system. Network protocols are developed to propagate this information, and distributed algorithms are developed to automatically adjust the number of time slots available for communication. These protocols and algorithms must be extremely efficient and only updated as network nodes move. In addition, queuing theory is used to analyze the delay characteristics of Carrier Sense Multiple Access (CSMA) networks. This report documents the analysis, simulation, and implementation of these algorithms performed under this Laboratory Directed Research and Development (LDRD) effort.

  20. Monitoring of Thermal Protection Systems Using Robust Self-Organizing Optical Fiber Sensing Networks

    Science.gov (United States)

    Richards, Lance

    2013-01-01

    The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, and an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during re-entry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry

  1. Enhanced sensing and communication via quantum networks

    Science.gov (United States)

    Smith, James F.

    2017-05-01

    A network based on quantum information has been developed to improve sensing and communications capabilities. Quantum teleportation offers features for communicating information not found in classical procedures. It is fundamental to the quantum network approach. A version of quantum teleportation based on hyper-entanglement is used to bring about these improvements. Recently invented methods of improving sensing and communication via quantum information based on hyper-entanglement are discussed. These techniques offer huge improvements in the SNR, signal to interference ratio, and time-on-target of various sensors including RADAR and LADAR. Hyper-entanglement refers to quantum entanglement in more than one degree of freedom, e.g. polarization, energy-time, orbital angular momentum (OAM), etc. The quantum network makes use of quantum memory located in each node of the network, thus the network forms a quantum repeater. The quantum repeater facilitates the use of quantum teleportation, and superdense coding. Superdense coding refers to the ability to incorporate more than one classical bit into each transmitted qubit. The network of sensors and/or communication devices has an enhanced resistance to interference sources. The repeater has the potential for greatly reducing loss in communications and sensor systems related to the effect of the atmosphere on fragile quantum states. Measures of effectiveness (MOEs) are discussed that show the utility of the network for improving sensing and communications in the presence of loss and noise. The quantum repeater will reduce overall size, weight, power and cost (SWAPC) of fielded components of systems.

  2. Wearable Networked Sensing for Human Mobility and Activity Analytics: A Systems Study

    OpenAIRE

    Dong, Bo; Biswas, Subir

    2012-01-01

    This paper presents implementation details, system characterization, and the performance of a wearable sensor network that was designed for human activity analysis. Specific machine learning mechanisms are implemented for recognizing a target set of activities with both out-of-body and on-body processing arrangements. Impacts of energy consumption by the on-body sensors are analyzed in terms of activity detection accuracy for out-of-body processing. Impacts of limited processing abilities in ...

  3. Properties of centralized cooperative sensing in cognitive radio networks

    Science.gov (United States)

    Skokowski, Paweł; Malon, Krzysztof; Łopatka, Jerzy

    2017-04-01

    Spectrum sensing is a functionality that enables network creation in the cognitive radio technology. Spectrum sensing is use for building the situation awareness knowledge for better use of radio resources and to adjust network parameters in case of jamming, interferences from legacy systems, decreasing link quality caused e.g. by nodes positions changes. This paper presents results from performed tests to compare cooperative centralized sensing versus local sensing. All tests were performed in created simulator developed in Matlab/Simulink environment.

  4. Monitoring of Thermal Protection Systems and MMOD using Robust Self-Organizing Optical Fiber Sensing Networks

    Science.gov (United States)

    Richards, Lance

    2014-01-01

    The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, such as those from Micrometeoroid Orbital Debris (MMOD). The approach uses an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during reentry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry.

  5. Smart sensing surveillance system

    Science.gov (United States)

    Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen

    2010-04-01

    An effective public safety sensor system for heavily-populated applications requires sophisticated and geographically-distributed infrastructures, centralized supervision, and deployment of large-scale security and surveillance networks. Artificial intelligence in sensor systems is a critical design to raise awareness levels, improve the performance of the system and adapt to a changing scenario and environment. In this paper, a highly-distributed, fault-tolerant, and energy-efficient Smart Sensing Surveillance System (S4) is presented to efficiently provide a 24/7 and all weather security operation in crowded environments or restricted areas. Technically, the S4 consists of a number of distributed sensor nodes integrated with specific passive sensors to rapidly collect, process, and disseminate heterogeneous sensor data from near omni-directions. These distributed sensor nodes can cooperatively work to send immediate security information when new objects appear. When the new objects are detected, the S4 will smartly select the available node with a Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR camera to track the objects and capture associated imagery. The S4 provides applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. Other imaging processes can be updated to meet specific requirements and operations. In the S4, all the sensor nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology. This UWB RF technology can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The Service Oriented Architecture of S4 enables remote applications to interact with the S4

  6. Development and Improvement of an Intelligent Cable Monitoring System for Underground Distribution Networks Using Distributed Temperature Sensing

    Directory of Open Access Journals (Sweden)

    Jintae Cho

    2014-02-01

    Full Text Available With power systems switching to smart grids, real-time and on-line monitoring technologies for underground distribution power cables have become a priority. Most distribution components have been developed with self-diagnostic sensors to realize self-healing, one of the smart grid functions in a distribution network. Nonetheless, implementing a real-time and on-line monitoring system for underground distribution cables has been difficult because of high cost and low sensitivity. Nowadays, optical fiber composite power cables (OFCPCs are being considered for communication and power delivery to cope with the increasing communication load in a distribution network. Therefore, the application of distributed temperature sensing (DTS technology on OFCPCs used as underground distribution lines is studied for the real-time and on-line monitoring of the underground distribution power cables. Faults can be reduced and operating ampacity of the underground distribution system can be increased. This paper presents the development and improvement of an intelligent cable monitoring system for the underground distribution power system, using DTS technology and OFCPCs as the underground distribution lines in the field.

  7. Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment

    Science.gov (United States)

    Thorne, Peter W.; Madonna, Fabio; Schulz, Joerg; Oakley, Tim; Ingleby, Bruce; Rosoldi, Marco; Tramutola, Emanuele; Arola, Antti; Buschmann, Matthias; Mikalsen, Anna C.; Davy, Richard; Voces, Corinne; Kreher, Karin; De Maziere, Martine; Pappalardo, Gelsomina

    2017-11-01

    There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies, etc. The Horizon 2020 project GAIA-CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is correct. Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available and maintains rich metadata. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based on such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate on networks measuring primarily a subset of the atmospheric Essential Climate Variables of interest to GAIA-CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream example applications of the GAIA-CLIM project. However, the approach laid out should be more widely applicable across a broad range of application

  8. Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment

    Directory of Open Access Journals (Sweden)

    P. W. Thorne

    2017-11-01

    Full Text Available There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies, etc. The Horizon 2020 project GAIA–CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is correct. Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available and maintains rich metadata. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based on such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate on networks measuring primarily a subset of the atmospheric Essential Climate Variables of interest to GAIA–CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream example applications of the GAIA–CLIM project. However, the approach laid out should be more widely applicable across

  9. Temporal compressive sensing systems

    Energy Technology Data Exchange (ETDEWEB)

    Reed, Bryan W.

    2017-12-12

    Methods and systems for temporal compressive sensing are disclosed, where within each of one or more sensor array data acquisition periods, one or more sensor array measurement datasets comprising distinct linear combinations of time slice data are acquired, and where mathematical reconstruction allows for calculation of accurate representations of the individual time slice datasets.

  10. Nanosensors-Cellphone Integration for Extended Chemical Sensing Network

    Science.gov (United States)

    Li, Jing

    2011-01-01

    This poster is to present the development of a cellphone sensor network for extended chemical sensing. The nanosensors using carbon nanotubes and other nanostructures are used with low power and high sensitivity for chemical detection. The sensing module has been miniaturized to a small size that can plug in or clip on to a smartphone. The chemical information detected by the nanosensors are acquired by a smartphone and transmitted via cellphone 3g or WiFi network to an internet server. The whole integrated sensing system from sensor to cellphone to a cloud will provide an extended chemical sensing network that can cover nation wide and even cover global wide for early warning of a hazardous event.

  11. Combining multiple algorithms for road network tracking from multiple source remotely sensed imagery: a practical system and performance evaluation.

    Science.gov (United States)

    Lin, Xiangguo; Liu, Zhengjun; Zhang, Jixian; Shen, Jing

    2009-01-01

    In light of the increasing availability of commercial high-resolution imaging sensors, automatic interpretation tools are needed to extract road features. Currently, many approaches for road extraction are available, but it is acknowledged that there is no single method that would be successful in extracting all types of roads from any remotely sensed imagery. In this paper, a novel classification of roads is proposed, based on both the roads' geometrical, radiometric properties and the characteristics of the sensors. Subsequently, a general road tracking framework is proposed, and one or more suitable road trackers are designed or combined for each type of roads. Extensive experiments are performed to extract roads from aerial/satellite imagery, and the results show that a combination strategy can automatically extract more than 60% of the total roads from very high resolution imagery such as QuickBird and DMC images, with a time-saving of approximately 20%, and acceptable spatial accuracy. It is proven that a combination of multiple algorithms is more reliable, more efficient and more robust for extracting road networks from multiple-source remotely sensed imagery than the individual algorithms.

  12. Cognitive networked sensing and big data

    CERN Document Server

    Qiu, Robert

    2013-01-01

    Wireless Distributed Computing and Cognitive Sensing defines high-dimensional data processing in the context of wireless distributed computing and cognitive sensing. This book presents the challenges that are unique to this area such as synchronization caused by the high mobility of the nodes. The author will discuss the integration of software defined radio implementation and testbed development. The book will also bridge new research results and contextual reviews. Also the author provides an examination of large cognitive radio network; hardware testbed; distributed sensing; and distributed

  13. Studying Sensing-Based Systems

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun

    2013-01-01

    Recent sensing-based systems involve a multitude of users, devices, and places. These types of systems challenge existing approaches for conducting valid system evaluations. Here, the author discusses such evaluation challenges and revisits existing system evaluation methodologies....

  14. Uncovering transportation networks from traffic flux by compressed sensing

    Science.gov (United States)

    Tang, Si-Qi; Shen, Zhesi; Wang, Wen-Xu; Di, Zengru

    2015-08-01

    Transportation and communication networks are ubiquitous in nature and society. Uncovering the underlying topology as well as link weights, is fundamental to understanding traffic dynamics and designing effective control strategies to facilitate transmission efficiency. We develop a general method for reconstructing transportation networks from detectable traffic flux data using the aid of a compressed sensing algorithm. Our approach enables full reconstruction of network topology and link weights for both directed and undirected networks from relatively small amounts of data compared to the network size. The limited data requirement and certain resistance to noise allows our method to achieve real-time network reconstruction. We substantiate the effectiveness of our method through systematic numerical tests with respect to several different network structures and transmission strategies. We expect our approach to be widely applicable in a variety of transportation and communication systems.

  15. A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks

    Directory of Open Access Journals (Sweden)

    Aamir Shahzad

    2016-03-01

    Full Text Available In Industrial systems, Supervisory control and data acquisition (SCADA system, the pseudo-transport layer of the distributed network protocol (DNP3 performs the functions of the transport layer and network layer of the open systems interconnection (OSI model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design.

  16. Smart sensing surveillance video system

    Science.gov (United States)

    Hsu, Charles; Szu, Harold

    2016-05-01

    An intelligent video surveillance system is able to detect and identify abnormal and alarming situations by analyzing object movement. The Smart Sensing Surveillance Video (S3V) System is proposed to minimize video processing and transmission, thus allowing a fixed number of cameras to be connected on the system, and making it suitable for its applications in remote battlefield, tactical, and civilian applications including border surveillance, special force operations, airfield protection, perimeter and building protection, and etc. The S3V System would be more effective if equipped with visual understanding capabilities to detect, analyze, and recognize objects, track motions, and predict intentions. In addition, alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. The S3V System capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments. It would be directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.

  17. EDITORIAL: Sensors and sensing systems

    Science.gov (United States)

    Dewhurst, Richard; Tian, Gui Yun

    2008-02-01

    Sensors are very important for measurement science and technology. They serve as a vital component in new measurement techniques and instrumentation systems. Key qualities of a good sensor system are high resolution, high reliability, low cost, appropriate output for a given input (good sensitivity), rapid response time, small random error in results, and small systematic error. Linearity is also useful, but with the advent of lookup tables and software, it is not as important as it used to be. In the last several years, considerable effort around the world has been devoted to a wide range of sensors from nanoscale sensors to sensor networks. Collectively, these vast and multidisciplinary efforts are developing important technological roadmaps to futuristic sensors with new modalities, significantly enhanced effectiveness and integrated functionality (data processing, computation, decision making and communications). When properly organized, they will have important relevance to life science and security applications, e.g. the sensing and monitoring of chemical, biological, radiological and explosive threats. A special feature in this issue takes a snapshot of some recent developments that were first presented at an international conference, the 2007 IEEE International Conference on Networking, Sensing and Control (ICNSC). The conference discussed recent developments, from which a few papers have since been brought together in this special feature. Gas sensing for environmental monitoring remains a topical subject, and two papers deal with this issue. One is concerned with the exploitation of nanostructured Au-doped cobalt oxyhydroxide-based carbon monoxide sensors for fire detection at its earlier stages (Zhuiykov and Dowling), whilst another examines the role of oxygen in high temperature hydrogen sulfide detection using MISiC sensors (Weng et al). Again for environmental monitoring, another paper deals with accurate sound source localization in a reverberant

  18. Real-time network traffic classification technique for wireless local area networks based on compressed sensing

    Science.gov (United States)

    Balouchestani, Mohammadreza

    2017-05-01

    Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

  19. A Heuristic Decision Making Model to Mitigate Adverse Consequences in a Network Centric Warfare/Sense and Respond System

    Science.gov (United States)

    2005-05-01

    information and technology to respond to discontinuous change at the 17 strategic, tactical, and operational levels (Alberts et al, 1999; Haeckel ...Education, (2003). Haeckel , Stephan H. Adaptive Enterprise: Creating and Leading Sense-and-Respond Organizations, Boston: Harvard Business School

  20. Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

    Science.gov (United States)

    Zhang, Zhen; Ma, Cheng; Zhu, Rong

    2016-10-14

    High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

  1. Human behavior understanding in networked sensing theory and applications of networks of sensors

    CERN Document Server

    Spagnolo, Paolo; Distante, Cosimo

    2014-01-01

    This unique text/reference provides a broad overview of both the technical challenges in sensor network development, and the real-world applications of distributed sensing. Important aspects of distributed computing in large-scale networked sensor systems are analyzed in the context of human behavior understanding, including such topics as systems design tools and techniques, in-network signals, and information processing. Additionally, the book examines a varied range of application scenarios, covering surveillance, indexing and retrieval, patient care, industrial safety, social and ambient

  2. Unveiling the relationship between complex networks metrics and word senses

    CERN Document Server

    Amancio, Diego R; Costa, Luciano da F; 10.1209/0295-5075/98/18002

    2013-01-01

    The automatic disambiguation of word senses (i.e., the identification of which of the meanings is used in a given context for a word that has multiple meanings) is essential for such applications as machine translation and information retrieval, and represents a key step for developing the so-called Semantic Web. Humans disambiguate words in a straightforward fashion, but this does not apply to computers. In this paper we address the problem of Word Sense Disambiguation (WSD) by treating texts as complex networks, and show that word senses can be distinguished upon characterizing the local structure around ambiguous words. Our goal was not to obtain the best possible disambiguation system, but we nevertheless found that in half of the cases our approach outperforms traditional shallow methods. We show that the hierarchical connectivity and clustering of words are usually the most relevant features for WSD. The results reported here shine light on the relationship between semantic and structural parameters of ...

  3. Enhancing Sensing and Channel Access in Cognitive Radio Networks

    KAUST Repository

    Hamza, Doha R.

    2014-06-18

    Cognitive radio technology is a promising technology to solve the wireless spectrum scarcity problem by intelligently allowing secondary, or unlicensed, users access to the primary, licensed, users\\' frequency bands. Cognitive technology involves two main tasks: 1) sensing the wireless medium to assess the presence of the primary users and 2) designing secondary spectrum access techniques that maximize the secondary users\\' benefits while maintaining the primary users\\' privileged status. On the spectrum sensing side, we make two contributions. First, we maximize a utility function representing the secondary throughput while constraining the collision probability with the primary below a certain value. We optimize therein the channel sensing time, the sensing decision threshold, the channel probing time, together with the channel sensing order for wideband primary channels. Second, we design a cooperative spectrum sensing technique termed sensing with equal gain combining whereby cognitive radios simultaneously transmit their sensing results to the fusion center over multipath fading reporting channels. The proposed scheme is shown to outperform orthogonal reporting systems in terms of achievable secondary throughput and to be robust against phase and synchronization errors. On the spectrum access side, we make four contributions. First, we design a secondary scheduling scheme with the goal of minimizing the secondary queueing delay under constraints on the average secondary transmit power and the maximum tolerable primary outage probability. Second, we design another secondary scheduling scheme based on the spectrum sensing results and the primary automatic repeat request feedback. The optimal medium access probabilities are obtained via maximizing the secondary throughput subject to constraints that guarantee quality of service parameters for the primary. Third, we propose a three-message superposition coding scheme to maximize the secondary throughput without

  4. Compressed sensing for distributed systems

    CERN Document Server

    Coluccia, Giulio; Magli, Enrico

    2015-01-01

    This book presents a survey of the state-of-the art in the exciting and timely topic of compressed sensing for distributed systems. It has to be noted that, while compressed sensing has been studied for some time now, its distributed applications are relatively new. Remarkably, such applications are ideally suited to exploit all the benefits that compressed sensing can provide. The objective of this book is to provide the reader with a comprehensive survey of this topic, from the basic concepts to different classes of centralized and distributed reconstruction algorithms, as well as a comparison of these techniques. This book collects different contributions on these aspects. It presents the underlying theory in a complete and unified way for the first time, presenting various signal models and their use cases. It contains a theoretical part collecting latest results in rate-distortion analysis of distributed compressed sensing, as well as practical implementations of algorithms obtaining performance close to...

  5. A Novel Sensing Method and Sensing Algorithm Development for a Ubiquitous Network

    Directory of Open Access Journals (Sweden)

    Sungwook Yu

    2010-08-01

    Full Text Available This paper proposes a novel technique which provides energy efficient circuit design for sensors networks. The overall system presented requires a minimum number of independently communicating sensors and sub-circuits which enable it to reduce the power consumption by setting unused sensors to idle. This technique reduces hardware requirements, time and interconnection problems with a supervisory control. Our proposed algorithm, which hands over the controls to two software mangers for the sensing and moving subsystems can greatly improve the overall system performance. Based on the experimental results, we observed that our system, which is using sensing and moving managers, the four sensors required only 3.4 mW power consumption when a robot arm is moved a total distance of 17 cm. This system is designed for robot applications but could be implemented to many other human environments such as “ubiquitous cities”, “smart homes”, etc.

  6. Exploratory community sensing in social networks

    Science.gov (United States)

    Khrabrov, Alexy; Stocco, Gabriel; Cybenko, George

    2010-04-01

    Social networks generally provide an implementation of some kind of groups or communities which users can voluntarily join. Twitter does not have this functionality, and there is no notion of a formal group or community. We propose a method for identification of communities and assignment of semantic meaning to the discussion topics of the resulting communities. Using this analysis method and a sample of roughly a month's worth of Tweets from Twitter's "gardenhose" feed, we demonstrate the discovery of meaningful user communities on Twitter. We examine Twitter data streaming in real time and treat it as a sensor. Twitter is a social network which pioneered microblogging with the messages fitting an SMS, and a variety of clients, browsers, smart phones and PDAs are used for status updates by individuals, businesses, media outlets and even devices all over the world. Often an aggregate trend of such statuses may represent an important development in the world, which has been demonstrated with the Iran and Moldova elections and the anniversary of the Tiananmen in China. We propose using Twitter as a sensor, tracking individuals and communities of interest, and characterizing individual roles and dynamics of their communications. We developed a novel algorithm of community identification in social networks based on direct communication, as opposed to linking. We show ways to find communities of interest and then browse their neighborhoods by either similarity or diversity of individuals and groups adjacent to the one of interest. We use frequent collocations and statistically improbable phrases to summarize the focus of the community, giving a quick overview of its main topics. Our methods provide insight into the largest social sensor network in the world and constitute a platform for social sensing.

  7. High Resolution Sensing and Control of Urban Water Networks

    Science.gov (United States)

    Bartos, M. D.; Wong, B. P.; Kerkez, B.

    2016-12-01

    We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.

  8. A Prototype Network for Remote Sensing Validation in China

    Directory of Open Access Journals (Sweden)

    Mingguo Ma

    2015-04-01

    Full Text Available Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC. The VRPC aims to improve remote sensing products at a regional scale in China. These improvements will enhance the applicability of the key remote sensing products in understanding and interpretation of typical land surface processes in China. The framework of the VRPC is introduced first, including its four basic components. Then, the basic selection principles of the observation sites are described, and the principles for the validation of the remote sensing products are established. The VRPC will be realized in stages. In the first stage, four stations that have improved remote sensing observation facilities have been incorporated according to the selection principles. Certain core observation sites have been constructed at these stations. Next the Heihe Station is introduced in detail as an example. The three levels of observation (the research base, pixel-scale validation sites, and regional coverage adopted by the Heihe Station are carefully explained. The pixel-scale validation sites with nested multi-scale observation systems in this station are the most unique feature, and these sites aim to solve some key scientific problems associated with remote sensing product validation (e.g., the scale effect and scale transformation. Multi-year of in situ measurements will ensure the high accuracy and inter-annual validity of the land products, which will provide dynamic regional monitoring and simulation capabilities in China. The observation sites of the VRPC are open, with the goal of increasing cooperation and exchange with global programs.

  9. Advanced Energy Detector Based Cooperative Spectrum Sensing In Cognitive Networks

    OpenAIRE

    Ritu; Seehra Ameeta

    2016-01-01

    Cognitive radio is a befitting hopeful technology for future. Spectrum sensing is the most critical function of cognitive radio. Most of the spectrums sensing processes proposed earlier become impractical at lower signal to noise ratio conditions. Paper presents advanced cooperative spectrum sensing technique used in cognitive radio (CR) systems. By spectrum sensing it detects the presence of a primary user (PU) on a concerned spectrum. The accuracy of spectrum sensing depends on both sensing...

  10. Pain Sensing System for Animals

    Directory of Open Access Journals (Sweden)

    Ibrahim AL-BAHADLY

    2010-12-01

    Full Text Available Castration, tail docking and ear tagging are examples of painful process that the lambs in New Zealand undergo in their early life. Massey University is conducting a research to measure the pain sensitivity in animals based upon applying mechanical force. The research will help in better understanding the development of pain sensitivity in the animal, and hence improving the welfare of the lambs and other animals. The traditional measurement system is pneumatic and it has some associated drawbacks such as; inaccuracy in measuring the applied force, inconsistent rate of force application, leaks in the system, and issues of impracticality and safety. This paper presents a new pain sensing system based on the use of stepping motor for applying force and flexiforce sensor for measuring the applied force. The new sensing system was successfully tested on a frozen lamb leg and then on life sheep.

  11. Inferring cell-scale signalling networks via compressive sensing.

    Directory of Open Access Journals (Sweden)

    Lei Nie

    Full Text Available Signalling network inference is a central problem in system biology. Previous studies investigate this problem by independently inferring local signalling networks and then linking them together via crosstalk. Since a cellular signalling system is in fact indivisible, this reductionistic approach may have an impact on the accuracy of the inference results. Preferably, a cell-scale signalling network should be inferred as a whole. However, the holistic approach suffers from three practical issues: scalability, measurement and overfitting. Here we make this approach feasible based on two key observations: 1 variations of concentrations are sparse due to separations of timescales; 2 several species can be measured together using cross-reactivity. We propose a method, CCELL, for cell-scale signalling network inference from time series generated by immunoprecipitation using Bayesian compressive sensing. A set of benchmark networks with varying numbers of time-variant species is used to demonstrate the effectiveness of our method. Instead of exhaustively measuring all individual species, high accuracy is achieved from relatively few measurements.

  12. Compressive Sensing in Communication Systems

    DEFF Research Database (Denmark)

    Fyhn, Karsten

    2013-01-01

    . The need for cheaper, smarter and more energy efficient wireless devices is greater now than ever. This thesis addresses this problem and concerns the application of the recently developed sampling theory of compressive sensing in communication systems. Compressive sensing is the merging of signal......Wireless communication is omnipresent today, but this development has led to frequency spectrum becoming a limited resource. Furthermore, wireless devices become more and more energy-limited, due to the demand for continual wireless communication of higher and higher amounts of information...... acquisition and compression. It allows for sampling a signal with a rate below the bound dictated by the celebrated Shannon-Nyquist sampling theorem. In some communication systems this necessary minimum sample rate, dictated by the Shannon-Nyquist sampling theorem, is so high it is at the limit of what...

  13. Optimized Reputable Sensing Participants Extraction for Participatory Sensor Networks

    Directory of Open Access Journals (Sweden)

    Weiwei Yuan

    2014-01-01

    Full Text Available By collecting data via sensors embedded personal smart devices, sensing participants play a key role in participatory sensor networks. Using information provided by reputable sensing participants ensures the reliability of participatory sensing data. Setting a threshold for the reputation, and those whose reputations are bigger than this value are regarded as reputable. The bigger the threshold value is, the more reliable the extracted reputable sensing participant is. However, if the threshold value is too big, only very limited participatory sensing data can be involved. This may cause unexpected bias in information collection. Existing works did not consider the relationship between the reliability of extracted reputable sensing participants and the ratio of usable participatory sensing data. In this work, we propose a criterion for optimized reputable sensing participant extraction in participatory sensor networks. This is achieved based on the mathematical analysis on the ratio of available participatory sensing data and the reliability of extracted reputable sensing participants. Our suggested threshold value for reputable sensing participant extraction is only related to the power of sensing participant’s reputation distribution. It is easy to be applied in real applications. Simulation results tested on real application data further verified the effectiveness of our proposed method.

  14. Computer network defense system

    Science.gov (United States)

    Urias, Vincent; Stout, William M. S.; Loverro, Caleb

    2017-08-22

    A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves network connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.

  15. Reconstruction of Complex Network based on the Noise via QR Decomposition and Compressed Sensing.

    Science.gov (United States)

    Li, Lixiang; Xu, Dafei; Peng, Haipeng; Kurths, Jürgen; Yang, Yixian

    2017-11-08

    It is generally known that the states of network nodes are stable and have strong correlations in a linear network system. We find that without the control input, the method of compressed sensing can not succeed in reconstructing complex networks in which the states of nodes are generated through the linear network system. However, noise can drive the dynamics between nodes to break the stability of the system state. Therefore, a new method integrating QR decomposition and compressed sensing is proposed to solve the reconstruction problem of complex networks under the assistance of the input noise. The state matrix of the system is decomposed by QR decomposition. We construct the measurement matrix with the aid of Gaussian noise so that the sparse input matrix can be reconstructed by compressed sensing. We also discover that noise can build a bridge between the dynamics and the topological structure. Experiments are presented to show that the proposed method is more accurate and more efficient to reconstruct four model networks and six real networks by the comparisons between the proposed method and only compressed sensing. In addition, the proposed method can reconstruct not only the sparse complex networks, but also the dense complex networks.

  16. Precipitation Estimation from Remotely Sensed Data Using Deep Neural Network

    Science.gov (United States)

    Tao, Y.; Gao, X.; Hsu, K. L.; Sorooshian, S.; Ihler, A.

    2015-12-01

    This research develops a precipitation estimation system from remote sensed data using state-of-the-art machine learning algorithms. Compared to ground-based precipitation measurements, satellite-based precipitation estimation products have advantages of temporal resolution and spatial coverage. Also, the massive amount of satellite data contains various measures related to precipitation formation and development. On the other hand, deep learning algorithms were newly developed in the area of machine learning, which was a breakthrough to deal with large and complex dataset, especially to image data. Here, we attempt to engage deep learning techniques to provide hourly precipitation estimation from satellite information, such as long wave infrared data. The brightness temperature data from infrared data is considered to contain cloud information. Radar stage IV dataset is used as ground measurement for parameter calibration. Stacked denoising auto-encoders (SDAE) is applied here to build a 4-layer neural network with 1000 hidden nodes for each hidden layer. SDAE involves two major steps: (1) greedily pre-training each layer as a denoising auto-encoder using the outputs of previous trained hidden layer output starting from visible layer to initialize parameters; (2) fine-tuning the whole deep neural network with supervised criteria. The results are compared with satellite precipitation product PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Network Cloud Classification System). Based on the results, we have several valuable conclusions: By properly training the neural network, it is able to extract useful information for precipitation estimation. For example, it can reduce the mean squared error of the precipitation by 58% for the summer season in the central United States of the validation period. The SDAE method captures the shape of the precipitation from the cloud shape better compared to the CCS product. Design of

  17. Compressive sensing based data collection in wireless sensor networks

    NARCIS (Netherlands)

    Masoum, Alireza; Meratnia, Nirvana; Havinga, Paul J.M.

    2017-01-01

    Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we introduce a distributed compressive sensing approach, which utilizes spatial correlation among sensor nodes to group them

  18. A Sensing Error Aware MAC Protocol for Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Donglin Hu

    2012-08-01

    Full Text Available Cognitive radios (CR are intelligent radio devices that can sense the radio environment and adapt to changes in the radio environment. Spectrum sensing and spectrum access are the two key CR functions. In this paper, we present a spectrum sensing error aware MAC protocol for a CR network collocated with multiple primary networks. We explicitly consider both types of sensing errors in the CR MAC design, since such errors are inevitable for practical spectrum sensors and more importantly, such errors could have significant impact on the performance of the CR MAC protocol. Two spectrum sensing polices are presented, with which secondary users collaboratively sense the licensed channels. The sensing policies are then incorporated into p-Persistent CSMA to coordinate opportunistic spectrum access for CR network users.We present an analysis of the interference and throughput performance of the proposed CR MAC, and find the analysis highly accurate in our simulation studies. The proposed sensing error aware CR MAC protocol outperforms two existing approaches with considerable margins in our simulations, which justify the importance of considering spectrum sensing errors in CR MAC design.

  19. Advanced wireless mobile collaborative sensing network for tactical and strategic missions

    Science.gov (United States)

    Xu, Hao

    2017-05-01

    In this paper, an advanced wireless mobile collaborative sensing network will be developed. Through properly combining wireless sensor network, emerging mobile robots and multi-antenna sensing/communication techniques, we could demonstrate superiority of developed sensing network. To be concrete, heterogeneous mobile robots including unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) are equipped with multi-model sensors and wireless transceiver antennas. Through real-time collaborative formation control, multiple mobile robots can team the best formation that can provide most accurate sensing results. Also, formatting multiple mobile robots can also construct a multiple-input multiple-output (MIMO) communication system that can provide a reliable and high performance communication network.

  20. Cooperation Scheme For Distributed Spectrum Sensing In Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Ying Dai

    2014-09-01

    Full Text Available Spectrum sensing is an essential phase in cognitive radio networks (CRNs. It enables secondary users (SUs to access licensed spectrum, which is temporarily not occupied by the primary users (PUs. The widely used scheme of spectrum sensing is cooperative sensing, in which an SU shares its sensing results with other SUs to improve the overall sensing performance, while maximizing its throughput. For a single SU, if its sensing results are shared early, it would have more time for data transmission, which improves the throughput. However, when multiple SUs send their sensing results early, they are more likely to send out their sensing results simultaneously over the same signaling channel. Under these conditions, conflicts would likely happen. Then, both the sensing performance and throughput would be affected. Therefore, it is important to take when-to-share into account. We model the spectrum sensing as an evolutionary game. Different from previous works, the strategy set for each player in our game model contains not only whether to share its sensing results, but also when to share. The payoff for each player is defined based on the throughput, which considers the influence of the time spent both on sensing and sharing. We prove the existence of the evolutionarily stable strategy (ESS. In addition, we propose a practical algorithm for each secondary user to converge to the ESS. We conduct experiments on our testbed consisting of 4 USRP N200s. The experimental results verify for our model, including the convergence to the ESS.

  1. Implementation of Compressed Sensing in Telecardiology Sensor Networks

    Directory of Open Access Journals (Sweden)

    Eduardo Correia Pinheiro

    2010-01-01

    Compressed sensing implementation in wireless sensor networks (WSNs promises to bring gains not only in power savings to the devices, but also with minor impact in signal quality. Several cardiac signals have a sparse representation in some wavelet transformations. The compressed sensing paradigm states that signals can be recovered from a few projections into another basis, incoherent with the first. This paper evaluates the compressed sensing paradigm impact in a cardiac monitoring WSN, discussing the implications in data reliability, energy management, and the improvements accomplished by in-network processing.

  2. Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Caiyun Huang

    2014-07-01

    Full Text Available As a newly proposed theory, compressive sensing (CS is commonly used in signal processing area. This paper investigates the applications of compressed sensing (CS in wireless sensor networks (WSNs. First, the development and research status of compressed sensing technology and wireless sensor networks are described, then a detailed investigation of WSNs research based on CS are conducted from aspects of data fusion, signal acquisition, signal routing transmission, and signal reconstruction. At the end of the paper, we conclude our survey and point out the possible future research directions.

  3. Network operating system

    Science.gov (United States)

    1985-01-01

    Long-term and short-term objectives for the development of a network operating system for the Space Station are stated. The short-term objective is to develop a prototype network operating system for a 100 megabit/second fiber optic data bus. The long-term objective is to establish guidelines for writing a detailed specification for a Space Station network operating system. Major milestones are noted. Information is given in outline form.

  4. Model establishing and performance analysis of service stratum traffic in the integrated sensing network

    Science.gov (United States)

    Ge, Zhiqun; Wang, Ying; Zhang, Xiaolu; Zheng, Yu; Zhao, Xinqun; Sun, Xiaohan

    2017-01-01

    We propose a time-division hybrid-user data flow model scheme based on semi-Markov state-transition algorithm for multiclass business and service in Integrated Sensing Network (ISN). Two typical flow models, visual sense and auditory sense service models, are set up due to the real situation of service stratum traffic, respectively. The experimental system based on the Asynchronous Optical Packet Switching (AOPS) network simulation platform is established for the feasibility of the proposed data flow model. The results show that the proposed models achieve reasonable packet loss rate and delay time in the case of different business and service levels.

  5. Bridge SHM system based on fiber optical sensing technology

    Science.gov (United States)

    Li, Sheng; Fan, Dian; Fu, Jiang-hua; Huang, Xing; Jiang, De-sheng

    2015-09-01

    The latest progress of our lab in recent 10 years on the area of bridge structural health monitoring (SHM) based on optical fiber sensing technology is introduced. Firstly, in the part of sensing technology, optical fiber force test-ring, optical fiber vibration sensor, optical fiber smart cable, optical fiber prestressing loss monitoring method and optical fiber continuous curve mode inspection system are developed, which not only rich the sensor types, but also provides new monitoring means that are needed for the bridge health monitoring system. Secondly, in the optical fiber sensing network and computer system platform, the monitoring system architecture model is designed to effectively meet the integration scale and effect requirement of engineering application, especially the bridge expert system proposed integration of sensing information and informatization manual inspection to realize the mode of multi index intelligence and practical monitoring, diagnosis and evaluation. Finally, the Jingyue bridge monitoring system as the representative, the research on the technology of engineering applications are given.

  6. Traffic Based Optimization of Spectrum Sensing in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Changhua Yao

    2014-01-01

    Full Text Available We propose a more practical spectrum sensing optimization problem in cognitive radio networks (CRN, by considering the data traffic of second user (SU. Compared with most existing work, we do not assume that SU always has packets to transmit; instead, we use the actual data transmitted per second rather than the channel capacity as the achievable throughput, to reformulate the Sensing-Throughput Tradeoff problem. We mathematically analyze the problem of optimal sensing time to maximize the achievable throughput, based on the data traffic of SU. Our model is more general because the traditional Sensing-Throughput Tradeoff model can be seen as a special case of our model. We also prove that the throughput is a concave function of sensing time and there is only one optimal sensing time value which is determined by the data traffic. Simulation results show that the proposed approach outperforms existing methods.

  7. Triangulation positioning system network

    Directory of Open Access Journals (Sweden)

    Sfendourakis Marios

    2017-01-01

    Full Text Available This paper presents ongoing work on localization and positioning through triangulation procedure for a Fixed Sensors Network - FSN.The FSN has to work as a system.As the triangulation problem becomes high complicated in a case with large numbers of sensors and transmitters, an adequate grid topology is needed in order to tackle the detection complexity.For that reason a Network grid topology is presented and areas that are problematic and need further analysis are analyzed.The Network System in order to deal with problems of saturation and False Triangulations - FTRNs will have to find adequate methods in every sub-area of the Area Of Interest - AOI.Also, concepts like Sensor blindness and overall Network blindness, are presented. All these concepts affect the Network detection rate and its performance and ought to be considered in a way that the network overall performance won’t be degraded.Network performance should be monitored contentiously, with right algorithms and methods.It is also shown that as the number of TRNs and FTRNs is increased Detection Complexity - DC is increased.It is hoped that with further research all the characteristics of a triangulation system network for positioning will be gained and the system will be able to perform autonomously with a high detection rate.

  8. Efficient DV-HOP Localization for Wireless Cyber-Physical Social Sensing System: A Correntropy-Based Neural Network Learning Scheme

    Directory of Open Access Journals (Sweden)

    Yang Xu

    2017-01-01

    Full Text Available Integrating wireless sensor network (WSN into the emerging computing paradigm, e.g., cyber-physical social sensing (CPSS, has witnessed a growing interest, and WSN can serve as a social network while receiving more attention from the social computing research field. Then, the localization of sensor nodes has become an essential requirement for many applications over WSN. Meanwhile, the localization information of unknown nodes has strongly affected the performance of WSN. The received signal strength indication (RSSI as a typical range-based algorithm for positioning sensor nodes in WSN could achieve accurate location with hardware saving, but is sensitive to environmental noises. Moreover, the original distance vector hop (DV-HOP as an important range-free localization algorithm is simple, inexpensive and not related to the environment factors, but performs poorly when lacking anchor nodes. Motivated by these, various improved DV-HOP schemes with RSSI have been introduced, and we present a new neural network (NN-based node localization scheme, named RHOP-ELM-RCC, through the use of DV-HOP, RSSI and a regularized correntropy criterion (RCC-based extreme learning machine (ELM algorithm (ELM-RCC. Firstly, the proposed scheme employs both RSSI and DV-HOP to evaluate the distances between nodes to enhance the accuracy of distance estimation at a reasonable cost. Then, with the help of ELM featured with a fast learning speed with a good generalization performance and minimal human intervention, a single hidden layer feedforward network (SLFN on the basis of ELM-RCC is used to implement the optimization task for obtaining the location of unknown nodes. Since the RSSI may be influenced by the environmental noises and may bring estimation error, the RCC instead of the mean square error (MSE estimation, which is sensitive to noises, is exploited in ELM. Hence, it may make the estimation more robust against outliers. Additionally, the least square

  9. Efficient DV-HOP Localization for Wireless Cyber-Physical Social Sensing System: A Correntropy-Based Neural Network Learning Scheme.

    Science.gov (United States)

    Xu, Yang; Luo, Xiong; Wang, Weiping; Zhao, Wenbing

    2017-01-12

    Integrating wireless sensor network (WSN) into the emerging computing paradigm, e.g., cyber-physical social sensing (CPSS), has witnessed a growing interest, and WSN can serve as a social network while receiving more attention from the social computing research field. Then, the localization of sensor nodes has become an essential requirement for many applications over WSN. Meanwhile, the localization information of unknown nodes has strongly affected the performance of WSN. The received signal strength indication (RSSI) as a typical range-based algorithm for positioning sensor nodes in WSN could achieve accurate location with hardware saving, but is sensitive to environmental noises. Moreover, the original distance vector hop (DV-HOP) as an important range-free localization algorithm is simple, inexpensive and not related to the environment factors, but performs poorly when lacking anchor nodes. Motivated by these, various improved DV-HOP schemes with RSSI have been introduced, and we present a new neural network (NN)-based node localization scheme, named RHOP-ELM-RCC, through the use of DV-HOP, RSSI and a regularized correntropy criterion (RCC)-based extreme learning machine (ELM) algorithm (ELM-RCC). Firstly, the proposed scheme employs both RSSI and DV-HOP to evaluate the distances between nodes to enhance the accuracy of distance estimation at a reasonable cost. Then, with the help of ELM featured with a fast learning speed with a good generalization performance and minimal human intervention, a single hidden layer feedforward network (SLFN) on the basis of ELM-RCC is used to implement the optimization task for obtaining the location of unknown nodes. Since the RSSI may be influenced by the environmental noises and may bring estimation error, the RCC instead of the mean square error (MSE) estimation, which is sensitive to noises, is exploited in ELM. Hence, it may make the estimation more robust against outliers. Additionally, the least square estimation (LSE

  10. Smart Sensor Network System For Environment Monitoring

    Directory of Open Access Journals (Sweden)

    Javed Ali Baloch

    2012-07-01

    Full Text Available SSN (Smart Sensor Network systems could be used to monitor buildings with modern infrastructure, plant sites with chemical pollution, horticulture, natural habitat, wastewater management and modern transport system. To sense attributes of phenomena and make decisions on the basis of the sensed value is the primary goal of such systems. In this paper a Smart Spatially aware sensor system is presented. A smart system, which could continuously monitor the network to observe the functionality and trigger, alerts to the base station if a change in the system occurs and provide feedback periodically, on demand or even continuously depending on the nature of the application. The results of the simulation trials presented in this paper exhibit the performance of a Smart Spatially Aware Sensor Networks.

  11. Natural Resource Information System. Remote Sensing Studies.

    Science.gov (United States)

    Leachtenauer, J.; And Others

    A major design objective of the Natural Resource Information System entailed the use of remote sensing data as an input to the system. Potential applications of remote sensing data were therefore reviewed and available imagery interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and…

  12. Coordinated Sensing in Intelligent Camera Networks

    OpenAIRE

    Ding, Chong

    2013-01-01

    The cost and size of video sensors has led to camera networks becoming pervasive in our lives. However, the ability to analyze these images efficiently is very much a function of the quality of the acquired images. Human control of pan-tilt-zoom (PTZ) cameras is impractical and unreliable when high quality images are needed of multiple events distributed over a large area. This dissertation considers the problem of automatically controlling the fields of view of individual cameras in a camera...

  13. RSComPro: An Open Communication Protocol for Remote Sensing Systems

    DEFF Research Database (Denmark)

    Vasiljevic, Nikola; Trujillo, Juan-José

    The remote sensing protocol (RSComPro) is a communication protocol, which has been developed for controlling multiple remote sensing systems simultaneously through a UDP/IP and TPC/IP network. This protocol is meant to be open to the remote sensing community. The scope is the implementation of so...

  14. RSComPro: An Open Communication Protocol for Remote Sensing Systems

    DEFF Research Database (Denmark)

    Vasiljevic, Nikola; Trujillo, Juan-José

    The remote sensing protocol (RSComPro) is a communication protocol which has been developed for controlling multiple remote sensing systems simultaneously through a UDP/IP and TPC/IP network. This protocol is meant to be open to the remote sensing community. The scope is the implementation of so-...

  15. Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review

    OpenAIRE

    Ireyuwa E. Igbinosa; Olutayo O. Oyerinde; Viranjay M. Srivastava; Stanley Mneney

    2015-01-01

    Spectrum sensing is an important functional unit of the cognitive radio networks. The spectrum sensing is one of the main challenges encountered by cognitive radio. This paper presents a survey of spectrum sensing techniques and they are studied from a cognitive radio perspective. The challenges that go with spectrum sensing are reviewed. Two sensing schemes, namely; cooperative sensing and eigenvalue-based sensing are studied. The various advantages and disadvantages are highlighted. Based o...

  16. Computational modeling of the quorum-sensing network in bacteria

    Science.gov (United States)

    Fenley, Andrew; Banik, Suman; Kulkarni, Rahul

    2007-03-01

    Certain species of bacteria are able produce and sense the concentration of small molecules called autodinducers in order to coordinate gene regulation in response to population density, a process known as ``quorum-sensing''. The resulting regulation of gene expression involves both transcriptional and post-transcriptional regulators. In particular, the species of bacteria in the Vibrio genus use small RNAs to regulate the master protein controlling the quorum-sensing response (luminescence, biofilm formation, virulence...). We model the network of interactions using a modular approach which provides a quantitative understanding of how signal transduction occurs. The parameters of the input-module are fit to current experimental results allowing for testable predictions to be made for future experiments. The results of our analysis offer a revised perspective on quorum-sensing based regulation.

  17. Remote Sensing Wind and Wind Shear System.

    Science.gov (United States)

    Contents: Remote sensing of wind shear and the theory and development of acoustic doppler; Wind studies; A comparison of methods for the remote detection of winds in the airport environment; Acoustic doppler system development; System calibration; Airport operational tests.

  18. A mobile-agent based wireless sensing network for structural monitoring applications

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Stuart G [Los Alamos National Laboratory; Farinholt, Kevin M [Los Alamos National Laboratory; Figueiredo, Eloi [Los Alamos National Laboratory; Park, Gyuhae [Los Alamos National Laboratory; Farrar, Charles R [Los Alamos National Laboratory; Flynn, Eric B [UCSD; Mascarenas, David L [UCSD; Todd, Michael D [UCSD

    2008-01-01

    A new wireless sensing network paradigm is presented for structural monitoring applications. In this approach, both power and data interrogation commands are conveyed via a mobile agent that is sent to sensor nodes to perform intended interrogations, which can alleviate several limitations of the traditional sensing networks. Furthermore, the mobile agent provides computational power to make near real-time assessments on the structural conditions. This paper will discuss such prototype systems, which are used to interrogate impedance-based sensors for structural health monitoring applications. Our wireless sensor node is specifically designed to accept various energy sources, including wireless energy transmission, and to be wirelessly triggered on an as-needed basis by the mobile agent or other sensor nodes. The capabilities of this proposed sensing network paradigm are demonstrated in the laboratory and the field.

  19. Network systems security analysis

    Science.gov (United States)

    Yilmaz, Ä.°smail

    2015-05-01

    Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.

  20. Radar network communication through sensing of frequency hopping

    Science.gov (United States)

    Dowla, Farid; Nekoogar, Faranak

    2013-05-28

    In one embodiment, a radar communication system includes a plurality of radars having a communication range and being capable of operating at a sensing frequency and a reporting frequency, wherein the reporting frequency is different than the sensing frequency, each radar is adapted for operating at the sensing frequency until an event is detected, each radar in the plurality of radars has an identification/location frequency for reporting information different from the sensing frequency, a first radar of the radars which senses the event sends a reporting frequency corresponding to its identification/location frequency when the event is detected, and all other radars in the plurality of radars switch their reporting frequencies to match the reporting frequency of the first radar upon detecting the reporting frequency switch of a radar within the communication range. In another embodiment, a method is presented for communicating information in a radar system.

  1. Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

    Science.gov (United States)

    Missif, Lial Raja; Kadhum, Mohammad M.

    2017-09-01

    Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

  2. The missing sense modality: the immune system.

    Science.gov (United States)

    Bedford, Felice L

    2011-01-01

    The five senses were handed down by Aristotle. I argue that it has only taken two millennia to recognize that the immune system has been the hidden sensory modality. The immune system completes the range of operation allowing detection of meaningful entities at all distances, from very near to very far. It also withstands the often implicit criteria for being a sense modality. Finally, cross-modal interactions between the immune system and vision and other sense modalities should be possible, opening up new research directions.

  3. Sensing performances of pure and hybridized carbon nanotubes-ZnO nanowire networks: A detailed study.

    Science.gov (United States)

    Lupan, Oleg; Schütt, Fabian; Postica, Vasile; Smazna, Daria; Mishra, Yogendra Kumar; Adelung, Rainer

    2017-11-07

    In this work, the influence of carbon nanotube (CNT) hybridization on ultraviolet (UV) and gas sensing properties of individual and networked ZnO nanowires (NWs) is investigated in detail. The CNT concentration was varied to achieve optimal conditions for the hybrid with improved sensing properties. In case of CNT decorated ZnO nanonetworks, the influence of relative humidity (RH) and applied bias voltage on the UV sensing properties was thoroughly studied. By rising the CNT content to about 2.0 wt% (with respect to the entire ZnO network) the UV sensing response is considerably increased from 150 to 7300 (about 50 times). With respect to gas sensing, the ZnO-CNT networks demonstrate an excellent selectivity as well as a high gas response to NH3 vapor. A response of 430 to 50 ppm at room temperature was obtained, with an estimated detection limit of about 0.4 ppm. Based on those results, several devices consisting of individual ZnO NWs covered with CNTs were fabricated using a FIB/SEM system. The highest sensing performance was obtained for the finest NW with diameter (D) of 100 nm,  with a response of about 4 to 10 ppm NH3 vapor at room temperature.

  4. Sensory acquisition in active sensing systems.

    Science.gov (United States)

    Nelson, M E; MacIver, M A

    2006-06-01

    A defining feature of active sensing is the use of self-generated energy to probe the environment. Familiar biological examples include echolocation in bats and dolphins and active electrolocation in weakly electric fish. Organisms that utilize active sensing systems can potentially exert control over the characteristics of the probe energy, such as its intensity, direction, timing, and spectral characteristics. This is in contrast to passive sensing systems, which rely on extrinsic energy sources that are not directly controllable by the organism. The ability to control the probe energy adds a new dimension to the task of acquiring relevant information about the environment. Physical and ecological constraints confronted by active sensing systems include issues of signal propagation, attenuation, speed, energetics, and conspicuousness. These constraints influence the type of energy that organisms use to probe the environment, the amount of energy devoted to the process, and the way in which the nervous system integrates sensory and motor functions for optimizing sensory acquisition performance.

  5. Cognitive radio networks efficient resource allocation in cooperative sensing, cellular communications, high-speed vehicles, and smart grid

    CERN Document Server

    Jiang, Tao; Cao, Yang

    2015-01-01

    PrefaceAcknowledgmentsAbout the AuthorsIntroductionCognitive Radio-Based NetworksOpportunistic Spectrum Access NetworksCognitive Radio Networks with Cooperative SensingCognitive Radio Networks for Cellular CommunicationsCognitive Radio Networks for High-Speed VehiclesCognitive Radio Networks for a Smart GridContent and OrganizationTransmission Slot Allocation in an Opportunistic Spectrum Access NetworkSingle-User Single-Channel System ModelProbabilistic Slot Allocation SchemeOptimal Probabilistic Slot AllocationBaseline PerformanceExponential DistributionHyper-Erlang DistributionPerformance An

  6. Circular sensing networks for guided waves based structural health monitoring

    Science.gov (United States)

    Wandowski, T.; Malinowski, P. H.; Ostachowicz, W. M.

    2016-01-01

    In this paper, results of damage localization performed for four sensing network configurations are compared. Process of damage localization is based on guided waves propagation phenomenon. Guided waves are excited using piezoelectric transducer and received by scanning laser vibrometer. Different excitation frequencies are also investigated. In experimental investigations two types of piezoelectric transducers are used as guided waves exciters. Frequency-magnitude characteristics of symmetric and antisymmetric modes are created for both types of transducers. These characteristics allow a choice of an excitation frequency for efficient generation of selected wave mode. The amplitude of second mode in this case has negligibly small value. Finally, sensing networks in the form of circle with three different diameters are realized based on piezoelectric transducers. Damage localization algorithm is prepared in MATLAB® environment as well as in C++.

  7. Space remote sensing systems an introduction

    CERN Document Server

    Chen, H S

    1985-01-01

    Space Remote Sensing Systems: An Introduction discusses the space remote sensing system, which is a modern high-technology field developed from earth sciences, engineering, and space systems technology for environmental protection, resource monitoring, climate prediction, weather forecasting, ocean measurement, and many other applications. This book consists of 10 chapters. Chapter 1 describes the science of the atmosphere and the earth's surface. Chapter 2 discusses spaceborne radiation collector systems, while Chapter 3 focuses on space detector and CCD systems. The passive space optical rad

  8. Novel Spectrum Sensing Algorithms for OFDM Cognitive Radio Networks.

    Science.gov (United States)

    Shi, Zhenguo; Wu, Zhilu; Yin, Zhendong; Cheng, Qingqing

    2015-06-15

    Spectrum sensing technology plays an increasingly important role in cognitive radio networks. Consequently, several spectrum sensing algorithms have been proposed in the literature. In this paper, we present a new spectrum sensing algorithm "Differential Characteristics-Based OFDM (DC-OFDM)" for detecting OFDM signal on account of differential characteristics. We put the primary value on channel gain θ around zero to detect the presence of primary user. Furthermore, utilizing the same method of differential operation, we improve two traditional OFDM sensing algorithms (cyclic prefix and pilot tones detecting algorithms), and propose a "Differential Characteristics-Based Cyclic Prefix (DC-CP)" detector and a "Differential Characteristics-Based Pilot Tones (DC-PT)" detector, respectively. DC-CP detector is based on auto-correlation vector to sense the spectrum, while the DC-PT detector takes the frequency-domain cross-correlation of PT as the test statistic to detect the primary user. Moreover, the distributions of the test statistics of the three proposed methods have been derived. Simulation results illustrate that all of the three proposed methods can achieve good performance under low signal to noise ratio (SNR) with the presence of timing delay. Specifically, the DC-OFDM detector gets the best performance among the presented detectors. Moreover, both of the DC-CP and DC-PT detector achieve significant improvements compared with their corresponding original detectors.

  9. Equal gain combining for cooperative spectrum sensing in cognitive radio networks

    KAUST Repository

    Hamza, Doha R.

    2014-08-01

    Sensing with equal gain combining (SEGC), a novel cooperative spectrum sensing technique for cognitive radio networks, is proposed. Cognitive radios simultaneously transmit their sensing results to the fusion center (FC) over multipath fading reporting channels. The cognitive radios estimate the phases of the reporting channels and use those estimates for coherent combining of the sensing results at the FC. A global decision is made at the FC by comparing the received signal with a threshold. We obtain the global detection probabilities and secondary throughput exactly through a moment generating function approach. We verify our solution via system simulation and demonstrate that the Chernoff bound and central limit theory approximation are not tight. The cases of hard sensing and soft sensing are considered and we provide examples in which hard sensing is advantageous to soft sensing. We contrast the performance of SEGC with maximum ratio combining of the sensors\\' results and provide examples where the former is superior. Furthermore, we evaluate the performance of SEGC against existing orthogonal reporting techniques such as time division multiple access (TDMA). SEGC performance always dominates that of TDMA in terms of secondary throughput. We also study the impact of phase and synchronization errors and demonstrate the robustness of the SEGC technique against such imperfections. © 2002-2012 IEEE.

  10. Free space optical sensor network for fixed infrastructure sensing

    Science.gov (United States)

    Agrawal, Navik; Milner, Stuart D.; Davis, Christopher C.

    2009-08-01

    Free space optical (FSO) links for indoor sensor networks can provide data rates that can range from bits/s to hundreds of Mb/s. In addition, they offer physical security, and in contrast with omnidirectional RF networks, they avoid interference with other electronic systems. These features are advantageous for communication over short distances in fixed infrastructure sensor networks. In this paper the system architecture for a fixed infrastructure FSO sensor network is presented. The system includes a network of small, low power (mW), sensor systems, or "motes," that transmit data optically to a central "cluster head," which controls the network traffic of all the motes and can aggregate the sensor information. The cluster head is designed with multiple vertical cavity surface emitting lasers oriented in different directions and controlled to diverge at 12º in order to provide signal coverage over a wide field of view. Both the cluster head and motes form a local area network. Our system design focuses on low-power wireless motes that can maintain successful communication over distances up to a few meters without having to use stringent optical alignment techniques, and our network design focuses on controlling mote sleep cycles for energy efficiency. This paper presents the design as well as the experimental link and optical communications performance of a prototype FSO-based sensor network.

  11. A Single-Walled Carbon Nanotube Network Gas Sensing Device

    Directory of Open Access Journals (Sweden)

    I-Ju Teng

    2011-08-01

    Full Text Available The goal of this research was to develop a chemical gas sensing device based on single-walled carbon nanotube (SWCNT networks. The SWCNT networks are synthesized on Al2O3-deposted SiO2/Si substrates with 10 nm-thick Fe as the catalyst precursor layer using microwave plasma chemical vapor deposition (MPCVD. The development of interconnected SWCNT networks can be exploited to recognize the identities of different chemical gases by the strength of their particular surface adsorptive and desorptive responses to various types of chemical vapors. The physical responses on the surface of the SWCNT networks cause superficial changes in the electric charge that can be converted into electronic signals for identification. In this study, we tested NO2 and NH3 vapors at ppm levels at room temperature with our self-made gas sensing device, which was able to obtain responses to sensitivity changes with a concentration of 10 ppm for NO2 and 24 ppm for NH3.

  12. SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks

    Science.gov (United States)

    Lin, Likun

    Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network

  13. Compressed sensing based missing nodes prediction in temporal communication network

    Science.gov (United States)

    Cheng, Guangquan; Ma, Yang; Liu, Zhong; Xie, Fuli

    2018-02-01

    The reconstruction of complex network topology is of great theoretical and practical significance. Most research so far focuses on the prediction of missing links. There are many mature algorithms for link prediction which have achieved good results, but research on the prediction of missing nodes has just begun. In this paper, we propose an algorithm for missing node prediction in complex networks. We detect the position of missing nodes based on their neighbor nodes under the theory of compressed sensing, and extend the algorithm to the case of multiple missing nodes using spectral clustering. Experiments on real public network datasets and simulated datasets show that our algorithm can detect the locations of hidden nodes effectively with high precision.

  14. Remote sensing using MIMO systems

    Science.gov (United States)

    Bikhazi, Nicolas; Young, William F; Nguyen, Hung D

    2015-04-28

    A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.

  15. Adaptive threshold determination for efficient channel sensing in cognitive radio network using mobile sensors

    Science.gov (United States)

    Morshed, M. N.; Khatun, S.; Kamarudin, L. M.; Aljunid, S. A.; Ahmad, R. B.; Zakaria, A.; Fakir, M. M.

    2017-03-01

    Spectrum saturation problem is a major issue in wireless communication systems all over the world. Huge number of users is joining each day to the existing fixed band frequency but the bandwidth is not increasing. These requirements demand for efficient and intelligent use of spectrum. To solve this issue, the Cognitive Radio (CR) is the best choice. Spectrum sensing of a wireless heterogeneous network is a fundamental issue to detect the presence of primary users' signals in CR networks. In order to protect primary users (PUs) from harmful interference, the spectrum sensing scheme is required to perform well even in low signal-to-noise ratio (SNR) environments. Meanwhile, the sensing period is usually required to be short enough so that secondary (unlicensed) users (SUs) can fully utilize the available spectrum. CR networks can be designed to manage the radio spectrum more efficiently by utilizing the spectrum holes in primary user's licensed frequency bands. In this paper, we have proposed an adaptive threshold detection method to detect presence of PU signal using free space path loss (FSPL) model in 2.4 GHz WLAN network. The model is designed for mobile sensors embedded in smartphones. The mobile sensors acts as SU while the existing WLAN network (channels) works as PU. The theoretical results show that the desired threshold range detection of mobile sensors mainly depends on the noise floor level of the location in consideration.

  16. Poster Abstract: Towards a Categorization Framework for Occupancy Sensing Systems

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun; Lazarova-Molnar, Sanja; Jradi, Muhyiddine

    2015-01-01

    on occupancy sensing systems goes beyond basic methods, there is an increasing need for better comparison of proposed occupancy sensing systems. Developers of occupancy sensing systems are also lacking good frameworks for understanding different options when building occupancy sensing systems. This poster...

  17. Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

    Directory of Open Access Journals (Sweden)

    Laisen Nie

    2018-01-01

    Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

  18. Path Network Recovery Using Remote Sensing Data and Geospatial-Temporal Semantic Graphs

    Energy Technology Data Exchange (ETDEWEB)

    McLendon, William C.,; Brost, Randolph

    2016-05-01

    Remote sensing systems produce large volumes of high-resolution images that are difficult to search. The GeoGraphy (pronounced Geo-Graph-y) framework [2, 20] encodes remote sensing imagery into a geospatial-temporal semantic graph representation to enable high level semantic searches to be performed. Typically scene objects such as buildings and trees tend to be shaped like blocks with few holes, but other shapes generated from path networks tend to have a large number of holes and can span a large geographic region due to their connectedness. For example, we have a dataset covering the city of Philadelphia in which there is a single road network node spanning a 6 mile x 8 mile region. Even a simple question such as "find two houses near the same street" might give unexpected results. More generally, nodes arising from networks of paths (roads, sidewalks, trails, etc.) require additional processing to make them useful for searches in GeoGraphy. We have assigned the term Path Network Recovery to this process. Path Network Recovery is a three-step process involving (1) partitioning the network node into segments, (2) repairing broken path segments interrupted by occlusions or sensor noise, and (3) adding path-aware search semantics into GeoQuestions. This report covers the path network recovery process, how it is used, and some example use cases of the current capabilities.

  19. Network operating system

    Science.gov (United States)

    Perotto, E.

    1987-08-01

    The Network Operating System is an addition to CMS designed to allow multitasking operation, while conserving all the facilities of CMS: file system, interactivity, high level language environment. Multitasking is useful for server virtual machines, e.g. Network Transport Managers, File Managers, Disk space Managers, Tape Unit Managers, where the execution of a task involves long waits due to I/O completion, VCMF communication delays or human responses, during which the task status stays as a control block in memory, while the virtual machine serves other users executing the same lines of code. Multitasking is not only for multi-user service: a big data reduction program may run as a main task, while a side task, connected to the virtual console, gives reports on the ongoing work of the main task in response to user commands and steers the main task through common data. All the service routines (Wait, Create and Delete Task, Get and Release Buffer, VMCF Open and Close Link, Send and Receive, I/O and Console Routines) are FORTRAN callable, and may be used from any language environment consistent with the same parameter passing conventions. The outstanding feature of this system is efficiency, no user defined SVC are used, and the use of other privileged instructions as LPSW or SSM is the bare necessary, so that CP (with the associated overhead) is not too involved. System code and read-only data are write-protected with a different storage key from CMS and user program.

  20. Study on cooperative active sensing system

    Energy Technology Data Exchange (ETDEWEB)

    Kita, Nobuyuki [Electrotechnical Lab., Tsukuba, Ibaraki (Japan)

    1996-05-01

    Electrotechnical Laboratory is involved in the development and the improvement of three dimensional geometrical modeling for the work environment including various kinds of robots. Here, the research on the system which allows to materialize an active sensing by the cooperation of robots and the construction of an experimental system for the assessment of such modeling were reviewed. In the second stage of this project, the development of cooperative active sensory system with small size mobile robots as an operation platform was attempted. Thus, studies on the sensing techniques for robot operation and the real-time sensing techniques were started. An electric binocular head was prepared after consideration of size, cost and convenience and attached to the commercially available mobile robot base (Mouse 89, Japan System Design Co., Ltd.). The small mobile robot capable of binocular visual tracing thus obtained was confirmed to be highly efficient by various cooperative control experiments although the head was prepared at the sacrifice of control characteristics. Next, a real-time sensing system which allows to trace a moving object was constructed on the basis of Zero Disparity Filter (ZDF) produced by Kaenel et al. and further improved in the respect of the difficulty in real time processing and an expanded type ZDF was obtained. This system is routinely used as an basic vision unit for a mobile robot in the presence. (M.N.)

  1. A patch-based convolutional neural network for remote sensing image classification.

    Science.gov (United States)

    Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

    2017-11-01

    Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. A Web Service-based framework model for people-centric sensing applications applied to social networking.

    Science.gov (United States)

    Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

    2012-01-01

    As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

  3. Real time network traffic monitoring for wireless local area networks based on compressed sensing

    Science.gov (United States)

    Balouchestani, Mohammadreza

    2017-05-01

    A wireless local area network (WLAN) is an important type of wireless networks which connotes different wireless nodes in a local area network. WLANs suffer from important problems such as network load balancing, large amount of energy, and load of sampling. This paper presents a new networking traffic approach based on Compressed Sensing (CS) for improving the quality of WLANs. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, which is a good record for WLANs. The proposed architecture is increased Data Throughput (DT) to 22 % and Signal to Noise (S/N) ratio to 17 %, which provide a good background for establishing high qualified local area networks. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog-CS framework is applied at the sensing step before analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed algorithm out-performs existing algorithms by achieving a good level of Quality of Service (QoS). This ability allows reducing 15 % of Bit Error Rate (BER) at each wireless node.

  4. [Odor sensing system and olfactory display].

    Science.gov (United States)

    Nakamoto, Takamichi

    2014-01-01

    In this review, an odor sensing system and an olfactory display are introduced into people in pharmacy. An odor sensing system consists of an array of sensors with partially overlapping specificities and pattern recognition technique. One of examples of odor sensing systems is a halitosis sensor which quantifies the mixture composition of three volatile sulfide compounds. A halitosis sensor was realized using a preconcentrator to raise sensitivity and an electrochemical sensor array to suppress the influence of humidity. Partial least squares (PLS) method was used to quantify the mixture composition. The experiment reveals that the sufficient accuracy was obtained. Moreover, the olfactory display, which present scents to human noses, is explained. A multi-component olfactory display enables the presentation of a variety of smells. The two types of multi-component olfactory display are described. The first one uses many solenoid valves with high speed switching. The valve ON frequency determines the concentration of the corresponding odor component. The latter one consists of miniaturized liquid pumps and a surface acoustic wave (SAW) atomizer. It enables the wearable olfactory display without smell persistence. Finally, the application of the olfactory display is demonstrated. Virtual ice cream shop with scents was made as a content of interactive art. People can enjoy harmony among vision, audition and olfaction. In conclusion, both odor sensing system and olfactory display can contribute to the field of human health care.

  5. Demonstration of UAV deployment and control of mobile wireless sensing networks for modal analysis of structures

    Science.gov (United States)

    Zhou, Hao; Hirose, Mitsuhito; Greenwood, William; Xiao, Yong; Lynch, Jerome; Zekkos, Dimitrios; Kamat, Vineet

    2016-04-01

    Unmanned aerial vehicles (UAVs) can serve as a powerful mobile sensing platform for assessing the health of civil infrastructure systems. To date, the majority of their uses have been dedicated to vision and laser-based spatial imaging using on-board cameras and LiDAR units, respectively. Comparatively less work has focused on integration of other sensing modalities relevant to structural monitoring applications. The overarching goal of this study is to explore the ability for UAVs to deploy a network of wireless sensors on structures for controlled vibration testing. The study develops a UAV platform with an integrated robotic gripper that can be used to install wireless sensors in structures, drop a heavy weight for the introduction of impact loads, and to uninstall wireless sensors for reinstallation elsewhere. A pose estimation algorithm is embedded in the UAV to estimate the location of the UAV during sensor placement and impact load introduction. The Martlet wireless sensor network architecture is integrated with the UAV to provide the UAV a mobile sensing capability. The UAV is programmed to command field deployed Martlets, aggregate and temporarily store data from the wireless sensor network, and to communicate data to a fixed base station on site. This study demonstrates the integrated UAV system using a simply supported beam in the lab with Martlet wireless sensors placed by the UAV and impact load testing performed. The study verifies the feasibility of the integrated UAV-wireless monitoring system architecture with accurate modal characteristics of the beam estimated by modal analysis.

  6. Computer Networks A Systems Approach

    CERN Document Server

    Peterson, Larry L

    2011-01-01

    This best-selling and classic book teaches you the key principles of computer networks with examples drawn from the real world of network and protocol design. Using the Internet as the primary example, the authors explain various protocols and networking technologies. Their systems-oriented approach encourages you to think about how individual network components fit into a larger, complex system of interactions. Whatever your perspective, whether it be that of an application developer, network administrator, or a designer of network equipment or protocols, you will come away with a "big pictur

  7. Intelligent hand-portable proliferation sensing system

    Energy Technology Data Exchange (ETDEWEB)

    Dieckman, S.L.; Bostrom, G.A.; Waterfield, L.G.; Jendrzejczyk, J.A.; Ahuja, S.; Raptis, A.C.

    1997-08-01

    Argonne National Laboratory, with support from DOE`s Office of Nonproliferation and National Security, is currently developing an intelligent hand-portable sensor system. This system is designed specifically to support the intelligence community with the task of in-field sensing of nuclear proliferation and related activities. Based upon pulsed laser photo-ionization time-of-flight mass spectrometry technology, this novel sensing system is capable of quickly providing a molecular or atomic analysis of specimens. The system is capable of analyzing virtually any gas phase molecule, or molecule that can be induced into the gas phase by (for example) sample heating. This system has the unique advantages of providing unprecedented portability, excellent sensitivity, tremendous fieldability, and a high performance/cost ratio. The system will be capable of operating in a highly automated manner for on-site inspections, and easily modified for other applications such as perimeter monitoring aboard a plane or drone. The paper describes the sensing system.

  8. Ultra Small Integrated Optical Fiber Sensing System

    Directory of Open Access Journals (Sweden)

    Peter Van Daele

    2012-09-01

    Full Text Available This paper introduces a revolutionary way to interrogate optical fiber sensors based on fiber Bragg gratings (FBGs and to integrate the necessary driving optoelectronic components with the sensor elements. Low-cost optoelectronic chips are used to interrogate the optical fibers, creating a portable dynamic sensing system as an alternative for the traditionally bulky and expensive fiber sensor interrogation units. The possibility to embed these laser and detector chips is demonstrated resulting in an ultra thin flexible optoelectronic package of only 40 μm, provided with an integrated planar fiber pigtail. The result is a fully embedded flexible sensing system with a thickness of only 1 mm, based on a single Vertical-Cavity Surface-Emitting Laser (VCSEL, fiber sensor and photodetector chip. Temperature, strain and electrodynamic shaking tests have been performed on our system, not limited to static read-out measurements but dynamically reconstructing full spectral information datasets.

  9. Microsensors to the Model Forecasts: Multiscale Embedded Networked Sensing of Nutrients in the Watershed

    Science.gov (United States)

    Harmon, T. C.

    2005-12-01

    Hydrologic and water quality observatories are being planned with a vision of enhancing our ability to better understand, forecast and adaptively manage both water quantity and quality. To adequately cover these spatially and temporally variable systems, distributed, embedded sensor networks must be designed with the proper mix (multimodality) of sensors to quantify key system properties, including temperature and chemical distributions, as well as mass and energy fluxes, and to do so across multiple scales. Given resource limitations, process models need to be coupled to the sensor network to interpolate between sensor data. This work focuses on the spatially distributed flux of nutrients, specifically nitrate, in surface-subsurface environments. It begins at the sensor level, describing the development and testing of nitrate microsensors that are scaleable to large, dense sensor networks required to cover heterogeneous watersheds, including associated soil and sediment systems. First and second generation miniature and inexpensive nitrate sensors (ion selective electrodes) fabricated by depositing conducting polymers on carbon substrates are presented in the context of laboratory and field tests. While these sensors are limited to relatively short deployments (4-8 weeks), there are potential strategies for overcoming this problem. Scale-up to one- and three-dimensional soil/sediment sensor arrays is discussed in the context of two deployments: (1) a groundwater quality protection network, where recycled wastewater that is potentially high in nitrate is being used for agricultural irrigation, and (2) nonpoint source nitrate pollution in rivers and groundwater in agricultural watersheds. Recent hardware (wireless transceivers) and software advancements (e.g., network topology design and debugging, energy management) intended for networks spanning 100s of m in space are outlined in these examples. The discussion extends to sensor form factor, in situ calibration

  10. Opportunistic Sensing in Train Safety Systems

    NARCIS (Netherlands)

    Scholten, Johan; Bakker, Pascal

    2011-01-01

    Train safety systems are complex and expensive, and changing them requires huge investments. Changes are evolutionary and small. Current developments, like faster - high speed - trains and a higher train density on the railway network, have initiated research on safety systems that can cope with the

  11. Network of networks in Linux operating system

    Science.gov (United States)

    Wang, Haoqin; Chen, Zhen; Xiao, Guanping; Zheng, Zheng

    2016-04-01

    Operating system represents one of the most complex man-made systems. In this paper, we analyze Linux Operating System (LOS) as a complex network via modeling functions as nodes and function calls as edges. It is found that for the LOS network and modularized components within it, the out-degree follows an exponential distribution and the in-degree follows a power-law distribution. For better understanding the underlying design principles of LOS, we explore the coupling correlations of components in LOS from aspects of topology and function. The result shows that the component for device drivers has a strong manifestation in topology while a weak manifestation in function. However, the component for process management shows the contrary phenomenon. Moreover, in an effort to investigate the impact of system failures on networks, we make a comparison between the networks traced from normal and failure status of LOS. This leads to a conclusion that the failure will change function calls which should be executed in normal status and introduce new function calls in the meanwhile.

  12. Compressive Sensing for Feedback Reduction in Wireless Multiuser Networks

    KAUST Repository

    Elkhalil, Khalil

    2015-05-01

    User/relay selection is a simple technique that achieves spatial diversity in multiuser networks. However, for user/relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating users/relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed-back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. Motivated by the aforementioned challenges, we propose a limited feedback user/relay selection scheme that is based on the theory of compressed sensing. Firstly, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback air-time. Following that, the CSI of the selected relays is estimated using minimum mean square error estimation without any additional feedback. To minimize the effect of noise on the fed-back CSI, we introduce a back-off strategy that optimally backs-off on the noisy received CSI. In the second part of the thesis, we propose a feedback reduction scheme for full-duplex relay-aided multiuser networks. The proposed scheme permits the base station (BS) to obtain channel state information (CSI) from a subset of strong users under substantially reduced feedback overhead. More specifically, we cast the problem of user identification and CSI estimation as a block sparse signal recovery problem in compressive sensing (CS). Using existing CS block recovery algorithms, we first obtain the identity of the strong users and then estimate their CSI using the best linear unbiased estimator (BLUE). Moreover, we derive the

  13. Views of wireless network systems.

    Energy Technology Data Exchange (ETDEWEB)

    Young, William Frederick; Duggan, David Patrick

    2003-10-01

    Wireless networking is becoming a common element of industrial, corporate, and home networks. Commercial wireless network systems have become reliable, while the cost of these solutions has become more affordable than equivalent wired network solutions. The security risks of wireless systems are higher than wired and have not been studied in depth. This report starts to bring together information on wireless architectures and their connection to wired networks. We detail information contained on the many different views of a wireless network system. The method of using multiple views of a system to assist in the determination of vulnerabilities comes from the Information Design Assurance Red Team (IDART{trademark}) Methodology of system analysis developed at Sandia National Laboratories.

  14. Mapping biological systems to network systems

    CERN Document Server

    Rathore, Heena

    2016-01-01

    The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

  15. Remote shock sensing and notification system

    Energy Technology Data Exchange (ETDEWEB)

    Muralidharan, Govindarajan [Knoxville, TN; Britton, Charles L [Alcoa, TN; Pearce, James [Lenoir City, TN; Jagadish, Usha [Knoxville, TN; Sikka, Vinod K [Oak Ridge, TN

    2010-11-02

    A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interface circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitter with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

  16. Remote shock sensing and notification system

    Science.gov (United States)

    Muralidharan, Govindarajan; Britton, Charles L.; Pearce, James; Jagadish, Usha; Sikka, Vinod K.

    2008-11-11

    A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interference circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitting with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

  17. Reciprocally-Benefited Secure Transmission for Spectrum Sensing-Based Cognitive Radio Sensor Networks.

    Science.gov (United States)

    Wang, Dawei; Ren, Pinyi; Du, Qinghe; Sun, Li; Wang, Yichen

    2016-11-25

    The rapid proliferation of independently-designed and -deployed wireless sensor networks extremely crowds the wireless spectrum and promotes the emergence of cognitive radio sensor networks (CRSN). In CRSN, the sensor node (SN) can make full use of the unutilized licensed spectrum, and the spectrum efficiency is greatly improved. However, inevitable spectrum sensing errors will adversely interfere with the primary transmission, which may result in primary transmission outage. To compensate the adverse effect of spectrum sensing errors, we propose a reciprocally-benefited secure transmission strategy, in which SN's interference to the eavesdropper is employed to protect the primary confidential messages while the CRSN is also rewarded with a loose spectrum sensing error probability constraint. Specifically, according to the spectrum sensing results and primary users' activities, there are four system states in this strategy. For each state, we analyze the primary secrecy rate and the SN's transmission rate by taking into account the spectrum sensing errors. Then, the SN's transmit power is optimally allocated for each state so that the average transmission rate of CRSN is maximized under the constraint of the primary maximum permitted secrecy outage probability. In addition, the performance tradeoff between the transmission rate of CRSN and the primary secrecy outage probability is investigated. Moreover, we analyze the primary secrecy rate for the asymptotic scenarios and derive the closed-form expression of the SN's transmission outage probability. Simulation results show that: (1) the performance of the SN's average throughput in the proposed strategy outperforms the conventional overlay strategy; (2) both the primary network and CRSN benefit from the proposed strategy.

  18. Hierarchies in light sensing and dynamic interactions between ocular and extraocular sensory networks in a flatworm

    Science.gov (United States)

    Shettigar, Nishan; Joshi, Asawari; Dalmeida, Rimple; Gopalkrishna, Rohini; Chakravarthy, Anirudh; Patnaik, Siddharth; Mathew, Manoj; Palakodeti, Dasaradhi; Gulyani, Akash

    2017-01-01

    Light sensing has independently evolved multiple times under diverse selective pressures but has been examined only in a handful among the millions of light-responsive organisms. Unsurprisingly, mechanistic insights into how differential light processing can cause distinct behavioral outputs are limited. We show how an organism can achieve complex light processing with a simple “eye” while also having independent but mutually interacting light sensing networks. Although planarian flatworms lack wavelength-specific eye photoreceptors, a 25 nm change in light wavelength is sufficient to completely switch their phototactic behavior. Quantitative photoassays, eye-brain confocal imaging, and RNA interference/knockdown studies reveal that flatworms are able to compare small differences in the amounts of light absorbed at the eyes through a single eye opsin and convert them into binary behavioral outputs. Because planarians can fully regenerate, eye-brain injury-regeneration studies showed that this acute light intensity sensing and processing are layered on simple light detection. Unlike intact worms, partially regenerated animals with eyes can sense light but cannot sense finer gradients. Planarians also show a “reflex-like,” eye-independent (extraocular/whole-body) response to low ultraviolet A light, apart from the “processive” eye-brain–mediated (ocular) response. Competition experiments between ocular and extraocular sensory systems reveal dynamic interchanging hierarchies. In intact worms, cerebral ocular response can override the reflex-like extraocular response. However, injury-regeneration again offers a time window wherein both responses coexist, but the dominance of the ocular response is reversed. Overall, we demonstrate acute light intensity–based behavioral switching and two evolutionarily distinct but interacting light sensing networks in a regenerating organism. PMID:28782018

  19. Centralized cooperative spectrum sensing for ad-hoc disaster relief network clusters

    DEFF Research Database (Denmark)

    Pratas, Nuno; Marchetti, Nicola; Prasad, Neeli R.

    2010-01-01

    Disaster relief networks have to be highly adaptable and resilient. Cognitive radio enhanced ad-hoc architecture have been put forward as a candidate to enable such networks. Spectrum sensing is the cornerstone of the cognitive radio paradigm, and it has been the target of intensive research....... The main common conclusion was that the achievable spectrum sensing accuracy can be greatly enhanced through the use of cooperative sensing schemes. When considering applying Cognitive Radio to ad-hoc disaster relief networks, spectrum sensing cooperative schemes are paramount. A centralized cluster...

  20. Risks in Networked Computer Systems

    OpenAIRE

    Klingsheim, André N.

    2008-01-01

    Networked computer systems yield great value to businesses and governments, but also create risks. The eight papers in this thesis highlight vulnerabilities in computer systems that lead to security and privacy risks. A broad range of systems is discussed in this thesis: Norwegian online banking systems, the Norwegian Automated Teller Machine (ATM) system during the 90's, mobile phones, web applications, and wireless networks. One paper also comments on legal risks to bank cust...

  1. Quorum sensing and social networking in the microbial world.

    Science.gov (United States)

    Atkinson, Steve; Williams, Paul

    2009-11-06

    For many years, bacterial cells were considered primarily as selfish individuals, but, in recent years, it has become evident that, far from operating in isolation, they coordinate collective behaviour in response to environmental challenges using sophisticated intercellular communication networks. Cell-to-cell communication between bacteria is mediated by small diffusible signal molecules that trigger changes in gene expression in response to fluctuations in population density. This process, generally referred to as quorum sensing (QS), controls diverse phenotypes in numerous Gram-positive and Gram-negative bacteria. Recent advances have revealed that bacteria are not limited to communication within their own species but are capable of 'listening in' and 'broadcasting to' unrelated species to intercept messages and coerce cohabitants into behavioural modifications, either for the good of the population or for the benefit of one species over another. It is also evident that QS is not limited to the bacterial kingdom. The study of two-way intercellular signalling networks between bacteria and both uni- and multicellular eukaryotes as well as between eukaryotes is just beginning to unveil a rich diversity of communication pathways.

  2. Building Extraction from Remote Sensing Data Using Fully Convolutional Networks

    Science.gov (United States)

    Bittner, K.; Cui, S.; Reinartz, P.

    2017-05-01

    Building detection and footprint extraction are highly demanded for many remote sensing applications. Though most previous works have shown promising results, the automatic extraction of building footprints still remains a nontrivial topic, especially in complex urban areas. Recently developed extensions of the CNN framework made it possible to perform dense pixel-wise classification of input images. Based on these abilities we propose a methodology, which automatically generates a full resolution binary building mask out of a Digital Surface Model (DSM) using a Fully Convolution Network (FCN) architecture. The advantage of using the depth information is that it provides geometrical silhouettes and allows a better separation of buildings from background as well as through its invariance to illumination and color variations. The proposed framework has mainly two steps. Firstly, the FCN is trained on a large set of patches consisting of normalized DSM (nDSM) as inputs and available ground truth building mask as target outputs. Secondly, the generated predictions from FCN are viewed as unary terms for a Fully connected Conditional Random Fields (FCRF), which enables us to create a final binary building mask. A series of experiments demonstrate that our methodology is able to extract accurate building footprints which are close to the buildings original shapes to a high degree. The quantitative and qualitative analysis show the significant improvements of the results in contrast to the multy-layer fully connected network from our previous work.

  3. BUILDING EXTRACTION FROM REMOTE SENSING DATA USING FULLY CONVOLUTIONAL NETWORKS

    Directory of Open Access Journals (Sweden)

    K. Bittner

    2017-05-01

    Full Text Available Building detection and footprint extraction are highly demanded for many remote sensing applications. Though most previous works have shown promising results, the automatic extraction of building footprints still remains a nontrivial topic, especially in complex urban areas. Recently developed extensions of the CNN framework made it possible to perform dense pixel-wise classification of input images. Based on these abilities we propose a methodology, which automatically generates a full resolution binary building mask out of a Digital Surface Model (DSM using a Fully Convolution Network (FCN architecture. The advantage of using the depth information is that it provides geometrical silhouettes and allows a better separation of buildings from background as well as through its invariance to illumination and color variations. The proposed framework has mainly two steps. Firstly, the FCN is trained on a large set of patches consisting of normalized DSM (nDSM as inputs and available ground truth building mask as target outputs. Secondly, the generated predictions from FCN are viewed as unary terms for a Fully connected Conditional Random Fields (FCRF, which enables us to create a final binary building mask. A series of experiments demonstrate that our methodology is able to extract accurate building footprints which are close to the buildings original shapes to a high degree. The quantitative and qualitative analysis show the significant improvements of the results in contrast to the multy-layer fully connected network from our previous work.

  4. Opportunistic Relay Selection in Multicast Relay Networks using Compressive Sensing

    KAUST Repository

    Elkhalil, Khalil

    2014-12-01

    Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. However, for relay selection algorithms to make a selection decision, channel state information (CSI) from all cooperating relays is usually required at a central node. This requirement poses two important challenges. Firstly, CSI acquisition generates a great deal of feedback overhead (air-time) that could result in significant transmission delays. Secondly, the fed back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. In this paper, we introduce a limited feedback relay selection algorithm for a multicast relay network. The proposed algorithm exploits the theory of compressive sensing to first obtain the identity of the “strong” relays with limited feedback. Following that, the CSI of the selected relays is estimated using linear minimum mean square error estimation. To minimize the effect of noise on the fed back CSI, we introduce a back-off strategy that optimally backs-off on the noisy estimated CSI. For a fixed group size, we provide closed form expressions for the scaling law of the maximum equivalent SNR for both Decode and Forward (DF) and Amplify and Forward (AF) cases. Numerical results show that the proposed algorithm drastically reduces the feedback air-time and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback channels.

  5. [Network structures in biological systems].

    Science.gov (United States)

    Oleskin, A V

    2013-01-01

    Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

  6. Language Networks as Complex Systems

    Science.gov (United States)

    Lee, Max Kueiming; Ou, Sheue-Jen

    2008-01-01

    Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

  7. Financial Network Systemic Risk Contributions

    NARCIS (Netherlands)

    Hautsch, N.; Schaumburg, J.; Schienle, M.

    2015-01-01

    We propose the realized systemic risk beta as a measure of financial companies' contribution to systemic risk, given network interdependence between firms' tail risk exposures. Conditional on statistically pre-identified network spillover effects and market and balance sheet information, we define

  8. Wireless sensor systems for sense/decide/act/communicate.

    Energy Technology Data Exchange (ETDEWEB)

    Berry, Nina M.; Cushner, Adam; Baker, James A.; Davis, Jesse Zehring; Stark, Douglas P.; Ko, Teresa H.; Kyker, Ronald D.; Stinnett, Regan White; Pate, Ronald C.; Van Dyke, Colin; Kyckelhahn, Brian

    2003-12-01

    After 9/11, the United States (U.S.) was suddenly pushed into challenging situations they could no longer ignore as simple spectators. The War on Terrorism (WoT) was suddenly ignited and no one knows when this war will end. While the government is exploring many existing and potential technologies, the area of wireless Sensor networks (WSN) has emerged as a foundation for establish future national security. Unlike other technologies, WSN could provide virtual presence capabilities needed for precision awareness and response in military, intelligence, and homeland security applications. The Advance Concept Group (ACG) vision of Sense/Decide/Act/Communicate (SDAC) sensor system is an instantiation of the WSN concept that takes a 'systems of systems' view. Each sensing nodes will exhibit the ability to: Sense the environment around them, Decide as a collective what the situation of their environment is, Act in an intelligent and coordinated manner in response to this situational determination, and Communicate their actions amongst each other and to a human command. This LDRD report provides a review of the research and development done to bring the SDAC vision closer to reality.

  9. Networking systems design and development

    CERN Document Server

    Chao, Lee

    2009-01-01

    Effectively integrating theory and hands-on practice, Networking Systems Design and Development provides students and IT professionals with the knowledge and skills needed to design, implement, and manage fully functioning network systems using readily available Linux networking tools. Recognizing that most students are beginners in the field of networking, the text provides step-by-step instruction for setting up a virtual lab environment at home. Grounded in real-world applications, this book provides the ideal blend of conceptual instruction and lab work to give students and IT professional

  10. Communicating embedded systems networks applications

    CERN Document Server

    Krief, Francine

    2013-01-01

    Embedded systems become more and more complex and require having some knowledge in various disciplines such as electronics, data processing, telecommunications and networks. Without detailing all the aspects related to the design of embedded systems, this book, which was written by specialists in electronics, data processing and telecommunications and networks, gives an interesting point of view of communication techniques and problems in embedded systems. This choice is easily justified by the fact that embedded systems are today massively communicating and that telecommunications and network

  11. Remote management for multipoint sensing systems using hetero-core spliced optical fiber sensors.

    Science.gov (United States)

    Goh, Lee See; Anoda, Yuji; Kazuhiro, Watanabe; Shinomiya, Norihiko

    2013-12-27

    This paper describes the design and experimental verification of a multipoint sensing system with hetero-core spliced optical fiber sensors and its remote management using an internet-standard protocol. The study proposes two different types of design and conducts experiments to verify those systems' feasibility. In order to manage the sensing systems remotely, the management method uses a standard operation and maintenance protocol for internet: the Simple Network Management Protocol is proposed. The purpose of this study is to construct a multipoint sensing system remote management tool by which the system can also determine the status and the identity of fiber optic sensors. The constructed sensing systems are verified and the results have demonstrated that the first proposed system can distinguish the responses from different hetero-core spliced optical fiber sensors remotely. The second proposed system shows that data communications are performed successfully while identifying the status of hetero-core spliced optical fiber sensors remotely.

  12. Reverse Engineering Sparse Gene Regulatory Networks Using Cubature Kalman Filter and Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Amina Noor

    2013-01-01

    Full Text Available This paper proposes a novel algorithm for inferring gene regulatory networks which makes use of cubature Kalman filter (CKF and Kalman filter (KF techniques in conjunction with compressed sensing methods. The gene network is described using a state-space model. A nonlinear model for the evolution of gene expression is considered, while the gene expression data is assumed to follow a linear Gaussian model. The hidden states are estimated using CKF. The system parameters are modeled as a Gauss-Markov process and are estimated using compressed sensing-based KF. These parameters provide insight into the regulatory relations among the genes. The Cramér-Rao lower bound of the parameter estimates is calculated for the system model and used as a benchmark to assess the estimation accuracy. The proposed algorithm is evaluated rigorously using synthetic data in different scenarios which include different number of genes and varying number of sample points. In addition, the algorithm is tested on the DREAM4 in silico data sets as well as the in vivo data sets from IRMA network. The proposed algorithm shows superior performance in terms of accuracy, robustness, and scalability.

  13. Optimisation of sensing time and transmission time in cognitive radio-based smart grid networks

    Science.gov (United States)

    Yang, Chao; Fu, Yuli; Yang, Junjie

    2016-07-01

    Cognitive radio (CR)-based smart grid (SG) networks have been widely recognised as emerging communication paradigms in power grids. However, a sufficient spectrum resource and reliability are two major challenges for real-time applications in CR-based SG networks. In this article, we study the traffic data collection problem. Based on the two-stage power pricing model, the power price is associated with the efficient received traffic data in a metre data management system (MDMS). In order to minimise the system power price, a wideband hybrid access strategy is proposed and analysed, to share the spectrum between the SG nodes and CR networks. The sensing time and transmission time are jointly optimised, while both the interference to primary users and the spectrum opportunity loss of secondary users are considered. Two algorithms are proposed to solve the joint optimisation problem. Simulation results show that the proposed joint optimisation algorithms outperform the fixed parameters (sensing time and transmission time) algorithms, and the power cost is reduced efficiently.

  14. Delays and networked control systems

    CERN Document Server

    Hetel, Laurentiu; Daafouz, Jamal; Johansson, Karl

    2016-01-01

    This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students. .

  15. A Terminal Area Icing Remote Sensing System

    Science.gov (United States)

    Reehorst, Andrew L.; Serke, David J.

    2014-01-01

    NASA and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology is now being extended to provide volumetric coverage surrounding an airport. With volumetric airport terminal area coverage, the resulting icing hazard information will be usable by aircrews, traffic control, and airline dispatch to make strategic and tactical decisions regarding routing when conditions are conducive to airframe icing. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize cloud radar, microwave radiometry, and NEXRAD radar. This terminal area icing remote sensing system will use the data streams from these instruments to provide icing hazard classification along the defined approach paths into an airport. Strategies for comparison to in-situ instruments on aircraft and weather balloons for a planned NASA field test are discussed, as are possible future applications into the NextGen airspace system.

  16. Interorganizational Innovation in Systemic Networks

    DEFF Research Database (Denmark)

    Seemann, Janne; Dinesen, Birthe; Gustafsson, Jeppe

    2013-01-01

    that linear n-stage models by reducing complexity and flux end up focusing only on the surface of the network and are thus unable to grasp important aspects of network dynamics. The paper suggests that there is a need for a more dynamic innovation model able to grasp the whole picture of dynamics in systemic...... patients with chronic obstructive pulmonary disease (COPD) to avoid readmission, perform self monitoring and to maintain rehabilitation in their homes. The aim of the paper is to identify, analyze and discuss innovation dynamics in the COPD network and on a preliminary basis to identify implications...... for managing innovations in systemic networks. The main argument of this paper is that innovation dynamics in systemic networks should be understood as a complex interplay of four logics: 1) Fragmented innovation, 2) Interface innovation, 3) Competing innovation, 4) Co-innovation. The findings indicate...

  17. Asynchronous control for networked systems

    CERN Document Server

    Rubio, Francisco; Bencomo, Sebastián

    2015-01-01

    This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

  18. Performance of Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Yingwei Zhang

    2013-01-01

    Full Text Available Data packet dropout is a special kind of time delay problem. In this paper, predictive controllers for networked control systems (NCSs with dual-network are designed by model predictive control method. The contributions are as follows. (1 The predictive control problem of the dual-network is considered. (2 The predictive performance of the dual-network is evaluated. (3 Compared to the popular networked control systems, the optimal controller of the new NCSs with data packets dropout is designed, which can minimize infinite performance index at each sampling time and guarantee the closed-loop system stability. Finally, the simulation results show the feasibility and effectiveness of the controllers designed.

  19. Energy Minimization Approach for Cooperative Spectrum Sensing in Cognitive Radio Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    I. Mustapha

    2017-08-01

    Full Text Available Cooperative spectrum sensing is a promising method for improving spectrum sensing performance in cognitive radio. Although it yields better spectrum sensing performance, it also incurs additional energy consumption that drains more energy from the sensor nodes and hence shortens the lifetime of sensor networks. This paper proposes energy minimization approach to reduce energy consumption due to spectrum sensing and sensed result reporting in a cooperative spectrum sensing. The approach determines optimal number of cooperative sensing nodes using particle swarm optimization. We derived mathematical lower bound and upper bound for the number of cooperative sensing nodes in the network. Then we formulate a constraint optimization problem and used particle swarm optimization to simultaneously optimize the two mathematical bounds to determine the optimal number of sensing nodes. Simulation results indicate viability of the proposed approach and show that significant amount of energy savings can be achieved by employing optimal number of sensing nodes for cooperative spectrum sensing. Performance comparison with conventional approach shows performance improvement of the proposed approach over the conventional method in minimizing spectrum sensing energy consumption without compromising spectrum sensing performance.

  20. Remote Management for Multipoint Sensing Systems Using Hetero-Core Spliced Optical Fiber Sensors

    Directory of Open Access Journals (Sweden)

    Lee See Goh

    2013-12-01

    Full Text Available This paper describes the design and experimental verification of a multipoint sensing system with hetero-core spliced optical fiber sensors and its remote management using an internet-standard protocol. The study proposes two different types of design and conducts experiments to verify those systems’ feasibility. In order to manage the sensing systems remotely, the management method uses a standard operation and maintenance protocol for internet: the Simple Network Management Protocol is proposed. The purpose of this study is to construct a multipoint sensing system remote management tool by which the system can also determine the status and the identity of fiber optic sensors. The constructed sensing systems are verified and the results have demonstrated that the first proposed system can distinguish the responses from different hetero-core spliced optical fiber sensors remotely. The second proposed system shows that data communications are performed successfully while identifying the status of hetero-core spliced optical fiber sensors remotely.

  1. An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network

    Energy Technology Data Exchange (ETDEWEB)

    Dong, Bing; Lam, Khee Poh; Zhang, Rui; Chiou, Yun-Shang [Center for Building Performance and Diagnostics, Carnegie Mellon University, Pittsburgh, PA 15213 (United States); Andrews, Burton; Hoeynck, Michael; Benitez, Diego [Research and Technology Center, Robert BOSCH LLC, Pittsburgh, PA 15212 (United States)

    2010-07-15

    This paper describes a large-scale wireless and wired environmental sensor network test-bed and its application to occupancy detection in an open-plan office building. Detection of occupant presence has been used extensively in built environments for applications such as demand-controlled ventilation and security; however, the ability to discern the actual number of people in a room is beyond the scope of current sensing techniques. To address this problem, a complex sensor network is deployed in the Robert L. Preger Intelligent Workplace comprising a wireless ambient-sensing system, a wired carbon dioxide sensing system, and a wired indoor air quality sensing system. A wired camera network is implemented as well for establishing true occupancy levels to be used as ground truth information for deriving algorithmic relationships with the environment conditions. To our knowledge, this extensive and diverse ambient-sensing infrastructure of the ITEST setup as well as the continuous data-collection capability is unprecedented. Final results indicate that there are significant correlations between measured environmental conditions and occupancy status. An average of 73% accuracy on the occupancy number detection was achieved by Hidden Markov Models during testing periods. This paper serves as an exploration to the research of ITEST for occupancy detection in offices. In addition, its utility extends to a wide variety of other building technology research areas such as human-centered environmental control, security, energy efficient and sustainable green buildings. (author)

  2. Remote Sensing Image Fusion with Convolutional Neural Network

    Science.gov (United States)

    Zhong, Jinying; Yang, Bin; Huang, Guoyu; Zhong, Fei; Chen, Zhongze

    2016-12-01

    Remote sensing image fusion (RSIF) is referenced as restoring the high-resolution multispectral image from its corresponding low-resolution multispectral (LMS) image aided by the panchromatic (PAN) image. Most RSIF methods assume that the missing spatial details of the LMS image can be obtained from the high resolution PAN image. However, the distortions would be produced due to the much difference between the structural component of LMS image and that of PAN image. Actually, the LMS image can fully utilize its spatial details to improve the resolution. In this paper, a novel two-stage RSIF algorithm is proposed, which makes full use of both spatial details and spectral information of the LMS image itself. In the first stage, the convolutional neural network based super-resolution is used to increase the spatial resolution of the LMS image. In the second stage, Gram-Schmidt transform is employed to fuse the enhanced MS and the PAN images for further improvement the resolution of MS image. Since the spatial resolution enhancement in the first stage, the spectral distortions in the fused image would be decreased in evidence. Moreover, the spatial details can be preserved to construct the fused images. The QuickBird satellite source images are used to test the performances of the proposed method. The experimental results demonstrate that the proposed method can achieve better spatial details and spectral information simultaneously compared with other well-known methods.

  3. Hybrid Accuracy-Time Trade-off Solution for Spectrum Sensing in Cognitive Radio Networks

    DEFF Research Database (Denmark)

    Ivanov, Antoni Stefkov; Mihovska, Albena Dimitrova; Poulkov, Vladimir

    2018-01-01

    The rise of the cognitive radio systems as a concept for future networks has seen a great amount of scientific effort in the recent years. Appropriately, much attention is given to how the vital function of spectrum sensing should be executed. The cognitive radio device is required to be able...... parameters, therefore, a suitable trade-off is necessary for an optimal efficiency. We propose a dual-approach solution. The decision about the spectrum occupancy is made using the measured signal-to-noise ratio (SNR) and the received signal levels as inputs in a fuzzy logic algorithm. The result...

  4. A polygon model for wireless sensor network deployment with directional sensing areas.

    Science.gov (United States)

    Wu, Chun-Hsien; Chung, Yeh-Ching

    2009-01-01

    The modeling of the sensing area of a sensor node is essential for the deployment algorithm of wireless sensor networks (WSNs). In this paper, a polygon model is proposed for the sensor node with directional sensing area. In addition, a WSN deployment algorithm is presented with topology control and scoring mechanisms to maintain network connectivity and improve sensing coverage rate. To evaluate the proposed polygon model and WSN deployment algorithm, a simulation is conducted. The simulation results show that the proposed polygon model outperforms the existed disk model and circular sector model in terms of the maximum sensing coverage rate.

  5. Airborne multidimensional integrated remote sensing system

    Science.gov (United States)

    Xu, Weiming; Wang, Jianyu; Shu, Rong; He, Zhiping; Ma, Yanhua

    2006-12-01

    In this paper, we present a kind of airborne multidimensional integrated remote sensing system that consists of an imaging spectrometer, a three-line scanner, a laser ranger, a position & orientation subsystem and a stabilizer PAV30. The imaging spectrometer is composed of two sets of identical push-broom high spectral imager with a field of view of 22°, which provides a field of view of 42°. The spectral range of the imaging spectrometer is from 420nm to 900nm, and its spectral resolution is 5nm. The three-line scanner is composed of two pieces of panchromatic CCD and a RGB CCD with 20° stereo angle and 10cm GSD(Ground Sample Distance) with 1000m flying height. The laser ranger can provide height data of three points every other four scanning lines of the spectral imager and those three points are calibrated to match the corresponding pixels of the spectral imager. The post-processing attitude accuracy of POS/AV 510 used as the position & orientation subsystem, which is the aerial special exterior parameters measuring product of Canadian Applanix Corporation, is 0.005° combined with base station data. The airborne multidimensional integrated remote sensing system was implemented successfully, performed the first flying experiment on April, 2005, and obtained satisfying data.

  6. Learning-Based Spectrum Sensing for Cognitive Radio Systems

    Directory of Open Access Journals (Sweden)

    Yasmin Hassan

    2012-01-01

    Full Text Available This paper presents a novel pattern recognition approach to spectrum sensing in collaborative cognitive radio systems. In the proposed scheme, discriminative features from the received signal are extracted at each node and used by a classifier at a central node to make a global decision about the availability of spectrum holes for use by the cognitive radio network. Specifically, linear and polynomial classifiers are proposed with energy, cyclostationary, or coherent features. Simulation results in terms of detection and false alarm probabilities of all proposed schemes are presented. It is concluded that cyclostationary-based schemes are the most reliable in terms of detecting primary users in the spectrum, however, at the expense of a longer sensing time compared to coherent based schemes. Results show that the performance is improved by having more users collaborating in providing features to the classifier. It is also shown that, in this spectrum sensing application, a linear classifier has a comparable performance to a second-order polynomial classifier and hence provides a better choice due to its simplicity. Finally, the impact of the observation window on the detection performance is presented.

  7. RECOMMENDER SYSTEMS IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Cleomar Valois Batista Jr

    2011-12-01

    Full Text Available The continued and diversified growth of social networks has changed the way in which users interact with them. With these changes, what once was limited to social contact is now used for exchanging ideas and opinions, creating the need for new features. Users have so much information at their fingertips that they are unable to process it by themselves; hence, the need to develop new tools. Recommender systems were developed to address this need and many techniques were used for different approaches to the problem. To make relevant recommendations, these systems use large sets of data, not taking the social network of the user into consideration. Developing a recommender system that takes into account the social network of the user is another way of tackling the problem. The purpose of this project is to use the theory of six degrees of separation (Watts 2003 amongst users of a social network to enhance existing recommender systems.

  8. Wireless Sensor Network Based Smart Parking System

    Directory of Open Access Journals (Sweden)

    Jeffrey JOSEPH

    2014-01-01

    Full Text Available Ambient Intelligence is a vision in which various devices come together and process information from multiple sources in order to exert control on the physical environment. In addition to computation and control, communication plays a crucial role in the overall functionality of such a system. Wireless Sensor Networks are one such class of networks, which meet these criteria. These networks consist of spatially distributed sensor motes which work in a co-operative manner to sense and control the environment. In this work, an implementation of an energy-efficient and cost-effective, wireless sensor networks based vehicle parking system for a multi-floor indoor parking facility has been introduced. The system monitors the availability of free parking slots and guides the vehicle to the nearest free slot. The amount of time the vehicle has been parked is monitored for billing purposes. The status of the motes (dead/alive is also recorded. Information like slot allocated, directions to the slot and billing data is sent as a message to customer’s mobile phones. This paper extends our previous work 1 with the development of a low cost sensor mote, about one tenth the cost of a commercially available mote, keeping in mind the price sensitive markets of the developing countries.

  9. Micro-system inertial sensing technology overview.

    Energy Technology Data Exchange (ETDEWEB)

    Allen, James Joe

    2009-02-01

    The purpose of this report is to provide an overview of Micro-System technology as it applies to inertial sensing. Transduction methods are reviewed with capacitance and piezoresistive being the most often used in COTS Micro-electro-mechanical system (MEMS) inertial sensors. Optical transduction is the most recent transduction method having significant impact on improving sensor resolution. A few other methods are motioned which are in a R&D status to hopefully allow MEMS inertial sensors to become viable as a navigation grade sensor. The accelerometer, gyroscope and gravity gradiometer are the type of inertial sensors which are reviewed in this report. Their method of operation and a sampling of COTS sensors and grade are reviewed as well.

  10. Distributed fiber optic moisture intrusion sensing system

    Science.gov (United States)

    Weiss, Jonathan D.

    2003-06-24

    Method and system for monitoring and identifying moisture intrusion in soil such as is contained in landfills housing radioactive and/or hazardous waste. The invention utilizes the principle that moist or wet soil has a higher thermal conductance than dry soil. The invention employs optical time delay reflectometry in connection with a distributed temperature sensing system together with heating means in order to identify discrete areas within a volume of soil wherein temperature is lower. According to the invention an optical element and, optionally, a heating element may be included in a cable or other similar structure and arranged in a serpentine fashion within a volume of soil to achieve efficient temperature detection across a large area or three dimensional volume of soil. Remediation, moisture countermeasures, or other responsive action may then be coordinated based on the assumption that cooler regions within a soil volume may signal moisture intrusion where those regions are located.

  11. SYMBIOTIC SENSING: Exploring and Exploiting Cooperative Sensing in Heterogeneous Sensor Networks

    NARCIS (Netherlands)

    Le Viet Duc, L Duc

    2016-01-01

    During the last several years we have witnessed the emergence of smartphone-based sensing applications that include activity recognition, urban sensing, social sensing, and health monitoring. In fact, most smartphones have various sensors, wireless communication interfaces, a large memory capacity,

  12. Building a sense of virtual community: the role of the features of social networking sites.

    Science.gov (United States)

    Chen, Chi-Wen; Lin, Chiun-Sin

    2014-07-01

    In recent years, social networking sites have received increased attention because of the potential of this medium to transform business by building virtual communities. However, theoretical and empirical studies investigating how specific features of social networking sites contribute to building a sense of virtual community (SOVC)-an important dimension of a successful virtual community-are rare. Furthermore, SOVC scales have been developed, and research on this issue has been called for, but few studies have heeded this call. On the basis of prior literature, this study proposes that perceptions of the three most salient features of social networking sites-system quality (SQ), information quality (IQ), and social information exchange (SIE)-play a key role in fostering SOVC. In particular, SQ is proposed to increase IQ and SIE, and SIE is proposed to enhance IQ, both of which thereafter build SOVC. The research model was examined in the context of Facebook, one of the most popular social networking sites in the world. We adopted Blanchard's scales to measure SOVC. Data gathered using a Web-based questionnaire, and analyzed with partial least squares, were utilized to test the model. The results demonstrate that SIE, SQ, and IQ are the factors that form SOVC. The findings also suggest that SQ plays a fundamental role in supporting SIE and IQ in social networking sites. Implications for theory, practice, and future research directions are discussed.

  13. A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients.

    Science.gov (United States)

    Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

    2016-02-05

    Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they are susceptible to subjective factors; (2) they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information.

  14. A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients

    Science.gov (United States)

    Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

    2016-01-01

    Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they are susceptible to subjective factors; (2) they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information. PMID:26861337

  15. A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients

    Directory of Open Access Journals (Sweden)

    Lei Yu

    2016-02-01

    Full Text Available Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1 they are susceptible to subjective factors; (2 they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information.

  16. Stretchable Electronic Sensors of Nanocomposite Network Films for Ultrasensitive Chemical Vapor Sensing.

    Science.gov (United States)

    Yan, Hong; Zhong, Mengjuan; Lv, Ze; Wan, Pengbo

    2017-11-01

    A stretchable, transparent, and body-attachable chemical sensor is assembled from the stretchable nanocomposite network film for ultrasensitive chemical vapor sensing. The stretchable nanocomposite network film is fabricated by in situ preparation of polyaniline/MoS2 (PANI/MoS2 ) nanocomposite in MoS2 suspension and simultaneously nanocomposite deposition onto prestrain elastomeric polydimethylsiloxane substrate. The assembled stretchable electronic sensor demonstrates ultrasensitive sensing performance as low as 50 ppb, robust sensing stability, and reliable stretchability for high-performance chemical vapor sensing. The ultrasensitive sensing performance of the stretchable electronic sensors could be ascribed to the synergistic sensing advantages of MoS2 and PANI, higher specific surface area, the reliable sensing channels of interconnected network, and the effectively exposed sensing materials. It is expected to hold great promise for assembling various flexible stretchable chemical vapor sensors with ultrasensitive sensing performance, superior sensing stability, reliable stretchability, and robust portability to be potentially integrated into wearable electronics for real-time monitoring of environment safety and human healthcare. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Cooperative spectrum sensing schemes with the interference constraint in cognitive radio networks.

    Science.gov (United States)

    Do, Tri-Nhu; An, Beongku

    2014-05-05

    In this paper, we propose cooperative spectrum sensing schemes, called decode-and-forward cooperative spectrum sensing (DF-CSS) scheme and amplify-and-forward cooperative spectrum sensing (AF-CSS) scheme, in cognitive radio networks. The main goals and features of the proposed cooperative spectrum sensing schemes are as follows: first, we solve the problem of high demand for bandwidth in a soft decision scheme using in our proposed schemes. Furthermore, the impact of transmission power of relaying users which is determined by the interference constraint on sensing performance of cooperative spectrum sensing schemes is also investigated. Second, we analyze the sensing performance of our proposed cooperative spectrum sensing schemes in terms of detection probability and interference probability, respectively. We take into account the interference caused by secondary user (SU) to primary user (PU) in the case that the transmission power of the relaying users exceeds a predefined interference constraint assigned by the primary user. The simulation results show that in cooperative spectrum sensing schemes the total sensing performance depends not only on the interference tolerance level, but also on the relay protocols used. We also prove that high transmission power of relaying users increases the interference between the secondary networks and the primary network.

  18. Phone-sized whispering-gallery microresonator sensing system

    CERN Document Server

    Xu, Xiangyi; Zhao, Guangming; Yang, Lan

    2016-01-01

    We develop a compact whispering-gallery-mode (WGM) sensing system by integrating multiple components, including a tunable laser, a temperature controller, a function generator, an oscilloscope, a photodiode detector, and a testing computer, into a phone-sized embedded system. We demonstrate a thermal sensing experiment by using this portable system. Such a system successfully eliminates bulky measurement equipment required for characterizing optical resonators and will open up new avenues for practical sensing applications by using ultra-high Q WGM resonators.

  19. Remote sensing validation through SOOP technology: implementation of Spectra system

    Science.gov (United States)

    Piermattei, Viviana; Madonia, Alice; Bonamano, Simone; Consalvi, Natalizia; Caligiore, Aurelio; Falcone, Daniela; Puri, Pio; Sarti, Fabio; Spaccavento, Giovanni; Lucarini, Diego; Pacci, Giacomo; Amitrano, Luigi; Iacullo, Salvatore; D'Andrea, Salvatore; Marcelli, Marco

    2017-04-01

    The development of low-cost instrumentation plays a key role in marine environmental studies and represents one of the most innovative aspects of marine research. The availability of low-cost technologies allows the realization of extended observatory networks for the study of marine phenomena through an integrated approach merging observations, remote sensing and operational oceanography. Marine services and practical applications critically depends on the availability of large amount of data collected with sufficiently dense spatial and temporal sampling. This issue directly influences the robustness both of ocean forecasting models and remote sensing observations through data assimilation and validation processes, particularly in the biological domain. For this reason it is necessary the development of cheap, small and integrated smart sensors, which could be functional both for satellite data validation and forecasting models data assimilation as well as to support early warning systems for environmental pollution control and prevention. This is particularly true in coastal areas, which are subjected to multiple anthropic pressures. Moreover, coastal waters can be classified like case 2 waters, where the optical properties of inorganic suspended matter and chromophoric dissolved organic matter must be considered and separated by the chlorophyll a contribution. Due to the high costs of mooring systems, research vessels, measure platforms and instrumentation a big effort was dedicated to the design, development and realization of a new low cost mini-FerryBox system: Spectra. Thanks to the modularity and user-friendly employment of the system, Spectra allows to acquire continuous in situ measures of temperature, conductivity, turbidity, chlorophyll a and chromophoric dissolved organic matter (CDOM) fluorescences from voluntary vessels, even by non specialized operators (Marcelli et al., 2014; 2016). This work shows the preliminary application of this technology to

  20. Multilevel Complex Networks and Systems

    Science.gov (United States)

    Caldarelli, Guido

    2014-03-01

    Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.

  1. Neural networks for learning and prediction with applications to remote sensing and speech perception

    Science.gov (United States)

    Gjaja, Marin N.

    1997-11-01

    Neural networks for supervised and unsupervised learning are developed and applied to problems in remote sensing, continuous map learning, and speech perception. Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART networks synthesize fuzzy logic and neural networks, and supervised ARTMAP networks incorporate ART modules for prediction and classification. New ART and ARTMAP methods resulting from analyses of data structure, parameter specification, and category selection are developed. Architectural modifications providing flexibility for a variety of applications are also introduced and explored. A new methodology for automatic mapping from Landsat Thematic Mapper (TM) and terrain data, based on fuzzy ARTMAP, is developed. System capabilities are tested on a challenging remote sensing problem, prediction of vegetation classes in the Cleveland National Forest from spectral and terrain features. After training at the pixel level, performance is tested at the stand level, using sites not seen during training. Results are compared to those of maximum likelihood classifiers, back propagation neural networks, and K-nearest neighbor algorithms. Best performance is obtained using a hybrid system based on a convex combination of fuzzy ARTMAP and maximum likelihood predictions. This work forms the foundation for additional studies exploring fuzzy ARTMAP's capability to estimate class mixture composition for non-homogeneous sites. Exploratory simulations apply ARTMAP to the problem of learning continuous multidimensional mappings. A novel system architecture retains basic ARTMAP properties of incremental and fast learning in an on-line setting while adding components to solve this class of problems. The perceptual magnet effect is a language-specific phenomenon arising early in infant speech development that is characterized by a warping of speech sound perception. An

  2. Development of the gravity sensing system.

    Science.gov (United States)

    Peusner, K D

    2001-01-15

    The utricle and saccule contain hair cells, which are the peripheral sensors of change in gravity that transmit signals regarding these changes to the neural components of the vestibular system. Although the fundamental neural pathways, especially the vestibular reflex pathways, have been investigated extensively, the principals underlying the functional development of this system are under study at present. The objective of this review is to identify the gravity-sensing components of the vestibular system and to present an overview of the research performed on their development. The second part of this review is focused on one important aspect of development, the emergence of electrical excitability using the chick tangential vestibular nucleus as a model. The importance of this research to understanding vestibular compensation and vestibular disturbance during spaceflight is considered. Because there is a conservation of the fundamental pathways and function in vertebrate phylogeny from birds through mammals, findings from studies on avians should contribute significantly to understanding the mechanisms operating in mammals. Also, we expect that as the events and basic mechanisms underlying normal vestibular development are revealed, these will provide practical tools to investigate the pattern of recovery from dysfunction of the vestibular system. This is related to the evidence suggesting that recovery of function in different systems and cell lines, including neurons, involves repeating certain patterns established during development. Copyright 2001 Wiley-Liss, Inc.

  3. Effectiveness of compressed sensing and transmission in wireless sensor networks for structural health monitoring

    Science.gov (United States)

    Fujiwara, Takahiro; Uchiito, Haruki; Tokairin, Tomoya; Kawai, Hiroyuki

    2017-04-01

    Regarding Structural Health Monitoring (SHM) for seismic acceleration, Wireless Sensor Networks (WSN) is a promising tool for low-cost monitoring. Compressed sensing and transmission schemes have been drawing attention to achieve effective data collection in WSN. Especially, SHM systems installing massive nodes of WSN require efficient data transmission due to restricted communications capability. The dominant frequency band of seismic acceleration is occupied within 100 Hz or less. In addition, the response motions on upper floors of a structure are activated at a natural frequency, resulting in induced shaking at the specified narrow band. Focusing on the vibration characteristics of structures, we introduce data compression techniques for seismic acceleration monitoring in order to reduce the amount of transmission data. We carry out a compressed sensing and transmission scheme by band pass filtering for seismic acceleration data. The algorithm executes the discrete Fourier transform for the frequency domain and band path filtering for the compressed transmission. Assuming that the compressed data is transmitted through computer networks, restoration of the data is performed by the inverse Fourier transform in the receiving node. This paper discusses the evaluation of the compressed sensing for seismic acceleration by way of an average error. The results present the average error was 0.06 or less for the horizontal acceleration, in conditions where the acceleration was compressed into 1/32. Especially, the average error on the 4th floor achieved a small error of 0.02. Those results indicate that compressed sensing and transmission technique is effective to reduce the amount of data with maintaining the small average error.

  4. TinyONet: A Cache-Based Sensor Network Bridge Enabling Sensing Data Reusability and Customized Wireless Sensor Network Services

    Directory of Open Access Journals (Sweden)

    Yong-Jin Park

    2008-12-01

    Full Text Available In recent years, a few protocol bridge research projects have been announced to enable a seamless integration of Wireless Sensor Networks (WSNs with the TCP/IP network. These studies have ensured the transparent end-to-end communication between two network sides in the node-centric manner. Researchers expect this integration will trigger the development of various application domains. However, prior research projects have not fully explored some essential features for WSNs, especially the reusability of sensing data and the data-centric communication. To resolve these issues, we suggested a new protocol bridge system named TinyONet. In TinyONet, virtual sensors play roles as virtual counterparts of physical sensors and they dynamically group to make a functional entity, Slice. Instead of direct interaction with individual physical sensors, each sensor application uses its own WSN service provided by Slices. If a new kind of service is required in TinyONet, the corresponding function can be dynamically added at runtime. Beside the data-centric communication, it also supports the node-centric communication and the synchronous access. In order to show the effectiveness of the system, we implemented TinyONet on an embedded Linux machine and evaluated it with several experimental scenarios.

  5. The Fundamental Framework of Remote Sensing Validation System

    Science.gov (United States)

    Jiang, X.-G.; Xi, X.-H.; Wu, M.-J.; Li, Z.-L.

    2009-04-01

    Remote sensing is a very complicated course. It is influenced by many factors, such as speciality of remote sensing sensor, radiant transmission characteristic of atmosphere, work environment of remote sensing platform, data transmission, data reception, data processing, and property of observed object etc. Whether the received data is consistent with the design specifications? Can the data meet the demands of remote sensing applications? How about the accuracy of the data products, retrieval products and application products of remote sensing? It is essential to carry out the validation to assess the data quality and application potential. Validation is effective approach to valuate remote sensing products. It is the significant link between remote sensing data and information. Research on remote sensing validation is very important for sensor development, data quality analysis and control. This paper focuses on the study of remote sensing validation and validation system. Different from the previous work done by other researchers, we study the validation from the viewpoint of systematic engineering considering that validation is involved with many aspects as talked about. Validation is not just a single and simple course. It is complicated system. Validation system is the important part of whole earth observation system. First of all, in this paper the category of remote sensing validation is defined. Remote sensing validation includes not only the data products validation, but also the retrieval products validation and application products validation. Second, the new concept, remote sensing validation system, is proposed. Then, the general framework, software structure and functions of validation system are studied and put forward. The validation system is composed of validation field module, data acquirement module, data processing module, data storage and management module, data scaling module, and remote sensing products validation module. And finally the

  6. A novel statistical spring-bead based network model for self-sensing smart polymer materials

    Science.gov (United States)

    Zhang, Jinjun; Koo, Bonsung; Liu, Yingtao; Zou, Jin; Chattopadhyay, Aditi; Dai, Lenore

    2015-08-01

    This paper presents a multiscale modeling approach to simulating the self-sensing behavior of a load sensitive smart polymer material. A statistical spring-bead based network model is developed to bridge the molecular dynamics simulations at the nanoscale and the finite element model at the macroscale. Parametric studies are conducted on the developed network model to investigate the effects of the thermoset crosslinking degree on the mechanical response of the self-sensing material. A comparison between experimental and simulation results shows that the multiscale framework is able to capture the global mechanical response with adequate accuracy and the network model is also capable of simulating the self-sensing phenomenon of the smart polymer. Finally, the molecular dynamics simulation and network model based simulation are implemented to evaluate damage initiation in the self-sensing material under monotonic loading.

  7. [Evaluation of eco-environmental quality based on artificial neural network and remote sensing techniques].

    Science.gov (United States)

    Li, Hongyi; Shi, Zhou; Sha, Jinming; Cheng, Jieliang

    2006-08-01

    In the present study, vegetation, soil brightness, and moisture indices were extracted from Landsat ETM remote sensing image, heat indices were extracted from MODIS land surface temperature product, and climate index and other auxiliary geographical information were selected as the input of neural network. The remote sensing eco-environmental background value of standard interest region evaluated in situ was selected as the output of neural network, and the back propagation (BP) neural network prediction model containing three layers was designed. The network was trained, and the remote sensing eco-environmental background value of Fuzhou in China was predicted by using software MATLAB. The class mapping of remote sensing eco-environmental background values based on evaluation standard showed that the total classification accuracy was 87. 8%. The method with a scheme of prediction first and classification then could provide acceptable results in accord with the regional eco-environment types.

  8. Compressive sensing reconstruction of feed-forward connectivity in pulse-coupled nonlinear networks

    Science.gov (United States)

    Barranca, Victor J.; Zhou, Douglas; Cai, David

    2016-06-01

    Utilizing the sparsity ubiquitous in real-world network connectivity, we develop a theoretical framework for efficiently reconstructing sparse feed-forward connections in a pulse-coupled nonlinear network through its output activities. Using only a small ensemble of random inputs, we solve this inverse problem through the compressive sensing theory based on a hidden linear structure intrinsic to the nonlinear network dynamics. The accuracy of the reconstruction is further verified by the fact that complex inputs can be well recovered using the reconstructed connectivity. We expect this Rapid Communication provides a new perspective for understanding the structure-function relationship as well as compressive sensing principle in nonlinear network dynamics.

  9. Planning Tripoli Metro Network by the Use of Remote Sensing Imagery

    Science.gov (United States)

    Alhusain, O.; Engedy, Gy.; Milady, A.; Paulini, L.; Soos, G.

    2012-08-01

    Tripoli, the capital city of Libya is going through significant and integrated development process, this development is expected to continue in the next few decades. The Libyan authorities have put it as their goal to develop Tripoli to an important metropolis in North Africa. To achieve this goal, they identified goals for the city's future development in all human, economic, cultural, touristic, and nonetheless infrastructure levels. On the infrastructure development level, among other things, they have identified the development of public transportation as one of the important development priorities. At present, public transportation in Tripoli is carried out by a limited capacity bus network alongside of individual transportation. However, movement in the city is characterized mainly by individual transportation with all its disadvantages such as traffic jams, significant air pollution with both carbon monoxide and dust, and lack of parking space. The Libyan authorities wisely opted for an efficient, modern, and environment friendly solution for public transportation, this was to plan a complex Metro Network as the backbone of public transportation in the city, and to develop and integrate the bus network and other means of transportation to be in harmony with the planned Metro network. The Metro network is planned to provide convenient connections to Tripoli International Airport and to the planned Railway station. They plan to build a system of Park and Ride (P+R) facilities at suitable locations along the Metro lines. This paper will present in details the planned Metro Network, some of the applied technological solutions, the importance of applying remote sensing and GIS technologies in different planning phases, and problems and benefits associated with the use of multi-temporal-, multi-format spatial data in the whole network planning phase.

  10. Promoting Social Network Awareness: A Social Network Monitoring System

    Science.gov (United States)

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  11. Optimal periodic cooperative spectrum sensing based on weight fusion in cognitive radio networks.

    Science.gov (United States)

    Liu, Xin; Jia, Min; Gu, Xuemai; Tan, Xuezhi

    2013-04-19

    The performance of cooperative spectrum sensing in cognitive radio (CR) networks depends on the sensing mode, the sensing time and the number of cooperative users. In order to improve the sensing performance and reduce the interference to the primary user (PU), a periodic cooperative spectrum sensing model based on weight fusion is proposed in this paper. Moreover, the sensing period, the sensing time and the searching time are optimized, respectively. Firstly the sensing period is optimized to improve the spectrum utilization and reduce the interference, then the joint optimization algorithm of the local sensing time and the number of cooperative users, is proposed to obtain the optimal sensing time for improving the throughput of the cognitive radio user (CRU) during each period, and finally the water-filling principle is applied to optimize the searching time in order to make the CRU find an idle channel within the shortest time. The simulation results show that compared with the previous algorithms, the optimal sensing period can improve the spectrum utilization of the CRU and decrease the interference to the PU significantly, the optimal sensing time can make the CRU achieve the largest throughput, and the optimal searching time can make the CRU find an idle channel with the least time.

  12. An integrated risk sensing system for geo-structural safety

    Directory of Open Access Journals (Sweden)

    H.W. Huang

    2017-04-01

    Full Text Available Over the last decades, geo-structures are experiencing a rapid development in China. The potential risks inherent in the huge amount of construction and asset operation projects in China were well managed in the major project, i.e. the project of Shanghai Yangtze tunnel in 2002. Since then, risk assessment of geo-structures has been gradually developed from a qualitative manner to a quantitative manner. However, the current practices of risk management have been paid considerable attention to the assessment, but little on risk control. As a result, the responses to risks occurrences after a comprehensive assessment are basically too late. In this paper, a smart system for risk sensing incorporating the wireless sensor network (WSN on-site visualization techniques and the resilience-based repair strategy was proposed. The merit of this system is the real-time monitoring for geo-structural performance and dynamic pre-warning for safety of on-site workers. The sectional convergence, joint opening, and seepage of segmental lining of shield tunnel were monitored by the micro-electro-mechanical systems (MEMS based sensors. The light emitting diode (LED coupling with the above WSN system was used to indicate different risk levels on site. By sensing the risks and telling the risks in real time, the geo-risks could be controlled and the safety of geo-structures could be assured to a certain degree. Finally, a resilience-based analysis model was proposed for designing the repair strategy by using the measured data from the WSN system. The application and efficiency of this system have been validated by two cases including Shanghai metro tunnel and underwater road tunnel.

  13. Epidermal electronic systems for sensing and therapy

    Science.gov (United States)

    Lu, Nanshu; Ameri, Shideh K.; Ha, Taewoo; Nicolini, Luke; Stier, Andrew; Wang, Pulin

    2017-04-01

    Epidermal electronic system is a class of hair thin, skin soft, stretchable sensors and electronics capable of continuous and long-term physiological sensing and clinical therapy when applied on human skin. The high cost of manpower, materials, and photolithographic facilities associated with its manufacture limit the availability of disposable epidermal electronics. We have invented a cost and time effective, completely dry, benchtop "cut-and-paste" method for the green, freeform and portable manufacture of epidermal electronics within minutes. We have applied the "cut-and-paste" method to manufacture epidermal electrodes, hydration and temperature sensors, conformable power-efficient heaters, as well as cuffless continuous blood pressure monitors out of metal thin films, two-dimensional (2D) materials, and piezoelectric polymer sheets. For demonstration purpose, we will discuss three examples of "cut-and-pasted" epidermal electronic systems in this paper. The first will be submicron thick, transparent epidermal graphene electrodes that can be directly transferred to human skin like a temporary transfer tattoo and can measure electrocardiogram (ECG) with signal-to-noise ratio and motion artifacts on par with conventional gel electrodes. The second will be a chest patch which houses both electrodes and pressure sensors for the synchronous measurements of ECG and seismocardiogram (SCG) such that beat-to-beat blood pressure can be inferred from the time interval between the R peak of the ECG and the AC peak of the SCG. The last example will be a highly conformable, low power consumption epidermal heater for thermal therapy.

  14. Multiparameter fiber optic sensing system for monitoring enhanced geothermal systems

    Energy Technology Data Exchange (ETDEWEB)

    Challener, William A

    2014-12-04

    The goal of this project was to design, fabricate and test an optical fiber cable which supports multiple sensing modalities for measurements in the harsh environment of enhanced geothermal systems. To accomplish this task, optical fiber was tested at both high temperatures and strains for mechanical integrity, and in the presence of hydrogen for resistance to darkening. Both single mode (SM) and multimode (MM) commercially available optical fiber were identified and selected for the cable based on the results of these tests. The cable was designed and fabricated using a tube-within-tube construction containing two MM fibers and one SM fiber, and without supporting gel that is not suitable for high temperature environments. Commercial fiber optic sensing instruments using Raman DTS (distributed temperature sensing), Brillouin DTSS (distributed temperature and strain sensing), and Raleigh COTDR (coherent optical time domain reflectometry) were selected for field testing. A microelectromechanical systems (MEMS) pressure sensor was designed, fabricated, packaged, and calibrated for high pressure measurements at high temperatures and spliced to the cable. A fiber Bragg grating (FBG) temperature sensor was also spliced to the cable. A geothermal well was selected and its temperature and pressure were logged. The cable was then deployed in the well in two separate field tests and measurements were made on these different sensing modalities. Raman DTS measurements were found to be accurate to ±5°C, even with some residual hydrogen darkening. Brillouin DTSS measurements were in good agreement with the Raman results. The Rayleigh COTDR instrument was able to detect some acoustic signatures, but was generally disappointing. The FBG sensor was used to determine the effects of hydrogen darkening, but drift over time made it unreliable as a temperature or pressure sensor. The MEMS sensor was found to be highly stable and accurate to better than its 0.1% calibration.

  15. Remote sensing and simulation modeling for on-demand irrigation systems management

    NARCIS (Netherlands)

    Urso, D' G.; Menenti, M.; Santini, A.

    1995-01-01

    This paper describes a procedure for monitoring and improving the performance of on-demand irrigation networks, based on the integration of remote sensing techniques and simulation modelling of water flow in each component of the system. In order to adequately reproduce the actual operation of an

  16. Remote sensing and simulation modelling for on-demand irrigation systems management

    NARCIS (Netherlands)

    Urso, D' G.; Menenti, M.; Santini, A.

    1996-01-01

    This paper describes a procedure for monitoring and improving the performance of on-demand irrigation networks, based on the integration of remote sensing techniques and simulation modelling of water flow in each component of the system. In order to adequately reproduce the actual operation of an

  17. Plant systems biology: network matters.

    Science.gov (United States)

    Lucas, Mikaël; Laplaze, Laurent; Bennett, Malcolm J

    2011-04-01

    Systems biology is all about networks. A recent trend has been to associate systems biology exclusively with the study of gene regulatory or protein-interaction networks. However, systems biology approaches can be applied at many other scales, from the subatomic to the ecosystem scales. In this review, we describe studies at the sub-cellular, tissue, whole plant and crop scales and highlight how these studies can be related to systems biology. We discuss the properties of system approaches at each scale as well as their current limits, and pinpoint in each case advances unique to the considered scale but representing potential for the other scales. We conclude by examining plant models bridging different scales and considering the future prospects of plant systems biology. © 2011 Blackwell Publishing Ltd.

  18. Networks, linkages, and migration systems.

    Science.gov (United States)

    Fawcett, J T

    1989-01-01

    Recent theoretical interest in migration systems calls attention to the functions of diverse linkages between countries in stimulating, directing,and maintaining international flows of people. This article proposes a conceptual framework for the non-people linkages in international migration systems and discusses the implications for population movement of the 4 categories and 3 types of linkages that define the network. The 4 categories include 1) state to state relations, 2) mass culture connections, 3) family and personal networks, and 4) migrant agency activities. The 3 types of linkages are 1) tangible linkages, 2) regulatory linkages, and 3) relational linkages.

  19. Network operating system focus technology

    Science.gov (United States)

    1985-01-01

    An activity structured to provide specific design requirements and specifications for the Space Station Data Management System (DMS) Network Operating System (NOS) is outlined. Examples are given of the types of supporting studies and implementation tasks presently underway to realize a DMS test bed capability to develop hands-on understanding of NOS requirements as driven by actual subsystem test beds participating in the overall Johnson Space Center test bed program. Classical operating system elements and principal NOS functions are listed.

  20. Quality Analysis of Massive High-Definition Video Streaming in Two-Tiered Embedded Camera-Sensing Systems

    OpenAIRE

    Joongheon Kim; Eun-Seok Ryu

    2014-01-01

    This paper presents the quality analysis results of high-definition video streaming in two-tiered camera sensor network applications. In the camera-sensing system, multiple cameras sense visual scenes in their target fields and transmit the video streams via IEEE 802.15.3c multigigabit wireless links. However, the wireless transmission introduces interferences to the other links. This paper analyzes the capacity degradation due to the interference impacts from the camera-sensing nodes to the ...

  1. Decentralized cooperative spectrum sensing for ad-hoc disaster relief network clusters

    DEFF Research Database (Denmark)

    Pratas, Nuno; Marchetti, Nicola; Prasad, Neeli R.

    2010-01-01

    been the target of intensive research, of which the main common conclusion was that the achievable spectrum sensing accuracy can be greatly enhanced through the use of cooperative sensing schemes. When considering applying Cognitive Radio to ad-hoc disaster relief networks, the use of spectrum sensing...... through a framework, which allows gauging the accuracy of multi narrow-band spectrum sensing cooperative schemes as well as to gauge the error in the estimation of each of the channels un-occupancy. Through that evaluation it is shown that the proposed decentralized scheme performance reaches...

  2. Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

    Science.gov (United States)

    Mollenhauer, Hannes; Schima, Robert; Remmler, Paul; Mollenhauer, Olaf; Hutschenreuther, Tino; Toepfer, Hannes; Dietrich, Peter; Bumberger, Jan

    2015-04-01

    For an adequate characterization of ecosystems it is necessary to detect individual processes with suitable monitoring strategies and methods. Due to the natural complexity of all environmental compartments, single point or temporally and spatially fixed measurements are mostly insufficient for an adequate representation. The application of mobile wireless sensor networks for soil and atmosphere sensing offers significant benefits, due to the simple adjustment of the sensor distribution, the sensor types and the sample rate (e.g. by using optimization approaches or event triggering modes) to the local test conditions. This can be essential for the monitoring of heterogeneous and dynamic environmental systems and processes. One significant advantage in the application of mobile ad-hoc wireless sensor networks is their self-organizing behavior. Thus, the network autonomously initializes and optimizes itself. Due to the localization via satellite a major reduction in installation and operation costs and time is generated. In addition, single point measurements with a sensor are significantly improved by measuring at several optimized points continuously. Since performing analog and digital signal processing and computation in the sensor nodes close to the sensors a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of nodes. Furthermore, the miniaturization of the nodes and energy harvesting are current topics under investigation. First results of field measurements are given to present the potentials and limitations of this application in environmental science. In particular, collected in-situ data with numerous specific soil and atmosphere parameters per sensor node (more than 25) recorded over several days illustrates the high performance of this system for advanced soil sensing and soil-atmosphere interaction monitoring. Moreover, investigations of biotic and abiotic process interactions and optimization

  3. Highly Enhanced Vapor Sensing of Multiwalled Carbon Nanotube Network Sensors by n-Butylamine Functionalization

    Directory of Open Access Journals (Sweden)

    P. Slobodian

    2014-01-01

    Full Text Available The sensing of volatile organic compounds by multiwall carbon nanotube networks of randomly entangled pristine nanotubes or the nanotubes functionalized by n-butylamine, which were deposited on polyurethane supporting electrospinned nonwoven membrane, has been investigated. The results show that the sensing of volatile organic compounds by functionalized nanotubes considerably increases with respect to pristine nanotubes. The increase is highly dependent on used vapor polarity. For the case of highly polar methanol, the functionalized MWCNT network exhibits even more than eightfold higher sensitivity in comparison to the network prepared from pristine nanotubes.

  4. Networked control of microgrid system of systems

    Science.gov (United States)

    Mahmoud, Magdi S.; Rahman, Mohamed Saif Ur; AL-Sunni, Fouad M.

    2016-08-01

    The microgrid has made its mark in distributed generation and has attracted widespread research. However, microgrid is a complex system which needs to be viewed from an intelligent system of systems perspective. In this paper, a network control system of systems is designed for the islanded microgrid system consisting of three distributed generation units as three subsystems supplying a load. The controller stabilises the microgrid system in the presence of communication infractions such as packet dropouts and delays. Simulation results are included to elucidate the effectiveness of the proposed control strategy.

  5. A Low-Cost Body Inertial-Sensing Network for Practical Gait Discrimination of Hemiplegia Patients

    Science.gov (United States)

    Guo, Yanwei; Wu, Dan; Liu, Guanzheng; Zhao, Guoru; Huang, Bangyu

    2012-01-01

    Abstract Gait analysis is widely used in detecting human walking disorders. Current gait analysis methods like video- or optical-based systems are expensive and cause invasion of human privacy. This article presents a self-developed low-cost body inertial-sensing network, which contains a base station, three wearable inertial measurement nodes, and the affiliated wireless communication protocol, for practical gait discrimination between hemiplegia patients and asymptomatic subjects. Every sensing node contains one three-axis accelerometer, one three-axis magnetometer, and one three-axis gyroscope. Seven hemiplegia patients (all were abnormal on the right side) and 7 asymptomatic subjects were examined. The three measurement nodes were attached on the thigh, the shank, and the dorsum of the foot, respectively (all on the right side of the body). A new method, which does not need to obtain accurate positions of the sensors, was used to calculate angles of knee flexion/extension and foot in the gait cycle. The angle amplitudes of initial contact, toe off, and knee flexion/extension were extracted. The results showed that there were significant differences between the two groups in the three angle amplitudes examined (−0.52±0.98° versus 6.94±2.63°, 28.33±11.66° versus 47.34±7.90°, and 26.85±8.6° versus 50.91±6.60°, respectively). It was concluded that the body inertial-sensing network platform provided a practical approach for wearable biomotion acquisition and was effective for discriminating gait symptoms between hemiplegia and asymptomatic subjects. PMID:22449064

  6. A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

    Directory of Open Access Journals (Sweden)

    Jorge Sá Silva

    2012-02-01

    Full Text Available As the Internet evolved, social networks (such as Facebook have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype.

  7. Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

    Directory of Open Access Journals (Sweden)

    Jun Wu

    2017-07-01

    Full Text Available Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

  8. Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

    Science.gov (United States)

    Wu, Jun; Su, Zhou; Li, Jianhua

    2017-01-01

    Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems. PMID:28758943

  9. Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems.

    Science.gov (United States)

    Wu, Jun; Su, Zhou; Wang, Shen; Li, Jianhua

    2017-07-30

    Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on "friend" relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

  10. Architecting Communication Network of Networks for Space System of Systems

    Science.gov (United States)

    Bhasin, Kul B.; Hayden, Jeffrey L.

    2008-01-01

    The National Aeronautics and Space Administration (NASA) and the Department of Defense (DoD) are planning Space System of Systems (SoS) to address the new challenges of space exploration, defense, communications, navigation, Earth observation, and science. In addition, these complex systems must provide interoperability, enhanced reliability, common interfaces, dynamic operations, and autonomy in system management. Both NASA and the DoD have chosen to meet the new demands with high data rate communication systems and space Internet technologies that bring Internet Protocols (IP), routers, servers, software, and interfaces to space networks to enable as much autonomous operation of those networks as possible. These technologies reduce the cost of operations and, with higher bandwidths, support the expected voice, video, and data needed to coordinate activities at each stage of an exploration mission. In this paper, we discuss, in a generic fashion, how the architectural approaches and processes are being developed and used for defining a hypothetical communication and navigation networks infrastructure to support lunar exploration. Examples are given of the products generated by the architecture development process.

  11. Network centrality of metro systems.

    Directory of Open Access Journals (Sweden)

    Sybil Derrible

    Full Text Available Whilst being hailed as the remedy to the world's ills, cities will need to adapt in the 21(st century. In particular, the role of public transport is likely to increase significantly, and new methods and technics to better plan transit systems are in dire need. This paper examines one fundamental aspect of transit: network centrality. By applying the notion of betweenness centrality to 28 worldwide metro systems, the main goal of this paper is to study the emergence of global trends in the evolution of centrality with network size and examine several individual systems in more detail. Betweenness was notably found to consistently become more evenly distributed with size (i.e. no "winner takes all" unlike other complex network properties. Two distinct regimes were also observed that are representative of their structure. Moreover, the share of betweenness was found to decrease in a power law with size (with exponent 1 for the average node, but the share of most central nodes decreases much slower than least central nodes (0.87 vs. 2.48. Finally the betweenness of individual stations in several systems were examined, which can be useful to locate stations where passengers can be redistributed to relieve pressure from overcrowded stations. Overall, this study offers significant insights that can help planners in their task to design the systems of tomorrow, and similar undertakings can easily be imagined to other urban infrastructure systems (e.g., electricity grid, water/wastewater system, etc. to develop more sustainable cities.

  12. SINGLE-IMAGE SUPER RESOLUTION FOR MULTISPECTRAL REMOTE SENSING DATA USING CONVOLUTIONAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    L. Liebel

    2016-06-01

    Full Text Available In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN, can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

  13. Remote sensing of multimodal transportation systems.

    Science.gov (United States)

    2016-09-01

    Hyperspectral remote sensing is an emerging field with many potential applications in the observation, management, and maintenance of the global transportation infrastructure. This report describes the development of an affordable framework to captur...

  14. Systems engineering technology for networks

    Science.gov (United States)

    1994-01-01

    The report summarizes research pursued within the Systems Engineering Design Laboratory at Virginia Polytechnic Institute and State University between May 16, 1993 and January 31, 1994. The project was proposed in cooperation with the Computational Science and Engineering Research Center at Howard University. Its purpose was to investigate emerging systems engineering tools and their applicability in analyzing the NASA Network Control Center (NCC) on the basis of metrics and measures.

  15. Active Sensing System with In Situ Adjustable Sensor Morphology

    Science.gov (United States)

    Nurzaman, Surya G.; Culha, Utku; Brodbeck, Luzius; Wang, Liyu; Iida, Fumiya

    2013-01-01

    Background Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. Methodology This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. Conclusions/Significance The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed. PMID:24416094

  16. Active sensing system with in situ adjustable sensor morphology.

    Directory of Open Access Journals (Sweden)

    Surya G Nurzaman

    Full Text Available BACKGROUND: Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. METHODOLOGY: This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA. It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. CONCLUSIONS/SIGNIFICANCE: The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed.

  17. Active sensing system with in situ adjustable sensor morphology.

    Science.gov (United States)

    Nurzaman, Surya G; Culha, Utku; Brodbeck, Luzius; Wang, Liyu; Iida, Fumiya

    2013-01-01

    Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed.

  18. Integration of wireless sensor network and remote sensing for monitoring and determining irrigation demand in Cyprus

    Science.gov (United States)

    Agapiou, Athos; Papadavid, George; Hadjimitsis, Diofantos G.

    2009-09-01

    This paper aims to highlight the benefits from the integration of wireless sensor network / meteorological data and remote sensing for monitoring and determine irrigation demand in Cyprus. Estimating evapotranspiration in Cyprus will help, in taking measures for an effective irrigation water management in the future in the island. For this purpose both multi-spectral satellite images (Landsat 7 ETM+ and ASTER) and hydro-meteorological data from wireless sensors and automatic meteorological stations have been used. The wireless sensor network, which consist approximately twenty wireless nodes, was placed in our case study. The wireless sensor network acts as a wide area distributed data collection system deployed to collect and reliably transmit soil and air environmental data to a remote base-station hosted at Cyprus University of Technology. Furthermore auxiliary meteorological field data, from an automatic meteorological station, nearby our case study, where used such as solar radiation, air temperature, air humidity and wind speed. These data were used in conjunction with remote sensing results. Satellite images where used in ERDAS Imagine Software after the necessary processing: geometric rectification, radiometric calibration and atmospheric corrections. The satellite images were atmospheric corrected and calibrated using spectro-radiometers and sun-photometers measurements taken in situ, in an agricultural area, south-west of the island of Cyprus. Evapotranspiration is difficult to determine since it combines various meteorological and field parameters while in literature quite many different models for estimating ET are indicated. For estimating evapotranspiration from satellite images and the hydro-meteorological data different methods have been evaluated such as FAO Penman-Monteith, Carlson-Buffum and Granger methods. These results have been compared with E-pan methods. Finally a water management irrigation schedule has been applied. The final results are

  19. The LILARTI neural network system

    Energy Technology Data Exchange (ETDEWEB)

    Allen, J.D. Jr.; Schell, F.M.; Dodd, C.V.

    1992-10-01

    The material of this Technical Memorandum is intended to provide the reader with conceptual and technical background information on the LILARTI neural network system of detail sufficient to confer an understanding of the LILARTI method as it is presently allied and to facilitate application of the method to problems beyond the scope of this document. Of particular importance in this regard are the descriptive sections and the Appendices which include operating instructions, partial listings of program output and data files, and network construction information.

  20. VCSEL-based gigabit IR-UWB link for converged communication and sensing applications in optical metro-access networks

    DEFF Research Database (Denmark)

    Pham, Tien Thang; Gibbon, Timothy Braidwood; Tafur Monroy, Idelfonso

    2012-01-01

    We report on experimental demonstration of an impulse radio ultrawideband (IR-UWB) based converged communication and sensing system. A 1550-nm VCSEL-generated IR-UWB signal is used for 2-Gbps wireless data distribution over 800-m and 50-km single mode fiber links which present short-range in...... application, paving the way forward for the development and deployment of converged UWB VCSEL-based technologies in access and in-building networks of the future....

  1. Network-based Parallel Retrieval Onboard Computing Environment for Sensor Systems Deployed on NASA Unmanned Aircraft Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Remote Sensing Solutions proposes to develop the Network-based Parallel Retrieval Onboard Computing Environment for Sensor Systems (nPROCESS) for deployment on...

  2. Ultra-short FBG based distributed sensing using shifted optical Gaussian filters and microwave-network analysis.

    Science.gov (United States)

    Cheng, Rui; Xia, Li; Sima, Chaotan; Ran, Yanli; Rohollahnejad, Jalal; Zhou, Jiaao; Wen, Yongqiang; Yu, Can

    2016-02-08

    Ultrashort fiber Bragg gratings (US-FBGs) have significant potential as weak grating sensors for distributed sensing, but the exploitation have been limited by their inherent broad spectra that are undesirable for most traditional wavelength measurements. To address this, we have recently introduced a new interrogation concept using shifted optical Gaussian filters (SOGF) which is well suitable for US-FBG measurements. Here, we apply it to demonstrate, for the first time, an US-FBG-based self-referencing distributed optical sensing technique, with the advantages of adjustable sensitivity and range, high-speed and wide-range (potentially >14000 με) intensity-based detection, and resistance to disturbance by nonuniform parameter distribution. The entire system is essentially based on a microwave network, which incorporates the SOGF with a fiber delay-line between the two arms. Differential detections of the cascaded US-FBGs are performed individually in the network time-domain response which can be obtained by analyzing its complex frequency response. Experimental results are presented and discussed using eight cascaded US-FBGs. A comprehensive numerical analysis is also conducted to assess the system performance, which shows that the use of US-FBGs instead of conventional weak FBGs could significantly improve the power budget and capacity of the distributed sensing system while maintaining the crosstalk level and intensity decay rate, providing a promising route for future sensing applications.

  3. The Citizens and Remote Sensing Observational Network (CARSON) Guide: Merging NASA Remote Sensing Data with Local Environmental Awareness

    Science.gov (United States)

    Acker, James; Riebeek, Holli; Ledley, Tamara Shapiro; Herring, David; Lloyd, Steven

    2008-01-01

    "Citizen science" generally refers to observatoinal research and data collection conducted by non-professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local nad regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote sensing data sets. The CARSON (Citizens and Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museuma and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on

  4. The Citizens And Remote Sensing Observational Network (CARSON) Guide: Merging NASA Remote-Sensing Data with Local Environmental Awareness

    Science.gov (United States)

    Acker, J.; Riebeek, H.; Ledley, T. S.; Herring, D.; Lloyd, S.

    2008-12-01

    "Citizen science" generally refers to observational research and data collection conducted by non- professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local and regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote-sensing data sets. The CARSON (Citizens And Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museums and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on

  5. The Design of Vibration Sensing System Used for the Internet of Things

    Science.gov (United States)

    Ji, Wei; Ma, Xuejie

    2016-06-01

    A vibration sensing system used for the Internet of Things is presented in this paper. Using the distributed feedback fiber lasers (DFB-FL) collects external sound signals and digital phase generated carrier (PGC) method realizes wavelength demodulation. The platform is designed based on an open architecture and B/S (Browser/Server) technology which makes it an ideal platform to be operated under a network environment. The sensing system is no power supply and could be monitored anytime and anywhere which is the requirement of Internet of things.

  6. Coalitional Games in Partition Form for Joint Spectrum Sensing and Access in Cognitive Radio Networks

    CERN Document Server

    Saad, Walid; Zheng, Rong; Hjørungnes, Are; Başar, Tamer; Poor, H Vincent

    2012-01-01

    Unlicensed secondary users (SUs) in cognitive radio networks are subject to an inherent tradeoff between spectrum sensing and spectrum access. Although each SU has an incentive to sense the primary user (PU) channels for locating spectrum holes, this exploration of the spectrum can come at the expense of a shorter transmission time, and, hence, a possibly smaller capacity for data transmission. This paper investigates the impact of this tradeoff on the cooperative strategies of a network of SUs that seek to cooperate in order to improve their view of the spectrum (sensing), reduce the possibility of interference among each other, and improve their transmission capacity (access). The problem is modeled as a coalitional game in partition form and an algorithm for coalition formation is proposed. Using the proposed algorithm, the SUs can make individual distributed decisions to join or leave a coalition while maximizing their utilities which capture the average time spent for sensing as well as the capacity achi...

  7. Gait Dynamics Sensing Using IMU Sensor Array System

    Directory of Open Access Journals (Sweden)

    Slavomir Kardos

    2017-01-01

    Full Text Available The article deals with a progressive approach in gait sensing. It is incorporated by IMU (Inertia Measurement Unit complex sensors whose field of acting is mainly the motion sensing in medicine, automotive and other industry, self-balancing systems, etc. They allow acquiring the position and orientation of an object in 3D space. Using several IMU units the sensing array for gait dynamics was made. Based on human gait analysis the 7-sensor array was designed to build a gait motion dynamics sensing system with the possibility of graphical interpretation of data from the sensing modules in real-time graphical application interface under the LabVIEW platform. The results of analyses can serve as the information for medical diagnostic purposes. The main control part of the system is microcontroller, whose function is to control the data collection and flow, provide the communication and power management.

  8. Physical limits to biomechanical sensing in disordered fibre networks

    Science.gov (United States)

    Beroz, Farzan; Jawerth, Louise M.; Münster, Stefan; Weitz, David A.; Broedersz, Chase P.; Wingreen, Ned S.

    2017-07-01

    Cells actively probe and respond to the stiffness of their surroundings. Since mechanosensory cells in connective tissue are surrounded by a disordered network of biopolymers, their in vivo mechanical environment can be extremely heterogeneous. Here we investigate how this heterogeneity impacts mechanosensing by modelling the cell as an idealized local stiffness sensor inside a disordered fibre network. For all types of networks we study, including experimentally-imaged collagen and fibrin architectures, we find that measurements applied at different points yield a strikingly broad range of local stiffnesses, spanning roughly two decades. We verify via simulations and scaling arguments that this broad range of local stiffnesses is a generic property of disordered fibre networks. Finally, we show that to obtain optimal, reliable estimates of global tissue stiffness, a cell must adjust its size, shape, and position to integrate multiple stiffness measurements over extended regions of space.

  9. Microfluidic Systems for Pathogen Sensing: A Review

    Directory of Open Access Journals (Sweden)

    Peter Ertl

    2009-06-01

    Full Text Available Rapid pathogen sensing remains a pressing issue today since conventional identification methodsare tedious, cost intensive and time consuming, typically requiring from 48 to 72 h. In turn, chip based technologies, such as microarrays and microfluidic biochips, offer real alternatives capable of filling this technological gap. In particular microfluidic biochips make the development of fast, sensitive and portable diagnostic tools possible, thus promising rapid and accurate detection of a variety of pathogens. This paper will provide a broad overview of the novel achievements in the field of pathogen sensing by focusing on methods and devices that compliment microfluidics.

  10. Remote sensing with unmanned aircraft systems for precision agriculture applications

    Science.gov (United States)

    The Federal Aviation Administration is revising regulations for using unmanned aircraft systems (UAS) in the national airspace. An important potential application of UAS may be as a remote-sensing platform for precision agriculture, but simply down-scaling remote sensing methodologies developed usi...

  11. Facsimile Network System in RCP

    Science.gov (United States)

    Muramatsu, Kazuya

    Recruit Computer Print Corp. has compiled Weekly Housing Magazine by use of its own CTS (Computerized Type Setting) resulting in the real estate database as byproduct. Based on the database it has made the network linking with sponsors, real estate companies. It has transmitted lists for data cleaning directly from computer enabling to save manpower and reduce time in the compilation process. The author describes the objectives, details, functions and promise of the system.

  12. Glucose-Sensing in the Reward System

    NARCIS (Netherlands)

    Koekkoek, Laura L.; Mul, Joram D.; la Fleur, Susanne E.

    2017-01-01

    Glucose-sensing neurons are neurons that alter their activity in response to changes in extracellular glucose. These neurons, which are an important mechanism the brain uses to monitor changes in glycaemia, are present in the hypothalamus, where they have been thoroughly investigated. Recently,

  13. Network Centrality of Metro Systems

    Science.gov (United States)

    Derrible, Sybil

    2012-01-01

    Whilst being hailed as the remedy to the world’s ills, cities will need to adapt in the 21st century. In particular, the role of public transport is likely to increase significantly, and new methods and technics to better plan transit systems are in dire need. This paper examines one fundamental aspect of transit: network centrality. By applying the notion of betweenness centrality to 28 worldwide metro systems, the main goal of this paper is to study the emergence of global trends in the evolution of centrality with network size and examine several individual systems in more detail. Betweenness was notably found to consistently become more evenly distributed with size (i.e. no “winner takes all”) unlike other complex network properties. Two distinct regimes were also observed that are representative of their structure. Moreover, the share of betweenness was found to decrease in a power law with size (with exponent 1 for the average node), but the share of most central nodes decreases much slower than least central nodes (0.87 vs. 2.48). Finally the betweenness of individual stations in several systems were examined, which can be useful to locate stations where passengers can be redistributed to relieve pressure from overcrowded stations. Overall, this study offers significant insights that can help planners in their task to design the systems of tomorrow, and similar undertakings can easily be imagined to other urban infrastructure systems (e.g., electricity grid, water/wastewater system, etc.) to develop more sustainable cities. PMID:22792373

  14. Energy Efficient Cooperative Spectrum Sensing in Cognitive Radio Networks Using Distributed Dynamic Load Balanced Clustering Scheme

    Directory of Open Access Journals (Sweden)

    Muthukkumar R.

    2016-07-01

    Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.

  15. On the Feedback Reduction of Relay Multiuser Networks using Compressive Sensing

    KAUST Repository

    Elkhalil, Khalil

    2016-01-29

    This paper presents a comprehensive performance analysis of full-duplex multiuser relay networks employing opportunistic scheduling with noisy and compressive feedback. Specifically, two feedback techniques based on compressive sensing (CS) theory are introduced and their effect on the system performance is analyzed. The problem of joint user identity and signal-tonoise ratio (SNR) estimation at the base-station is casted as a block sparse signal recovery problem in CS. Using existing CS block recovery algorithms, the identity of the strong users is obtained and their corresponding SNRs are estimated using the best linear unbiased estimator (BLUE). To minimize the effect of feedback noise on the estimated SNRs, a back-off strategy that optimally backs-off on the noisy estimated SNRs is introduced, and the error covariance matrix of the noise after CS recovery is derived. Finally, closed-form expressions for the end-to-end SNRs of the system are derived. Numerical results show that the proposed techniques drastically reduce the feedback air-time and achieve a rate close to that obtained by scheduling techniques that require dedicated error-free feedback from all network users. Key findings of this paper suggest that the choice of half-duplex or full-duplex SNR feedback is dependent on the channel coherence interval, and on low coherence intervals, full-duplex feedback is superior to the interference-free half-duplex feedback.

  16. Signaling Network of Environmental Sensing and Adaptation in Plants:. Key Roles of Calcium Ion

    Science.gov (United States)

    Kurusu, Takamitsu; Kuchitsu, Kazuyuki

    2011-01-01

    Considering the important issues concerning food, environment, and energy that humans are facing in the 21st century, humans mostly depend on plants. Unlike animals which move from an inappropriate environment, plants do not move, but rapidly sense diverse environmental changes or invasion by other organisms such as pathogens and insects in the place they root, and adapt themselves by changing their own bodies, through which they developed adaptability. Whole genetic information corresponding to the blueprints of many biological systems has recently been analyzed, and comparative genomic studies facilitated tracing strategies of each organism in their evolutional processes. Comparison of factors involved in intracellular signal transduction between animals and plants indicated diversification of different gene sets. Reversible binding of Ca2+ to sensor proteins play key roles as a molecular switch both in animals and plants. Molecular mechanisms for signaling network of environmental sensing and adaptation in plants will be discussed with special reference to Ca2+ as a key element in information processing.

  17. Unsupervised Remote Sensing Domain Adaptation Method with Adversarial Network and Auxiliary Task

    Directory of Open Access Journals (Sweden)

    XU Suhui

    2017-12-01

    Full Text Available An important prerequisite when annotating the remote sensing images by machine learning is that there are enough training samples for training, but labeling the samples is very time-consuming. In this paper, we solve the problem of unsupervised learning with small sample size in remote sensing image scene classification by domain adaptation method. A new domain adaptation framework is proposed which combines adversarial network and auxiliary task. Firstly, a novel remote sensing scene classification framework is established based on deep convolution neural networks. Secondly, a domain classifier is added to the network, in order to learn the domain-invariant features. The gradient direction of the domain loss is opposite to the label loss during the back propagation, which makes the domain predictor failed to distinguish the sample's domain. Lastly, we introduce an auxiliary task for the network, which augments the training samples and improves the generalization ability of the network. The experiments demonstrate better results in unsupervised classification with small sample sizes of remote sensing images compared to the baseline unsupervised domain adaptation approaches.

  18. Vehicle Safety Enhancement System: Sensing and Communication

    OpenAIRE

    Huihuan Qian; Yongquan Chen; Yuandong Sun; Niansheng Liu; Ning Ding; Yangsheng Xu; Guoqing Xu; Yunjian Tang; Jingyu Yan

    2013-01-01

    With the substantial increase of vehicles on road, driving safety and transportation efficiency have become increasingly concerned focus from drivers, passengers, and governments. Wireless networks constructed by vehicles and infrastructures provide abundant information to share for the sake of both enhanced safety and network efficiency. This paper presents the systematic research to enhance the vehicle safety by wireless communication, in the aspects of information acquisition through vehic...

  19. Three-dimensional optical sensing network written in fused silica glass with femtosecond laser.

    Science.gov (United States)

    Zhang, Haibin; Ho, Stephen; Eaton, Shane M; Li, Jianzhao; Herman, Peter R

    2008-09-01

    A single-step fast-writing method of burst ultrafast laser modification was applied to form a mesh network of multi-wavelength Bragg grating waveguides in bulk fused silica glass. Strain-optic and thermo-optic responses of the laser-written internal sensors are reported for the first time. A dual planar layout provided independent temperature- and strain-compensated characterization of temperature and strain distribution with coarse spatial resolution. The grating responses were thermally stable to 500 masculineC. To our best knowledge, the grating network represents the first demonstration of 3D distributed optical sensing network in a bulk transparent medium. Such 3D grating networks open new directions for strain and temperature sensing in optical circuits, optofluidic, MEMS or lab-on-a-chip microsystems, actuators, and windows and other large display or civil structures.

  20. Remote sensing of multimodal transportation systems : research brief.

    Science.gov (United States)

    2016-09-01

    Remote Sensing of Multimodal Transportation Systems : Rapid condition monitoring and performance evaluations of the vast and vulnerable transportation infrastructure has been elusive. The framework and models developed in this research will enable th...

  1. Neural networks applied to the classification of remotely sensed data

    NARCIS (Netherlands)

    Mulder, Nanno; Spreeuwers, Lieuwe Jan

    1991-01-01

    A neural network with topology 2-8-8 is evaluated against the standard of supervised non-parametric maximum likelihood classification. The purpose of the evaluation is to compare the performance in terms of training speed and quality of classification. Classification is done on multispectral data

  2. Spectrally Adaptable Compressive Sensing Imaging System

    Science.gov (United States)

    2014-05-01

    Compressive Sensing Imaging System” Submitted by: Gonzalo R. Arce, PI Dennis W. Prather and Javier Garcia-Frias Department of Electrical and Computer...spatio-spectral data cube. Push broom spectral imaging sensors, for instance, capture the spectral data cube by using a dispersive element as a prism...Multishot measurements can be attained by successively shifting, along the horizontal axis, the fixed coded aperture in CASSI. A novel piezo- electrical

  3. Robotic Tactile Sensing Technologies and System

    CERN Document Server

    Dahiya, Ravinder S

    2013-01-01

    Future robots are expected to work closely and interact safely with real-world objects and humans alike. Sense of touch is important in this context, as it helps estimate properties such as shape, texture, hardness, material type and many more; provides action related information, such as slip detection; and helps carrying out actions such as rolling an object between fingers without dropping it. This book presents an in-depth description of the solutions available for gathering tactile data, obtaining aforementioned tactile information from the data and effectively using the same in various robotic tasks. Better integration of tactile sensors on a robot’s body is prerequisite for the effective utilization of tactile data. For this reason, the hardware, software and application related issues (and resulting trade-offs) that must be considered to make tactile sensing an effective component of robotic platforms are discussed in-depth.To this end, human touch sensing has also been explored. The design hints co...

  4. Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields

    Directory of Open Access Journals (Sweden)

    Teerapong Panboonyuen

    2017-07-01

    Full Text Available Object segmentation of remotely-sensed aerial (or very-high resolution, VHS images and satellite (or high-resolution, HR images, has been applied to many application domains, especially in road extraction in which the segmented objects are served as a mandatory layer in geospatial databases. Several attempts at applying the deep convolutional neural network (DCNN to extract roads from remote sensing images have been made; however, the accuracy is still limited. In this paper, we present an enhanced DCNN framework specifically tailored for road extraction of remote sensing images by applying landscape metrics (LMs and conditional random fields (CRFs. To improve the DCNN, a modern activation function called the exponential linear unit (ELU, is employed in our network, resulting in a higher number of, and yet more accurate, extracted roads. To further reduce falsely classified road objects, a solution based on an adoption of LMs is proposed. Finally, to sharpen the extracted roads, a CRF method is added to our framework. The experiments were conducted on Massachusetts road aerial imagery as well as the Thailand Earth Observation System (THEOS satellite imagery data sets. The results showed that our proposed framework outperformed Segnet, a state-of-the-art object segmentation technique, on any kinds of remote sensing imagery, in most of the cases in terms of precision, recall, and F 1 .

  5. Mathematical Analysis of a PDE System for Biological Network Formation

    KAUST Repository

    Haskovec, Jan

    2015-02-04

    Motivated by recent physics papers describing rules for natural network formation, we study an elliptic-parabolic system of partial differential equations proposed by Hu and Cai [13, 15]. The model describes the pressure field thanks to Darcy\\'s type equation and the dynamics of the conductance network under pressure force effects with a diffusion rate D >= 0 representing randomness in the material structure. We prove the existence of global weak solutions and of local mild solutions and study their long term behavior. It turns out that, by energy dissipation, steady states play a central role to understand the network formation capacity of the system. We show that for a large diffusion coefficient D, the zero steady state is stable, while network formation occurs for small values of D due to the instability of the zero steady state, and the borderline case D = 0 exhibits a large class of dynamically stable (in the linearized sense) steady states.

  6. Goodness-of-fit based secure cooperative spectrum sensing for cognitive radio network.

    Science.gov (United States)

    Vu-Van, Hiep; Koo, Insoo

    2014-01-01

    Cognitive radio (CR) is a promising technology for improving usage of frequency band. Cognitive radio users (CUs) are allowed to use the bands without interference in operation of licensed users. Reliable sensing information about status of licensed band is a prerequirement for CR network. Cooperative spectrum sensing (CSS) is able to offer an improved sensing reliability compared to individual sensing. However, the sensing performance of CSS can be destroyed due to the appearance of some malicious users. In this paper, we propose a goodness-of-fit (GOF) based cooperative spectrum sensing scheme to detect the dissimilarity between sensing information of normal CUs and that of malicious users, and reject their harmful effect to CSS. The empirical CDF will be used in GOF test to determine the measured distance between distributions of observation sample set according to each hypothesis of licensed user signal. Further, the DS theory is used to combine results of multi-GOF tests. The simulation results demonstrate that the proposed scheme can protect the sensing process against the attack from malicious users.

  7. Flexible electronics-compatible non-enzymatic glucose sensing via transparent CuO nanowire networks on PET films

    Science.gov (United States)

    Bell, Caroline; Nammari, Abdullah; Uttamchandani, Pranay; Rai, Amit; Shah, Pujan; Moore, Arden L.

    2017-06-01

    Diabetic individuals need simple, accurate, and cost effective means by which to independently assess their glucose levels in a non-invasive way. In this work, a sensor based on randomly oriented CuO nanowire networks supported by a polyethylene terephthalate thin film is evaluated as a flexible, transparent, non-enzymatic glucose sensing system analogous to those envisioned for future wearable diagnostic devices. The amperometric sensing characteristics of this type of device architecture are evaluated both before and after bending, with the system’s glucose response, sensitivity, lower limit of detection, and effect of applied bias being experimentally determined. The obtained data shows that the sensor is capable of measuring changes in glucose levels within a physiologically relevant range (0-12 mM glucose) and at lower limits of detection (0.05 mM glucose at +0.6 V bias) consistent with patient tears and saliva. Unlike existing studies utilizing a conductive backing layer or macroscopic electrode setup, this sensor demonstrates a percolation network-like trend of current versus glucose concentration. In this implementation, controlling the architectural details of the CuO nanowire network could conceivably allow the sensor’s sensitivity and optimal sensing range to be tuned. Overall, this work shows that integrating CuO nanowires into a sensor architecture compatible with transparent, flexible electronics is a promising avenue to realizing next generation wearable non-enzymatic glucose diagnostic devices.

  8. Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

    Directory of Open Access Journals (Sweden)

    Andre Terzic

    2009-04-01

    Full Text Available Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7 are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network.

  9. Word sense disambiguation via high order of learning in complex networks

    CERN Document Server

    Silva, Thiago C; 10.1209/0295-5075/98/58001

    2013-01-01

    Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be corre...

  10. Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities

    Science.gov (United States)

    Yusufaly, Tahir I.; Boedicker, James Q.

    2017-08-01

    Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely understood in heterogeneous communities, where variant bacterial strains possess distinct QS systems that produce chemically unique AIs. AI molecules bind to ‘cognate’ receptors, but also to ‘non-cognate’ receptors found in other strains, resulting in inter-strain crosstalk. Understanding these interactions is a prerequisite for deciphering the consequences of crosstalk in real ecosystems, where multiple AIs are regularly present in the same environment. As a step towards this goal, we map crosstalk in a heterogeneous community of variant QS strains onto an artificial neural network model. This formulation allows us to systematically analyze how crosstalk regulates the community’s capacity for flexible decision making, as quantified by the Boltzmann entropy of all QS gene expression states of the system. In a mean-field limit of complete cross-inhibition between variant strains, the model is exactly solvable, allowing for an analytical formula for the number of variants that maximize capacity as a function of signal kinetics and activation parameters. An analysis of previous experimental results on the Staphylococcus aureus two-component Agr system indicates that the observed combination of variant numbers, gene expression rates and threshold concentrations lies near this critical regime of parameter space where capacity peaks. The results are suggestive of a potential evolutionary driving force for diversification in certain QS systems.

  11. Sensing Coverage Prediction for Wireless Sensor Networks in Shadowed and Multipath Environment

    Directory of Open Access Journals (Sweden)

    Sushil Kumar

    2013-01-01

    Full Text Available Sensing coverage problem in wireless sensor networks is a measure of quality of service (QoS. Coverage refers to how well a sensing field is monitored or tracked by the sensors. Aim of the paper is to have a priori estimate for number of sensors to be deployed in a harsh environment to achieve desired coverage. We have proposed a new sensing channel model that considers combined impact of shadowing fading and multipath effects. A mathematical model for calculating coverage probability in the presence of multipath fading combined with shadowing is derived based on received signal strength (RSS. Further, the coverage probability derivations obtained using Rayleigh fading and lognormal shadowing fading are validated by node deployment using Poisson distribution. A comparative study between our proposed sensing channel model and different existing sensing models for the network coverage has also been presented. Our proposed sensing model is more suitable for realistic environment since it determines the optimum number of sensors required for desirable coverage in fading conditions.

  12. Secure cooperative spectrum sensing for the cognitive radio network using nonuniform reliability.

    Science.gov (United States)

    Usman, Muhammad; Koo, Insoo

    2014-01-01

    Both reliable detection of the primary signal in a noisy and fading environment and nullifying the effect of unauthorized users are important tasks in cognitive radio networks. To address these issues, we consider a cooperative spectrum sensing approach where each user is assigned nonuniform reliability based on the sensing performance. Users with poor channel or faulty sensor are assigned low reliability. The nonuniform reliabilities serve as identification tags and are used to isolate users with malicious behavior. We consider a link layer attack similar to the Byzantine attack, which falsifies the spectrum sensing data. Three different strategies are presented in this paper to ignore unreliable and malicious users in the network. Considering only reliable users for global decision improves sensing time and decreases collisions in the control channel. The fusion center uses the degree of reliability as a weighting factor to determine the global decision in scheme I. Schemes II and III consider the unreliability of users, which makes the computations even simpler. The proposed schemes reduce the number of sensing reports and increase the inference accuracy. The advantages of our proposed schemes over conventional cooperative spectrum sensing and the Chair-Varshney optimum rule are demonstrated through simulations.

  13. Dynamic mechanisms of cell rigidity sensing: insights from a computational model of actomyosin networks.

    Directory of Open Access Journals (Sweden)

    Carlos Borau

    Full Text Available Cells modulate themselves in response to the surrounding environment like substrate elasticity, exhibiting structural reorganization driven by the contractility of cytoskeleton. The cytoskeleton is the scaffolding structure of eukaryotic cells, playing a central role in many mechanical and biological functions. It is composed of a network of actins, actin cross-linking proteins (ACPs, and molecular motors. The motors generate contractile forces by sliding couples of actin filaments in a polar fashion, and the contractile response of the cytoskeleton network is known to be modulated also by external stimuli, such as substrate stiffness. This implies an important role of actomyosin contractility in the cell mechano-sensing. However, how cells sense matrix stiffness via the contractility remains an open question. Here, we present a 3-D Brownian dynamics computational model of a cross-linked actin network including the dynamics of molecular motors and ACPs. The mechano-sensing properties of this active network are investigated by evaluating contraction and stress in response to different substrate stiffness. Results demonstrate two mechanisms that act to limit internal stress: (i In stiff substrates, motors walk until they exert their maximum force, leading to a plateau stress that is independent of substrate stiffness, whereas (ii in soft substrates, motors walk until they become blocked by other motors or ACPs, leading to submaximal stress levels. Therefore, this study provides new insights into the role of molecular motors in the contraction and rigidity sensing of cells.

  14. Do Institutional Social Networks Work? Fostering a Sense of Community and Enhancing Learning

    Science.gov (United States)

    Hatzipanagos, Stylianos; John, Bernadette A.

    2017-01-01

    In this paper we report on the evaluation of an institutional social network (KINSHIP) whose aims were to foster an improved sense of community, enhance communication and serve as a space to model digital professionalism for students at King's College London, UK. Our evaluation focused on a pilot where students' needs with regard to the provision…

  15. Scene Classification of Remote Sensing Image Based on Multi-scale Feature and Deep Neural Network

    Directory of Open Access Journals (Sweden)

    XU Suhui

    2016-07-01

    Full Text Available Aiming at low precision of remote sensing image scene classification owing to small sample sizes, a new classification approach is proposed based on multi-scale deep convolutional neural network (MS-DCNN, which is composed of nonsubsampled Contourlet transform (NSCT, deep convolutional neural network (DCNN, and multiple-kernel support vector machine (MKSVM. Firstly, remote sensing image multi-scale decomposition is conducted via NSCT. Secondly, the decomposing high frequency and low frequency subbands are trained by DCNN to obtain image features in different scales. Finally, MKSVM is adopted to integrate multi-scale image features and implement remote sensing image scene classification. The experiment results in the standard image classification data sets indicate that the proposed approach obtains great classification effect due to combining the recognition superiority to different scenes of low frequency and high frequency subbands.

  16. Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Anbo [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2016-09-30

    This report summarizes technical progress on the program “Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments” funded by the National Energy Technology Laboratory of the U.S. Department of Energy, and performed by the Center for Photonics Technology at Virginia Tech. The objective of this project is to develop a first-of-a-kind technology for remote fiber optic generation and detection of acoustic waves for structural health monitoring in harsh environments. During the project period, which is from April 1, 2013 to Septemeber 30, 2016, three different acoustic generation mechanisms were studied in detail for their applications in building a fiber optic acoustic generation unit (AGU), including laser induced plasma breakdown (LIP), Erbium-doped fiber laser absorption, and metal laser absorption. By comparing the performance of the AGUs designed based on these three mechanisms and analyzing the experimental results with simulations, the metal laser absorption method was selected to build a complete fiber optic structure health monitoring (FO-SHM) system for the proposed high temperature multi-parameter structure health monitoring application. Based on the simulation of elastic wave propagation and fiber Bragg grating acoustic pulse detection, an FO-SHM element together with a completed interrogation system were designed and built. This system was first tested on an aluminum piece in the low-temperature range and successfully demonstrated its capability of multi-parameter monitoring and multi-point sensing. In the later stages of the project, the research was focused on improving the surface attachment design and preparing the FO-SHM element for high temperature environment tests. After several upgrades to the surface attachment methods, the FO-SHM element was able to work reliably up to 600oC when attached to P91 pipes, which are the target material of this project. In the final stage of this project, this FO

  17. Brain Networks Responsible for Sense of Agency: An EEG Study.

    Directory of Open Access Journals (Sweden)

    Suk Yun Kang

    Full Text Available Self-agency (SA is a person's feeling that his action was generated by himself. The neural substrates of SA have been investigated in many neuroimaging studies, but the functional connectivity of identified regions has rarely been investigated. The goal of this study is to investigate the neural network related to SA.SA of hand movements was modulated with virtual reality. We examined the cortical network relating to SA modulation with electroencephalography (EEG power spectrum and phase coherence of alpha, beta, and gamma frequency bands in 16 right-handed, healthy volunteers.In the alpha band, significant relative power changes and phase coherence of alpha band were associated with SA modulation. The relative power decrease over the central, bilateral parietal, and right temporal regions (C4, Pz, P3, P4, T6 became larger as participants more effectively controlled the virtual hand movements. The phase coherence of the alpha band within frontal areas (F7-FP2, F7-Fz was directly related to changes in SA. The functional connectivity was lower as the participants felt that they could control their virtual hand. In the other frequency bands, significant phase coherences were observed in the frontal (or central to parietal, temporal, and occipital regions during SA modulation (Fz-O1, F3-O1, Cz-O1, C3-T4L in beta band; FP1-T6, FP1-O2, F7-T4L, F8-Cz in gamma band.Our study suggests that alpha band activity may be the main neural oscillation of SA, which suggests that the neural network within the anterior frontal area may be important in the generation of SA.

  18. Brain Networks Responsible for Sense of Agency: An EEG Study.

    Science.gov (United States)

    Kang, Suk Yun; Im, Chang-Hwan; Shim, Miseon; Nahab, Fatta B; Park, Jihye; Kim, Do-Won; Kakareka, John; Miletta, Nathanial; Hallett, Mark

    2015-01-01

    Self-agency (SA) is a person's feeling that his action was generated by himself. The neural substrates of SA have been investigated in many neuroimaging studies, but the functional connectivity of identified regions has rarely been investigated. The goal of this study is to investigate the neural network related to SA. SA of hand movements was modulated with virtual reality. We examined the cortical network relating to SA modulation with electroencephalography (EEG) power spectrum and phase coherence of alpha, beta, and gamma frequency bands in 16 right-handed, healthy volunteers. In the alpha band, significant relative power changes and phase coherence of alpha band were associated with SA modulation. The relative power decrease over the central, bilateral parietal, and right temporal regions (C4, Pz, P3, P4, T6) became larger as participants more effectively controlled the virtual hand movements. The phase coherence of the alpha band within frontal areas (F7-FP2, F7-Fz) was directly related to changes in SA. The functional connectivity was lower as the participants felt that they could control their virtual hand. In the other frequency bands, significant phase coherences were observed in the frontal (or central) to parietal, temporal, and occipital regions during SA modulation (Fz-O1, F3-O1, Cz-O1, C3-T4L in beta band; FP1-T6, FP1-O2, F7-T4L, F8-Cz in gamma band). Our study suggests that alpha band activity may be the main neural oscillation of SA, which suggests that the neural network within the anterior frontal area may be important in the generation of SA.

  19. Pre-phase Improvement For Distributed Spectrum Sensing in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Ying Dai

    2014-09-01

    Full Text Available This paper considers a pre-phase of spectrum sensing in cognitive radio networks (CRNs, which is about how to choose a channel for spectrum sensing. We take the time dimension, spectrum dimension, and spacial dimension into account and propose a sense-in-order model. In this model, each node maintains four states regarding each channel, based on the neighbors’ shared information. We construct a state transition diagram for the four states and design an algorithm for every node to calculate the probability of choosing each channel. Extensive simulation results testify to the performance of our model. In addition, we conduct experiments on the USRP/Gnuradio testbed to prove the main part of the sense-in-order model with directional antennas. Experimental results show that the average success percentage under the settings of the testbed is above 70%.

  20. Optical code division multiplexed fiber Bragg grating sensing networks

    Science.gov (United States)

    Triana, Cristian; Varón, Margarita; Pastor, Daniel

    2015-09-01

    We present the application of Optical Code Division Multiplexing (OCDM) techniques in order to enhance the spectral operation and detection capability of fiber Bragg grating (FBG) sensors networks even under overlapping conditions. In this paper, Optical Orthogonal Codes (OOC) are used to design FBG sensors composed of more than one reflection band. Simulation of the interaction between the encoded Gaussian-shaped sensors is presented. Signal decoding is performed in the electrical domain without requiring additional optical components by means of the autocorrelation product between the reflected spectrum and each sensor-codeword. Results illustrate the accuracy and distinction capability of the method.

  1. Endogenous network of firms and systemic risk

    Science.gov (United States)

    Ma, Qianting; He, Jianmin; Li, Shouwei

    2018-02-01

    We construct an endogenous network characterized by commercial credit relationships connecting the upstream and downstream firms. Simulation results indicate that the endogenous network model displays a scale-free property which exists in real-world firm systems. In terms of the network structure, with the expansion of the scale of network nodes, the systemic risk increases significantly, while the heterogeneities of network nodes have no effect on systemic risk. As for firm micro-behaviors, including the selection range of trading partners, actual output, labor requirement, price of intermediate products and employee salaries, increase of all these parameters will lead to higher systemic risk.

  2. Large scale network-centric distributed systems

    CERN Document Server

    Sarbazi-Azad, Hamid

    2014-01-01

    A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

  3. A novel evaporation detection system using an impedance sensing chip.

    Science.gov (United States)

    Lin, Yung-Sheng; Chen, Cheng-You

    2014-11-21

    This paper presents a novel real-time impedance sensing chip for the evaporation detection of small volume solutions. Time sharing detection is performed for multiple sample measurements by a relay switching technique. In contrast to a conventional weight loss approach, the advantage of this proposed impedance sensing system is that it not only merely requires as little as 0.5 mL of test samples, but also provides high sensitivity and fast detection. More importantly, this proposed impedance sensing chip has advantages of a small chip size and easy decomposition for cleaning and reuse.

  4. Sparse Channel Estimation for MIMO-OFDM Two-Way Relay Network with Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Aihua Zhang

    2013-01-01

    Full Text Available Accurate channel impulse response (CIR is required for equalization and can help improve communication service quality in next-generation wireless communication systems. An example of an advanced system is amplify-and-forward multiple-input multiple-output two-way relay network, which is modulated by orthogonal frequency-division multiplexing. Linear channel estimation methods, for example, least squares and expectation conditional maximization, have been proposed previously for the system. However, these methods do not take advantage of channel sparsity, and they decrease estimation performance. We propose a sparse channel estimation scheme, which is different from linear methods, at end users under the relay channel to enable us to exploit sparsity. First, we formulate the sparse channel estimation problem as a compressed sensing problem by using sparse decomposition theory. Second, the CIR is reconstructed by CoSaMP and OMP algorithms. Finally, computer simulations are conducted to confirm the superiority of the proposed methods over traditional linear channel estimation methods.

  5. Green Cooperative Spectrum Sensing and Scheduling in Heterogeneous Cognitive Radio Networks

    KAUST Repository

    Celik, Abdulkadir

    2016-09-12

    In this paper, we consider heterogeneous cognitive radio networks (CRNs) comprising primary channels (PCs) with heterogeneous characteristics and secondary users (SUs) with various sensing and reporting qualities for different PCs. We first define the opportunity as the achievable total data rate and its cost as the energy consumption caused from sensing, reporting, and channel switching operations and formulate a joint spectrum discovery and energy efficiency objective to minimize the energy spent per unit of data rate. Then, a mixed integer nonlinear programming problem is formulated to determine: 1) the optimal subset of PCs to be scheduled for sensing; 2) the SU assignment set for each scheduled PC; and 3) sensing durations and detection thresholds of each SU on PCs it is assigned to sense. Thereafter, an equivalent convex framework is developed for specific instances of the above combinatorial problem. For comparison, optimal detection and sensing thresholds are also derived analytically under the homogeneity assumption. Based on these, a prioritized ordering heuristic is developed to order channels under the spectrum, energy, and spectrum-energy limited regimes. After that, a scheduling and assignment heuristic is proposed and is shown to perform very close to the exhaustive optimal solution. Finally, the behavior of the CRN is numerically analyzed under these regimes with respect to different numbers of SUs, PCs, and sensing qualities.

  6. ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Chaudhari

    2011-06-01

    Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

  7. System and Network Security Acronyms and Abbreviations

    Science.gov (United States)

    2009-09-01

    Systems Agency DLL dynamic link library DMA direct memory access DMZ demilitarized zone DN distinguished name DN domain name DNP Distributed...NetBIOS Network Basic Input/Output System NetBT NetBIOS over TCP/IP NFAT network forensic analysis tool NFC near field communication NFS network file...Software Reference Library NSS Network Security Services NSTB National SCADA Test Bed NSTISSC National Security Telecommunications and Information

  8. Surface sensing and signaling networks in plant pathogenic fungi.

    Science.gov (United States)

    Kou, Yanjun; Naqvi, Naweed I

    2016-09-01

    Pathogenic fungi have evolved highly varied and remarkable strategies to invade and infect their plant hosts. Typically, such fungal pathogens utilize highly specialized infection structures, morphologies or cell types produced from conidia or ascospores on the cognate host surfaces to gain entry therein. Such diverse infection strategies require intricate coordination in cell signaling and differentiation in phytopathogenic fungi. Here, we present an overview of our current understanding of cell signaling and infection-associated development that primes host penetration in the top ten plant pathogenic fungi, which utilize specific receptors to sense and respond to different surface cues, such as topographic features, hydrophobicity, hardness, plant lipids, phytohormones, and/or secreted enzymes. Subsequently, diverse signaling components such as G proteins, cyclic AMP/Protein Kinase A and MAP kinases are activated to enable the differentiation of infection structures. Recent studies have also provided fascinating insights into the spatio-temporal dynamics and specialized sequestration and trafficking of signaling moieties required for proper development of infection structures in phytopathogenic fungi. Molecular insight in such infection-related morphogenesis and cell signaling holds promise for identifying novel strategies for intervention of fungal diseases in plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Chip-scale hybrid optical sensing systems using digital signal processing.

    Science.gov (United States)

    Cho, Sang-Yeon; Borah, Deva K

    2009-01-05

    We propose a novel hybrid optical sensing system for standalone, chip-scale sensing applications. The hybrid optical sensing system detects any spectral shift of the microresonator sensor output by estimating the effective refractive index using maximum likelihood estimation. The performance evaluation of the proposed hybrid sensing system in the Gaussian-noise dominant environment shows excellent estimation accuracy. This innovative approach allows fully functional integrated hybrid sensing systems, offering great potential in various chip-scale sensing applications.

  10. On Connected Target Coverage for Wireless Heterogeneous Sensor Networks with Multiple Sensing Units

    Directory of Open Access Journals (Sweden)

    Hung-Chang Chen

    2009-06-01

    Full Text Available The paper considers the connected target coverage (CTC problem in wireless heterogeneous sensor networks (WHSNs with multiple sensing units, termed MU-CTC problem. MU-CTC problem can be reduced to a connected set cover problem and further formulated as an integer linear programming (ILP problem. However, the ILP problem is an NP-complete problem. Therefore, two distributed heuristic schemes, REFS (remaining energy first scheme and EEFS (energy efficiency first scheme, are proposed. In REFS, each sensor considers its remaining energy and its neighbors’ decisions to enable its sensing units and communication unit such that all targets can be covered for the required attributes and the sensed data can be delivered to the sink. The advantages of REFS are its simplicity and reduced communication overhead. However, to utilize sensors’ energy efficiently, EEFS is proposed. A sensor in EEFS considers its contribution to the coverage and the connectivity to make a better decision. To our best knowledge, this paper is the first to consider target coverage and connectivity jointly for WHSNs with multiple sensing units. Simulation results show that REFS and EEFS can both prolong the network lifetime effectively. EEFS outperforms REFS in network lifetime, but REFS is simpler.

  11. On connected target coverage for wireless heterogeneous sensor networks with multiple sensing units.

    Science.gov (United States)

    Shih, Kuei-Ping; Deng, Der-Jiunn; Chang, Ruay-Shiung; Chen, Hung-Chang

    2009-01-01

    The paper considers the connected target coverage (CTC) problem in wireless heterogeneous sensor networks (WHSNs) with multiple sensing units, termed MU-CTC problem. MU-CTC problem can be reduced to a connected set cover problem and further formulated as an integer linear programming (ILP) problem. However, the ILP problem is an NP-complete problem. Therefore, two distributed heuristic schemes, REFS (remaining energy first scheme) and EEFS (energy efficiency first scheme), are proposed. In REFS, each sensor considers its remaining energy and its neighbors' decisions to enable its sensing units and communication unit such that all targets can be covered for the required attributes and the sensed data can be delivered to the sink. The advantages of REFS are its simplicity and reduced communication overhead. However, to utilize sensors' energy efficiently, EEFS is proposed. A sensor in EEFS considers its contribution to the coverage and the connectivity to make a better decision. To our best knowledge, this paper is the first to consider target coverage and connectivity jointly for WHSNs with multiple sensing units. Simulation results show that REFS and EEFS can both prolong the network lifetime effectively. EEFS outperforms REFS in network lifetime, but REFS is simpler.

  12. Filtering and control of wireless networked systems

    CERN Document Server

    Zhang, Dan; Yu, Li

    2017-01-01

    This self-contained book, written by leading experts, offers a cutting-edge, in-depth overview of the filtering and control of wireless networked systems. It addresses the energy constraint and filter/controller gain variation problems, and presents both the centralized and the distributed solutions. The first two chapters provide an introduction to networked control systems and basic information on system analysis. Chapters (3–6) then discuss the centralized filtering of wireless networked systems, presenting different approaches to deal with energy efficiency and filter/controller gain variation problems. The next part (chapters 7–10) explores the distributed filtering of wireless networked systems, addressing the main problems of energy constraint and filter gain variation. The final part (chapters 11–14) focuses on the distributed control of wireless networked systems. networked systems for communication and control applications, the bo...

  13. A localized cooperative wideband spectrum sensing for dynamic access of TV bands using RF sensor networks

    KAUST Repository

    Mirza, Mohammed

    2011-07-01

    In this paper we address and simulate a Radio Frequency (RF) sensor network for a cooperative spectrum sensing and localization scheme. The proposed method integrates a Wavelet based Multi-Resolution Spectrum Sensing (MRSS), an N-bit hard combination technique for cooperative decision making and a Received Signal Strength (RSS) based localization algorithm to detect the availability of frequency bands and the location of the usable base station. We develop an N-bit hard combination technique and compare its performance to a traditionally used 2-bit hard combination for cooperative sensing. The key idea is to design a novel RF sensor network based cooperative wideband spectrum sensing and localization scheme by using a wavelet based Multi-Resolution Spectrum Sensing (MRSS) and Received Signal Strength (RSS) Localization techniques which were originally proposed for cognitive radio applications. The performance evaluations are also done to show the different detection accuracies for varying parameters such as number of sensor nodes, Signal to Noise Ratios (SNR) and number of averaged Power Spectral Densities (PSD). The proposed scheme improves the problems of shadowing, fading and noise. In addition, the RSS based localization technique was shown to be an acceptable means of estimating the position of the available transmitter. © 2011 IEEE.

  14. Angular Rate Sensing with GyroWheel Using Genetic Algorithm Optimized Neural Networks.

    Science.gov (United States)

    Zhao, Yuyu; Zhao, Hui; Huo, Xin; Yao, Yu

    2017-07-22

    GyroWheel is an integrated device that can provide three-axis control torques and two-axis angular rate sensing for small spacecrafts. Large tilt angle of its rotor and de-tuned spin rate lead to a complex and non-linear dynamics as well as difficulties in measuring angular rates. In this paper, the problem of angular rate sensing with the GyroWheel is investigated. Firstly, a simplified rate sensing equation is introduced, and the error characteristics of the method are analyzed. According to the analysis results, a rate sensing principle based on torque balance theory is developed, and a practical way to estimate the angular rates within the whole operating range of GyroWheel is provided by using explicit genetic algorithm optimized neural networks. The angular rates can be determined by the measurable values of the GyroWheel (including tilt angles, spin rate and torque coil currents), the weights and the biases of the neural networks. Finally, the simulation results are presented to illustrate the effectiveness of the proposed angular rate sensing method with GyroWheel.

  15. Innate immune sensing 2.0 - from linear activation pathways to fine tuned and regulated innate immune networks.

    Science.gov (United States)

    Volz, Thomas; Kaesler, Susanne; Biedermann, Tilo

    2012-01-01

    The innate immune system is based on pathogen recognition receptors that bind conserved microbial molecular structures, so called pathogen-associated molecular patterns (PAMPs). The characterization of the innate immune system was long based on a linear step-wise concept of recognition, activation pathways and effector defense mechanisms. Only more recently it was recognized that the innate immune system needs regulatory elements, sideways and crosstalks that allows it to fine tune and adapt its response. Thus, it is an emerging field within innate immunity research to try to understand how the immune outcome of innate immune sensing is regulated and why immune responses can be substantially different, even though the same PAMPs may have been 'sensed' at the surface organs such as the skin. Only the expansion of the innate immune system from 'pure' linear activation pathways to fine tuned and regulated innate immune networks allows us to integrate the generation of gradually accentuated and qualitatively different effector and tolerogenic immune responses. This article provides a review of the basic concepts and players of the innate immune system and will present some of the newer data defining the innate immune networks effectively regulating the immune homoeostasis and immune effector mechanisms with special focus on the skin as one of the organs involved in regulating the immune interface between the environment and the organism. © 2011 John Wiley & Sons A/S.

  16. Full-Duplex Cooperative Sensing for Spectrum-Heterogeneous Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2017-08-01

    Full Text Available In cognitive radio networks (CRNs, spectrum sensing is critical for guaranteeing that the opportunistic spectrum access by secondary users (SUs will not interrupt legitimate primary users (PUs. The application of full-duplex radio to spectrum sensing enables SU to carry out sensing and transmission simultaneously, improving both spectrum awareness and CRN throughput. However, the issue of spectrum sensing with full-duplex radios deployed in heterogeneous environments, where SUs may observe different spectrum activities, has not been addressed. In this paper, we give a first look into this problem and develop a light-weight cooperative sensing framework called PaCoSIF, which involves only a pairwise SU transmitter (SU-Tx and its receiver (SU-Rx in cooperation. A dedicated control channel is not required for pairwise cooperative sensing with instantaneous feedback (PaCoSIF because sensing results are collected and fused via the reverse channel provided by full-duplex radios. We present a detailed protocol description to illustrate how PaCoSIF works. However, it is a challenge to optimize the sensing performance of PaCoSIF since the two sensors suffer from spectrum heterogeneity and different kinds of interference. Our goal is to minimize the false alarm rate of PaCoSIF given the bound on the missed detection rate by adaptively adjusting the detection threshold of each sensor. We derive an expression for the optimal threshold using the Lagrange method and propose a fast binary-searching algorithm to solve it numerically. Simulations show that, with perfect signal-to-interference-and-noise-ratio (SINR information, PaCoSIF could decrease the false alarm rate and boost CRN throughput significantly against conventional cooperative sensing when SUs are deployed in spectrum-heterogeneous environments. Finally, the impact of SINR error upon the performance of PaCoSIF is evaluated via extensive simulations.

  17. Full-Duplex Cooperative Sensing for Spectrum-Heterogeneous Cognitive Radio Networks.

    Science.gov (United States)

    Liu, Peng; Qi, Wangdong; Yuan, En; Wei, Li; Zhao, Yuexin

    2017-08-02

    In cognitive radio networks (CRNs), spectrum sensing is critical for guaranteeing that the opportunistic spectrum access by secondary users (SUs) will not interrupt legitimate primary users (PUs). The application of full-duplex radio to spectrum sensing enables SU to carry out sensing and transmission simultaneously, improving both spectrum awareness and CRN throughput. However, the issue of spectrum sensing with full-duplex radios deployed in heterogeneous environments, where SUs may observe different spectrum activities, has not been addressed. In this paper, we give a first look into this problem and develop a light-weight cooperative sensing framework called PaCoSIF, which involves only a pairwise SU transmitter (SU-Tx) and its receiver (SU-Rx) in cooperation. A dedicated control channel is not required for pairwise cooperative sensing with instantaneous feedback (PaCoSIF) because sensing results are collected and fused via the reverse channel provided by full-duplex radios. We present a detailed protocol description to illustrate how PaCoSIF works. However, it is a challenge to optimize the sensing performance of PaCoSIF since the two sensors suffer from spectrum heterogeneity and different kinds of interference. Our goal is to minimize the false alarm rate of PaCoSIF given the bound on the missed detection rate by adaptively adjusting the detection threshold of each sensor. We derive an expression for the optimal threshold using the Lagrange method and propose a fast binary-searching algorithm to solve it numerically. Simulations show that, with perfect signal-to-interference-and-noise-ratio (SINR) information, PaCoSIF could decrease the false alarm rate and boost CRN throughput significantly against conventional cooperative sensing when SUs are deployed in spectrum-heterogeneous environments. Finally, the impact of SINR error upon the performance of PaCoSIF is evaluated via extensive simulations.

  18. Social Sensor Analytics: Making Sense of Network Models in Social Media

    Energy Technology Data Exchange (ETDEWEB)

    Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.; Sego, Landon H.; Corley, Courtney D.

    2015-07-27

    Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013 and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.

  19. On the Capability of Artificial Neural Networks to Compensate Nonlinearities in Wavelength Sensing

    Science.gov (United States)

    Hafiane, Mohamed Lamine; Dibi, Zohir; Manck, Otto

    2009-01-01

    An intelligent sensor for light wavelength readout, suitable for visible range optical applications, has been developed. Using buried triple photo-junction as basic pixel sensing element in combination with artificial neural network (ANN), the wavelength readout with a full-scale error of less than 1.5% over the range of 400 to 780 nm can be achieved. Through this work, the applicability of the ANN approach in optical sensing is investigated and compared with conventional methods, and a good compromise between accuracy and the possibility for on-chip implementation was thus found. Indeed, this technique can serve different purposes and may replace conventional methods. PMID:22574051

  20. Graphene-Elastomer Composites with Segregated Nanostructured Network for Liquid and Strain Sensing Application.

    Science.gov (United States)

    Lin, Yong; Dong, Xuchu; Liu, Shuqi; Chen, Song; Wei, Yong; Liu, Lan

    2016-09-14

    One of the critical issues for the fabrication of desirable sensing materials has focused on the construction of an effective continuous network with a low percolation threshold. Herein, graphene-based elastomer composites with a segregated nanostructured graphene network were prepared by a novel and effective ice-templating strategy. The segregated graphene network bestowed on the natural rubber (NR) composites an ultralow electrical percolation threshold (0.4 vol %), 8-fold lower than that of the NR/graphene composites with homogeneous dispersion morphology (3.6 vol %). The resulting composites containing 0.63 vol % graphene exhibited high liquid sensing responsivity (6700), low response time (114 s), and good reproducibility. The unique segregated structure also provides this graphene-based elastomer (containing 0.42 vol % graphene) with exceptionally high stretchability, sensitivity (gauge factor ≈ 139), and good reproducibility (∼400 cycles) of up to 60% strain under cyclic tests. The fascinating performances highlight the potential applications of graphene-elastomer composites with an effective segregated network as multifunctional sensing materials.

  1. A Situated Cultural Festival Learning System Based on Motion Sensing

    Science.gov (United States)

    Chang, Yi-Hsing; Lin, Yu-Kai; Fang, Rong-Jyue; Lu, You-Te

    2017-01-01

    A situated Chinese cultural festival learning system based on motion sensing is developed in this study. The primary design principle is to create a highly interactive learning environment, allowing learners to interact with Kinect through natural gestures in the designed learning situation to achieve efficient learning. The system has the…

  2. Making Sense of Alternative Assessment in a Qualitative Evaluation System

    Science.gov (United States)

    Rojas Serrano, Javier

    2017-01-01

    In a Colombian private English institution, a qualitative evaluation system has been incorporated. This type of evaluation poses challenges to students who have never been evaluated through a system that eliminates exams or quizzes and, as a consequence, these students have to start making sense of it. This study explores the way students face the…

  3. Developing an On-Demand Cloud-Based Sensing-as-a-Service System for Internet of Things

    Directory of Open Access Journals (Sweden)

    Mihui Kim

    2016-01-01

    Full Text Available The increasing number of Internet of Things (IoT devices with various sensors has resulted in a focus on Cloud-based sensing-as-a-service (CSaaS as a new value-added service, for example, providing temperature-sensing data via a cloud computing system. However, the industry encounters various challenges in the dynamic provisioning of on-demand CSaaS on diverse sensor networks. We require a system that will provide users with standardized access to various sensor networks and a level of abstraction that hides the underlying complexity. In this study, we aim to develop a cloud-based solution to address the challenges mentioned earlier. Our solution, SenseCloud, includes a sensor virtualization mechanism that interfaces with diverse sensor networks, a multitenancy mechanism that grants multiple users access to virtualized sensor networks while sharing the same underlying infrastructure, and a dynamic provisioning mechanism to allow the users to leverage the vast pool of resources on demand and on a pay-per-use basis. We implement a prototype of SenseCloud by using real sensors and verify the feasibility of our system and its performance. SenseCloud bridges the gap between sensor providers and sensor data consumers who wish to utilize sensor data.

  4. A Cross-Layer Approach in Sensing and Resource Allocation for Multimedia Transmission over Cognitive UWB Networks

    Directory of Open Access Journals (Sweden)

    Lo ACC

    2010-01-01

    Full Text Available We propose an MAC centric cross-layer approach to address the problem of multimedia transmission over cognitive Ultra Wideband (C-UWB networks. Several fundamental design issues, which are related to application (APP, medium access control (MAC, and physical (PHY layer, are discussed. Although substantial research has been carried out in the PHY layer perspective of cognitive radio system, this paper attempts to extend the existing research paradigm to MAC and APP layers, which can be considered as premature at this time. This paper proposed a cross-layer design that is aware of (a UWB wireless channel conditions, (b time slot allocations at the MAC layer, and (c MPEG-4 video at the APP layer. Two cooperative sensing mechanisms, namely, AND and OR, are analyzed in terms of probability of detection ( , probability of false alarm ( , and the required sensing period. Then, the impact of sensing scheduling to the MPEG-4 video transmission over wireless cognitive UWB networks is observed. In addition, we also proposed the packet reception rate- (PRR- based resource allocation scheme that is aware of the channel condition, target PRR, and queue status.

  5. Spectrum Sensing and Primary User Localization in Cognitive Radio Networks via Sparsity

    Directory of Open Access Journals (Sweden)

    Lanchao Liu

    2016-01-01

    Full Text Available The theory of compressive sensing (CS has been employed to detect available spectrum resource in cognitive radio (CR networks recently. Capitalizing on the spectrum resource underutilization and spatial sparsity of primary user (PU locations, CS enables the identification of the unused spectrum bands and PU locations at a low sampling rate. Although CS has been studied in the cooperative spectrum sensing mechanism in which CR nodes work collaboratively to accomplish the spectrum sensing and PU localization task, many important issues remain unsettled. Does the designed compressive spectrum sensing mechanism satisfy the Restricted Isometry Property, which guarantees a successful recovery of the original sparse signal? Can the spectrum sensing results help the localization of PUs? What are the characteristics of localization errors? To answer those questions, we try to justify the applicability of the CS theory to the compressive spectrum sensing framework in this paper, and propose a design of PU localization utilizing the spectrum usage information. The localization error is analyzed by the Cramér-Rao lower bound, which can be exploited to improve the localization performance. Detail analysis and simulations are presented to support the claims and demonstrate the efficacy and efficiency of the proposed mechanism.

  6. Making sense of enterprise systems in institutions

    DEFF Research Database (Denmark)

    Svejvig, Per; Jensen, Tina Blegind

    2013-01-01

    system travelled from a national to a local level, how the system moved from being highly customized to becoming a standard package and how the users’ enactment of the system reinforced existing institutional practices. Based on the findings, we frame our contributions into five lessons learned: (1......) An ES implementation entails mutual adaptations between the organization, human actors and enterprise system; (2) “small is beautiful” is almost a truism but may turn out to be an appropriate starting point; (3) a certain level of resilience is essential to cope with future upgrades and enhancements; (4...

  7. Operating systems and network protocols for wireless sensor networks.

    Science.gov (United States)

    Dutta, Prabal; Dunkels, Adam

    2012-01-13

    Sensor network protocols exist to satisfy the communication needs of diverse applications, including data collection, event detection, target tracking and control. Network protocols to enable these services are constrained by the extreme resource scarcity of sensor nodes-including energy, computing, communications and storage-which must be carefully managed and multiplexed by the operating system. These challenges have led to new protocols and operating systems that are efficient in their energy consumption, careful in their computational needs and miserly in their memory footprints, all while discovering neighbours, forming networks, delivering data and correcting failures.

  8. Collaboratively Adaptive Vibration Sensing System for High-fidelity Monitoring of Structural Responses Induced by Pedestrians

    Directory of Open Access Journals (Sweden)

    Shijia Pan

    2017-05-01

    Full Text Available This paper presents a collaboratively adaptive vibration monitoring system that captures high-fidelity structural vibration signals induced by pedestrians. These signals can be used for various human activities’ monitoring by inferring information about the impact sources, such as pedestrian footsteps, door opening and closing, and dragging objects. Such applications often require high-fidelity (high resolution and low distortion signals. Traditionally, expensive high resolution and high dynamic range sensors are adopted to ensure sufficient resolution. However, for sensing systems that use low-cost sensing devices, the resolution and dynamic range are often limited; hence this type of sensing methods is not well explored ubiquitously. We propose a low-cost sensing system that utilizes (1 a heuristic model of the investigating excitations and (2 shared information through networked devices to adapt hardware configurations and obtain high-fidelity structural vibration signals. To further explain the system, we use indoor pedestrian footstep sensing through ambient structural vibration as an example to demonstrate the system performance. We evaluate the application with three metrics that measure the signal quality from different aspects: the sufficient resolution rate to present signal resolution improvement without clipping, the clipping rate to measure the distortion of the footstep signal, and the signal magnitude to quantify the detailed resolution of the detected footstep signal. In experiments conducted in a school building, our system demonstrated up to 2× increase on the sufficient resolution rate and 2× less error rate when used to locate the pedestrians as they walk along the hallway, compared to a fixed sensing setting.

  9. Network Intrusion Detection System using Apache Storm

    Directory of Open Access Journals (Sweden)

    Muhammad Asif Manzoor

    2017-06-01

    Full Text Available Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various systems are proposed to enhance the network security. We are proposing to use anomaly based network intrusion detection system in this work. Anomaly based intrusion detection system can identify the new network threats. We also propose to use Real-time Big Data Stream Processing Framework, Apache Storm, for the implementation of network intrusion detection system. Apache Storm can help to manage the network traffic which is generated at enormous speed and size and the network traffic speed and size is constantly increasing. We have used Support Vector Machine in this work. We use Knowledge Discovery and Data Mining 1999 (KDD’99 dataset to test and evaluate our proposed solution.

  10. Model-based control of networked systems

    CERN Document Server

    Garcia, Eloy; Montestruque, Luis A

    2014-01-01

    This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.   The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.   Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...

  11. Unmanned aerial systems for photogrammetry and remote sensing: A review

    OpenAIRE

    Colomina, Ismael; Molina, Pere

    2014-01-01

    We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last...

  12. Multiple Classifier System for Remote Sensing Image Classification: A Review

    Directory of Open Access Journals (Sweden)

    Yi Liu

    2012-04-01

    Full Text Available Over the last two decades, multiple classifier system (MCS or classifier ensemble has shown great potential to improve the accuracy and reliability of remote sensing image classification. Although there are lots of literatures covering the MCS approaches, there is a lack of a comprehensive literature review which presents an overall architecture of the basic principles and trends behind the design of remote sensing classifier ensemble. Therefore, in order to give a reference point for MCS approaches, this paper attempts to explicitly review the remote sensing implementations of MCS and proposes some modified approaches. The effectiveness of existing and improved algorithms are analyzed and evaluated by multi-source remotely sensed images, including high spatial resolution image (QuickBird, hyperspectral image (OMISII and multi-spectral image (Landsat ETM+.Experimental results demonstrate that MCS can effectively improve the accuracy and stability of remote sensing image classification, and diversity measures play an active role for the combination of multiple classifiers. Furthermore, this survey provides a roadmap to guide future research, algorithm enhancement and facilitate knowledge accumulation of MCS in remote sensing community.

  13. Automated optical sensing system for biochemical assays

    Science.gov (United States)

    Oroszlan, Peter; Duveneck, Gert L.; Ehrat, Markus; Widmer, H. M.

    1994-03-01

    In this paper, we present a new system called FOBIA that was developed and optimized with respect to automated operation of repetitive assay cycles with regenerable bioaffinity sensors. The reliability and precision of the new system is demonstrated by an application in a competitive assay for the detection of the triazine herbicide Atrazine. Using one sensor in more than 300 repetitive cycles, a signal precision better than 5% was achieved.

  14. Self-sensing of dielectric elastomer actuator enhanced by artificial neural network

    Science.gov (United States)

    Ye, Zhihang; Chen, Zheng

    2017-09-01

    Dielectric elastomer (DE) is a type of soft actuating material, the shape of which can be changed under electrical voltage stimuli. DE materials have promising usage in future’s soft actuators and sensors, such as soft robotics, energy harvesters, and wearable sensors. In this paper, a stripe DE actuator with integrated sensing capability is designed, fabricated, and characterized. Since the strip actuator can be approximated as a compliant capacitor, it is possible to detect the actuator’s displacement by analyzing the actuator’s impedance change. An integrated sensing scheme that adds a high frequency probing signal into actuation signal is developed. Electrical impedance changes in the probing signal are extracted by fast Fourier transform algorithm, and nonlinear data fitting methods involving artificial neural network are implemented to detect the actuator’s displacement. A series of experiments show that by improving data processing and analyzing methods, the integrated sensing method can achieve error level of lower than 1%.

  15. Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

    Science.gov (United States)

    Ren, Shengwei; Zhang, Li; Zhang, Shibing

    2016-10-01

    Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

  16. Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks

    Science.gov (United States)

    Alshehhi, Rasha; Marpu, Prashanth Reddy; Woon, Wei Lee; Mura, Mauro Dalla

    2017-08-01

    Extraction of man-made objects (e.g., roads and buildings) from remotely sensed imagery plays an important role in many urban applications (e.g., urban land use and land cover assessment, updating geographical databases, change detection, etc). This task is normally difficult due to complex data in the form of heterogeneous appearance with large intra-class and lower inter-class variations. In this work, we propose a single patch-based Convolutional Neural Network (CNN) architecture for extraction of roads and buildings from high-resolution remote sensing data. Low-level features of roads and buildings (e.g., asymmetry and compactness) of adjacent regions are integrated with Convolutional Neural Network (CNN) features during the post-processing stage to improve the performance. Experiments are conducted on two challenging datasets of high-resolution images to demonstrate the performance of the proposed network architecture and the results are compared with other patch-based network architectures. The results demonstrate the validity and superior performance of the proposed network architecture for extracting roads and buildings in urban areas.

  17. Next generation infrared sensor instrumentation: remote sensing and sensor networks using the openPHOTONS repository

    Science.gov (United States)

    So, Stephen; Jeng, Evan; Smith, Clinton; Krueger, David; Wysocki, Gerard

    2010-09-01

    We describe our novel instrumentation architectures for infrared laser spectrometers. Compact, power efficient, low noise modules allow for optimized implementation of cell phone sized sensors using VCSELs, diode, and quantum cascade laser sources. These sensors can consume as little as 0.3W with full laser temperature (adapted to new optical configurations and applications. Such modules allow the development of flexible sensors, whether implementing closed path spectrometers, open path perimeter monitoring, or remote backscatter based sensors. This work is also the enabling technology for wireless sensor networks (WSN) of precision sensors, a desirable sensing paradigm for long term, wide area, precision, temporally and spatially resolved studies. This approach can complement existing remote sensing and mapping technologies including satellite observations and sparse networks of flux towers.

  18. Recommendation-Aware Smartphone Sensing System

    Directory of Open Access Journals (Sweden)

    Mu-Yen Chen

    2014-12-01

    Full Text Available The context-aware concept is to reduce the gap between users and information systems so that the information systems actively get to understand users’ context and demand and in return provide users with better experience. This study integrates the concept of context-aware with association algorithms to establish the context-aware recommendation systems (CARS. The CARS contains three modules and provides the product recommendations for users with their smartphone. First, the simple RSSI Indoor localization module (SRILM locates the user position and detects the context information surrounding around users. Second, the Apriori recommendation module (ARM provides effective recommended product information for users through association rules mining. The appropriate product information can be received effectiveness and greatly enhanced the recommendation service.

  19. Finding communities in networks in the strong and almost-strong sense

    Science.gov (United States)

    Cafieri, Sonia; Caporossi, Gilles; Hansen, Pierre; Perron, Sylvain; Costa, Alberto

    2012-04-01

    Finding communities, or clusters or modules, in networks can be done by optimizing an objective function defined globally and/or by specifying conditions which must be satisfied by all communities. Radicchi [Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.0400054101 101, 2658 (2004)] define a susbset of vertices of a network to be a community in the strong sense if each vertex of that subset has a larger inner degree than its outer degree. A partition in the strong sense has only strong communities. In this paper we first define an enumerative algorithm to list all partitions in the strong sense of a network of moderate size. The results of this algorithm are given for the Zachary karate club data set, which is solved by hand, as well as for several well-known real-world problems of the literature. Moreover, this algorithm is slightly modified in order to apply it to larger networks, keeping only partitions with the largest number of communities. It is shown that some of the partitions obtained are informative, although they often have only a few communities, while they fail to give any information in other cases having only one community. It appears that degree 2 vertices play a big role in forcing large inhomogeneous communities. Therefore, a weakening of the strong condition is proposed and explored: we define a partition in the almost-strong sense by substituting a nonstrict inequality to a strict one in the definition of strong community for all vertices of degree 2. Results, for the same set of problems as before, then give partitions with a larger number of communities and are more informative.

  20. BEMS systems give developer sixth sense.

    Science.gov (United States)

    Baillie, Jonathan

    2011-08-01

    Duty-bound under contracts with partner NHS PCTs, independent primary care contractors, and other community stakeholders who lease healthcare premises from it, to ensure that the buildings' energy systems and plant run efficiently and cost-effectively, Community Solutions, a leading investor in, and developer of, UK community-based health, social, and local authority services, is now standardising on Trend Controls' building energy management systems to ensure that such vital equipment runs within defined parameters, and that facilities without FM personnel on site day-to-day are kept both comfortable to work in, and fit-for-purpose.

  1. Study on additional carrier sensing for IEEE 802.15.4 wireless sensor networks.

    Science.gov (United States)

    Lee, Bih-Hwang; Lai, Ruei-Lung; Wu, Huai-Kuei; Wong, Chi-Ming

    2010-01-01

    Wireless sensor networks based on the IEEE 802.15.4 standard are able to achieve low-power transmissions in the guise of low-rate and short-distance wireless personal area networks (WPANs). The slotted carrier sense multiple access with collision avoidance (CSMA/CA) is used for contention mechanism. Sensor nodes perform a backoff process as soon as the clear channel assessment (CCA) detects a busy channel. In doing so they may neglect the implicit information of the failed CCA detection and further cause the redundant sensing. The blind backoff process in the slotted CSMA/CA will cause lower channel utilization. This paper proposes an additional carrier sensing (ACS) algorithm based on IEEE 802.15.4 to enhance the carrier sensing mechanism for the original slotted CSMA/CA. An analytical Markov chain model is developed to evaluate the performance of the ACS algorithm. Both analytical and simulation results show that the proposed algorithm performs better than IEEE 802.15.4, which in turn significantly improves throughput, average medium access control (MAC) delay and power consumption of CCA detection.

  2. Neural Network Back-Propagation Algorithm for Sensing Hypergols

    Science.gov (United States)

    Perotti, Jose; Lewis, Mark; Medelius, Pedro; Bastin, Gary

    2013-01-01

    Fast, continuous detection of a wide range of hazardous substances simultaneously is needed to achieve improved safety for personnel working with hypergolic fuels and oxidizers, as well as other hazardous substances, with a requirement for such detection systems to warn personnel immediately upon the sudden advent of hazardous conditions, with a high probability of detection and a low false alarm rate. The primary purpose of this software is to read the voltage outputs from voltage dividers containing carbon nano - tube sensors as a variable resistance leg, and to recognize quickly when a leak has occurred through recognizing that a generalized pattern change in resistivity of a carbon nanotube sensor has occurred upon exposure to dangerous substances, and, further, to identify quickly just what substance is present through detailed pattern recognition of the shape of the response provided by the carbon nanotube sensor.

  3. Chemo-optical micro-sensing systems

    NARCIS (Netherlands)

    Lambeck, Paul

    1991-01-01

    Chemo-optical microsensing systems, whether based on fiber optics or integrated optics, show promising prospects. The physical principles underlying chemo-optical waveguide sensors are discussed with the accent on linear evanescent field sensors. The role of the chemo-optical transduction layer is

  4. Material requirements for bio-inspired sensing systems

    Science.gov (United States)

    Biggins, Peter; Lloyd, Peter; Salmond, David; Kusterbeck, Anne

    2008-10-01

    The aim of developing bio-inspired sensing systems is to try and emulate the amazing sensitivity and specificity observed in the natural world. These capabilities have evolved, often for specific tasks, which provide the organism with an advantage in its fight to survive and prosper. Capabilities cover a wide range of sensing functions including vision, temperature, hearing, touch, taste and smell. For some functions, the capabilities of natural systems are still greater than that achieved by traditional engineering solutions; a good example being a dog's sense of smell. Furthermore, attempting to emulate aspects of biological optics, processing and guidance may lead to more simple and effective devices. A bio-inspired sensing system is much more than the sensory mechanism. A system will need to collect samples, especially if pathogens or chemicals are of interest. Other functions could include the provision of power, surfaces and receptors, structure, locomotion and control. In fact it is possible to conceive of a complete bio-inspired system concept which is likely to be radically different from more conventional approaches. This concept will be described and individual component technologies considered.

  5. Control theory of digitally networked dynamic systems

    CERN Document Server

    Lunze, Jan

    2013-01-01

    The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic

  6. Making sense of information in noisy networks: human communication, gossip, and distortion.

    Science.gov (United States)

    Laidre, Mark E; Lamb, Alex; Shultz, Susanne; Olsen, Megan

    2013-01-21

    Information from others can be unreliable. Humans nevertheless act on such information, including gossip, to make various social calculations, thus raising the question of whether individuals can sort through social information to identify what is, in fact, true. Inspired by empirical literature on people's decision-making when considering gossip, we built an agent-based simulation model to examine how well simple decision rules could make sense of information as it propagated through a network. Our simulations revealed that a minimalistic decision-rule 'Bit-wise mode' - which compared information from multiple sources and then sought a consensus majority for each component bit within the message - was consistently the most successful at converging upon the truth. This decision rule attained high relative fitness even in maximally noisy networks, composed entirely of nodes that distorted the message. The rule was also superior to other decision rules regardless of its frequency in the population. Simulations carried out with variable agent memory constraints, different numbers of observers who initiated information propagation, and a variety of network types suggested that the single most important factor in making sense of information was the number of independent sources that agents could consult. Broadly, our model suggests that despite the distortion information is subject to in the real world, it is nevertheless possible to make sense of it based on simple Darwinian computations that integrate multiple sources. Copyright © 2012 Elsevier Ltd. All rights reserved.

  7. gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks

    KAUST Repository

    Al-Halafi, Abdullah

    2016-09-08

    Wireless sensor networks (WSN) are widely used to sense and measure physical conditions for different purposes and within different regions. However due to the limited lifetime of the sensor\\'s energy source, many efforts are made to design energy efficient WSN. As a result, many techniques were presented in the literature such as power adaptation, sleep and wake-up, and scheduling in order to enhance WSN lifetime. These techniques where presented separately and shown to achieve some gain in terms of energy efficiency. In this paper, we present an energy efficient cross layer design for WSN that we named \\'green Task-Based Sensing\\' (gTBS) scheme. The gTBS design is a task based sensing scheme that not only prevents wasting power in unnecessary signaling, but also utilizes several techniques for achieving reliable and energy efficient WSN. The proposed gTBS combines the power adaptation with a sleep and wake-up technique that allows inactive nodes to sleep. Also, it adopts a gradient-oriented unicast approach to overcome the synchronization problem, minimize network traffic hurdles, and significantly reduce the overall power consumption of the network. We implement the gTBS on a testbed and we show that it reduces the power consumption by a factor of 20%-55% compared to traditional TBS. It also reduces the delay by 54%-145% and improves the delivery ratio by 24%-73%. © 2016 IEEE.

  8. A soft-hard combination-based cooperative spectrum sensing scheme for cognitive radio networks.

    Science.gov (United States)

    Do, Nhu Tri; An, Beongku

    2015-02-13

    In this paper we propose a soft-hard combination scheme, called SHC scheme, for cooperative spectrum sensing in cognitive radio networks. The SHC scheme deploys a cluster based network in which Likelihood Ratio Test (LRT)-based soft combination is applied at each cluster, and weighted decision fusion rule-based hard combination is utilized at the fusion center. The novelties of the SHC scheme are as follows: the structure of the SHC scheme reduces the complexity of cooperative detection which is an inherent limitation of soft combination schemes. By using the LRT, we can detect primary signals in a low signal-to-noise ratio regime (around an average of -15 dB). In addition, the computational complexity of the LRT is reduced since we derive the closed-form expression of the probability density function of LRT value. The SHC scheme also takes into account the different effects of large scale fading on different users in the wide area network. The simulation results show that the SHC scheme not only provides the better sensing performance compared to the conventional hard combination schemes, but also reduces sensing overhead in terms of reporting time compared to the conventional soft combination scheme using the LRT.

  9. Observing Arctic Ecology using Networked Infomechanical Systems

    Science.gov (United States)

    Healey, N. C.; Oberbauer, S. F.; Hollister, R. D.; Tweedie, C. E.; Welker, J. M.; Gould, W. A.

    2012-12-01

    Understanding ecological dynamics is important for investigation into the potential impacts of climate change in the Arctic. Established in the early 1990's, the International Tundra Experiment (ITEX) began observational inquiry of plant phenology, plant growth, community composition, and ecosystem properties as part of a greater effort to study changes across the Arctic. Unfortunately, these observations are labor intensive and time consuming, greatly limiting their frequency and spatial coverage. We have expanded the capability of ITEX to analyze ecological phenomenon with improved spatial and temporal resolution through the use of Networked Infomechanical Systems (NIMS) as part of the Arctic Observing Network (AON) program. The systems exhibit customizable infrastructure that supports a high level of versatility in sensor arrays in combination with information technology that allows for adaptable configurations to numerous environmental observation applications. We observe stereo and static time-lapse photography, air and surface temperature, incoming and outgoing long and short wave radiation, net radiation, and hyperspectral reflectance that provides critical information to understanding how vegetation in the Arctic is responding to ambient climate conditions. These measurements are conducted concurrent with ongoing manual measurements using ITEX protocols. Our NIMS travels at a rate of three centimeters per second while suspended on steel cables that are ~1 m from the surface spanning transects ~50 m in length. The transects are located to span soil moisture gradients across a variety of land cover types including dry heath, moist acidic tussock tundra, shrub tundra, wet meadows, dry meadows, and water tracks. We have deployed NIMS at four locations on the North Slope of Alaska, USA associated with 1 km2 ARCSS vegetation study grids including Barrow, Atqasuk, Toolik Lake, and Imnavait Creek. A fifth system has been deployed in Thule, Greenland beginning in

  10. A Versatile Prototyping System for Capacitive Sensing

    Directory of Open Access Journals (Sweden)

    Daniel HRACH

    2008-04-01

    Full Text Available This paper presents a multi-purpose and easy to handle rapid prototyping platform that has been designed for capacitive measurement systems. The core of the prototype platform is a Digital Signal Processor board that allows for the entire data acquisition, data (pre- processing and storage, and communication with any host computer. The platform is running on uCLinux operating system and features the possibility of a fast design and evaluation of capacitive sensor developments. To show the practical benefit of the prototyping platform, three exemplary applications are presented. For all applications, the platform is just plugged to the electrode structure of the sensor front-end without the need for analogue signal pre-conditioning.

  11. An Integrated System for Wildlife Sensing

    Science.gov (United States)

    2014-08-14

    more precisely, and would accommodate a tripod as well. 2. Multisensor fusion . Additional sensors could be mated with the FLIR camera, particularly...range sensors. Examples include light-weight laser rangefinders and ultrasound devices. In some cases, multisensor fusion can be performed using...integrated system for collecting visual data (video and still images) from an infrared camera along with registered sensor data (including GPS location

  12. Network management systems for active distribution networks. A feasibility study

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, D.A.

    2004-07-01

    A technical feasibility study on network management systems for active distribution networks is reported. The study investigated the potential for modifying a Distribution Network Operator (DNO) Supervisory Control and Data Acquisition System (SCADA) to give some degree of active management. Government incentives have encouraged more and more embedded generation being connected to the UK distribution networks and further acceleration of the process should support the 2010 target for a reduction in emissions of carbon dioxide. The report lists the objectives of the study and summarises what has been achieved; it also discusses limitations, reliability and resilience of existing SCADA. Safety and operational communications are discussed under staff safety and operational safety. Recommendations that could facilitate active management through SCADA are listed, together with suggestions for further study. The work was carried out as part of the DTI New and Renewable Energy Programme managed by Future Energy Solutions.

  13. Network systems and groupware for public facilities; Network system to groupware

    Energy Technology Data Exchange (ETDEWEB)

    Torimaru, K.; Kubo, S. [Fuji Electric Co. Ltd., Tokyo (Japan); Takeda, K. [Osaki Computer Engineering Co. Ltd., Tokyo (Japan)

    1999-12-10

    This paper outlines solutions for network systems and groupware for the infrastructure of information systems in public facilities. With regard to network systems, Fuji Electric's network solutions including requirements of public facilities and application examples are described. With regard to groupware, the status of groupware used for raising efficiency in public facilities and groupware packages marketed by Fuji Electric. (author)

  14. Learning Low Dimensional Convolutional Neural Networks for High-Resolution Remote Sensing Image Retrieval

    Directory of Open Access Journals (Sweden)

    Weixun Zhou

    2017-05-01

    Full Text Available Learning powerful feature representations for image retrieval has always been a challenging task in the field of remote sensing. Traditional methods focus on extracting low-level hand-crafted features which are not only time-consuming but also tend to achieve unsatisfactory performance due to the complexity of remote sensing images. In this paper, we investigate how to extract deep feature representations based on convolutional neural networks (CNNs for high-resolution remote sensing image retrieval (HRRSIR. To this end, several effective schemes are proposed to generate powerful feature representations for HRRSIR. In the first scheme, a CNN pre-trained on a different problem is treated as a feature extractor since there are no sufficiently-sized remote sensing datasets to train a CNN from scratch. In the second scheme, we investigate learning features that are specific to our problem by first fine-tuning the pre-trained CNN on a remote sensing dataset and then proposing a novel CNN architecture based on convolutional layers and a three-layer perceptron. The novel CNN has fewer parameters than the pre-trained and fine-tuned CNNs and can learn low dimensional features from limited labelled images. The schemes are evaluated on several challenging, publicly available datasets. The results indicate that the proposed schemes, particularly the novel CNN, achieve state-of-the-art performance.

  15. Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

    Science.gov (United States)

    Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

    2017-09-01

    With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

  16. APPLICATION OF CONVOLUTIONAL NEURAL NETWORK IN CLASSIFICATION OF HIGH RESOLUTION AGRICULTURAL REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    C. Yao

    2017-09-01

    Full Text Available With the rapid development of Precision Agriculture (PA promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN. For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

  17. Optimal Entropy-Based Cooperative Spectrum Sensing for Maritime Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Waleed Ejaz

    2013-11-01

    Full Text Available Maritime cognitive radio networks (MCRNs have recently been proposed for opportunistic utilization of the licensed band. Spectrum sensing is one of the key issues for the successful deployment of the MCRNs. The maritime environment is unique in terms of radio wave propagation over water, surface reflection and wave occlusions. In order to deal with the challenging maritime environment, we proposed an optimal entropy-based cooperative spectrum sensing. As the results of spectrum sensing are sensitive to the number of samples in an entropy-based local detection scheme, we first calculated the optimal number of samples. Next, a cooperative spectrum sensing scheme considering the conditions of the sea environment is proposed. Finally, the throughput optimization of the m-out-of-n rule is considered. Results revealed that although the existing schemes work well for the lower sea states, they fail to perform at higher sea states. Moreover, simulation results also indicated the robustness of the entropy-based scheme and the proposed cooperative spectrum sensing scheme at higher sea states in comparison with the traditional energy detector.

  18. Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks.

    Science.gov (United States)

    Zheng, Haifeng; Li, Jiayin; Feng, Xinxin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

    2017-11-08

    Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs .

  19. Multichannel-Sensing Scheduling and Transmission-Energy Optimizing in Cognitive Radio Networks with Energy Harvesting.

    Science.gov (United States)

    Hoan, Tran-Nhut-Khai; Hiep, Vu-Van; Koo, In-Soo

    2016-03-31

    This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary channels in which cognitive users (CUs) are powered by energy harvesters. The CUs are under the consideration that hardware constraints on radio devices only allow them to sense and transmit on one channel at a time. For a scenario where the arrival of harvested energy packets and the battery capacity are finite, we propose a scheme to optimize (i) the channel-sensing schedule (consisting of finding the optimal action (silent or active) and sensing order of channels) and (ii) the optimal transmission energy set corresponding to the channels in the sensing order for the operation of the CU in order to maximize the expected throughput of the CRN over multiple time slots. Frequency-switching delay, energy-switching cost, correlation in spectrum occupancy across time and frequency and errors in spectrum sensing are also considered in this work. The performance of the proposed scheme is evaluated via simulation. The simulation results show that the throughput of the proposed scheme is greatly improved, in comparison to related schemes in the literature. The collision ratio on the primary channels is also investigated.

  20. Wind Turbine Blade Deflection Sensing System Based on UWB Technology

    DEFF Research Database (Denmark)

    Franek, Ondrej; Zhang, Shuai; Jensen, Tobias Lindstrøm

    2016-01-01

    A microwave sensing system for estimating deflection of a wind turbine blade is presented. The system measures distances at two ultrawideband (UWB) wireless links between one antenna at the tip and two antennas at the root of the blade, which allows for determination of the tip position by triang......A microwave sensing system for estimating deflection of a wind turbine blade is presented. The system measures distances at two ultrawideband (UWB) wireless links between one antenna at the tip and two antennas at the root of the blade, which allows for determination of the tip position...... by the blade. It is demonstrated that despite the adverse effects of the multipath propagation the ranging accuracy of the system amounts to 1.5 cm, leading to maximum error of deflection 4.5 %....

  1. Spinal Cord Injury Model System Information Network

    Science.gov (United States)

    ... the UAB-SCIMS Contact the UAB-SCIMS UAB Spinal Cord Injury Model System Newly Injured Health Daily Living Consumer ... Information Network The University of Alabama at Birmingham Spinal Cord Injury Model System (UAB-SCIMS) maintains this Information Network ...

  2. Computer networks ISE a systems approach

    CERN Document Server

    Peterson, Larry L

    2007-01-01

    Computer Networks, 4E is the only introductory computer networking book written by authors who have had first-hand experience with many of the protocols discussed in the book, who have actually designed some of them as well, and who are still actively designing the computer networks today. This newly revised edition continues to provide an enduring, practical understanding of networks and their building blocks through rich, example-based instruction. The authors' focus is on the why of network design, not just the specifications comprising today's systems but how key technologies and p

  3. Fluorescent Sensing of Fluoride in Cellular System

    Science.gov (United States)

    Jiao, Yang; Zhu, Baocun; Chen, Jihua; Duan, Xiaohong

    2015-01-01

    Fluoride ions have the important roles in a lot of physiological activities related with biological and medical system, such as water fluoridation, caries treatment, and bone disease treatment. Great efforts have been made to develop new methods and strategies for F- detection in the past decades. Traditional methods for the detection of F- including ion chromatography, ion-selective electrodes, and spectroscopic techniques have the limitations in the biomedicine research. The fluorescent probes for F- are very promising that overcome some drawbacks of traditional fluoride detection methods. These probes exhibit high selectivity, high sensitivity as well as quick response to the detection of fluoride anions. The review commences with a brief description of photophysical mechanisms for fluorescent probes for fluoride, including photo induced electron transfer (PET), intramolecular charge transfer (ICT), fluorescence resonance energy transfer (FRET), and excited-state intramolecular proton transfer (ESIPT). Followed by a discussion about common dyes for fluorescent fluoride probes, such as anthracene, naphalimide, pyrene, BODIPY, fluorescein, rhodamine, resorufin, coumarin, cyanine, and near-infrared (NIR) dyes. We divide the fluorescent probes for fluoride in cellular application systems into nine groups, for example, type of hydrogen bonds, type of cleavage of Si-O bonds, type of Si-O bond cleavage and cylization reactions, etc. We also review the recent reported carriers in the delivery of fluorescent fluoride probes. Seventy-four typical fluorescent fluoride probes are listed and compared in detail, including quantum yield, reaction medium, excitation and emission wavelengths, linear detection range, selectivity for F-, mechanism, and analytical applications. Finally, we discuss the future challenges of the application of fluorescent fluoride probes in cellular system and in vivo. We wish that more and more excellent fluorescent fluoride probes will be developed

  4. Optically powered active sensing system for Internet Of Things

    Science.gov (United States)

    Gao, Chen; Wang, Jin; Yin, Long; Yang, Jing; Jiang, Jian; Wan, Hongdan

    2014-10-01

    Internet Of Things (IOT) drives a significant increase in the extent and type of sensing technology and equipment. Sensors, instrumentation, control electronics, data logging and transmission units comprising such sensing systems will all require to be powered. Conventionally, electrical powering is supplied by batteries or/and electric power cables. The power supply by batteries usually has a limited lifetime, while the electric power cables are susceptible to electromagnetic interference. In fact, the electromagnetic interference is the key issue limiting the power supply in the strong electromagnetic radiation area and other extreme environments. The novel alternative method of power supply is power over fiber (PoF) technique. As fibers are used as power supply lines instead, the delivery of the power is inherently immune to electromagnetic radiation, and avoids cumbersome shielding of power lines. Such a safer power supply mode would be a promising candidate for applications in IOT. In this work, we built up optically powered active sensing system, supplying uninterrupted power for the remote active sensors and communication modules. Also, we proposed a novel maximum power point tracking technique for photovoltaic power convertors. In our system, the actual output efficiency greater than 40% within 1W laser power. After 1km fiber transmission and opto-electric power conversion, a stable electric power of 210mW was obtained, which is sufficient for operating an active sensing system.

  5. Systemic risk on different interbank network topologies

    Science.gov (United States)

    Lenzu, Simone; Tedeschi, Gabriele

    2012-09-01

    In this paper we develop an interbank market with heterogeneous financial institutions that enter into lending agreements on different network structures. Credit relationships (links) evolve endogenously via a fitness mechanism based on agents' performance. By changing the agent's trust on its neighbor's performance, interbank linkages self-organize themselves into very different network architectures, ranging from random to scale-free topologies. We study which network architecture can make the financial system more resilient to random attacks and how systemic risk spreads over the network. To perturb the system, we generate a random attack via a liquidity shock. The hit bank is not automatically eliminated, but its failure is endogenously driven by its incapacity to raise liquidity in the interbank network. Our analysis shows that a random financial network can be more resilient than a scale free one in case of agents' heterogeneity.

  6. Social sensing building reliable systems on unreliable data

    CERN Document Server

    Wang, Dong; Kaplan, Lance

    2015-01-01

    Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individu

  7. Sapphire-fiber-based distributed high-temperature sensing system.

    Science.gov (United States)

    Liu, Bo; Yu, Zhihao; Hill, Cary; Cheng, Yujie; Homa, Daniel; Pickrell, Gary; Wang, Anbo

    2016-09-15

    We present, for the first time to our knowledge, a sapphire-fiber-based distributed high-temperature sensing system based on a Raman distributed sensing technique. High peak power laser pulses at 532 nm were coupled into the sapphire fiber to generate the Raman signal. The returned Raman Stokes and anti-Stokes signals were measured in the time domain to determine the temperature distribution along the fiber. The sensor was demonstrated from room temperature up to 1200°C in which the average standard deviation is about 3.7°C and a spatial resolution of about 14 cm was achieved.

  8. Design and Management of Networked Information Systems

    DEFF Research Database (Denmark)

    Havn, Erling; Bansler, Jørgen P.

    1996-01-01

    -based IS. There are several reasons for this: (a) Networked IS are large and complex systems; (b) in most cases, one has to deal with a number of existing - probably heterogenous - technical hardware and software platforms and link them together in a network; (c) differences in organizational culture, work......In this paper, we present a newly started research project at the Center for Tele-Information at the Technical University of Denmark. The project focuses on the design and management of networked information systems, that is computer-based IS linked by a wide area network and supporting...... communication between geographically dispersed organizational units. Examples include logistics systems, airline booking systems, and CSCW systems. We assume that the design and implementation of networked IS is significantly more difficult and risky than the development of traditional "stand-alone" computer...

  9. ATTENTIONAL NETWORKS AND SELECTIVE VISUAL SYSTEM

    National Research Council Canada - National Science Library

    ALEJANDRO CASTILLO MORENO; ANGÉLICA PATERNINA MARÍN

    2006-01-01

    ... system.From this last point of view, we will emphasize on the attentional networks theory of Posner, thatproposes different systems to explain diverse aspects of attention, but they are related to each...

  10. Data Aggregation Based on Overlapping Rate of Sensing Area in Wireless Sensor Networks.

    Science.gov (United States)

    Tang, Xiaolan; Xie, Hua; Chen, Wenlong; Niu, Jianwei; Wang, Shuhang

    2017-06-29

    Wireless sensor networks are required in smart applications to provide accurate control, where the high density of sensors brings in a large quantity of redundant data. In order to reduce the waste of limited network resources, data aggregation is utilized to avoid redundancy forwarding. However, most of aggregation schemes reduce information accuracy and prolong end-to-end delay when eliminating transmission overhead. In this paper, we propose a data aggregation scheme based on overlapping rate of sensing area, namely AggOR, aiming for energy-efficient data collection in wireless sensor networks with high information accuracy. According to aggregation rules, gathering nodes are selected from candidate parent nodes and appropriate neighbor nodes considering a preset threshold of overlapping rate of sensing area. Therefore, the collected data in a gathering area are highly correlated, and a large amount of redundant data could be cleaned. Meanwhile, AggOR keeps the original entropy by only deleting the duplicated data. Experiment results show that compared with others, AggOR has a high data accuracy and a short end-to-end delay with a similar network lifetime.

  11. Intelligent Balanced Device and its Sensing System for Beam Pumping Units

    Directory of Open Access Journals (Sweden)

    Hangxin WEI

    2014-11-01

    Full Text Available In order to save the energy of the beam pumping unit, the intelligent balanced device was developed. The device can adjust the position of the balanced-block automatically by the single chip microcomputer controller, and the fuzzy PD control algorithm was used to control the servo motor of the device. Since some signals should be inputted into the intelligent balanced device to calculate the balanced index of the pumping unit, the signals sensing system were designed. The sensing system includes the electric current sensor and voltage sensor of the main motor, the displacement sensor and the force sensor of the horse head. The sensing network has three layers: slave station, relay station and master station. The data transmission between them is based on ZigBee and GPRS method which can adapt the environment of the oil field. The results of application show that the intelligent balanced device and its sensing system can have the effect of reducing the power consumption, working reliability and communication efficiently.

  12. Sensory systems II senses other than vision

    CERN Document Server

    Wolfe, Jeremy M

    1988-01-01

    This series of books, "Readings from the Encyclopedia of Neuroscience." consists of collections of subject-clustered articles taken from the Encyclopedia of Neuroscience. The Encyclopedia of Neuroscience is a reference source and compendium of more than 700 articles written by world authorities and covering all of neuroscience. We define neuroscience broadly as including all those fields that have as a primary goal the under­ standing of how the brain and nervous system work to mediate/control behavior, including the mental behavior of humans. Those interested in specific aspects of the neurosciences, particular subject areas or specialties, can of course browse through the alphabetically arranged articles of the En­ cyclopedia or use its index to find the topics they wish to read. However. for those readers-students, specialists, or others-who will find it useful to have collections of subject-clustered articles from the Encyclopedia, we issue this series of "Readings" in paperback. Students in neuroscienc...

  13. Neural network based system for equipment surveillance

    Science.gov (United States)

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

    1998-04-28

    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  14. Seamless integrated network system for wireless communication systems

    NARCIS (Netherlands)

    Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

    2006-01-01

    To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

  15. Seamless integrated network system for wireless communication systems

    NARCIS (Netherlands)

    Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

    2002-01-01

    To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

  16. Adaptive Sensing Based on Profiles for Sensor Systems

    Directory of Open Access Journals (Sweden)

    Yoshiteru Ishida

    2009-10-01

    Full Text Available This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission.

  17. Effective Data Acquisition Protocol for Multi-Hop Heterogeneous Wireless Sensor Networks Using Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Ahmed M. Khedr

    2015-10-01

    Full Text Available In designing wireless sensor networks (WSNs, it is important to reduce energy dissipation and prolong network lifetime. Clustering of nodes is one of the most effective approaches for conserving energy in WSNs. Cluster formation protocols generally consider the heterogeneity of sensor nodes in terms of energy difference of nodes but ignore the different transmission ranges of them. In this paper, we propose an effective data acquisition clustered protocol using compressive sensing (EDACP-CS for heterogeneous WSNs that aims to conserve the energy of sensor nodes in the presence of energy and transmission range heterogeneity. In EDACP-CS, cluster heads are selected based on the distance from the base station and sensor residual energy. Simulation results show that our protocol offers a much better performance than the existing protocols in terms of energy consumption, stability, network lifetime, and throughput.

  18. The mathematics of networks of linear systems

    CERN Document Server

    Fuhrmann, Paul A

    2015-01-01

    This book provides the mathematical foundations of networks of linear control systems, developed from an algebraic systems theory perspective. This includes a thorough treatment of questions of controllability, observability, realization theory, as well as feedback control and observer theory. The potential of networks for linear systems in controlling large-scale networks of interconnected dynamical systems could provide insight into a diversity of scientific and technological disciplines. The scope of the book is quite extensive, ranging from introductory material to advanced topics of current research, making it a suitable reference for graduate students and researchers in the field of networks of linear systems. Part I can be used as the basis for a first course in algebraic system theory, while Part II serves for a second, advanced, course on linear systems. Finally, Part III, which is largely independent of the previous parts, is ideally suited for advanced research seminars aimed at preparing graduate ...

  19. Hybrid architecture active wavefront sensing and control system, and method

    Science.gov (United States)

    Feinberg, Lee D. (Inventor); Dean, Bruce H. (Inventor); Hyde, Tristram T. (Inventor)

    2011-01-01

    According to various embodiments, provided herein is an optical system and method that can be configured to perform image analysis. The optical system can comprise a telescope assembly and one or more hybrid instruments. The one or more hybrid instruments can be configured to receive image data from the telescope assembly and perform a fine guidance operation and a wavefront sensing operation, simultaneously, on the image data received from the telescope assembly.

  20. Network Physiology: How Organ Systems Dynamically Interact.

    Directory of Open Access Journals (Sweden)

    Ronny P Bartsch

    Full Text Available We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS, we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

  1. Network Physiology: How Organ Systems Dynamically Interact.

    Science.gov (United States)

    Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

  2. Remote tactile sensing system integrated with magnetic synapse.

    Science.gov (United States)

    Oh, Sunjong; Jung, Youngdo; Kim, Seonggi; Kim, SungJoon; Hu, Xinghao; Lim, Hyuneui; Kim, CheolGi

    2017-12-05

    Mechanoreceptors in a fingertip convert external tactile stimulations into electrical signals, which are transmitted by the nervous system through synaptic transmitters and then perceived by the brain with high accuracy and reliability. Inspired by the human synapse system, this paper reports a robust tactile sensing system consisting of a remote touch tip and a magnetic synapse. External pressure on the remote touch tip is transferred in the form of air pressure to the magnetic synapse, where its variation is converted into electrical signals. The developed system has high sensitivity and a wide dynamic range. The remote sensing system demonstrated tactile capabilities over wide pressure range with a minimum detectable pressure of 6 Pa. In addition, it could measure tactile stimulation up to 1,000 Hz without distortion and hysteresis, owing to the separation of the touching and sensing parts. The excellent performance of the system in terms of surface texture discrimination, heartbeat measurement from the human wrist, and satisfactory detection quality in water indicates that it has considerable potential for various mechanosensory applications in different environments.

  3. Differential network entropy reveals cancer system hallmarks

    Science.gov (United States)

    West, James; Bianconi, Ginestra; Severini, Simone; Teschendorff, Andrew E.

    2012-01-01

    The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network we here demonstrate that cancer cells are characterised by an increase in network entropy. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local network entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local correlation patterns. In particular, we find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in network entropy. These findings may have potential implications for identifying novel drug targets. PMID:23150773

  4. Unmanned aerial systems for photogrammetry and remote sensing: A review

    Science.gov (United States)

    Colomina, I.; Molina, P.

    2014-06-01

    We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.

  5. Efficient Lossy Compression for Compressive Sensing Acquisition of Images in Compressive Sensing Imaging Systems

    Directory of Open Access Journals (Sweden)

    Xiangwei Li

    2014-12-01

    Full Text Available Compressive Sensing Imaging (CSI is a new framework for image acquisition, which enables the simultaneous acquisition and compression of a scene. Since the characteristics of Compressive Sensing (CS acquisition are very different from traditional image acquisition, the general image compression solution may not work well. In this paper, we propose an efficient lossy compression solution for CS acquisition of images by considering the distinctive features of the CSI. First, we design an adaptive compressive sensing acquisition method for images according to the sampling rate, which could achieve better CS reconstruction quality for the acquired image. Second, we develop a universal quantization for the obtained CS measurements from CS acquisition without knowing any a priori information about the captured image. Finally, we apply these two methods in the CSI system for efficient lossy compression of CS acquisition. Simulation results demonstrate that the proposed solution improves the rate-distortion performance by 0.4~2 dB comparing with current state-of-the-art, while maintaining a low computational complexity.

  6. Experimental quantum compressed sensing for a seven-qubit system

    Science.gov (United States)

    Riofrío, C. A.; Gross, D.; Flammia, S. T.; Monz, T.; Nigg, D.; Blatt, R.; Eisert, J.

    2017-05-01

    Well-controlled quantum devices with their increasing system size face a new roadblock hindering further development of quantum technologies. The effort of quantum tomography--the reconstruction of states and processes of a quantum device--scales unfavourably: state-of-the-art systems can no longer be characterized. Quantum compressed sensing mitigates this problem by reconstructing states from incomplete data. Here we present an experimental implementation of compressed tomography of a seven-qubit system--a topological colour code prepared in a trapped ion architecture. We are in the highly incomplete--127 Pauli basis measurement settings--and highly noisy--100 repetitions each--regime. Originally, compressed sensing was advocated for states with few non-zero eigenvalues. We argue that low-rank estimates are appropriate in general since statistical noise enables reliable reconstruction of only the leading eigenvectors. The remaining eigenvectors behave consistently with a random-matrix model that carries no information about the true state.

  7. Three-dimensional conductive networks based on stacked SiO2@graphene frameworks for enhanced gas sensing.

    Science.gov (United States)

    Huang, Da; Yang, Zhi; Li, Xiaolin; Zhang, Liling; Hu, Jing; Su, Yanjie; Hu, Nantao; Yin, Guilin; He, Dannong; Zhang, Yafei

    2017-01-07

    Graphene is an ideal candidate for gas sensing due to its excellent conductivity and large specific surface areas. However, it usually suffers from sheet stacking, which seriously debilitates its sensing performance. Herein, we demonstrate a three-dimensional conductive network based on stacked SiO2@graphene core-shell hybrid frameworks for enhanced gas sensing. SiO2 spheres are uniformly encapsulated by graphene oxide (GO) through an electrostatic self-assembly approach to form SiO2@GO core-shell hybrid frameworks, which are reduced through thermal annealing to establish three-dimensional (3D) conductive sensing networks. The SiO2 supported 3D conductive graphene frameworks reveal superior sensing performance to bare reduced graphene oxide (RGO) films, which can be attributed to their less agglomeration and larger surface area. The response value of the 3D framework based sensor for 50 ppm NH3 and 50 ppm NO2 increased 8 times and 5 times, respectively. Additionally, the sensing performance degradation caused by the stacking of the sensing materials is significantly suppressed because the graphene layers are separated by the SiO2 spheres. The sensing performance decays by 92% for the bare RGO films when the concentration of the sensing material increases 8 times, while there is only a decay of 25% for that of the SiO2@graphene core-shell hybrid frameworks. This work provides an insight into 3D frameworks of hybrid materials for effectively improving gas sensing performance.

  8. Plantar Pressure Detection with Fiber Bragg Gratings Sensing System

    Directory of Open Access Journals (Sweden)

    Tsair-Chun Liang

    2016-10-01

    Full Text Available In this paper, a novel fiber-optic sensing system based on fiber Bragg gratings (FBGs to measure foot plantar pressure is proposed. This study first explores the Pedar-X insole foot pressure types of the adult-size chart and then defines six measurement areas to effectively identify four foot types: neutral foot, cavus foot, supinated foot and flat foot. The plantar pressure signals are detected by only six FBGs, which are embedded in silicone rubber. The performance of the fiber optic sensing is examined and compared with a digital pressure plate of i-Step P1000 with 1024 barometric sensors. In the experiment, there are 11 participants with different foot types to participate in the test. The Pearson correlation coefficient, which is determined from the measured results of the homemade fiber-optic plantar pressure system and i-Step P1000 plantar pressure plate, reaches up to 0.671 (p < 0.01. According to the measured results from the plantar pressure data, the proposed fiber optic sensing system can successfully identify the four different foot types. Measurements of this study have demonstrated the feasibility of the proposed system so that it can be an alternative for plantar pressure detection systems.

  9. Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

    Science.gov (United States)

    Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.

    1993-01-01

    Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.

  10. Process query systems for network security monitoring

    Science.gov (United States)

    Berk, Vincent; Fox, Naomi

    2005-05-01

    In this paper we present the architecture of our network security monitoring infrastructure based on a Process Query System (PQS). PQS offers a new and powerful way of efficiently processing data streams, based on process descriptions that are submitted as queries. In this case the data streams are familiar network sensors, such as Snort, Netfilter, and Tripwire. The process queries describe the dynamics of network attacks and failures, such as worms, multistage attacks, and router failures. Using PQS the task of monitoring enterprise class networks is simplified, offering a priority-based GUI to the security administrator that clearly outlines events that require immediate attention. The PQS-Net system is deployed on an unsecured production network; the system has successfully detected many diverse attacks and failures.

  11. High-speed, intra-system networks

    Energy Technology Data Exchange (ETDEWEB)

    Quinn, Heather M [Los Alamos National Laboratory; Graham, Paul S [Los Alamos National Laboratory; Manuzzato, Andrea [Los Alamos National Laboratory; Fairbanks, Tom [Los Alamos National Laboratory; Dallmann, Nicholas [Los Alamos National Laboratory; Desgeorges, Rose [Los Alamos National Laboratory

    2010-06-28

    Recently, engineers have been studying on-payload networks for fast communication paths. Using intra-system networks as a means to connect devices together allows for a flexible payload design that does not rely on dedicated communication paths between devices. In this manner, the data flow architecture of the system can be dynamically reconfigured to allow data routes to be optimized for the application or configured to route around devices that are temporarily or permanently unavailable. To use intra-system networks, devices will need network controllers and switches. These devices are likely to be affected by single-event effects, which could affect data communication. In this paper we will present radiation data and performance analysis for using a Broadcom network controller in a neutron environment.

  12. The layered sensing operations center: a modeling and simulation approach to developing complex ISR networks

    Science.gov (United States)

    Curtis, Christopher; Lenzo, Matthew; McClure, Matthew; Preiss, Bruce

    2010-04-01

    In order to anticipate the constantly changing landscape of global warfare, the United States Air Force must acquire new capabilities in the field of Intelligence, Surveillance, and Reconnaissance (ISR). To meet this challenge, the Air Force Research Laboratory (AFRL) is developing a unifying construct of "Layered Sensing" which will provide military decision-makers at all levels with the timely, actionable, and trusted information necessary for complete battlespace awareness. Layered Sensing is characterized by the appropriate combination of sensors and platforms (including those for persistent sensing), infrastructure, and exploitation capabilities to enable this synergistic awareness. To achieve the Layered Sensing vision, AFRL is pursuing a Modeling & Simulation (M&S) strategy through the Layered Sensing Operations Center (LSOC). An experimental ISR system-of-systems test-bed, the LSOC integrates DoD standard simulation tools with commercial, off-the-shelf video game technology for rapid scenario development and visualization. These tools will help facilitate sensor management performance characterization, system development, and operator behavioral analysis. Flexible and cost-effective, the LSOC will implement a non-proprietary, open-architecture framework with well-defined interfaces. This framework will incentivize the transition of current ISR performance models to service-oriented software design for maximum re-use and consistency. This paper will present the LSOC's development and implementation thus far as well as a summary of lessons learned and future plans for the LSOC.

  13. Learning Low Dimensional Convolutional Neural Networks for High-Resolution Remote Sensing Image Retrieval

    Science.gov (United States)

    Zhou, Weixun; Newsam, Shawn; Li, Congmin; Shao, Zhenfeng

    2017-05-01

    Learning powerful feature representations for image retrieval has always been a challenging task in the field of remote sensing. Traditional methods focus on extracting low-level hand-crafted features which are not only time-consuming but also tend to achieve unsatisfactory performance due to the content complexity of remote sensing images. In this paper, we investigate how to extract deep feature representations based on convolutional neural networks (CNN) for high-resolution remote sensing image retrieval (HRRSIR). To this end, two effective schemes are proposed to generate powerful feature representations for HRRSIR. In the first scheme, the deep features are extracted from the fully-connected and convolutional layers of the pre-trained CNN models, respectively; in the second scheme, we propose a novel CNN architecture based on conventional convolution layers and a three-layer perceptron. The novel CNN model is then trained on a large remote sensing dataset to learn low dimensional features. The two schemes are evaluated on several public and challenging datasets, and the results indicate that the proposed schemes and in particular the novel CNN are able to achieve state-of-the-art performance.

  14. Intelligent environmental sensing

    CERN Document Server

    Mukhopadhyay, Subhas

    2015-01-01

    Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

  15. Developing aircraft photonic networks for airplane systems

    DEFF Research Database (Denmark)

    White, Henry J.; Brownjohn, Nick; Baptista, João

    2013-01-01

    Achieving affordable high speed fiber optic communication networks for airplane systems has proved to be challenging. In this paper we describe a summary of the EU Framework 7 project DAPHNE (Developing Aircraft Photonic Networks). DAPHNE aimed to exploit photonic technology from terrestrial comm...

  16. Fuzzy stochastic neural network model for structural system identification

    Science.gov (United States)

    Jiang, Xiaomo; Mahadevan, Sankaran; Yuan, Yong

    2017-01-01

    This paper presents a dynamic fuzzy stochastic neural network model for nonparametric system identification using ambient vibration data. The model is developed to handle two types of imprecision in the sensed data: fuzzy information and measurement uncertainties. The dimension of the input vector is determined by using the false nearest neighbor approach. A Bayesian information criterion is applied to obtain the optimum number of stochastic neurons in the model. A fuzzy C-means clustering algorithm is employed as a data mining tool to divide the sensed data into clusters with common features. The fuzzy stochastic model is created by combining the fuzzy clusters of input vectors with the radial basis activation functions in the stochastic neural network. A natural gradient method is developed based on the Kullback-Leibler distance criterion for quick convergence of the model training. The model is validated using a power density pseudospectrum approach and a Bayesian hypothesis testing-based metric. The proposed methodology is investigated with numerically simulated data from a Markov Chain model and a two-story planar frame, and experimentally sensed data from ambient vibration data of a benchmark structure.

  17. Network model of security system

    Directory of Open Access Journals (Sweden)

    Adamczyk Piotr

    2016-01-01

    Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.

  18. Mechanics of localized slippage in tactile sensing and application to soft sensing systems

    CERN Document Server

    Ho, Anh-Van

    2014-01-01

    Localized slippage occurs during any relative sliding of soft contacts, ranging from human fingertips to robotic fingertips. Although this phenomenon is dominant for a very short time prior to gross slippage, localized slippage is a crucial factor for any to-be-developed soft sensing system to respond to slippage before it occurs. The content of this book addresses all aspects of localized slippage, including modeling and simulating it, as well as applying it to the construction of novel sensors with slip tactile perception.

  19. Mixing height determination using remote sensing systems. General remarks

    Energy Technology Data Exchange (ETDEWEB)

    Beyrich, F. [BTU Cottbus, LS Umweltmeteorologie, Cottbus (Germany)

    1997-10-01

    Remote sensing systems can be considered today as a real alternative to classical soundings with respect to the MH (mixing height) determination. They have the basic advantage to allow continuous monitoring of the ABL (atmospheric boundary layer). Some technical issues which limit their operational use at present should be solved in the near future (frequency allocation, eye safety, costs). Taking into account specific operating conditions and the formulated-above requirements of a sounding system to be used for MH determination it becomes obvious that none of the available systems meets all of them, i.e., the `Mixing height-meter` does not exist. Therefore, reliable MH determination under a wide variety of conditions can be achieved only by integrating different instruments into a complex sounding system. The S-profiles provide a suitable data base for MH estimation from all types of remote sensing instruments. The criteria to deduce MH-values from these profiles should consider the structure type and the evolution stage of the ABL as well as the shape of the profiles. A certain kind of harmonization concerning these criteria should be achieved. MH values derived automatically from remote sensing data appear to be not yet reliable enough for direct operational use, they should be in any case critically examined by a trained analyst. Contemporary mathematical methods (wavelet transforms, fuzzy logics) are supposed to allow considerable progress in this field in the near future. (au) 19 refs.

  20. The Networking of Interactive Bibliographic Retrieval Systems.

    Science.gov (United States)

    Marcus, Richard S.; Reintjes, J. Francis

    Research in networking of heterogeneous interactive bibliographic retrieval systems is being conducted which centers on the concept of a virtual retrieval system. Such a virtual system would be created through a translating computer interface that would provide access to the different retrieval systems and data bases in a uniform and convenient…

  1. Reliability Modeling of Microelectromechanical Systems Using Neural Networks

    Science.gov (United States)

    Perera. J. Sebastian

    2000-01-01

    Microelectromechanical systems (MEMS) are a broad and rapidly expanding field that is currently receiving a great deal of attention because of the potential to significantly improve the ability to sense, analyze, and control a variety of processes, such as heating and ventilation systems, automobiles, medicine, aeronautical flight, military surveillance, weather forecasting, and space exploration. MEMS are very small and are a blend of electrical and mechanical components, with electrical and mechanical systems on one chip. This research establishes reliability estimation and prediction for MEMS devices at the conceptual design phase using neural networks. At the conceptual design phase, before devices are built and tested, traditional methods of quantifying reliability are inadequate because the device is not in existence and cannot be tested to establish the reliability distributions. A novel approach using neural networks is created to predict the overall reliability of a MEMS device based on its components and each component's attributes. The methodology begins with collecting attribute data (fabrication process, physical specifications, operating environment, property characteristics, packaging, etc.) and reliability data for many types of microengines. The data are partitioned into training data (the majority) and validation data (the remainder). A neural network is applied to the training data (both attribute and reliability); the attributes become the system inputs and reliability data (cycles to failure), the system output. After the neural network is trained with sufficient data. the validation data are used to verify the neural networks provided accurate reliability estimates. Now, the reliability of a new proposed MEMS device can be estimated by using the appropriate trained neural networks developed in this work.

  2. A Low-Overhead Energy Detection Based Cooperative Sensing Protocol for Cognitive Radio Systems

    CERN Document Server

    Zhang, Shunqing; Lau, Vincent K N

    2009-01-01

    Cognitive radio and dynamic spectrum access represent a new paradigm shift in more effective use of limited radio spectrum. One core component behind dynamic spectrum access is the sensing of primary user activity in the shared spectrum. Conventional distributed sensing and centralized decision framework involving multiple sensor nodes is proposed to enhance the sensing performance. However, it is difficult to apply the conventional schemes in reality since the overhead in sensing measurement and sensing reporting as well as in sensing report combining limit the number of sensor nodes that can participate in distributive sensing. In this paper, we shall propose a novel, low overhead and low complexity energy detection based cooperative sensing framework for the cognitive radio systems which addresses the above two issues. The energy detection based cooperative sensing scheme greatly reduces the quiet period overhead (for sensing measurement) as well as sensing reporting overhead of the secondary systems and t...

  3. A Sensing Platform For A UHF RFID System

    Directory of Open Access Journals (Sweden)

    Young Ho Lee

    2015-08-01

    Full Text Available As the read range of passive UHF RFID broadens up to 11 meters compared to 1-meter range of HF RFID passive tags have been used for many applications such as tracking medical devices and objects of daily living. The RF communication link between the reader antenna and tags for indoors exhibits intermittent loss of signal reception due to antenna orientation mismatch and breakpoints within the antenna coverage area. We propose a design of a sensing platform for tracking objects using a UHF RFID system with passive tags that provides continuous signal reception over the coverage area. We first investigated causes of power loss for passive tags and then designed a sensing platform solution using antenna diversity. The causes of tags power loss were eliminated with angle and spatial diversity methods that can cover an arbitrary area of interest. We implemented this design in an indoor setting of a trauma resuscitation room and evaluated it by experimental measurement of signal strength at different points and angles in the area of interest. Our sensing platform supported complete coverage and uninterrupted interrogation of tags as they moved in the area of interest. We conclude that this sensing platform will be suitable for uninterrupted object tracking with UHF RFID technology in generic indoor spaces.

  4. A modular spectrum sensing system based on PSO-SVM.

    Science.gov (United States)

    Cai, Zhuoran; Zhao, Honglin; Yang, Zhutian; Mo, Yun

    2012-11-08

    In the cognitive radio system, spectrum sensing for detecting the presence of primary users in a licensed spectrum is a fundamental problem. Energy detection is the most popular spectrum sensing scheme used to differentiate the case where the primary user’s signal is present from the case where there is only noise. In fact, the nature of spectrum sensing can be taken as a binary classification problem, and energy detection is a linear classifier. If the signal-to-noise ratio (SNR) of the received signal is low, and the number of received signal samples for sensing is small, the binary classification problem is linearly inseparable. In this situation the performance of energy detection will decrease seriously. In this paper, a novel approach for obtaining a nonlinear threshold based on support vector machine with particle swarm optimization (PSO-SVM) to replace the linear threshold used in traditional energy detection is proposed. Simulations demonstrate that the performance of the proposed algorithm is much better than that of traditional energy detection.

  5. Wearable Eating Habit Sensing System Using Internal Body Sound

    Science.gov (United States)

    Shuzo, Masaki; Komori, Shintaro; Takashima, Tomoko; Lopez, Guillaume; Tatsuta, Seiji; Yanagimoto, Shintaro; Warisawa, Shin'ichi; Delaunay, Jean-Jacques; Yamada, Ichiro

    Continuous monitoring of eating habits could be useful in preventing lifestyle diseases such as metabolic syndrome. Conventional methods consist of self-reporting and calculating mastication frequency based on the myoelectric potential of the masseter muscle. Both these methods are significant burdens for the user. We developed a non-invasive, wearable sensing system that can record eating habits over a long period of time in daily life. Our sensing system is composed of two bone conduction microphones placed in the ears that send internal body sound data to a portable IC recorder. Applying frequency spectrum analysis on the collected sound data, we could not only count the number of mastications during eating, but also accurately differentiate between eating, drinking, and speaking activities. This information can be used to evaluate the regularity of meals. Moreover, we were able to analyze sound features to classify the types of foods eaten by food texture.

  6. Research on Key Technology of Mining Remote Sensing Dynamic Monitoring Information System

    Science.gov (United States)

    Sun, J.; Xiang, H.

    2017-09-01

    Problems exist in remote sensing dynamic monitoring of mining are expounded, general idea of building remote sensing dynamic monitoring information system is presented, and timely release of service-oriented remote sensing monitoring results is established. Mobile device-based data verification subsystem is developed using mobile GIS, remote sensing dynamic monitoring information system of mining is constructed, and "timely release, fast handling and timely feedback" rapid response mechanism of remote sensing dynamic monitoring is implemented.

  7. Network Basic Language Translation System: Security Infrastructure

    National Research Council Canada - National Science Library

    Mittrick, Mark R

    2007-01-01

    .... The Network Basic Language Translation System (NetBLTS) was proposed and accepted as part of the U.S. Army Research Laboratory's offering of initiatives within the Horizontal Fusion portfolio in 2003...

  8. A Collaborative Approach for Monitoring Nodes Behavior during Spectrum Sensing to Mitigate Multiple Attacks in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Mahmoud Khasawneh

    2017-01-01

    Full Text Available Spectrum sensing is the first step to overcome the spectrum scarcity problem in Cognitive Radio Networks (CRNs wherein all unutilized subbands in the radio environment are explored for better spectrum utilization. Adversary nodes can threaten these spectrum sensing results by launching passive and active attacks that prevent legitimate nodes from using the spectrum efficiently. Securing the spectrum sensing process has become an important issue in CRNs in order to ensure reliable and secure spectrum sensing and fair management of resources. In this paper, a novel collaborative approach during spectrum sensing process is proposed. It monitors the behavior of sensing nodes and identifies the malicious and misbehaving sensing nodes. The proposed approach measures the node’s sensing reliability using a value called belief level. All the sensing nodes are grouped into a specific number of clusters. In each cluster, a sensing node is selected as a cluster head that is responsible for collecting sensing-reputation reports from different cognitive nodes about each node in the same cluster. The cluster head analyzes information to monitor and judge the nodes’ behavior. By simulating the proposed approach, we showed its importance and its efficiency for achieving better spectrum security by mitigating multiple passive and active attacks.

  9. An electrochemical albumin-sensing system utilizing microfluidic technology

    Science.gov (United States)

    Huang, Chao-June; Lu, Chiu-Chun; Lin, Thong-Yueh; Chou, Tse-Chuan; Lee, Gwo-Bin

    2007-04-01

    This paper reports an integrated microfluidic chip capable of detecting the concentration of albumin in urine by using an electrochemical method in an automatic format. The integrated microfluidic chip was fabricated by using microelectromechanical system techniques. The albumin detection was conducted by using the electrochemical sensing method, in which the albumin in urine was detected by measuring the difference of peak currents between a bare reference electrode and an albumin-adsorption electrode. To perform the detection of the albumin in an automatic format, pneumatic microvalves and micropumps were integrated onto the microfluidic chip. The albumin sample and interference mixture solutions such as homovanillic acid, dopamine, norepinephrine and epinephrine were first stored in one of the three reservoirs. Then the solution comprising the albumin sample and interference solutions was transported to pass through the detection zone utilizing the pneumatic micropump. Experimental data showed that the developed system can successfully detect the concentration of the albumin in the existence of interference materials. When compared with the traditional albumin-sensing method, smaller amounts of samples were required to perform faster detection by using the integrated microfluidic chip. Additionally, the microfluidic chip integrated with pneumatic micropumps and microvalves facilitates the transportation of the samples in an automatic mode with lesser human intervention. The development of the integrated microfluidic albumin-sensing system may be promising for biomedical applications. Preliminary results of the current paper were presented at the 2nd International Meeting on Microsensors and Microsystems 2006 (National Cheng Kung University, Tainan, Taiwan, 15-18 January).

  10. Ammonia sensing system based on wavelength modulation spectroscopy

    Science.gov (United States)

    Viveiros, Duarte; Ferreira, João; Silva, Susana O.; Ribeiro, Joana; Flores, Deolinda; Santos, José L.; Frazão, Orlando; Baptista, José M.

    2015-06-01

    A sensing system in the near infrared region has been developed for ammonia sensing based on the wavelength modulation spectroscopy (WMS) principle. The WMS is a rather sensitive technique for detecting atomic/molecular species, presenting the advantage that it can be used in the near-infrared region by using the optical telecommunications technology. In this technique, the laser wavelength and intensity were modulated by applying a sine wave signal through the injection current, which allowed the shift of the detection bandwidth to higher frequencies where laser intensity noise was typically lower. Two multi-pass cells based on free space light propagation with 160 cm and 16 cm of optical path length were used, allowing the redundancy operation and technology validation. This system used a diode laser with an emission wavelength at 1512.21 nm, where NH3 has a strong absorption line. The control of the NH3 gas sensing system, as well as acquisition, processing and data presentation was performed.

  11. Maritime Semantic Labeling of Optical Remote Sensing Images with Multi-Scale Fully Convolutional Network

    Directory of Open Access Journals (Sweden)

    Haoning Lin

    2017-05-01

    Full Text Available In current remote sensing literature, the problems of sea-land segmentation and ship detection (including in-dock ships are investigated separately despite the high correlation between them. This inhibits joint optimization and makes the implementation of the methods highly complicated. In this paper, we propose a novel fully convolutional network to accomplish the two tasks simultaneously, in a semantic labeling fashion, i.e., to label every pixel of the image into 3 classes, sea, land and ships. A multi-scale structure for the network is proposed to address the huge scale gap between different classes of targets, i.e., sea/land and ships. Conventional multi-scale structure utilizes shortcuts to connect low level, fine scale feature maps to high level ones to increase the network’s ability to produce finer results. In contrast, our proposed multi-scale structure focuses on increasing the receptive field of the network while maintaining the ability towards fine scale details. The multi-scale convolution network accommodates the huge scale difference between sea-land and ships and provides comprehensive features, and is able to accomplish the tasks in an end-to-end manner that is easy for implementation and feasible for joint optimization. In the network, the input forks into fine-scale and coarse-scale paths, which share the same convolution layers to minimize network parameter increase, and then are joined together to produce the final result. The experiments show that the network tackles the semantic labeling problem with improved performance.

  12. New optical sensor systems for photogrammetry and remote sensing

    Science.gov (United States)

    Eckardt, Andreas; Börner, Anko; Jahn, Herbert; Hilbert, Stefan; Walter, Ingo

    2006-09-01

    Recent developments in the fields of detectors on one hand and a significant change of national and international political and commercial constraints on the other hand led to a large number of proposals for spaceborne sensor systems focusing on Earth observation in the last months. Due to the commercial availability of TDI lines and fast readable CCD-Chips new sensor concepts are feasible for high resolution sensor systems regarding geometry and radiometry und their data products. Systemic approaches are essential for the design of complex sensor systems for dedicated tasks. Starting with system theory optically, mechanical and electrical components are designed and deployed. Single modules and the entire system have to be calibrated using suitable procedures. The paper gives an overview about current activities at German Aerospace Center on the field of innovative sensor systems for photogrammetry and remote sensing.

  13. Network support for system initiated checkpoints

    Science.gov (United States)

    Chen, Dong; Heidelberger, Philip

    2013-01-29

    A system, method and computer program product for supporting system initiated checkpoints in parallel computing systems. The system and method generates selective control signals to perform checkpointing of system related data in presence of messaging activity associated with a user application running at the node. The checkpointing is initiated by the system such that checkpoint data of a plurality of network nodes may be obtained even in the presence of user applications running on highly parallel computers that include ongoing user messaging activity.

  14. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

    Directory of Open Access Journals (Sweden)

    Antonio Artuñedo

    2017-04-01

    Full Text Available Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

  15. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

    Science.gov (United States)

    Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

    2017-04-26

    Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

  16. Network science, nonlinear science and infrastructure systems

    CERN Document Server

    2007-01-01

    Network Science, Nonlinear Science and Infrastructure Systems has been written by leading scholars in these areas. Its express purpose is to develop common theoretical underpinnings to better solve modern infrastructural problems. It is felt by many who work in these fields that many modern communication problems, ranging from transportation networks to telecommunications, Internet, supply chains, etc., are fundamentally infrastructure problems. Moreover, these infrastructure problems would benefit greatly from a confluence of theoretical and methodological work done with the areas of Network Science, Dynamical Systems and Nonlinear Science. This book is dedicated to the formulation of infrastructural tools that will better solve these types of infrastructural problems. .

  17. Ethical Issues in Network System Design

    Directory of Open Access Journals (Sweden)

    Duncan Langford

    1997-05-01

    Full Text Available Today, most desktop computers and PCs are networked that is, they have the ability to link to other machines, usually to access data and other information held remotely. Such machines may sometimes be connected directly to each other, as part of an office or company computer system. More frequently, however, connected machines are at a considerable distance from each other, typically connected through links to global systems such as the Internet, or World Wide Web (WWW. The networked machine itself may be anything from a powerful company computer with direct Internet connections, to a small hobbyist machine, accessing a bulletin board through telephone and modem. It is important to remember that, whatever the type or the location of networked machines, their access to the network, and the network itself, was planned and constructed following deliberate design considerations. In this paper I discuss some ways in which the technical design of computer systems might appropriately be influenced by ethical issues, and examine pressures on computer scientists and others to technically control network related actions perceived as 'unethical'. After examination of the current situation, I draw together the issues, and conclude by suggesting some ethically based recommendations for the future design of networked systems.

  18. Multifunctional optical system-on-a-chip for heterogeneous fiber optic sensor networks

    Science.gov (United States)

    Yu, Miao; Pang, Cheng; Gupta, Ashwani

    2015-08-01

    In this article, we review our recent progress on the development of a multifunctional optical system-on-a-chip platform, which can be used for achieving heterogeneous wireless fiber optical sensor networks. A multifunctional optical sensor platform based on the micro-electromechanical systems (MEMS) technology is developed. The key component of the multifunctional optical sensor platform is a MEMS based tunable Fabry-Pérot (FP) filter, which can be used as a phase modulator or a wavelength tuning device in a multifunctional optical sensing system. Mechanics model of the FP filter and optics model of the multifunctional optical sensing system are developed to facilitate the design of the filter. The MEMS FP filter is implemented in a multifunctional optical sensing system including both Fabry-Perot interferometer based sensors and Fiber Bragg grating sensors. The experimental results indicate that this large dynamic range tunable filter can enable high performance heterogeneous optical sensing for many applications.

  19. Hydrogen gas sensing with networks of ultra-small palladium nanowires formed on filtration membranes.

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, X. Q.; Latimer, M. L.; Xiao, Z. L.; Panuganti, S.; Welp, U.; Kwok, W. K.; Xu, T. (Materials Science Division); (Northern Illinois Univ.)

    2010-11-29

    Hydrogen sensors based on single Pd nanowires show promising results in speed, sensitivity, and ultralow power consumption. The utilization of single Pd nanowires, however, face challenges in nanofabrication, manipulation, and achieving ultrasmall transverse dimensions. We report on hydrogen sensors that take advantage of single palladium nanowires in high speed and sensitivity and that can be fabricated conveniently. The sensors are based on networks of ultrasmall (<10 nm) palladium nanowires deposited onto commercially available filtration membranes. We investigated the sensitivities and response times of these sensors as a function of the thickness of the nanowires and also compared them with a continuous reference film. The superior performance of the ultrasmall Pd nanowire network based sensors demonstrates the novelty of our fabrication approach, which can be directly applied to palladium alloy and other hydrogen sensing materials.

  20. Sense of participation

    NARCIS (Netherlands)

    Bohorques Montemayor, L.; Nevejan, C.I.M.; Brazier, F.M.

    2013-01-01

    This paper explores the sense of participation of a spatially distributed individual—in the intersections of physical and mediated networks. This sense is fundamental to an individuals’ experience as a participant in systems designed to this purpose including today’s social media and new media

  1. A Wireless Sensor Network for Growth Environment Measurement and Multi-Band Optical Sensing to Diagnose Tree Vigor

    Directory of Open Access Journals (Sweden)

    Shinichi Kameoka

    2017-04-01

    Full Text Available We have tried to develop the guidance system for farmers to cultivate using various phenological indices. As the sensing part of this system, we deployed a new Wireless Sensor Network (WSN. This system uses the 920 MHz radio wave based on the Wireless Smart Utility Network that enables long-range wireless communication. In addition, the data acquired by the WSN were standardized for the advanced web service interoperability. By using these standardized data, we can create a web service that offers various kinds of phenological indices as secondary information to the farmers in the field. We have also established the field management system using thermal image, fluorescent and X-ray fluorescent methods, which enable the nondestructive, chemical-free, simple, and rapid measurement of fruits or trees. We can get the information about the transpiration of plants through a thermal image. The fluorescence sensor gives us information, such as nitrate balance index (NBI, that shows the nitrate balance inside the leaf, chlorophyll content, flavonol content and anthocyanin content. These methods allow one to quickly check the health of trees and find ways to improve the tree vigor of weak ones. Furthermore, the fluorescent x-ray sensor has the possibility to quantify the loss of minerals necessary for fruit growth.

  2. A Wireless Sensor Network for Growth Environment Measurement and Multi-Band Optical Sensing to Diagnose Tree Vigor.

    Science.gov (United States)

    Kameoka, Shinichi; Isoda, Shuhei; Hashimoto, Atsushi; Ito, Ryoei; Miyamoto, Satoru; Wada, Genki; Watanabe, Naoki; Yamakami, Takashi; Suzuki, Ken; Kameoka, Takaharu

    2017-04-27

    We have tried to develop the guidance system for farmers to cultivate using various phenological indices. As the sensing part of this system, we deployed a new Wireless Sensor Network (WSN). This system uses the 920 MHz radio wave based on the Wireless Smart Utility Network that enables long-range wireless communication. In addition, the data acquired by the WSN were standardized for the advanced web service interoperability. By using these standardized data, we can create a web service that offers various kinds of phenological indices as secondary information to the farmers in the field. We have also established the field management system using thermal image, fluorescent and X-ray fluorescent methods, which enable the nondestructive, chemical-free, simple, and rapid measurement of fruits or trees. We can get the information about the transpiration of plants through a thermal image. The fluorescence sensor gives us information, such as nitrate balance index (NBI), that shows the nitrate balance inside the leaf, chlorophyll content, flavonol content and anthocyanin content. These methods allow one to quickly check the health of trees and find ways to improve the tree vigor of weak ones. Furthermore, the fluorescent x-ray sensor has the possibility to quantify the loss of minerals necessary for fruit growth.

  3. WIRELESS SENSOR NETWORK BASED CONVEYOR SURVEILLANCE SYSTEM

    OpenAIRE

    Attila Trohák; Máté Kolozsi-Tóth; Péter Rádi

    2011-01-01

    In the paper we will introduce an intelligent conveyor surveillance system. We started a research project to design and develop a conveyor surveillance system based on wireless sensor network and GPRS communication. Our system is able to measure temperature on fixed and moving, rotating surfaces and able to detect smoke. We would like to introduce the developed devices and give an application example.

  4. Nutrient Sensing: Another Chemosensitivity of the Olfactory System

    Directory of Open Access Journals (Sweden)

    A-Karyn Julliard

    2017-07-01

    Full Text Available Olfaction is a major sensory modality involved in real time perception of the chemical composition of the external environment. Olfaction favors anticipation and rapid adaptation of behavioral responses necessary for animal survival. Furthermore, recent studies have demonstrated that there is a direct action of metabolic peptides on the olfactory network. Orexigenic peptides such as ghrelin and orexin increase olfactory sensitivity, which in turn, is decreased by anorexigenic hormones such as insulin and leptin. In addition to peptides, nutrients can play a key role on neuronal activity. Very little is known about nutrient sensing in olfactory areas. Nutrients, such as carbohydrates, amino acids, and lipids, could play a key role in modulating olfactory sensitivity to adjust feeding behavior according to metabolic need. Here we summarize recent findings on nutrient-sensing neurons in olfactory areas and delineate the limits of our knowledge on this topic. The present review opens new lines of investigations on the relationship between olfaction and food intake, which could contribute to determining the etiology of metabolic disorders.

  5. State-Of in Uav Remote Sensing Survey - First Insights Into Applications of Uav Sensing Systems

    Science.gov (United States)

    Aasen, H.

    2017-08-01

    UAVs are increasingly adapted as remote sensing platforms. Together with specialized sensors, they become powerful sensing systems for environmental monitoring and surveying. Spectral data has great capabilities to the gather information about biophysical and biochemical properties. Still, capturing meaningful spectral data in a reproducible way is not trivial. Since a couple of years small and lightweight spectral sensors, which can be carried on small flexible platforms, have become available. With their adaption in the community, the responsibility to ensure the quality of the data is increasingly shifted from specialized companies and agencies to individual researchers or research teams. Due to the complexity of the data acquisition of spectral data, this poses a challenge for the community and standardized protocols, metadata and best practice procedures are needed to make data intercomparable. In November 2016, the ESSEM COST action Innovative optical Tools for proximal sensing of ecophysiological processes (OPTIMISE; http://optimise.dcs.aber.ac.uk/) held a workshop on best practices for UAV spectral sampling. The objective of this meeting was to trace the way from particle to pixel and identify influences on the data quality / reliability, to figure out how well we are currently doing with spectral sampling from UAVs and how we can improve. Additionally, a survey was designed to be distributed within the community to get an overview over the current practices and raise awareness for the topic. This talk will introduce the approach of the OPTIMISE community towards best practises in UAV spectral sampling and present first results of the survey (survey/"target="_blank">http://optimise.dcs.aber.ac.uk/uav-survey/). This contribution briefly introduces the survey and gives some insights into the first results given by the interviewees.

  6. Automated Analysis of Security in Networking Systems

    DEFF Research Database (Denmark)

    Buchholtz, Mikael

    2004-01-01

    It has for a long time been a challenge to built secure networking systems. One way to counter this problem is to provide developers of software applications for networking systems with easy-to-use tools that can check security properties before the applications ever reach the marked. These tools...... will both help raise the general level of awareness of the problems and prevent the most basic flaws from occurring. This thesis contributes to the development of such tools. Networking systems typically try to attain secure communication by applying standard cryptographic techniques. In this thesis...... attacks, and attacks launched by insiders. Finally, the perspectives for the application of the analysis techniques are discussed, thereby, coming a small step closer to providing developers with easy- to-use tools for validating the security of networking applications....

  7. [Renewal of NIHS computer network system].

    Science.gov (United States)

    Segawa, Katsunori; Nakano, Tatsuya; Saito, Yoshiro

    2012-01-01

    Updated version of National Institute of Health Sciences Computer Network System (NIHS-NET) is described. In order to reduce its electric power consumption, the main server system was newly built using the virtual machine technology. The service that each machine provided in the previous network system should be maintained as much as possible. Thus, the individual server was constructed for each service, because a virtual server often show decrement in its performance as compared with a physical server. As a result, though the number of virtual servers was increased and the network communication became complicated among the servers, the conventional service was able to be maintained, and security level was able to be rather improved, along with saving electrical powers. The updated NIHS-NET bears multiple security countermeasures. To maximal use of these measures, awareness for the network security by all users is expected.

  8. A protein switch sensing system for the quantification of sulfate.

    Science.gov (United States)

    Hamorsky, Krystal Teasley; Ensor, Charles Mark; Pasini, Patrizia; Daunert, Sylvia

    2012-02-01

    Protein engineering has generated versatile methods and technologies that have been instrumental in advancements in the fields of sensing, therapeutics, and diagnostics. Herein, we demonstrate the employment of rational design to engineer a unique bioluminescence-based protein switch. A fusion protein switch combines two totally unrelated proteins, with distinct characteristics, in a manner such that the function of one protein is dependent on another. Herein we report a protein switch sensing system by insertion of the sulfate-binding protein (SBP) into the structure of the photoprotein aequorin (AEQ). In the presence of sulfate, SBP undergoes a conformational change bringing the two segments of AEQ together, "turning on" bioluminescence in a dose-dependent fashion, thus allowing quantitative detection of sulfate. A calibration plot was obtained by correlating the amount of bioluminescence generated with the concentration of sulfate present. The switch demonstrated selectivity and reproducibility, and a detection limit of 1.6×10(-4)M for sulfate. Moreover, the sensing system was validated by performing sulfate detection in clinical and environmental samples, such as, serum, urine, and tap water. The detection limits and working ranges in all three samples fall within the average normal/recommended sulfate levels in the respective matrices. Published by Elsevier Inc.

  9. Tribotronic Transistor Array as an Active Tactile Sensing System.

    Science.gov (United States)

    Yang, Zhi Wei; Pang, Yaokun; Zhang, Limin; Lu, Cunxin; Chen, Jian; Zhou, Tao; Zhang, Chi; Wang, Zhong Lin

    2016-12-27

    Large-scale tactile sensor arrays are of great importance in flexible electronics, human-robot interaction, and medical monitoring. In this paper, a flexible 10 × 10 tribotronic transistor array (TTA) is developed as an active tactile sensing system by incorporating field-effect transistor units and triboelectric nanogenerators into a polyimide substrate. The drain-source current of each tribotronic transistor can be individually modulated by the corresponding external contact, which has induced a local electrostatic potential to act as the conventional gate voltage. By scaling down the pixel size from 5 × 5 to 0.5 × 0.5 mm 2 , the sensitivities of single pixels are systematically investigated. The pixels of the TTA show excellent durability, independence, and synchronicity, which are suitable for applications in real-time tactile sensing, motion monitoring, and spatial mapping. The integrated tribotronics provides an unconventional route to realize an active tactile sensing system, with prospective applications in wearable electronics, human-machine interfaces, fingerprint identification, and so on.

  10. Properties of polypyrrole polyvinilsulfate films for dual actuator sensing systems

    Science.gov (United States)

    Pascual, Victor H.; Otero, Toribio F.; Schumacher, Johanna

    2017-04-01

    One of the challenges of modern science is the development of actuators able to sense working conditions while actuation, mimicking the way in which biological organs work. Actuation of those organs includes nervous (electric) pulses dense reactive gels, chemical reactions exchange of ions and solvent. For that purpose, conducting polymers are being widely studied. In this work the properties of self-supported films of the polypyrrole:polyvinilsulfate (PPy/PVS) blend polymer were assessed. X-ray photoelectron spectroscopy (XPS) studies show how during reduction / oxidation the polymer exchanges cations when immersed in a NaClO4 aqueous solution, revealing free positive charges in the electrolytic solution as the driving agents leading to the swelling/shrinking of the polymer. Eventually it is the phenomenon responsible of the actuation of the polymeric motors. Submitting the system to consecutive potential sweeps shows the reaction is really sensing the scan rate used in each cycle revealing that while actuating the system is actually sensing the electrochemical working conditions.

  11. The sense of smell in systemic lupus erythematosus.

    Science.gov (United States)

    Shoenfeld, Netta; Agmon-Levin, Nancy; Flitman-Katzevman, Iveta; Paran, Daphna; Katz, Bat-sheva Porat; Kivity, Shaye; Langevitz, Pnina; Zandman-Goddard, Gisele; Shoenfeld, Yehuda

    2009-05-01

    To assess the olfactory functions in systemic lupus erythematosus (SLE) patients compared with age- and sex-matched healthy controls, and to examine the association between the sense of smell and disease activity and central nervous system (CNS) involvement. Olfactory functions in 50 SLE patients and 50 age- and sex-matched controls were evaluated using the Sniffin' Sticks test, the 3 stages of which are threshold, discrimination, and identification (TDI) of different odors. TDI scores were analyzed according to SLE disease activity and CNS involvement. In both the SLE and control groups, smell deficit correlated with male sex and older age. A decrease in the sense of smell was observed in SLE patients (46%) and controls (25%) (Psmell (anosmia) was documented only in SLE patients (10%). Total TDI scores and individual stages of smell correlated with SLE Disease Activity Index (Psmell in SLE patients compared with healthy subjects and that the decrease in the sense of smell among SLE patients correlates with disease activity and CNS involvement.

  12. Automatic Registration and Mosaicking System for Remotely Sensed Imagery

    Directory of Open Access Journals (Sweden)

    Emiliano Castejon

    2006-04-01

    Full Text Available Image registration is an important operation in many remote sensing applications and it, besides other tasks, involves the identification of corresponding control points in the images. As manual identification of control points may be time-consuming and tiring, several automatic techniques have been developed. This paper describes a system for automatic registration and mosaic of remote sensing images under development at The National Institute for Space Research (INPE and at The University of California, Santa Barbara (UCSB. The user can provide information to the system in order to speed up the registration process as well as to avoid mismatched control points. Based on statistical procedure, the system gives an indication of the registration quality. This allows users to stop the processing, to modify the registration parameters or to continue the processing. Extensive system tests have been performed with different types of data (optical, radar, multi-sensor, high-resolution images and video sequences in order to check the system performance. An online demo system is available on the internet ( which contains several examples that can be carried out using web browser.

  13. Design and Realization of Network Teaching System

    Directory of Open Access Journals (Sweden)

    Ji Shan Shan

    2016-01-01

    Full Text Available Since 21 century, with the wide spread in family and public, network has been applied in many new fields, and the application in classes is of no exception. In traditional education, teachers give lessons to students face to face. Hence, the teaching quality depends largely on the quality and initiative of the individual teacher. However, the serious disadvantages of this mode are that teachers completely dominate the classroom and may ignore the subjective cognition role of the students, which may be bad for the growth of creativity and the innovative thinking ability. Obviously, traditional education mode cannot meet the requirements of the this new era which leads to the booming developing tendency of the network. As a new teaching measure, scientifically combining modern information technology and teaching practice, network teaching not only changes the traditional education by the means and form, but even also gives new meanings to teaching concept, process, method as well as teacher-student role and other deep levels. With the help of network teaching system, on-line classroom learning, relevant information systematization, standardization and automation, this system provides students with an efficient online learning method with high quality. This also helps to solve the disadvantages of the traditional teaching mode and promote the teaching methods to a new stage. It improves the network teaching platform, enriches the network teaching resources, and establishes a network teaching system, so as to improve information quality of teachers and students and assist in improving teaching quality of schools.

  14. Quasisynchronization in Quorum Sensing Systems with Parameter Mismatches

    Directory of Open Access Journals (Sweden)

    Jianbao Zhang

    2014-01-01

    Full Text Available The paper investigates quasisynchronization in a communication system, which consists of cells communicating through quorum sensing. With the help of Lyapunov function method and Lur’e system approach, some sufficient conditions for quasisynchronization are presented, and a bound on the synchronization errors is derived. The obtained theoretical results show that the synchronization quality is influenced by two parameters detrimentally: the error bound depends almost linearly on the mismatches between cells and depends sensitively on the diffusion rates of the signals inward the cell membrane. Numerical experiments are carried out to verify the theoretical results.

  15. A Nonlinear Multiparameters Temperature Error Modeling and Compensation of POS Applied in Airborne Remote Sensing System

    Directory of Open Access Journals (Sweden)

    Jianli Li

    2014-01-01

    Full Text Available The position and orientation system (POS is a key equipment for airborne remote sensing systems, which provides high-precision position, velocity, and attitude information for various imaging payloads. Temperature error is the main source that affects the precision of POS. Traditional temperature error model is single temperature parameter linear function, which is not sufficient for the higher accuracy requirement of POS. The traditional compensation method based on neural network faces great problem in the repeatability error under different temperature conditions. In order to improve the precision and generalization ability of the temperature error compensation for POS, a nonlinear multiparameters temperature error modeling and compensation method based on Bayesian regularization neural network was proposed. The temperature error of POS was analyzed and a nonlinear multiparameters model was established. Bayesian regularization method was used as the evaluation criterion, which further optimized the coefficients of the temperature error. The experimental results show that the proposed method can improve temperature environmental adaptability and precision. The developed POS had been successfully applied in airborne TSMFTIS remote sensing system for the first time, which improved the accuracy of the reconstructed spectrum by 47.99%.

  16. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number....... Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...

  17. Reconfigurable radio systems network architectures and standards

    CERN Document Server

    Iacobucci, Maria Stella

    2013-01-01

    This timely book provides a standards-based view of the development, evolution, techniques and potential future scenarios for the deployment of reconfigurable radio systems.  After an introduction to radiomobile and radio systems deployed in the access network, the book describes cognitive radio concepts and capabilities, which are the basis for reconfigurable radio systems.  The self-organizing network features introduced in 3GPP standards are discussed and IEEE 802.22, the first standard based on cognitive radio, is described. Then the ETSI reconfigurable radio systems functional ar

  18. Deterministic System Identification Using RBF Networks

    Directory of Open Access Journals (Sweden)

    Joilson Batista de Almeida Rego

    2014-01-01

    Full Text Available This paper presents an artificial intelligence application using a nonconventional mathematical tool: the radial basis function (RBF networks, aiming to identify the current plant of an induction motor or other nonlinear systems. Here, the objective is to present the RBF response to different nonlinear systems and analyze the obtained results. A RBF network is trained and simulated in order to obtain the dynamical solution with basin of attraction and equilibrium point for known and unknown system and establish a relationship between these dynamical systems and the RBF response. On the basis of several examples, the results indicating the effectiveness of this approach are demonstrated.

  19. Thermal protection for a self-sensing piezoelectric control system

    Science.gov (United States)

    Simmers, Garnett E., Jr.; Sodano, Henry A.; Park, Gyuhae; Inman, Daniel J.

    2007-12-01

    Piezoelectric materials exhibit high electromechanical coupling that allows them to both generate an electrical signal when strained and, conversely, to produce a strain under an applied electric field. This coupling has led to the use of these materials for a variety of sensing and actuation purposes. One unique application of these materials is their use as self-sensing actuators where both the sensing and actuation functions are performed by a single patch of material. Since the actuation and sensing voltages both exist simultaneously in the piezoelectric material, a specially designed electric circuit, referred to as a bridge circuit, is required to realize the concept. Configuration of the material in this manner is advantageous for control systems due to the enhanced stability associated when collocated control is applied. While certain advantages result from this type of system, precise equilibrium of the bridge circuit is required to achieve stability. This equilibrium is easy to achieve in theory, but difficult in practice due to the thermal dependence of the piezoelectric material's dielectric constant. This study will investigate a novel method of accounting for these changes through the use of thermal switches to passively adjust the bridge circuit and maintain a balanced state. The proposed concept will be theoretically modeled and simulated in a vibration control application to identify the thermal range for stability with and without the array of switches. It will be shown that, through the use of nine thermal switches, the stable operating range can be increased by 95 °C while maintaining vibration control performance.

  20. Meteorological, environmental remote sensing and neural network analysis of the epidemiology of malaria transmission in Thailand

    Directory of Open Access Journals (Sweden)

    Richard Kiang

    2006-11-01

    Full Text Available In many malarious regions malaria transmission roughly coincides with rainy seasons, which provide for more abundant larval habitats. In addition to precipitation, other meteorological and environmental factors may also influence malaria transmission. These factors can be remotely sensed using earth observing environmental satellites and estimated with seasonal climate forecasts. The use of remote sensing usage as an early warning tool for malaria epidemics have been broadly studied in recent years, especially for Africa, where the majority of the world’s malaria occurs. Although the Greater Mekong Subregion (GMS, which includes Thailand and the surrounding countries, is an epicenter of multidrug resistant falciparum malaria, the meteorological and environmental factors affecting malaria transmissions in the GMS have not been examined in detail. In this study, the parasitological data used consisted of the monthly malaria epidemiology data at the provincial level compiled by the Thai Ministry of Public Health. Precipitation, temperature, relative humidity, and vegetation index obtained from both climate time series and satellite measurements were used as independent variables to model malaria. We used neural network methods, an artificial-intelligence technique, to model the dependency of malaria transmission on these variables. The average training accuracy of the neural network analysis for three provinces (Kanchanaburi, Mae Hong Son, and Tak which are among the provinces most endemic for malaria, is 72.8% and the average testing accuracy is 62.9% based on the 1994-1999 data. A more complex neural network architecture resulted in higher training accuracy but also lower testing accuracy. Taking into account of the uncertainty regarding reported malaria cases, we divided the malaria cases into bands (classes to compute training accuracy. Using the same neural network architecture on the 19 most endemic provinces for years 1994 to 2000, the

  1. ISTA-Net: Iterative Shrinkage-Thresholding Algorithm Inspired Deep Network for Image Compressive Sensing

    KAUST Repository

    Zhang, Jian

    2017-06-24

    Traditional methods for image compressive sensing (CS) reconstruction solve a well-defined inverse problem that is based on a predefined CS model, which defines the underlying structure of the problem and is generally solved by employing convergent iterative solvers. These optimization-based CS methods face the challenge of choosing optimal transforms and tuning parameters in their solvers, while also suffering from high computational complexity in most cases. Recently, some deep network based CS algorithms have been proposed to improve CS reconstruction performance, while dramatically reducing time complexity as compared to optimization-based methods. Despite their impressive results, the proposed networks (either with fully-connected or repetitive convolutional layers) lack any structural diversity and they are trained as a black box, void of any insights from the CS domain. In this paper, we combine the merits of both types of CS methods: the structure insights of optimization-based method and the performance/speed of network-based ones. We propose a novel structured deep network, dubbed ISTA-Net, which is inspired by the Iterative Shrinkage-Thresholding Algorithm (ISTA) for optimizing a general $l_1$ norm CS reconstruction model. ISTA-Net essentially implements a truncated form of ISTA, where all ISTA-Net parameters are learned end-to-end to minimize a reconstruction error in training. Borrowing more insights from the optimization realm, we propose an accelerated version of ISTA-Net, dubbed FISTA-Net, which is inspired by the fast iterative shrinkage-thresholding algorithm (FISTA). Interestingly, this acceleration naturally leads to skip connections in the underlying network design. Extensive CS experiments demonstrate that the proposed ISTA-Net and FISTA-Net outperform existing optimization-based and network-based CS methods by large margins, while maintaining a fast runtime.

  2. Surface Plasmon Resonance Sensing of Biorecognition Interactions within the Tumor Suppressor p53 Network.

    Science.gov (United States)

    Moscetti, Ilaria; Cannistraro, Salvatore; Bizzarri, Anna Rita

    2017-11-20

    Surface Plasmon Resonance (SPR) is a powerful technique to study the kinetics of biomolecules undergoing biorecognition processes, particularly suited for protein-protein interactions of biomedical interest. The potentiality of SPR was exploited to sense the interactions occurring within the network of the tumor suppressor p53, which is crucial for maintaining genome integrity and whose function is inactivated, mainly by down regulation or by mutation, in the majority of human tumors. This study includes p53 down-regulators, p53 mutants and also the p53 family members, p63 and p73, which could vicariate p53 protective function. Furthermore, the application of SPR was extended to sense the interaction of p53 with anti-cancer drugs, which might restore p53 function. An extended review of previous published work and unpublished kinetic data is provided, dealing with the interaction between the p53 family members, or their mutants and two anticancer molecules, Azurin and its cell-penetrating peptide, p28. All the kinetic results are discussed in connection with those obtained by a complementary approach operating at the single molecule level, namely Atomic Force Spectroscopy and the related literature data. The overview of the SPR kinetic results may significantly contribute to a deeper understanding of the interactions within p53 network, also in the perspective of designing suitable anticancer drugs.

  3. Surface Plasmon Resonance Sensing of Biorecognition Interactions within the Tumor Suppressor p53 Network

    Directory of Open Access Journals (Sweden)

    Ilaria Moscetti

    2017-11-01

    Full Text Available Surface Plasmon Resonance (SPR is a powerful technique to study the kinetics of biomolecules undergoing biorecognition processes, particularly suited for protein-protein interactions of biomedical interest. The potentiality of SPR was exploited to sense the interactions occurring within the network of the tumor suppressor p53, which is crucial for maintaining genome integrity and whose function is inactivated, mainly by down regulation or by mutation, in the majority of human tumors. This study includes p53 down-regulators, p53 mutants and also the p53 family members, p63 and p73, which could vicariate p53 protective function. Furthermore, the application of SPR was extended to sense the interaction of p53 with anti-cancer drugs, which might restore p53 function. An extended review of previous published work and unpublished kinetic data is provided, dealing with the interaction between the p53 family members, or their mutants and two anticancer molecules, Azurin and its cell-penetrating peptide, p28. All the kinetic results are discussed in connection with those obtained by a complementary approach operating at the single molecule level, namely Atomic Force Spectroscopy and the related literature data. The overview of the SPR kinetic results may significantly contribute to a deeper understanding of the interactions within p53 network, also in the perspective of designing suitable anticancer drugs.

  4. Zombie algorithms: a timesaving remote sensing systems engineering tool

    Science.gov (United States)

    Ardanuy, Philip E.; Powell, Dylan C.; Marley, Stephen

    2008-08-01

    In modern horror fiction, zombies are generally undead corpses brought back from the dead by supernatural or scientific means, and are rarely under anyone's direct control. They typically have very limited intelligence, and hunger for the flesh of the living [1]. Typical spectroradiometric or hyperspectral instruments providess calibrated radiances for a number of remote sensing algorithms. The algorithms typically must meet specified latency and availability requirements while yielding products at the required quality. These systems, whether research, operational, or a hybrid, are typically cost constrained. Complexity of the algorithms can be high, and may evolve and mature over time as sensor characterization changes, product validation occurs, and areas of scientific basis improvement are identified and completed. This suggests the need for a systems engineering process for algorithm maintenance that is agile, cost efficient, repeatable, and predictable. Experience on remote sensing science data systems suggests the benefits of "plug-n-play" concepts of operation. The concept, while intuitively simple, can be challenging to implement in practice. The use of zombie algorithms-empty shells that outwardly resemble the form, fit, and function of a "complete" algorithm without the implemented theoretical basis-provides the ground systems advantages equivalent to those obtained by integrating sensor engineering models onto the spacecraft bus. Combined with a mature, repeatable process for incorporating the theoretical basis, or scientific core, into the "head" of the zombie algorithm, along with associated scripting and registration, provides an easy "on ramp" for the rapid and low-risk integration of scientific applications into operational systems.

  5. Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

    Science.gov (United States)

    Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

    2011-01-01

    Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

  6. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun

    2012-01-01

    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  7. Targeted and anonymized smartphone-based public health interventions in a participatory sensing system.

    Science.gov (United States)

    Clarke, Andrew; Steele, Robert

    2014-01-01

    Public health interventions comprising information dissemination to affect behavioral adjustment have long been a significant component of public health campaigns. However, there has been limited development of public health intervention systems to make use of advances in mobile computing and telecommunications technologies. Such developments pose significant challenges to privacy and security where potentially sensitive data may be collected. In our previous work we identified and demonstrated the feasibility of using mobile devices as anonymous public health data collection devices as part of a Health Participatory Sensing Network (HPSN). An advanced capability of these networks extended in this paper would be the ability to distribute, apply, report on and analyze the usage and effectiveness of targeted public health interventions in an anonymous way. In this paper we describe such a platform, its place in the HPSN and demonstrate its feasibility through an implementation.

  8. System and method for evaluating wind flow fields using remote sensing devices

    Energy Technology Data Exchange (ETDEWEB)

    Schroeder, John; Hirth, Brian; Guynes, Jerry

    2016-12-13

    The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.

  9. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Nestor DUQUE

    2013-07-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  10. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Gustavo ISAZA

    2012-12-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  11. Understanding Supply Networks from Complex Adaptive Systems

    Directory of Open Access Journals (Sweden)

    Jamur Johnas Marchi

    2014-10-01

    Full Text Available This theoretical paper is based on complex adaptive systems (CAS that integrate dynamic and holistic elements, aiming to discuss supply networks as complex systems and their dynamic and co-evolutionary processes. The CAS approach can give clues to understand the dynamic nature and co-evolution of supply networks because it consists of an approach that incorporates systems and complexity. This paper’s overall contribution is to reinforce the theoretical discussion of studies that have addressed supply chain issues, such as CAS.

  12. Ultrasonic sensing of GMAW: Laser/EMAT defect detection system

    Energy Technology Data Exchange (ETDEWEB)

    Carlson, N.M.; Johnson, J.A.; Larsen, E.D. [EG and G Idaho, Inc., Idaho Falls, ID (United States); Van Clark, A. Jr.; Schaps, S.R.; Fortunko, C.M. [National Inst. of Standards and Technology, Boulder, CO (United States)

    1992-08-01

    In-process ultrasonic sensing of welding allows detection of weld defects in real time. A noncontacting ultrasonic system is being developed to operate in a production environment. The principal components are a pulsed laser for ultrasound generation and an electromagnetic acoustic transducer (EMAT) for ultrasound reception. A PC-based data acquisition system determines the quality of the weld on a pass-by-pass basis. The laser/EMAT system interrogates the area in the weld volume where defects are most likely to occur. This area of interest is identified by computer calculations on a pass-by-pass basis using weld planning information provided by the off-line programmer. The absence of a signal above the threshold level in the computer-calculated time interval indicates a disruption of the sound path by a defect. The ultrasonic sensor system then provides an input signal to the weld controller about the defect condition. 8 refs.

  13. Optical wireless networked-systems: applications to aircrafts

    Science.gov (United States)

    Kavehrad, Mohsen; Fadlullah, Jarir

    2011-01-01

    This paper focuses on leveraging the progress in semiconductor technologies to facilitate production of efficient light-based in-flight entertainment (IFE), distributed sensing, navigation and control systems. We demonstrate the ease of configuring "engineered pipes" using cheap lenses, etc. to achieve simple linear transmission capacity growth. Investigation of energy-efficient, miniaturized transceivers will create a wireless medium, for both inter and intra aircrafts, providing enhanced security, and improved quality-of-service for communications links in greater harmony with onboard systems. The applications will seamlessly inter-connect multiple intelligent devices in a network that is deployable for aircrafts navigation systems, onboard sensors and entertainment data delivery systems, and high-definition audio-visual broadcasting systems. Recent experimental results on a high-capacity infrared (808 nm) system are presented. The light source can be applied in a hybrid package along with a visible lighting LED for both lighting and communications. Also, we present a pragmatic combination of light communications through "Spotlighting" and existing onboard power-lines. It is demonstrated in details that a high-capacity IFE visible light system communicating over existing power-lines (VLC/PLC) may lead to savings in many areas through reduction of size, weight and energy consumption. This paper addresses the challenges of integrating optimized optical devices in the variety of environments described above, and presents mitigation and tailoring approaches for a multi-purpose optical network.

  14. Rational positive systems for reaction networks

    NARCIS (Netherlands)

    J.H. van Schuppen (Jan)

    2003-01-01

    textabstractThe purpose of the lecture associated with this paper is to present problems, concepts, and theorems of control and system theory for a subclass of the rational positive systems of which examples have been published as models of biochemical cell reaction networks. The recent advances in

  15. Designing Networked Adaptive Interactive Hybrid Systems

    NARCIS (Netherlands)

    Kester, L.J.H.M.

    2008-01-01

    Advances in network technologies enable distributed systems, operating in complex physical environments, to coordinate their activities over larger areas within shorter time intervals. In these systems humans and intelligent machines will, in close interaction, be able to reach their goals under

  16. Development of a Near Ground Remote Sensing System.

    Science.gov (United States)

    Zhang, Yanchao; Xiao, Yuzhao; Zhuang, Zaichun; Zhou, Liping; Liu, Fei; He, Yong

    2016-05-06

    Unmanned Aerial Vehicles (UAVs) have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1) mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2) power supply and control parts; (3) onboard application components. This platform covers five degrees of freedom (DOFs): horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail's repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies.

  17. Development of a Near Ground Remote Sensing System

    Directory of Open Access Journals (Sweden)

    Yanchao Zhang

    2016-05-01

    Full Text Available Unmanned Aerial Vehicles (UAVs have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1 mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2 power supply and control parts; (3 onboard application components. This platform covers five degrees of freedom (DOFs: horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail’s repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies.

  18. Recent progress in multidimensional optical sensing and imaging systems (MOSIS)

    Science.gov (United States)

    Shen, Xin; Javidi, Bahram

    2017-05-01

    We present recent progress of the previously reported Multidimensional Optical Sensing and Imaging Systems (MOSIS) 2.0 for target recognition, material inspection and integrated visualization. The degrees of freedom of MOSIS 2.0 include three-dimensional (3D) imaging, polarimetric imaging and multispectral imaging. Each of these features provides unique information about a scene. 3D computationally reconstructed images mitigate the occlusion in front of the object, which can be used for 3D object recognition. The degree of polarization (DoP) of the light reflected from object surface is measured by 3D polarimetric imaging. Multispectral imaging is able to segment targets with specific spectral properties.

  19. Evaluating neural networks and artificial intelligence systems

    Science.gov (United States)

    Alberts, David S.

    1994-02-01

    Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.

  20. Development of a remote sensing algorithm for cyanobacterial phycocyanin pigment in the Baltic Sea using neural network approach

    Science.gov (United States)

    Riha, Stefan; Krawczyk, Harald

    2011-11-01

    Water quality monitoring in the Baltic Sea is of high ecological importance for all its neighbouring countries. They are highly interested in a regular monitoring of water quality parameters of their regional zones. A special attention is paid to the occurrence and dissemination of algae blooms. Among the appearing blooms the possibly toxicological or harmful cyanobacteria cultures are a special case of investigation, due to their specific optical properties and due to the negative influence on the ecological state of the aquatic system. Satellite remote sensing, with its high temporal and spatial resolution opportunities, allows the frequent observations of large areas of the Baltic Sea with special focus on its two seasonal algae blooms. For a better monitoring of the cyanobacteria dominated summer blooms, adapted algorithms are needed which take into account the special optical properties of blue-green algae. Chlorophyll-a standard algorithms typically fail in a correct recognition of these occurrences. To significantly improve the opportunities of observation and propagation of the cyanobacteria blooms, the Marine Remote Sensing group of DLR has started the development of a model based inversion algorithm that includes a four component bio-optical water model for Case2 waters, which extends the commonly calculated parameter set chlorophyll, Suspended Matter and CDOM with an additional parameter for the estimation of phycocyanin absorption. It was necessary to carry out detailed optical laboratory measurements with different cyanobacteria cultures, occurring in the Baltic Sea, for the generation of a specific bio-optical model. The inversion of satellite remote sensing data is based on an artificial Neural Network technique. This is a model based multivariate non-linear inversion approach. The specifically designed Neural Network is trained with a comprehensive dataset of simulated reflectance values taking into account the laboratory obtained specific optical

  1. 78 FR 44536 - Proposed Information Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems

    Science.gov (United States)

    2013-07-24

    ... of Private Remote-Sensing Space Systems AGENCY: National Oceanic and Atmospheric Administration (NOAA... of remote-sensing space systems. The information in applications and subsequent reports is needed to ensure compliance with the Land Remote- Sensing Policy Act of 1992 and with the national security and...

  2. 75 FR 32360 - Proposed Information Collection; Comment Request; Licensing of Private Remote-Sensing Space Systems

    Science.gov (United States)

    2010-06-08

    ... of Private Remote-Sensing Space Systems AGENCY: National Oceanic and Atmospheric Administration (NOAA... the licensing of private operators of remote-sensing space systems. The information in applications and subsequent reports is needed to ensure compliance with the Land Remote- Sensing Policy Act of 1992...

  3. Load Sensing Systems - A Review of the Research Contributions Throughout the Last Decades

    DEFF Research Database (Denmark)

    Pedersen, Henrik Clemmensen; Andersen, Torben Ole; Hansen, Michael Rygaard

    2004-01-01

    The paper describes the major research contributions made in the research of hydraulic load sensing systems throughout the last decades. Furthermore, the paper investigates the efforts put into electronic load sensing and the most promising alternatives to load sensing systems. Finally, the paper...

  4. 15 CFR 960.12 - Data policy for remote sensing space systems.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Data policy for remote sensing space... REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE LICENSING OF PRIVATE REMOTE SENSING SYSTEMS Licenses § 960.12 Data policy for remote sensing space systems. (a) In accordance with the Act, if the U.S. Government...

  5. Implementation of Network Leader Sponsored Supply Chain Management Systems: A Case Study of Supplier IT Business Value

    Science.gov (United States)

    Miller, Mark S.

    2010-01-01

    This qualitative multiple-case study was conducted to explore and understand how the implementation of required relationship-specific supply chain management system (SCMS) dictated by the network leader within a supplier network affects a supplier organization. The study, on a very broad sense, attempted to research the current validity of how the…

  6. Feedback Reduction in Broadcast and two Hop Multiuser Networks: A Compressed Sensing Approach

    KAUST Repository

    Shibli, Hussain J.

    2013-05-21

    In multiuser wireless networks, the base stations (BSs) rely on the channel state information (CSI) of the users to in order to perform user scheduling and downlink transmission. While the downlink channels can be easily estimated at all user terminals via a single broadcast, several key challenges are faced during uplink (feedback) transmission. Firstly, the noisy and fading feedback channels are usually unknown at the base station, and therefore, channel training is usually required from all users. Secondly, the amount of air-time required for feedback transmission grows linearly with the number of users. This domination of the network resources by feedback information leads to increased scheduling delay and outdated CSI at the BS. In this thesis, we tackle the above challenges and propose feedback reduction algorithms based on the theory of compressive sensing (CS). The proposed algorithms encompass both single and dual hop wireless networks, and; i) permit the BS to obtain CSI with acceptable recovery guarantees under substantially reduced feedback overhead, ii) are agnostic to the statistics of the feedback channels, and iii) utilize the apriori statistics of the additive noise to identify strong users. Numerical results show that the proposed algorithms are able to reduce the feedback overhead, improve detection at the BS, and achieve a sum-rate close to that obtained by noiseless dedicated feedback algorithms.

  7. The probabilistic neural network architecture for high speed classification of remotely sensed imagery

    Science.gov (United States)

    Chettri, Samir R.; Cromp, Robert F.

    1993-01-01

    In this paper we discuss a neural network architecture (the Probabilistic Neural Net or the PNN) that, to the best of our knowledge, has not previously been applied to remotely sensed data. The PNN is a supervised non-parametric classification algorithm as opposed to the Gaussian maximum likelihood classifier (GMLC). The PNN works by fitting a Gaussian kernel to each training point. The width of the Gaussian is controlled by a tuning parameter called the window width. If very small widths are used, the method is equivalent to the nearest neighbor method. For large windows, the PNN behaves like the GMLC. The basic implementation of the PNN requires no training time at all. In this respect it is far better than the commonly used backpropagation neural network which can be shown to take O(N6) time for training where N is the dimensionality of the input vector. In addition the PNN can be implemented in a feed forward mode in hardware. The disadvantage of the PNN is that it requires all the training data to be stored. Some solutions to this problem are discussed in the paper. Finally, we discuss the accuracy of the PNN with respect to the GMLC and the backpropagation neural network (BPNN). The PNN is shown to be better than GMLC and not as good as the BPNN with regards to classification accuracy.

  8. Combined Saliency with Multi-Convolutional Neural Network for High Resolution Remote Sensing Scene Classification

    Directory of Open Access Journals (Sweden)

    HE Xiaofei

    2016-09-01

    Full Text Available The scene information existing in high resolution remote sensing images is important for image interpretation and understanding of the real world. Traditional scene classification methods often use middle and low-level artificial features, but high resolution images have rich information and complex scene configuration, which need high-level feature to express. A joint saliency and multi-convolutional neural network method is proposed in this paper. Firstly, we obtain meaningful patches that include dominant image information by saliency sampling. Secondly, these patches will be set as a sample input to the convolutional neural network for training, obtain feature expression on different levels. Finally, we embed the multi-layer features into the support vector machine (SVM for image classification. Experiments using two high resolution image scene data show that saliency sampling can effectively get the main target, weaken the impact of other unrelated targets, and reduce data redundancy; convolutional neural network can automatically learn the high-level feature, compared to existing methods, the proposed method can effectively improve the classification accuracy.

  9. Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

    CERN Document Server

    Su, Housheng

    2013-01-01

    Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

  10. A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yongwei Zhang

    2017-01-01

    Full Text Available In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.

  11. Intelligent Wireless Sensor Networks for System Health Monitoring

    Science.gov (United States)

    Alena, Rick

    2011-01-01

    Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of

  12. Dynamical systems on networks a tutorial

    CERN Document Server

    Porter, Mason A

    2016-01-01

    This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Appli...

  13. Soft sensing of system parameters in membrane distillation

    KAUST Repository

    Laleg-Kirati, Taous-Meriem

    2017-03-23

    Various examples of methods and systems are provided for soft sensing of system parameters in membrane distillation (MD). In one example, a system includes a MD module comprising a feed side and a permeate side separated by a membrane boundary layer; and processing circuitry configured to estimate feed solution temperatures and permeate solution temperatures of the MD module using monitored outlet temperatures of the feed side and the permeate side. In another example, a method includes monitoring outlet temperatures of a feed side and a permeate side of a MD module to determine a current feed outlet temperature and a current permeate outlet temperature; and determining a plurality of estimated temperature states of a membrane boundary layer separating the feed side and the permeate side of the MD module using the current feed outlet temperature and the current permeate outlet temperature.

  14. Network analysis of eight industrial symbiosis systems

    Science.gov (United States)

    Zhang, Yan; Zheng, Hongmei; Shi, Han; Yu, Xiangyi; Liu, Gengyuan; Su, Meirong; Li, Yating; Chai, Yingying

    2016-06-01

    Industrial symbiosis is the quintessential characteristic of an eco-industrial park. To divide parks into different types, previous studies mostly focused on qualitative judgments, and failed to use metrics to conduct quantitative research on the internal structural or functional characteristics of a park. To analyze a park's structural attributes, a range of metrics from network analysis have been applied, but few researchers have compared two or more symbioses using multiple metrics. In this study, we used two metrics (density and network degree centralization) to compare the degrees of completeness and dependence of eight diverse but representative industrial symbiosis networks. Through the combination of the two metrics, we divided the networks into three types: weak completeness, and two forms of strong completeness, namely "anchor tenant" mutualism and "equality-oriented" mutualism. The results showed that the networks with a weak degree of completeness were sparse and had few connections among nodes; for "anchor tenant" mutualism, the degree of completeness was relatively high, but the affiliated members were too dependent on core members; and the members in "equality-oriented" mutualism had equal roles, with diverse and flexible symbiotic paths. These results revealed some of the systems' internal structure and how different structures influenced the exchanges of materials, energy, and knowledge among members of a system, thereby providing insights into threats that may destabilize the network. Based on this analysis, we provide examples of the advantages and effectiveness of recent improvement projects in a typical Chinese eco-industrial park (Shandong Lubei).

  15. Food Security, Decision Making and the Use of Remote Sensing in Famine Early Warning Systems

    Science.gov (United States)

    Brown, Molly E.

    2008-01-01

    Famine early warning systems use remote sensing in combination with socio-economic and household food economy analysis to provide timely and rigorous information on emerging food security crises. The Famine Early Warning Systems Network (FEWS NET) is the US Agency for International Development's decision support system in 20 African countries, as well as in Guatemala, Haiti and Afghanistan. FEWS NET provides early and actionable policy guidance for the US Government and its humanitarian aid partners. As we move into an era of climate change where weather hazards will become more frequent and severe, understanding how to provide quantitative and actionable scientific information for policy makers using biophysical data is critical for an appropriate and effective response.

  16. Strategic Investment in Protection in Networked Systems

    CERN Document Server

    Leduc, Matt V

    2015-01-01

    We study the incentives that agents have to invest in costly protection against cascading failures in networked systems. Applications include vaccination, computer security and airport security. Agents are connected through a network and can fail either intrinsically or as a result of the failure of a subset of their neighbors. We characterize the equilibrium based on an agent's failure probability and derive conditions under which equilibrium strategies are monotone in degree (i.e. in how connected an agent is on the network). We show that different kinds of applications (e.g. vaccination, airport security) lead to very different equilibrium patterns of investments in protection, with important welfare and risk implications. Our equilibrium concept is flexible enough to allow for comparative statics in terms of network properties and we show that it is also robust to the introduction of global externalities (e.g. price feedback, congestion).

  17. VSAT networks in the INTELSAT system

    Science.gov (United States)

    Albuquerque, Jose P. A.; Buchsbaum, Luiz M.; Meulman, Christopher B.; Rieger, Frederic; Zhu, Xiaobo

    1993-08-01

    This paper describes how VSAT networks currently operate in the INTELSAT system. Four classes of VSAT networks (data transaction; circuit-switched; data distribution; microterminals) are identified, and it is verified that all of them can operate with INTELSAT satellites. Most VSAT networks in operation on INTELSAT today operate in fractional transponder leases. Fractional transponder capacity estimates are presented for a wide range of scenarios and different INTELSAT satellite series. These estimates clearly show increasing bandwidth utilization efficiencies for newer generations of INTELSAT satellites. Provided that VSAT and hub sizes are appropriately selected, efficiencies are already significant with existing satellites. Two possible ways of increasing the utilization of satellite resources are examined in the paper: demand assignment multiple access (DAMA) and multiple channel-per-carrier (MCPC) techniques. The impact of using DAMA in circuit-switched VSAT networks is quantified.

  18. Llamas: Large-area microphone arrays and sensing systems

    Science.gov (United States)

    Sanz-Robinson, Josue

    Large-area electronics (LAE) provides a platform to build sensing systems, based on distributing large numbers of densely spaced sensors over a physically-expansive space. Due to their flexible, "wallpaper-like" form factor, these systems can be seamlessly deployed in everyday spaces. They go beyond just supplying sensor readings, but rather they aim to transform the wealth of data from these sensors into actionable inferences about our physical environment. This requires vertically integrated systems that span the entirety of the signal processing chain, including transducers and devices, circuits, and signal processing algorithms. To this end we develop hybrid LAE / CMOS systems, which exploit the complementary strengths of LAE, enabling spatially distributed sensors, and CMOS ICs, providing computational capacity for signal processing. To explore the development of hybrid sensing systems, based on vertical integration across the signal processing chain, we focus on two main drivers: (1) thin-film diodes, and (2) microphone arrays for blind source separation: 1) Thin-film diodes are a key building block for many applications, such as RFID tags or power transfer over non-contact inductive links, which require rectifiers for AC-to-DC conversion. We developed hybrid amorphous / nanocrystalline silicon diodes, which are fabricated at low temperatures (circuit level we developed localized a-Si TFT amplifiers, and a custom CMOS IC, for system control, sensor readout and digitization. On a signal processing level we developed an algorithm for blind source separation in a real, reverberant room, based on beamforming and binary masking. It requires no knowledge about the location of the speakers or microphones. Instead, it uses cluster analysis techniques to determine the time delays for beamforming; thus, adapting to the unique acoustic environment of the room.

  19. Social Network Supported Process Recommender System

    Science.gov (United States)

    Ye, Yanming; Yin, Jianwei; Xu, Yueshen

    2014-01-01

    Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced. PMID:24672309

  20. Restaurant Management System Over Private Network

    Directory of Open Access Journals (Sweden)

    Amanat Dhillon

    2017-08-01

    Full Text Available Restaurant Management System over Private Network is an automated business environment which allows restaurants to reduce operational costs increase efficiency of business improve customer satisfaction cut down labour costs decrease order processing time and provide better Quality-of-ServiceQ-S. This system manages a digital menu allowing the customers to place orders easily. Authentication fields for employees enable better administration of the restaurant. The whole restaurant is integrated into one private network thereby improving security and eliminating the need for a constant internet connection.

  1. Sensing risk, fearing uncertainty: systems science approach to change

    OpenAIRE

    Janecka, Ivo P.

    2014-01-01

    BackgroundMedicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in o...

  2. A virtual remote sensing observation network for continuous, near-real-time monitoring of atmospheric instability

    Science.gov (United States)

    Toporov, Maria; Löhnert, Ulrich; Potthast, Roland; Cimini, Domenico; De Angelis, Francesco

    2017-04-01

    remote sensing (i.e. SEVIRI, AMSU) is used to complement observations from a virtual ground-based microwave radiometer network based on the reanalysis of the COSMO model for Europe. In this contribution, we present a synergetic retrieval algorithm of stability indices from satellite observations and ground-based microwave measurements based on the COSMO-DE reanalysis as truth. In order to make the approach feasible for data assimilation applications at national weather services, we simulate satellite observations with the standard RTTOV model and use the newly developed RTTOV-gb (ground-based) for the ground-based radiometers (De Angelis et al., 2016). For the detection of significant instabilities, we show the synergy benefit in terms of uncertainty reduction, probability of detection and other forecast skill scores. The overall goal of ARON is to quantify the impact of ground-based vertical profilers within an integrated forecasting system, which combines short-term and now-casting.

  3. Software for a GPS-Reflection Remote-Sensing System

    Science.gov (United States)

    Lowe, Stephen

    2003-01-01

    A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

  4. A closed-loop neurobotic system for fine touch sensing

    Science.gov (United States)

    Bologna, L. L.; Pinoteau, J.; Passot, J.-B.; Garrido, J. A.; Vogel, J.; Ros Vidal, E.; Arleo, A.

    2013-08-01

    Objective. Fine touch sensing relies on peripheral-to-central neurotransmission of somesthetic percepts, as well as on active motion policies shaping tactile exploration. This paper presents a novel neuroengineering framework for robotic applications based on the multistage processing of fine tactile information in the closed action-perception loop. Approach. The integrated system modules focus on (i) neural coding principles of spatiotemporal spiking patterns at the periphery of the somatosensory pathway, (ii) probabilistic decoding mechanisms mediating cortical-like tactile recognition and (iii) decision-making and low-level motor adaptation underlying active touch sensing. We probed the resulting neural architecture through a Braille reading task. Main results. Our results on the peripheral encoding of primary contact features are consistent with experimental data on human slow-adapting type I mechanoreceptors. They also suggest second-order processing by cuneate neurons may resolve perceptual ambiguities, contributing to a fast and highly performing online discrimination of Braille inputs by a downstream probabilistic decoder. The implemented multilevel adaptive control provides robustness to motion inaccuracy, while making the number of finger accelerations covariate with Braille character complexity. The resulting modulation of fingertip kinematics is coherent with that observed in human Braille readers. Significance. This work provides a basis for the design and implementation of modular neuromimetic systems for fine touch discrimination in robotics.

  5. Preliminary AFBITS Network Control System

    Science.gov (United States)

    1975-06-01

    divided into time slots. This provides essentially simultaneous digital data service to a large number of individual subscribers. In a normal...model telephone switch, modern exchanges such as those developed by the Bell System or the independent Telco suppliers give a good indication of

  6. Evolution of Linux operating system network

    Science.gov (United States)

    Xiao, Guanping; Zheng, Zheng; Wang, Haoqin

    2017-01-01

    Linux operating system (LOS) is a sophisticated man-made system and one of the most ubiquitous operating systems. However, there is little research on the structure and functionality evolution of LOS from the prospective of networks. In this paper, we investigate the evolution of the LOS network. 62 major releases of LOS ranging from versions 1.0 to 4.1 are modeled as directed networks in which functions are denoted by nodes and function calls are denoted by edges. It is found that the size of the LOS network grows almost linearly, while clustering coefficient monotonically decays. The degree distributions are almost the same: the out-degree follows an exponential distribution while both in-degree and undirected degree follow power-law distributions. We further explore the functionality evolution of the LOS network. It is observed that the evolution of functional modules is shown as a sequence of seven events (changes) succeeding each other, including continuing, growth, contraction, birth, splitting, death and merging events. By means of a statistical analysis of these events in the top 4 largest components (i.e., arch, drivers, fs and net), it is shown that continuing, growth and contraction events occupy more than 95% events. Our work exemplifies a better understanding and describing of the dynamics of LOS evolution.

  7. Deep Salient Feature Based Anti-Noise Transfer Network for Scene Classification of Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Xi Gong

    2018-03-01

    Full Text Available Remote sensing (RS scene classification is important for RS imagery semantic interpretation. Although tremendous strides have been made in RS scene classification, one of the remaining open challenges is recognizing RS scenes in low quality variance (e.g., various scales and noises. This paper proposes a deep salient feature based anti-noise transfer network (DSFATN method that effectively enhances and explores the high-level features for RS scene classification in different scales and noise conditions. In DSFATN, a novel discriminative deep salient feature (DSF is introduced by saliency-guided DSF extraction, which conducts a patch-based visual saliency (PBVS algorithm using “visual attention” mechanisms to guide pre-trained CNNs for producing the discriminative high-level features. Then, an anti-noise network is proposed to learn and enhance the robust and anti-noise structure information of RS scene by directly propagating the label information to fully-connected layers. A joint loss is used to minimize the anti-noise network by integrating anti-noise constraint and a softmax classification loss. The proposed network architecture can be easily trained with a limited amount of training data. The experiments conducted on three different scale RS scene datasets show that the DSFATN method has achieved excellent performance and great robustness in different scales and noise conditions. It obtains classification accuracy of 98.25%, 98.46%, and 98.80%, respectively, on the UC Merced Land Use Dataset (UCM, the Google image dataset of SIRI-WHU, and the SAT-6 dataset, advancing the state-of-the-art substantially.

  8. Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Peter Corke

    2009-05-01

    Full Text Available Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs. We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

  9. Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing.

    Science.gov (United States)

    Handcock, Rebecca N; Swain, Dave L; Bishop-Hurley, Greg J; Patison, Kym P; Wark, Tim; Valencia, Philip; Corke, Peter; O'Neill, Christopher J

    2009-01-01

    Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

  10. Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

    Science.gov (United States)

    Handcock, Rebecca N.; Swain, Dave L.; Bishop-Hurley, Greg J.; Patison, Kym P.; Wark, Tim; Valencia, Philip; Corke, Peter; O'Neill, Christopher J.

    2009-01-01

    Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle. PMID:22412327

  11. Wideband Spectrum Sensing Based on Riemannian Distance for Cognitive Radio Networks.

    Science.gov (United States)

    Lu, Qiuyuan; Yang, Shengzhi; Liu, Fan

    2017-03-23

    Detecting the signals of the primary users in the wideband spectrum is a key issue for cognitive radio networks. In this paper, we consider the multi-antenna based signal detection in a wideband spectrum scenario where the noise statistical characteristics are assumed to be unknown. We reason that the covariance matrices of the spectrum subbands have structural constraints and that they describe a manifold in the signal space. Thus, we propose a novel signal detection algorithm based on Riemannian distance and Riemannian mean which is different from the traditional eigenvalue-based detector (EBD) derived with the generalized likelihood ratio criterion. Using the moment matching method, we obtain the closed expression of the decision threshold. From the considered simulation settings, it is shown that the proposed Riemannian distance detector (RDD) has a better performance than the traditional EBD in wideband spectrum sensing.

  12. A sensing role of the glutamine synthetase in the nitrogen regulation network in Fusarium fujikuroi.

    Directory of Open Access Journals (Sweden)

    Dominik Wagner

    Full Text Available In the plant pathogenic ascomycete Fusarium fujikuroi the synthesis of several economically important secondary metabolites (SM depends on the nitrogen status of the cells. Of these SMs, gibberellin and bikaverin synthesis is subject to nitrogen catabolite repression (NCR and is therefore only executed under nitrogen starvation conditions. How the signal of available nitrogen quantity and quality is sensed and transmitted to transcription factors is largely unknown. Earlier work revealed an essential regulatory role of the glutamine synthetase (GS in the nitrogen regulation network and secondary metabolism as its deletion resulted in total loss of SM gene expression. Here we present extensive gene regulation studies of the wild type, the Δgln1 mutant and complementation strains of the gln1 deletion mutant expressing heterologous GS-encoding genes of prokaryotic and eukaryotic origin or 14 different F. fujikuroi gln1 copies with site-directed mutations. All strains were grown under different nitrogen conditions and characterized regarding growth, expression of NCR-responsive genes and biosynthesis of SM. We provide evidence for distinct roles of the GS in sensing and transducing the signals to NCR-responsive genes. Three site directed mutations partially restored secondary metabolism and GS-dependent gene expression, but not glutamine formation, demonstrating for the first time that the catalytic and regulatory roles of GS can be separated. The distinct mutant phenotypes show that the GS (1 participates in NH4 (+-sensing and transducing the signal towards NCR-responsive transcription factors and their subsequent target genes; (2 affects carbon catabolism and (3 activates the expression of a distinct set of non-NCR GS-dependent genes. These novel insights into the regulatory role of the GS provide fascinating perspectives for elucidating regulatory roles of GS proteins of different organism in general.

  13. Social networks as embedded complex adaptive systems.

    Science.gov (United States)

    Benham-Hutchins, Marge; Clancy, Thomas R

    2010-09-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

  14. Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Fan Hu

    2015-11-01

    Full Text Available Learning efficient image representations is at the core of the scene classification task of remote sensing imagery. The existing methods for solving the scene classification task, based on either feature coding approaches with low-level hand-engineered features or unsupervised feature learning, can only generate mid-level image features with limited representative ability, which essentially prevents them from achieving better performance. Recently, the deep convolutional neural networks (CNNs, which are hierarchical architectures trained on large-scale datasets, have shown astounding performance in object recognition and detection. However, it is still not clear how to use these deep convolutional neural networks for high-resolution remote sensing (HRRS scene classification. In this paper, we investigate how to transfer features from these successfully pre-trained CNNs for HRRS scene classification. We propose two scenarios for generating image features via extracting CNN features from different layers. In the first scenario, the activation vectors extracted from fully-connected layers are regarded as the final image features; in the second scenario, we extract dense features from the last convolutional layer at multiple scales and then encode the dense features into global image features through commonly used feature coding approaches. Extensive experiments on two public scene classification datasets demonstrate that the image features obtained by the two proposed scenarios, even with a simple linear classifier, can result in remarkable performance and improve the state-of-the-art by a significant margin. The results reveal that the features from pre-trained CNNs generalize well to HRRS datasets and are more expressive than the low- and mid-level features. Moreover, we tentatively combine features extracted from different CNN models for better performance.

  15. Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks.

    Science.gov (United States)

    Shi, Heyuan; Song, Xiaoyu; Gu, Ming; Sun, Jiaguang

    2016-11-28

    The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN.

  16. Semitensor Product Compressive Sensing for Big Data Transmission in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Haipeng Peng

    2017-01-01

    Full Text Available Big data transmission in wireless sensor network (WSN consumes energy while the node in WSN is energy-limited, and the data transmitted needs to be encrypted resulting from the ease of being eavesdropped in WSN links. Compressive sensing (CS can encrypt data and reduce the data volume to solve these two problems. However, the nodes in WSNs are not only energy-limited, but also storage and calculation resource-constrained. The traditional CS uses the measurement matrix as the secret key, which consumes a huge storage space. Moreover, the calculation cost of the traditional CS is large. In this paper, semitensor product compressive sensing (STP-CS is proposed, which reduces the size of the secret key to save the storage space by breaking through the dimension match restriction of the matrix multiplication and decreases the calculation amount to save the calculation resource. Simulation results show that STP-CS encryption can achieve better performances of saving storage and calculation resources compared with the traditional CS encryption.

  17. The Deep Space Network Advanced Systems Program

    Science.gov (United States)

    Davarian, Faramaz

    2010-01-01

    The deep space network (DSN)--with its three complexes in Goldstone, California, Madrid, Spain, and Canberra, Australia--provides the resources to track and communicate with planetary and deep space missions. Each complex consists of an array of capabilities for tracking probes almost anywhere in the solar system. A number of innovative hardware, software and procedural tools are used for day-to-day operations at DSN complexes as well as at the network control at the Jet Propulsion Laboratory (JPL). Systems and technologies employed by the network include large-aperture antennas (34-m and 70-m), cryogenically cooled receivers, high-power transmitters, stable frequency and timing distribution assemblies, modulation and coding schemes, spacecraft transponders, radiometric tracking techniques, etc. The DSN operates at multiple frequencies, including the 2-GHz band, the 7/8-GHz band, and the 32/34-GHz band.

  18. Archiving and access systems for remote sensing: Chapter 6

    Science.gov (United States)

    Faundeen, John L.; Percivall, George; Baros, Shirley; Baumann, Peter; Becker, Peter H.; Behnke, J.; Benedict, Karl; Colaiacomo, Lucio; Di, Liping; Doescher, Chris; Dominguez, J.; Edberg, Roger; Ferguson, Mark; Foreman, Stephen; Giaretta, David; Hutchison, Vivian; Ip, Alex; James, N.L.; Khalsa, Siri Jodha S.; Lazorchak, B.; Lewis, Adam; Li, Fuqin; Lymburner, Leo; Lynnes, C.S.; Martens, Matt; Melrose, Rachel; Morris, Steve; Mueller, Norman; Navale, Vivek; Navulur, Kumar; Newman, D.J.; Oliver, Simon; Purss, Matthew; Ramapriyan, H.K.; Rew, Russ; Rosen, Michael; Savickas, John; Sixsmith, Joshua; Sohre, Tom; Thau, David; Uhlir, Paul; Wang, Lan-Wei; Young, Jeff

    2016-01-01

    Focuses on major developments inaugurated by the Committee on Earth Observation Satellites, the Group on Earth Observations System of Systems, and the International Council for Science World Data System at the global level; initiatives at national levels to create data centers (e.g. the National Aeronautics and Space Administration (NASA) Distributed Active Archive Centers and other international space agency counterparts), and non-government systems (e.g. Center for International Earth Science Information Network). Other major elements focus on emerging tool sets, requirements for metadata, data storage and refresh methods, the rise of cloud computing, and questions about what and how much data should be saved. The sub-sections of the chapter address topics relevant to the science, engineering and standards used for state-of-the-art operational and experimental systems.

  19. Stability of multiple access network control schemes with carrier sensing and exponential backoff

    Science.gov (United States)

    Barany, Ernest; Krupa, Maciej

    2006-05-01

    A new approach to determine the stability of multiple access network control schemes is presented. A “busy” network (the precise meaning of the term “busy” will be presented in the text) is modelled as a switched single-server hybrid dynamical system whose switching laws are stochastic and are based on typical multiple access network control protocols such as ALOHA and ethernet. The techniques are used to compute the critical ratio of traffic production per network node to total available bandwidth that ensures that data packets will not accumulate unboundedly in waiting queues at each node. This is a measure of stability of the network and is an emergent, global, property determined by decentralized, autonomous behavior of each node. The behavior of each individual node is regarded as “microscopic” and the collective behavior of the network as a whole are emergent consequences of such microscopic laws. The results follow from the stationary distribution property of ergodic Markov chains.

  20. Embedded systems handbook networked embedded systems

    CERN Document Server

    Zurawski, Richard

    2009-01-01

    Considered a standard industry resource, the Embedded Systems Handbook provided researchers and technicians with the authoritative information needed to launch a wealth of diverse applications, including those in automotive electronics, industrial automated systems, and building automation and control. Now a new resource is required to report on current developments and provide a technical reference for those looking to move the field forward yet again. Divided into two volumes to accommodate this growth, the Embedded Systems Handbook, Second Edition presents a comprehensive view on this area

  1. Protecting Mobile Crowd Sensing against Sybil Attacks Using Cloud Based Trust Management System

    Directory of Open Access Journals (Sweden)

    Shih-Hao Chang

    2016-01-01

    Full Text Available Mobile crowd sensing (MCS arises as a new sensing paradigm, which leverages citizens for large-scale sensing by various mobile devices to efficiently collect and share local information. Unlike other MCS application challenges that consider user privacy and data trustworthiness, this study focuses on the network trustworthiness problem, namely, Sybil attacks in MCS network. The Sybil attack in computer security is a type of security attack, which illegally forges multiple identities in peer-to-peer networks, namely, Sybil identities. These Sybil identities will falsify multiple identities that negatively influence the effectiveness of sensing data in this MCS network or degrading entire network performance. To cope with this problem, a cloud based trust management scheme (CbTMS was proposed to detect Sybil attacks in the MCS network. The CbTMS was proffered for performing active and passive checking scheme, in addition to the mobile PCS trustworthiness management, and includes a decision tree algorithm, to verify the covered nodes in the MCS network. Simulation studies show that our CbTMS can efficiently detect the malicious Sybil nodes in the network and cause 6.87 Wh power reduction compared with other malicious Sybil node attack mode.

  2. Data-Filtering System to Avoid Total Data Distortion in IoT Networking

    Directory of Open Access Journals (Sweden)

    Dae-Young Kim

    2017-01-01

    Full Text Available In the Internet of Things (IoT networking, numerous objects are connected to a network. They sense events and deliver the sensed information to the cloud. A lot of data is generated in the IoT network, and servers in the cloud gather the sensed data from the objects. Then, the servers analyze the collected data and provide proper intelligent services to users through the results of the analysis. When the server analyzes the collected data, if there exists malfunctioning data, distortional results of the analysis will be generated. The distortional results lead to misdirection of the intelligent services, leading to poor user experience. In the analysis for intelligent services in IoT, malfunctioning data should be avoided because integrity of the collected data is crucial. Therefore, this paper proposes a data-filtering system for the server in the cloud. The proposed data-filtering system is placed in front of the server and firstly receives the sensed data from the objects. It employs the naïve Bayesian classifier and, by learning, classifies the malfunctioning data from among the collected data. Data with integrity is delivered to the server for analysis. Because the proposed system filters the malfunctioning data, the server can obtain accurate analysis results and reduce computing load. The performance of the proposed data-filtering system is evaluated through computer simulation. Through the simulation results, the efficiency of the proposed data-filtering system is shown.

  3. Development of a remote sensing network for time-sensitive detection of fine scale damage to transportation infrastructure : [final report].

    Science.gov (United States)

    2015-09-23

    This research project aimed to develop a remote sensing system capable of rapidly identifying fine-scale damage to critical transportation infrastructure following hazard events. Such a system must be pre-planned for rapid deployment, automate proces...

  4. Advances in network systems architectures, security, and applications

    CERN Document Server

    Awad, Ali; Furtak, Janusz; Legierski, Jarosław

    2017-01-01

    This book provides the reader with a comprehensive selection of cutting–edge algorithms, technologies, and applications. The volume offers new insights into a range of fundamentally important topics in network architectures, network security, and network applications. It serves as a reference for researchers and practitioners by featuring research contributions exemplifying research done in the field of network systems. In addition, the book highlights several key topics in both theoretical and practical aspects of networking. These include wireless sensor networks, performance of TCP connections in mobile networks, photonic data transport networks, security policies, credentials management, data encryption for network transmission, risk management, live TV services, and multicore energy harvesting in distributed systems. .

  5. A Real-Time Smooth Weighted Data Fusion Algorithm for Greenhouse Sensing Based on Wireless Sensor Networks.

    Science.gov (United States)

    Zou, Tengyue; Wang, Yuanxia; Wang, Mengyi; Lin, Shouying

    2017-11-06

    Wireless sensor networks are widely used to acquire environmental parameters to support agricultural production. However, data variation and noise caused by actuators often produce complex measurement conditions. These factors can lead to nonconformity in reporting samples from different nodes and cause errors when making a final decision. Data fusion is well suited to reduce the influence of actuator-based noise and improve automation accuracy. A key step is to identify the sensor nodes disturbed by actuator noise and reduce their degree of participation in the data fusion results. A smoothing value is introduced and a searching method based on Prim's algorithm is designed to help obtain stable sensing data. A voting mechanism with dynamic weights is then proposed to obtain the data fusion result. The dynamic weighting process can sharply reduce the influence of actuator noise in data fusion and gradually condition the data to normal levels over time. To shorten the data fusion time in large networks, an acceleration method with prediction is also presented to reduce the data collection time. A real-time system is implemented on STMicroelectronics STM32F103 and NORDIC nRF24L01 platforms and the experimental results verify the improvement provided by these new algorithms.

  6. Additive Manufacturing Enabled Ubiquitous Sensing in Aerospace and Integrated Building Systems

    Science.gov (United States)

    Mantese, Joseph

    2015-03-01

    Ubiquitous sensing is rapidly emerging as a means for globally optimizing systems of systems by providing both real time PHM (prognostics, diagnostics, and health monitoring), as well as expanded in-the-loop control. In closed or proprietary systems, such as in aerospace vehicles and life safety or security building systems; wireless signals and power must be supplied to a sensor network via single or multiple data concentrators in an architecture that ensures reliable/secure interconnectivity. In addition, such networks must be robust to environmental factors, including: corrosion, EMI/RFI, and thermal/mechanical variations. In this talk, we describe the use of additive manufacturing processes guided by physics based models for seamlessly embedding a sensor suite into aerospace and building system components; while maintaining their structural integrity and providing wireless power, sensor interrogation, and real-time diagnostics. We detail this approach as it specifically applies to industrial gas turbines for stationary land power. This work is supported through a grant from the National Energy Technology Laboratory (NETL), a division of the Department of Energy.

  7. Controllable Buoys and Networked Buoy Systems

    Science.gov (United States)

    Davoodi, Faranak (Inventor); Davoudi, Farhooman (Inventor)

    2017-01-01

    Buoyant sensor networks are described, comprising floating buoys with sensors and energy harvesting capabilities. The buoys can control their buoyancy and motion, and can organize communication in a distributed fashion. Some buoys may have tethered underwater vehicles with a smart spooling system that allows the vehicles to dive deep underwater while remaining in communication and connection with the buoys.

  8. Comprehensive information system development and networking in ...

    African Journals Online (AJOL)

    Background/Aim: Hospital Information System(HIS) and Networking development is now the most important technology that must be embraced by all hospitals and clinics these days. Patients sometimes used to face problems in order to have quick and good services in the hospitals, often due to delay in searching for the ...

  9. Social network based dynamic transit service through the OMITS system.

    Science.gov (United States)

    2014-02-01

    The Open Mode Integrated Transportation System (OMITS) forms a sustainable information infrastructure for communication within and between the mobile/Internet network, the roadway : network, and the users social network. It manipulates the speed g...

  10. Network and adaptive system of systems modeling and analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Lawton, Craig R.; Campbell, James E. Dr. (.; .); Anderson, Dennis James; Eddy, John P.

    2007-05-01

    This report documents the results of an LDRD program entitled ''Network and Adaptive System of Systems Modeling and Analysis'' that was conducted during FY 2005 and FY 2006. The purpose of this study was to determine and implement ways to incorporate network communications modeling into existing System of Systems (SoS) modeling capabilities. Current SoS modeling, particularly for the Future Combat Systems (FCS) program, is conducted under the assumption that communication between the various systems is always possible and occurs instantaneously. A more realistic representation of these communications allows for better, more accurate simulation results. The current approach to meeting this objective has been to use existing capabilities to model network hardware reliability and adding capabilities to use that information to model the impact on the sustainment supply chain and operational availability.

  11. Design Criteria For Networked Image Analysis System

    Science.gov (United States)

    Reader, Cliff; Nitteberg, Alan

    1982-01-01

    Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

  12. Intelligent Systems: Terrestrial Observation and Prediction Using Remote Sensing Data

    Science.gov (United States)

    Coughlan, Joseph C.

    2005-01-01

    NASA has made science and technology investments to better utilize its large space-borne remote sensing data holdings of the Earth. With the launch of Terra, NASA created a data-rich environment where the challenge is to fully utilize the data collected from EOS however, despite unprecedented amounts of observed data, there is a need for increasing the frequency, resolution, and diversity of observations. Current terrestrial models that use remote sensing data were constructed in a relatively data and compute limited era and do not take full advantage of on-line learning methods and assimilation techniques that can exploit these data. NASA has invested in visualization, data mining and knowledge discovery methods which have facilitated data exploitation, but these methods are insufficient for improving Earth science models that have extensive background knowledge nor do these methods refine understanding of complex processes. Investing in interdisciplinary teams that include computational scientists can lead to new models and systems for online operation and analysis of data that can autonomously improve in prediction skill over time.

  13. Remote sensing of vegetation fires and its contribution to a fire management information system

    Science.gov (United States)

    Stephane P. Flasse; Simon N. Trigg; Pietro N. Ceccato; Anita H. Perryman; Andrew T. Hudak; Mark W. Thompson; Bruce H. Brockett; Moussa Drame; Tim Ntabeni; Philip E. Frost; Tobias Landmann; Johan L. le Roux

    2004-01-01

    In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then...

  14. On-chip bioassay using immobilized sensing bacteria in three-dimensional microfluidic network.

    Science.gov (United States)

    Tani, Hirofumi; Maehana, Koji; Kamidate, Tamio

    2007-01-01

    An on-chip whole-cell bioassay has been carried out using Escherichia coli tester strains for genotoxicity. In this assay format, the mutagen-responsive bioluminescence (BL) strains are immobilized in a chip assembly in which a silicon chip is placed between two poly(dimethylsiloxane) (PDMS) chips. In the chip assembly, microchannels fabricated on the two separate PDMS layers are connected via perforated microwells on the Si chip, and thus a three-dimensional microfluidic network is constructed. The strains mixed with agarose are loaded from the channels on one of the two PDMS layers into the wells on Si chip, followed by gelation. Induction of the expression of firefly luciferase in the tester strains and BL reaction are successively carried out by filling the channels on another PDMS layer with samples containing inducer (genotoxic substance) and then adenosine triphosphate/luciferin mixture, respectively. BL emission from each of the wells can be monitored by using a charge-coupled device camera to obtain an overall picture of the chip. The on-chip format based on a three-dimensional microfluidic network provides a combinatorial bioassay for multiple samples with multiple tester strains in a simple chip assembly. Thus, the presented method could be applied not only to various microbial sensing applications but also to other (bio)chemical analyses.

  15. Opportunistic Carrier Sensing for Energy-Efficient Information Retrieval in Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhao Qing

    2005-01-01

    Full Text Available We consider distributed information retrieval for sensor networks with cluster heads or mobile access points. The performance metric used in the design is energy efficiency defined as the ratio of the average number of bits reliably retrieved by the access point to the total amount of energy consumed. A distributed opportunistic transmission protocol is proposed using a combination of carrier sensing and backoff strategy that incorporates channel state information (CSI of individual sensors. By selecting a set of sensors with the best channel states to transmit, the proposed protocol achieves the upper bound on energy efficiency when the signal propagation delay is negligible. For networks with substantial propagation delays, a backoff function optimized for energy efficiency is proposed. The design of this backoff function utilizes properties of extreme statistics and is shown to have mild performance loss in practical scenarios. We also demonstrate that opportunistic strategies that use CSI may not be optimal when channel acquisition at individual sensors consumes substantial energy. We show further that there is an optimal sensor density for which the opportunistic information retrieval is the most energy efficient. This observation leads to the design of the optimal sensor duty cycle.

  16. Urban Land Use and Land Cover Classification Using Remotely Sensed SAR Data through Deep Belief Networks

    Directory of Open Access Journals (Sweden)

    Qi Lv

    2015-01-01

    Full Text Available Land use and land cover (LULC mapping in urban areas is one of the core applications in remote sensing, and it plays an important role in modern urban planning and management. Deep learning is springing up in the field of machine learning recently. By mimicking the hierarchical structure of the human brain, deep learning can gradually extract features from lower level to higher level. The Deep Belief Networks (DBN model is a widely investigated and deployed deep learning architecture. It combines the advantages of unsupervised and supervised learning and can archive good classification performance. This study proposes a classification approach based on the DBN model for detailed urban mapping using polarimetric synthetic aperture radar (PolSAR data. Through the DBN model, effective contextual mapping features can be automatically extracted from the PolSAR data to improve the classification performance. Two-date high-resolution RADARSAT-2 PolSAR data over the Great Toronto Area were used for evaluation. Comparisons with the support vector machine (SVM, conventional neural networks (NN, and stochastic Expectation-Maximization (SEM were conducted to assess the potential of the DBN-based classification approach. Experimental results show that the DBN-based method outperforms three other approaches and produces homogenous mapping results with preserved shape details.

  17. Androgynous, Reconfigurable Closed Loop Feedback Controlled Low Impact Docking System With Load Sensing Electromagnetic Capture Ring

    Science.gov (United States)

    Lewis, James L. (Inventor); Carroll, Monty B. (Inventor); Morales, Ray H. (Inventor); Le, Thang D. (Inventor)

    2002-01-01

    The present invention relates to a fully androgynous, reconfigurable closed loop feedback controlled low impact docking system with load sensing electromagnetic capture ring. The docking system of the present invention preferably comprises two Docking- assemblies, each docking assembly comprising a load sensing ring having an outer face, one of more electromagnets, one or more load cells coupled to said load sensing ring. The docking assembly further comprises a plurality of actuator arms coupled to said load sensing ring and capable of dynamically adjusting the orientation of said load sensing ring and a reconfigurable closed loop control system capable of analyzing signals originating from said plurality of load cells and of outputting real time control for each of the actuators. The docking assembly of the present invention incorporates an active load sensing system to automatically dynamically adjust the load sensing ring during capture instead of requiring significant force to push and realign the ring.

  18. Locomotive monitoring system using wireless sensor networks

    CSIR Research Space (South Africa)

    Croucamp, PL

    2014-07-01

    Full Text Available Conference on Industrial Informatics (INDIN), 27-30 July 2014 Locomotive monitoring system using wireless sensor networks P. L. Croucamp1, S. Rimer1 and C. Kruger2 1Department of Electrical and Electronic Engineering University of Johannesburg... Johannesburg, South Africa Email: suvendic@uj.ac.za 2Advanced Sensor Networks, Meraka. CSIR Pretoria, South Africa Email: ckruger1@csir.co.za Abstract Theft of cables used for powering a locomotive not only stops the train from functioning but also...

  19. A Knowledge Management System Using Bayesian Networks

    Science.gov (United States)

    Ribino, Patrizia; Oliveri, Antonio; Re, Giuseppe Lo; Gaglio, Salvatore

    In today's world, decision support and knowledge management processes are strategic and interdependent activities in many organizations. The companies' interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. This paper proposes a Knowledge Management System based on Bayesian networks. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and a Decision Support system to share documents and to plan how to best use firms' knowledge.

  20. Reaction networks and kinetics of biochemical systems.

    Science.gov (United States)

    Arceo, Carlene Perpetua P; Jose, Editha C; Lao, Angelyn R; Mendoza, Eduardo R

    2017-01-01

    This paper further develops the connection between Chemical Reaction Network Theory (CRNT) and Biochemical Systems Theory (BST) that we recently introduced [1]. We first use algebraic properties of kinetic sets to study the set of complex factorizable kinetics CFK(N) on a CRN, which shares many characteristics with its subset of mass action kinetics. In particular, we extend the Theorem of Feinberg-Horn [9] on the coincidence of the kinetic and stoichiometric subsets of a mass action system to CF kinetics, using the concept of span surjectivity. We also introduce the branching type of a network, which determines the availability of kinetics on it and allows us to characterize the networks for which all kinetics are complex factorizable: A "Kinetics Landscape" provides an overview of kinetics sets, their algebraic properties and containment relationships. We then apply our results and those (of other CRNT researchers) reviewed in [1] to fifteen BST models of complex biological systems and discover novel network and kinetic properties that so far have not been widely studied in CRNT. In our view, these findings show an important benefit of connecting CRNT and BST modeling efforts. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    DEFF Research Database (Denmark)

    Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

    2010-01-01

    BACKGROUND: Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different......-sensing and metabolic regulatory signal transduction pathways (STP) operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs...

  2. Radar sensing via a Micro-UAV-borne system

    Science.gov (United States)

    Catapano, Ilaria; Ludeno, Giovanni; Gennarelli, Gianluca; Soldovieri, Francesco; Rodi Vetrella, Amedeo; Fasano, Giancarmine

    2017-04-01

    In recent years, the miniaturization of flight control systems and payloads has contributed to a fast and widespread diffusion of micro-UAV (Unmanned Aircraft Vehicle). While micro-UAV can be a powerful tool in several civil applications such as environmental monitoring and surveillance, unleashing their full potential for societal benefits requires augmenting their sensing capability beyond the realm of active/passive optical sensors [1]. In this frame, radar systems are drawing attention since they allow performing missions in all-weather and day/night conditions and, thanks to the microwave ability to penetrate opaque media, they enable the detection and localization not only of surface objects but also of sub-surface/hidden targets. However, micro-UAV-borne radar imaging represents still a new frontier, since it is much more than a matter of technology miniaturization or payload installation, which can take advantage of the newly developed ultralight systems. Indeed, micro-UAV-borne radar imaging entails scientific challenges in terms of electromagnetic modeling and knowledge of flight dynamics and control. As a consequence, despite Synthetic Aperture Radar (SAR) imaging is a traditional remote sensing tool, its adaptation to micro-UAV is an open issue and so far only few case studies concerning the integration of SAR and UAV technologies have been reported worldwide [2]. In addition, only early results concerning subsurface imaging by means of an UAV-mounted radar are available [3]. As a contribution to radar imaging via autonomous micro-UAV, this communication presents a proof-of-concept experiment. This experiment represents the first step towards the development of a general methodological approach that exploits expertise about (sub-)surface imaging and aerospace systems with the aim to provide high-resolution images of the surveyed scene. In details, at the conference, we will present the results of a flight campaign carried out by using a single radar

  3. Situational Awareness of Network System Roles (SANSR)

    Energy Technology Data Exchange (ETDEWEB)

    Huffer, Kelly M [ORNL; Reed, Joel W [ORNL

    2017-01-01

    In a large enterprise it is difficult for cyber security analysts to know what services and roles every machine on the network is performing (e.g., file server, domain name server, email server). Using network flow data, already collected by most enterprises, we developed a proof-of-concept tool that discovers the roles of a system using both clustering and categorization techniques. The tool's role information would allow cyber analysts to detect consequential changes in the network, initiate incident response plans, and optimize their security posture. The results of this proof-of-concept tool proved to be quite accurate on three real data sets. We will present the algorithms used in the tool, describe the results of preliminary testing, provide visualizations of the results, and discuss areas for future work. Without this kind of situational awareness, cyber analysts cannot quickly diagnose an attack or prioritize remedial actions.

  4. Architecture for networked electronic patient record systems.

    Science.gov (United States)

    Takeda, H; Matsumura, Y; Kuwata, S; Nakano, H; Sakamoto, N; Yamamoto, R

    2000-11-01

    There have been two major approaches to the development of networked electronic patient record (EPR) architecture. One uses object-oriented methodologies for constructing the model, which include the GEHR project, Synapses, HL7 RIM and so on. The second approach uses document-oriented methodologies, as applied in examples of HL7 PRA. It is practically beneficial to take the advantages of both approaches and to add solution technologies for network security such as PKI. In recognition of the similarity with electronic commerce, a certificate authority as a trusted third party will be organised for establishing networked EPR system. This paper describes a Japanese functional model that has been developed, and proposes a document-object-oriented architecture, which is-compared with other existing models.

  5. An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

    Science.gov (United States)

    Taboun, Mohammed S; Brennan, Robert W

    2017-09-14

    With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

  6. An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Mohammed S. Taboun

    2017-09-01

    Full Text Available With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

  7. A Tagless Indoor Localization System Based on Capacitive Sensing Technology

    Directory of Open Access Journals (Sweden)

    Alireza Ramezani Akhmareh

    2016-09-01

    Full Text Available Accurate indoor person localization is essential for several services, such as assisted living. We introduce a tagless indoor person localization system based on capacitive sensing and localization algorithms that can determine the location with less than 0.2 m average error in a 3 m × 3 m room and has recall and precision better than 70%. We also discuss the effects of various noise types on the measurements and ways to reduce them using filters suitable for on-sensor implementation to lower communication energy consumption. We also compare the performance of several standard localization algorithms in terms of localization error, recall, precision, and accuracy of detection of the movement trajectory.

  8. A Tagless Indoor Localization System Based on Capacitive Sensing Technology

    Science.gov (United States)

    Ramezani Akhmareh, Alireza; Lazarescu, Mihai Teodor; Bin Tariq, Osama; Lavagno, Luciano

    2016-01-01

    Accurate indoor person localization is essential for several services, such as assisted living. We introduce a tagless indoor person localization system based on capacitive sensing and localization algorithms that can determine the location with less than 0.2 m average error in a 3 m × 3 m room and has recall and precision better than 70%. We also discuss the effects of various noise types on the measurements and ways to reduce them using filters suitable for on-sensor implementation to lower communication energy consumption. We also compare the performance of several standard localization algorithms in terms of localization error, recall, precision, and accuracy of detection of the movement trajectory. PMID:27618049

  9. Gas Main Sensor and Communications Network System

    Energy Technology Data Exchange (ETDEWEB)

    Hagen Schempf

    2006-05-31

    Automatika, Inc. was contracted by the Department of Energy (DOE) and with co-funding from the Northeast Gas Association (NGA), to develop an in-pipe natural gas prototype measurement and wireless communications system for assessing and monitoring distribution networks. This projected was completed in April 2006, and culminated in the installation of more than 2 dozen GasNet nodes in both low- and high-pressure cast-iron and steel mains owned by multiple utilities in the northeastern US. Utilities are currently logging data (off-line) and monitoring data in real time from single and multiple networked sensors over cellular networks and collecting data using wireless bluetooth PDA systems. The system was designed to be modular, using in-pipe sensor-wands capable of measuring, flow, pressure, temperature, water-content and vibration. Internal antennae allowed for the use of the pipe-internals as a waveguide for setting up a sensor network to collect data from multiple nodes simultaneously. Sensor nodes were designed to be installed with low- and no-blow techniques and tools. Using a multi-drop bus technique with a custom protocol, all electronics were designed to be buriable and allow for on-board data-collection (SD-card), wireless relaying and cellular network forwarding. Installation options afforded by the design included direct-burial and external polemounted variants. Power was provided by one or more batteries, direct AC-power (Class I Div.2) and solar-array. The utilities are currently in a data-collection phase and intend to use the collected (and processed) data to make capital improvement decisions, compare it to Stoner model predictions and evaluate the use of such a system for future expansion, technology-improvement and commercialization starting later in 2006.

  10. Structural systems identification of genetic regulatory networks.

    Science.gov (United States)

    Xiong, Hao; Choe, Yoonsuck

    2008-02-15

    Reverse engineering of genetic regulatory networks from experimental data is the first step toward the modeling of genetic networks. Linear state-space models, also known as linear dynamical models, have been applied to model genetic networks from gene expression time series data, but existing works have not taken into account available structural information. Without structural constraints, estimated models may contradict biological knowledge and estimation methods may over-fit. In this report, we extended expectation-maximization (EM) algorithms to incorporate prior network structure and to estimate genetic regulatory networks that can track and predict gene expression profiles. We applied our method to synthetic data and to SOS data and showed that our method significantly outperforms the regular EM without structural constraints. The Matlab code is available upon request and the SOS data can be downloaded from http://www.weizmann.ac.il/mcb/UriAlon/Papers/SOSData/, courtesy of Uri Alon. Zak's data is available from his website, http://www.che.udel.edu/systems/people/zak.

  11. A portable fluorescent sensing system using multiple LEDs

    Science.gov (United States)

    Shin, Young-Ho; Barnett, Jonathan Z.; Gutierrez-Wing, M. Teresa; Rusch, Kelly A.; Choi, Jin-Woo

    2017-02-01

    This paper presents a portable fluorescent sensing system that utilizes different light emitting diode (LED) excitation lights for multiple target detection. In order to identify different analytes, three different wavelengths (385 nm, 448 nm, and 590 nm) of excitation light emitting diodes were used to selectively stimulate the target analytes. A highly sensitive silicon photomultiplier (SiPM) was used to detect corresponding fluorescent signals from each analyte. Based on the unique fluorescent response of each analyte, it is possible to simultaneously differentiate one analyte from the other in a mixture of target analytes. A portable system was designed and fabricated consisting of a display module, battery, data storage card, and sample loading tray into a compact 3D-printed jig. The portable sensor system was demonstrated for quantification and differentiation of microalgae (Chlorella vulgaris) and cyanobacteria (Spirulina) by measuring fluorescent responses of chlorophyll a in microalgae and phycocyanin in cyanobacteria. Obtained results suggest that the developed portable sensor system could be used as a generic fluorescence sensor platform for on-site detection of multiple analytes of interest.

  12. GAS MAIN SENSOR AND COMMUNICATIONS NETWORK SYSTEM

    Energy Technology Data Exchange (ETDEWEB)

    Hagen Schempf

    2004-09-30

    Automatika, Inc. was contracted by the Department of Energy (DOE) and with co-funding from the New York Gas Group (NYGAS), to develop an in-pipe natural gas prototype measurement and wireless communications system for assessing and monitoring distribution networks. In Phase II of this three-phase program, an improved prototype system was built for low-pressure cast-iron and high-pressure steel (including a no-blow installation system) mains and tested in a serial-network configuration in a live network in Long Island with the support of Keyspan Energy, Inc. The experiment was carried out in several open-hole excavations over a multi-day period. The prototype units (3 total) combined sensors capable of monitoring pressure, flow, humidity, temperature and vibration, which were sampled and combined in data-packages in an in-pipe master-repeater-slave configuration in serial or ladder-network arrangements. It was verified that the system was capable of performing all data-sampling, data-storage and collection as expected, yielding interesting results as to flow-dynamics and vibration-detection. Wireless in-pipe communications were shown to be feasible and the system was demonstrated to run off in-ground battery- and above-ground solar power. The remote datalogger access and storage-card features were demonstrated and used to log and post-process system data. Real-time data-display on an updated Phase-I GUI was used for in-field demonstration and troubleshooting.

  13. System markets: Indirect network effects in action, or inaction?

    NARCIS (Netherlands)

    J.L.G. Binken (Jeroen)

    2010-01-01

    textabstractIn this dissertation, I empirically examine system markets up close. More specifically I examine indirect network effects, both demand-side and supply-side indirect network effects. Indirect network effects are the source of positive feedback in system markets, or so network effect

  14. A Networked Interactive Meteorological Modeling and Sensing System

    Science.gov (United States)

    2007-06-01

    Doppler lidar. l l ti t l it l i f t l li . 13 June 2007 8 Dual lidar winds south of OKC, July 2003 ARL Lidar ASU Lidar 13 June 2007 9... modular design allows the flexibility to handle the addition, subtraction, or replacement/upgrade of sensors, models, or other software with

  15. A biochemical network can control formation of a synthetic material by sensing numerous specific stimuli.

    Science.gov (United States)

    Hun Yeon, Ju; Chan, Karen Y T; Wong, Ting-Chia; Chan, Kelvin; Sutherland, Michael R; Ismagilov, Rustem F; Pryzdial, Edward L G; Kastrup, Christian J

    2015-05-15

    Developing bio-compatible smart materials that assemble in response to environmental cues requires strategies that can discriminate multiple specific stimuli in a complex milieu. Synthetic materials have yet to achieve this level of sensitivity, which would emulate the highly evolved and tailored reaction networks of complex biological systems. Here we show that the output of a naturally occurring network can be replaced with a synthetic material. Exploiting the blood coagulation system as an exquisite biological sensor, the fibrin clot end-product was replaced with a synthetic material under the biological control of a precisely regulated cross-linking enzyme. The functions of the coagulation network remained intact when the material was incorporated. Clot-like polymerization was induced in indirect response to distinct small molecules, phospholipids, enzymes, cells, viruses, an inorganic solid, a polyphenol, a polysaccharide, and a membrane protein. This strategy demonstrates for the first time that an existing stimulus-responsive biological network can be used to control the formation of a synthetic material by diverse classes of physiological triggers.

  16. CMOS indoor light energy harvesting system for wireless sensing applications

    CERN Document Server

    Ferreira Carvalho, Carlos Manuel

    2016-01-01

    This book discusses in detail the CMOS implementation of energy harvesting.  The authors describe an integrated, indoor light energy harvesting system, based on a controller circuit that dynamically and automatically adjusts its operation to meet the actual light circumstances of the environment where the system is placed.  The system is intended to power a sensor node, enabling an autonomous wireless sensor network (WSN). Although designed to cope with indoor light levels, the system is also able to work with higher levels, making it an all-round light energy harvesting system.  The discussion includes experimental data obtained from an integrated manufactured prototype, which in conjunction with a photovoltaic (PV) cell, serves as a proof of concept of the desired energy harvesting system.  ·         Discusses several energy sources which can be used to power energy harvesting systems and includes an overview of PV cell technologies  ·         Includes an introduction to voltage step-...

  17. System/360 Computer Assisted Network Scheduling (CANS) System

    Science.gov (United States)

    Brewer, A. C.

    1972-01-01

    Computer assisted scheduling techniques that produce conflict-free and efficient schedules have been developed and implemented to meet needs of the Manned Space Flight Network. CANS system provides effective management of resources in complex scheduling environment. System is automated resource scheduling, controlling, planning, information storage and retrieval tool.

  18. Analysis and design of networked control systems

    CERN Document Server

    You, Keyou; Xie, Lihua

    2015-01-01

    This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: ·         minimum data rate for stabilization of linear systems over noisy channels; ·         minimum network requirement for stabilization of linear systems over fading channels; and ·         stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are de...

  19. Conceptualizing and Advancing Research Networking Systems.

    Science.gov (United States)

    Schleyer, Titus; Butler, Brian S; Song, Mei; Spallek, Heiko

    2012-03-01

    Science in general, and biomedical research in particular, is becoming more collaborative. As a result, collaboration with the right individuals, teams, and institutions is increasingly crucial for scientific progress. We propose Research Networking Systems (RNS) as a new type of system designed to help scientists identify and choose collaborators, and suggest a corresponding research agenda. The research agenda covers four areas: foundations, presentation, architecture, and evaluation. Foundations includes project-, institution- and discipline-specific motivational factors; the role of social networks; and impression formation based on information beyond expertise and interests. Presentation addresses representing expertise in a comprehensive and up-to-date manner; the role of controlled vocabularies and folksonomies; the tension between seekers' need for comprehensive information and potential collaborators' desire to control how they are seen by others; and the need to support serendipitous discovery of collaborative opportunities. Architecture considers aggregation and synthesis of information from multiple sources, social system interoperability, and integration with the user's primary work context. Lastly, evaluation focuses on assessment of collaboration decisions, measurement of user-specific costs and benefits, and how the large-scale impact of RNS could be evaluated with longitudinal and naturalistic methods. We hope that this article stimulates the human-computer interaction, computer-supported cooperative work, and related communities to pursue a broad and comprehensive agenda for developing research networking systems.

  20. Conceptualizing and Advancing Research Networking Systems

    Science.gov (United States)

    SCHLEYER, TITUS; BUTLER, BRIAN S.; SONG, MEI; SPALLEK, HEIKO

    2013-01-01

    Science in general, and biomedical research in particular, is becoming more collaborative. As a result, collaboration with the right individuals, teams, and institutions is increasingly crucial for scientific progress. We propose Research Networking Systems (RNS) as a new type of system designed to help scientists identify and choose collaborators, and suggest a corresponding research agenda. The research agenda covers four areas: foundations, presentation, architecture, and evaluation. Foundations includes project-, institution- and discipline-specific motivational factors; the role of social networks; and impression formation based on information beyond expertise and interests. Presentation addresses representing expertise in a comprehensive and up-to-date manner; the role of controlled vocabularies and folksonomies; the tension between seekers’ need for comprehensive information and potential collaborators’ desire to control how they are seen by others; and the need to support serendipitous discovery of collaborative opportunities. Architecture considers aggregation and synthesis of information from multiple sources, social system interoperability, and integration with the user’s primary work context. Lastly, evaluation focuses on assessment of collaboration decisions, measurement of user-specific costs and benefits, and how the large-scale impact of RNS could be evaluated with longitudinal and naturalistic methods. We hope that this article stimulates the human-computer interaction, computer-supported cooperative work, and related communities to pursue a broad and comprehensive agenda for developing research networking systems. PMID:24376309

  1. Smart Sensing System for the Prognostic Monitoring of Bone Health

    KAUST Repository

    Afsarimanesh, Nasrin

    2016-06-24

    The objective of this paper is to report a novel non-invasive, real-time, and label-free smart assay technique for the prognostic detection of bone loss by electrochemical impedance spectroscopy (EIS). The proposed system incorporated an antibody-antigen-based sensor functionalization to induce selectivity for the C-terminal telopeptide type one collagen (CTx-I) molecules—a bone loss biomarker. Streptavidin agarose was immobilized on the sensing area of a silicon substrate-based planar sensor, patterned with gold interdigital electrodes, to capture the antibody-antigen complex. Calibration experiments were conducted with various known CTx-I concentrations in a buffer solution to obtain a reference curve that was used to quantify the concentration of an analyte in the unknown serum samples. Multivariate chemometric analyses were done to determine the performance viability of the developed system. The analyses suggested that a frequency of 710 Hz is the most discriminating regarding the system sensitivity. A detection limit of 0.147 ng/mL was achieved for the proposed sensor and the corresponding reference curve was linear in the range of 0.147 ng/mL to 2.669 ng/mL. Two sheep blood samples were tested by the developed technique and the results were validated using enzyme-linked immunosorbent assay (ELISA). The results from the proposed technique match those from the ELISA.

  2. Smart Sensing System for the Prognostic Monitoring of Bone Health

    Directory of Open Access Journals (Sweden)

    Nasrin Afsarimanesh

    2016-06-01

    Full Text Available The objective of this paper is to report a novel non-invasive, real-time, and label-free smart assay technique for the prognostic detection of bone loss by electrochemical impedance spectroscopy (EIS. The proposed system incorporated an antibody-antigen-based sensor functionalization to induce selectivity for the C-terminal telopeptide type one collagen (CTx-I molecules—a bone loss biomarker. Streptavidin agarose was immobilized on the sensing area of a silicon substrate-based planar sensor, patterned with gold interdigital electrodes, to capture the antibody-antigen complex. Calibration experiments were conducted with various known CTx-I concentrations in a buffer solution to obtain a reference curve that was used to quantify the concentration of an analyte in the unknown serum samples. Multivariate chemometric analyses were done to determine the performance viability of the developed system. The analyses suggested that a frequency of 710 Hz is the most discriminating regarding the system sensitivity. A detection limit of 0.147 ng/mL was achieved for the proposed sensor and the corresponding reference curve was linear in the range of 0.147 ng/mL to 2.669 ng/mL. Two sheep blood samples were tested by the developed technique and the results were validated using enzyme-linked immunosorbent assay (ELISA. The results from the proposed technique match those from the ELISA.

  3. A modern trans-ionospheric propagation sensing system

    Science.gov (United States)

    Bishop, G. J.; Klobuchar, J. A.; Ronn, A. E.; Bedard, M. G.

    1989-09-01

    One of the most important potential problems with modern military systems which utilize spacecraft is the effect of the ionosphere on the radio signals which pass to and from the spacecraft. Such systems include active communications and navigation satellites as well as both ground-based and potential space-based ranging systems. The major effects the ionosphere can have on such systems are the additional time delay the electrons in the earth's ionosphere add to the free space path delay, the short term rate of change of this additional delay, amplitude scintillation or fading effects the signal encounters due to irregularities in the ionosphere, and Faraday rotation of linearly polarized radio waves transmitted through the ionosphere. While some of these effects were studied adequate models of these effects on military systems still do not exist. A modern trans-ionospheric sensing system, called TISS, is being procured which will consist of a number of stations located throughout the world, making real time measurements of the time delay of the ionosphere, and its rate of change, as well as amplitude scintillation, along several different viewing directions from each station. These trans-ionospheric measurements will be used to allow models, which currently provide only monthly propagation parameters. The real-time specifications of these parameters can then be used as decision aids in both the tactical and the strategic military environments. The TISS will include first order artificial intelligence design to aid in gathering the most appropriate sets of available real-time trans-ionospheric propagation data, and will communicate these data sets to the Air Weather Service Forecasting Center where they will be tailored to specific military customers.

  4. Systems biology of plant molecular networks: from networks to models

    NARCIS (Netherlands)

    Valentim, F.L.

    2015-01-01

    Developmental processes are controlled by regulatory networks (GRNs), which are tightly coordinated networks of transcription factors (TFs) that activate and repress gene expression within a spatial and temporal context. In Arabidopsis thaliana, the key components and network structures of the GRNs

  5. A Global Landslide Nowcasting System using Remotely Sensed Information

    Science.gov (United States)

    Kirschbaum, Dalia; Stanely, Thomas

    2017-04-01

    A global Landslide Hazard Assessment model for Situational Awareness (LHASA) has been developed that combines susceptibility information with satellite-based precipitation to provide an indication of potential landslide activity at the global scale every 30 minutes. This model utilizes a 1-km global susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. A multi-satellite dataset from the Global Precipitation Measurement (GPM) mission is used to identify the current and antecedent rainfall conditions from the past 7 days. When both rainfall and susceptibility are high, a "nowcast" is issued to indicate areas where a landslide may be likely. The global LHASA model is currently being run in near real-time every 30 minutes and the outputs are available in several different formats at https://pmm.nasa.gov/precip-apps. This talk outlines the LHASA system, discusses the performance metrics and potential applications of the LHASA system.

  6. Combining Observations of a Digital Camera Network, Satellite Remote Sensing, and Micrometeorology for Improved Understanding of Forest Phenology

    Science.gov (United States)

    Braswell, B. H.; Richardson, A. D.; Ollinger, S. V.; Friedl, M. A.; Hollinger, D. Y.

    2009-04-01

    The observed phenological behavior of terrestrial ecosystems is a result of the seasonality of climatic forcing superposed with physical and biological responses of the plant-soil system. Biogeochemical models that represent rapid time scale phenomena well tend to simulate interannual variability and trends in productivity more accurately when phenology is prescribed, suggesting a gap in our understanding of the underlying processes or a generic means to represent their emergent behavior. Specifically, questions surround environmental triggers of leaf turnover, the relative importance of internal nutrient cycling, and the potential for generalization across broadly defined biome types. Satellite observations provide a spatially comprehensive record of the seasonality of land vegetation characteristics, but are most valuable when combined with direct measurements of ecosystem state. Time series of meteorology and fluxes (e.g. from eddy covariance tower sites) are one such data source, providing a valuable means to estimate productivity, but not a view of the state of the vegetation canopy. We have begun to assemble a network of digital cameras ('webcams') by deploying camera systems at existing research sites, and by harvesting imagery from collaborating sites and institutions. There are currently 80 cameras in the network, 17 of which are 'core' locations that are located at flux towers or field stations. We process and analyze the camera imagery as remote sensing data, utilizing the red, green, and blue, channels as a means to stratify the scenes and quantify relative vegetation 'greenness'. Our initial analyses have shown that these images do yield hourly-to-daily information about the seasonal cycle of vegetation state as compared both to fluxes and satellite indices. This presentation will summarize the current findings of the project, specifically focusing on (a) insights into controls on interannual variability at sites with long records (2000-present), and

  7. Pathways, Networks and Systems Medicine Conferences

    Energy Technology Data Exchange (ETDEWEB)

    Nadeau, Joseph H. [Pacific Northwest Research Institute

    2013-11-25

    The 6th Pathways, Networks and Systems Medicine Conference was held at the Minoa Palace Conference Center, Chania, Crete, Greece (16-21 June 2008). The Organizing Committee was composed of Joe Nadeau (CWRU, Cleveland), Rudi Balling (German Research Centre, Brauschweig), David Galas (Institute for Systems Biology, Seattle), Lee Hood (Institute for Systems Biology, Seattle), Diane Isonaka (Seattle), Fotis Kafatos (Imperial College, London), John Lambris (Univ. Pennsylvania, Philadelphia),Harris Lewin (Univ. of Indiana, Urbana-Champaign), Edison Liu (Genome Institute of Singapore, Singapore), and Shankar Subramaniam (Univ. California, San Diego). A total of 101 individuals from 21 countries participated in the conference: USA (48), Canada (5), France (5), Austria (4), Germany (3), Italy (3), UK (3), Greece (2), New Zealand (2), Singapore (2), Argentina (1), Australia (1), Cuba (1), Denmark (1), Japan (1), Mexico (1), Netherlands (1), Spain (1), Sweden (1), Switzerland (1). With respect to speakers, 29 were established faculty members and 13 were graduate students or postdoctoral fellows. With respect to gender representation, among speakers, 13 were female and 28 were male, and among all participants 43 were female and 58 were male. Program these included the following topics: Cancer Pathways and Networks (Day 1), Metabolic Disease Networks (Day 2), Day 3 ? Organs, Pathways and Stem Cells (Day 3), and Day 4 ? Inflammation, Immunity, Microbes and the Environment (Day 4). Proceedings of the Conference were not published.

  8. The network management expert system prototype for Sun Workstations

    Science.gov (United States)

    Leigh, Albert

    1990-01-01

    Networking has become one of the fastest growing areas in the computer industry. The emergence of distributed workstations make networking more popular because they need to have connectivity between themselves as well as with other computer systems to share information and system resources. Making the networks more efficient and expandable by selecting network services and devices that fit to one's need is vital to achieve reliability and fast throughput. Networks are dynamically changing and growing at a rate that outpaces the available human resources. Therefore, there is a need to multiply the expertise rapidly rather than employing more network managers. In addition, setting up and maintaining networks by following the manuals can be tedious and cumbersome even for an experienced network manager. This prototype expert system was developed to experiment on Sun Workstations to assist system and network managers in selecting and configurating network services.

  9. Indoor Positioning System Using Depth Maps and Wireless Networks

    Directory of Open Access Journals (Sweden)

    Jaime Duque Domingo

    2016-01-01

    Full Text Available This work presents a new Indoor Positioning System (IPS based on the combination of WiFi Positioning System (WPS and depth maps, for estimating the location of people. The combination of both technologies improves the efficiency of existing methods, based uniquely on wireless positioning techniques. While other positioning systems force users to wear special devices, the system proposed in this paper just requires the use of smartphones, besides the installation of RGB-D sensors in the sensing area. Furthermore, the system is not intrusive, being not necessary to know people’s identity. The paper exposes the method developed for putting together and exploiting both types of sensory information with positioning purposes: the measurements of the level of the signal received from different access points (APs of the wireless network and the depth maps provided by the RGB-D cameras. The obtained results show a significant improvement in terms of positioning with respect to common WiFi-based systems.

  10. Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review.

    Science.gov (United States)

    Zou, Liang; Ge, Chang; Wang, Z Jane; Cretu, Edmond; Li, Xiaoou

    2017-11-17

    During the last decades, smart tactile sensing systems based on different sensing techniques have been developed due to their high potential in industry and biomedical engineering. However, smart tactile sensing technologies and systems are still in their infancy, as many technological and system issues remain unresolved and require strong interdisciplinary efforts to address them. This paper provides an overview of smart tactile sensing systems, with a focus on signal processing technologies used to interpret the measured information from tactile sensors and/or sensors for other sensory modalities. The tactile sensing transduction and principles, fabrication and structures are also discussed with their merits and demerits. Finally, the challenges that tactile sensing technology needs to overcome are highlighted.

  11. Network resource control for grid workflow management systems

    NARCIS (Netherlands)

    Strijkers, R.J.; Cristea, M.; Korkhov, V.; Marchal, D.; Belloum, A.; Laat, C.de; Meijer, R.J.

    2010-01-01

    Grid workflow management systems automate the orchestration of scientific applications with large computational and data processing needs, but lack control over network resources. Consequently, the management system cannot prevent multiple communication intensive applications to compete for network

  12. Acetone sensing of multi-networked WO3-NiO core-shell nanorod sensors

    Science.gov (United States)

    Choi, Seungbok; Lee, Jae Kyung; Lee, Woo Seok; Lee, Chongmu; Lee, Wan In

    2017-10-01

    WO3-NiO core-shell nanorods were synthesized by thermal evaporation of a mixture of WO3 and graphite powders and immersion of the synthesized WO3 nanorods in an 20 mM of nickel(II) acetate tetrahydrate (Ni(OCOCH3)2·4H2O) solution followed by UV irradiation and annealing. Subsequently, multi-networked nanorod sensors were fabricated by connecting these nanostructures with electrodes. The sensing properties of pristine WO3 nanorod and WO3-NiO core-shell nanorod sensors toward acetone were examined. Subsequently, multi-networked nanorod sensors were fabricated by connecting these nanostructures with electrodes. The WO3-NiO core-shell nanorod sensor exhibited a stronger response to acetone gas and shorter response/recovery times than the pristine WO3 nanorod sensor. The pristine WO3 nanorods showed responses of approximately 1.36 to 200 ppm of CH3COCH3 at 300 °C. On the other hand, the WO3-NiO core-shell nanorods showed responses of 4.4 to the same concentration of CH3COCH3 at the same temperature. The core-shell nanorods exhibited response and recovery times of 51 s and 59 s, respectively for 200 ppm of CH3COCH3. On the other hand, the pristine WO3 nanorods exhibited response and recovery times of 51 s and 59 s, respectively, for the same concentration of CH3COCH3. NiO coating enhanced the selectivity of the WO3 nanorods for acetone as well as the sensitivity of the WO3 nanorods. The underlying mechanism of the enhanced response of the WO3-NiO core-shell nanorod sensor is also discussed in detail.

  13. Monitoring of Regional Land Surface Temperature in city by Wireless Sensing Network

    Science.gov (United States)

    Wang, Y.; Jiang, H.; Jin, J.

    2015-12-01

    Land surface temperature (LST) is an important environmental factor. The precise monitoring data of LST can provide crucial support for further ecological researches such as the environment change and urban heat island. The Wireless Sensing Network (WSN) is a kind of modern information technology which integrates sensor technology, automatic control technology with data network transmission, storage, processing and analysis technology. As a new kind of data collection method, WSN is innovatively applied to monitor regional LST in different land cover types of city in this study. The LST data with high temporal resolution is obtained from temperature sensors of WSN. The land cover types of city are extracted from WorldView-II image with high resolution. The Southeast University Wuxi Branch campus and its surroundings which covers 2 km2 is chosen as the study area in Wuxi city, Jiangsu province, China. WSN is established to continuously monitor LST in real-time for one week. Then, the heterogeneous pattern of LST is investigated at a fine spatial and temporal scale based on different land cover types. The result shows LST of streets is higher than LST of campus in the daytime, but lower than LST of campus at night. The spatial heterogeneity of LST in the campus is not significant. This is because the number of vehicle was larger in the daytime than that at night, while the population of campus in day and night almost having little change. Notably, the influence of plant activities (e.g. photosynthesis and respiration) on LST can be detected by WSN. This study is a new attempt to monitor regional environment of city by WSN technology. Moreover, compared to traditional methods, WSN technology can improve the detection of LST with finer temporal and spatial resolution.

  14. Cascade Convolutional Neural Network Based on Transfer-Learning for Aircraft Detection on High-Resolution Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Bin Pan

    2017-01-01

    Full Text Available Aircraft detection from high-resolution remote sensing images is important for civil and military applications. Recently, detection methods based on deep learning have rapidly advanced. However, they require numerous samples to train the detection model and cannot be directly used to efficiently handle large-area remote sensing images. A weakly supervised learning method (WSLM can detect a target with few samples. However, it cannot extract an adequate number of features, and the detection accuracy requires improvement. We propose a cascade convolutional neural network (CCNN framework based on transfer-learning and geometric feature constraints (GFC for aircraft detection. It achieves high accuracy and efficient detection with relatively few samples. A high-accuracy detection model is first obtained using transfer-learning to fine-tune pretrained models with few samples. Then, a GFC region proposal filtering method improves detection efficiency. The CCNN framework completes the aircraft detection for large-area remote sensing images. The framework first-level network is an image classifier, which filters the entire image, excluding most areas with no aircraft. The second-level network is an object detector, which rapidly detects aircraft from the first-level network output. Compared with WSLM, detection accuracy increased by 3.66%, false detection decreased by 64%, and missed detection decreased by 23.1%.

  15. Pulsed acoustic vortex sensing system volume III: PAVSS operation and software documentation

    Science.gov (United States)

    1977-06-01

    Avco Corporation's Systems Division designed and developed an engineered Pulsed Acoustic Vortex Sensing System (PAVSS). This system is capable of real-time detection, tracking, recording, and graphic display of aircraft trailing vortices. This volume...

  16. Communication-Free Distributed Coverage for Networked Systems

    KAUST Repository

    Yazicioglu, A. Yasin

    2016-01-15

    In this paper, we present a communication-free algorithm for distributed coverage of an arbitrary network by a group of mobile agents with local sensing capabilities. The network is represented as a graph, and the agents are arbitrarily deployed on some nodes of the graph. Any node of the graph is covered if it is within the sensing range of at least one agent. The agents are mobile devices that aim to explore the graph and to optimize their locations in a decentralized fashion by relying only on their sensory inputs. We formulate this problem in a game theoretic setting and propose a communication-free learning algorithm for maximizing the coverage.

  17. Environmental Sensing of Aquatic Systems at the University of Geneva.

    Science.gov (United States)

    Bakker, Eric; Tercier-Waeber, Mary-Lou; Cherubini, Thomas; Crespi, Miquel Coll; Crespo, Gastón A; Cuartero, Maria; Afshar, Majid Ghahraman; Jarolimova, Zdenka; Jeanneret, Stéphane; Mongin, Sandrine; Néel, Bastien; Pankratova, Nadezda; Touilloux, Romain; Xie, Xiaojiang; Zhai, Jingying

    2014-11-01

    Aquatic environments are complex living systems where biological and chemical constituents change rapidly with time and space and may exhibit synergistic interactions. To understand these processes, the traditional approach based on a typically monthly collection of samples followed by laboratory analysis is not adequate. It must be replaced by high-resolution autonomous in situ detection approaches. In our group at the University of Geneva, we aim to develop and deploy chemical sensor probes to understand complex aquatic systems. Most research centers around electrochemical sensing approaches, which involves: stripping voltammetry at gel-coated microelectrode arrays for direct measurements of bioavailable essential or toxic trace metals; direct potentiometry for the measurement of nutrients and other species involved in the nitrogen and carbon cycles; online desalination for oceanic measurements; the development of robust measurement principles such as thin layer coulometry, and speciation analysis by tandem electrochemical detection with potentiometry and dynamic electrochemistry. These fundamental developments are combined with instrument design, both in-house and with external partners, and result in field deployments in partnership with environmental researchers in Switzerland and the European Union.

  18. Obtaining Remote-Sensing Reflectance from Multiple Instrument Systems

    Science.gov (United States)

    Freeman, Scott A.; Proctor, Christopher W.; Werdell, P. Jeremy

    2014-01-01

    Obtaining accurate in situ measurements of Apparent Optical Properties (AOPs) is critical to maintaining satellite data quality. One approach to ensure accuracy is to deploy several independent instruments to measure the same phenomenon. During a cruise in June 2012, off the lee coast of the island of Hawaii, repeated profiles were made with two separate radiometric systems, one from Satlantic, Inc. (Hyperpro) and the other from Biospherical Instruments, Inc. (C-Ops). The C-Ops is multispectral, while the Hyperpro is hyperspectral. Both measure above-water solar irradiance (E(sub s)), downwelling in-water irradiance (E(sub d)), and upwelling in-water radiance (L(sub u)). From these measurements remotely-sensed reflectance (R(sub rs))can be calculated and compared with satellite data. All instruments were calibrated shortly before use, and while differences are to be expected due to temporal changes and spectral weighting differences, these should be consistent and minimal. We explore these differences, and compare to data retrieved from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODIS Aqua) when available. We also examine data collection and processing protocols for these systems.

  19. Improving tsunami warning systems with remote sensing and geographical information system input.

    Science.gov (United States)

    Wang, Jin-Feng; Li, Lian-Fa

    2008-12-01

    An optimal and integrative tsunami warning system is introduced that takes full advantage of remote sensing and geographical information systems (GIS) in monitoring, forecasting, detection, loss evaluation, and relief management for tsunamis. Using the primary impact zone in Banda Aceh, Indonesia as the pilot area, we conducted three simulations that showed that while the December 26, 2004 Indian Ocean tsunami claimed about 300,000 lives because there was no tsunami warning system at all, it is possible that only about 15,000 lives could have been lost if the area had used a tsunami warning system like that currently in use in the Pacific Ocean. The simulations further calculated that the death toll could have been about 3,000 deaths if there had been a disaster system further optimized with full use of remote sensing and GIS, although the number of badly damaged or destroyed houses (29,545) could have likely remained unchanged.

  20. Sensing risk, fearing uncertainty: systems science approach to change

    Science.gov (United States)

    Janecka, Ivo P.

    2014-01-01

    Background: Medicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases. There are two attributes of systems science that are especially relevant to this research: One—it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two—it gives pre-eminence to sensory input capable to register, evaluate, and react to change. Materials/Methods: Public domain records of change, during the last 50 years, have been studied in the context of systems science, the dynamic systems model, and various cycles. Results/Conclusions: Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems' relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems. From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence. PMID:24744723