WorldWideScience

Sample records for low-cost real-time network

  1. A Low-Cost, Real-Time Network for Radiological Monitoring Around Nuclear Facilities

    International Nuclear Information System (INIS)

    Bertoldo, N A

    2004-01-01

    A low-cost, real-time radiological sensor network for emergency response has been developed and deployed at the Lawrence Livermore National Laboratory (LLNL). The Real-Time Radiological Area Monitoring (RTRAM) network is comprised of 16 Geiger-Mueller (GM) sensors positioned on the site perimeter to continuously monitor radiological conditions as part of LLNL's comprehensive environment/safety/health protection program. The RTRAM network sensor locations coincide with wind sector directions to provide thorough coverage of the one square mile site. These low-power sensors transmit measurement data back to a central command center (CCC) computer through the LLNL telecommunications infrastructure. Alarm conditions are identified by comparing current data to predetermined threshold parameters and are validated by comparison with plausible dispersion modeling scenarios and prevailing meteorological conditions. Emergency response personnel are notified of alarm conditions by automatic radio- and computer- based notifications. A secure intranet provides emergency response personnel with current condition assessment data that enable them to direct field response efforts remotely. This system provides a low-cost real-time radiation monitoring solution that is easily converted to incorporate both a hard-wired interior perimeter with strategically positioned wireless secondary and tertiary concentric remote locations. These wireless stations would be configured with solar voltaic panels that provide current to recharge batteries and power the sensors and radio transceivers. These platforms would supply data transmission at a range of up to 95 km from a single transceiver location. As necessary, using radio transceivers in repeater mode can extend the transmission range. The RTRAM network as it is presently configured at LLNL has proven to be a reliable system since initial deployment in August 2001 and maintains stability during inclement weather conditions. With the proposed

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

    Science.gov (United States)

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

    2018-03-01

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

  3. Low-cost real-time automatic wheel classification system

    Science.gov (United States)

    Shabestari, Behrouz N.; Miller, John W. V.; Wedding, Victoria

    1992-11-01

    This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

  4. Hard Real-Time Networking on Firewire

    NARCIS (Netherlands)

    Zhang, Yuchen; Orlic, Bojan; Visser, Peter; Broenink, Jan

    2005-01-01

    This paper investigates the possibility of using standard, low-cost, widely used FireWire as a new generation fieldbus medium for real-time distributed control applications. A real-time software subsys- tem, RT-FireWire was designed that can, in combination with Linux-based real-time operating

  5. Real-Time Network Management

    National Research Council Canada - National Science Library

    Riolo, Joseph

    1998-01-01

    .... According to our Phase I research, it is possible to collect data on the network and morph it into queuing models to produce information about the network and physical layers of nodes on a network...

  6. A low-cost test-bed for real-time landmark tracking

    Science.gov (United States)

    Csaszar, Ambrus; Hanan, Jay C.; Moreels, Pierre; Assad, Christopher

    2007-04-01

    A low-cost vehicle test-bed system was developed to iteratively test, refine and demonstrate navigation algorithms before attempting to transfer the algorithms to more advanced rover prototypes. The platform used here was a modified radio controlled (RC) car. A microcontroller board and onboard laptop computer allow for either autonomous or remote operation via a computer workstation. The sensors onboard the vehicle represent the types currently used on NASA-JPL rover prototypes. For dead-reckoning navigation, optical wheel encoders, a single axis gyroscope, and 2-axis accelerometer were used. An ultrasound ranger is available to calculate distance as a substitute for the stereo vision systems presently used on rovers. The prototype also carries a small laptop computer with a USB camera and wireless transmitter to send real time video to an off-board computer. A real-time user interface was implemented that combines an automatic image feature selector, tracking parameter controls, streaming video viewer, and user generated or autonomous driving commands. Using the test-bed, real-time landmark tracking was demonstrated by autonomously driving the vehicle through the JPL Mars yard. The algorithms tracked rocks as waypoints. This generated coordinates calculating relative motion and visually servoing to science targets. A limitation for the current system is serial computing-each additional landmark is tracked in order-but since each landmark is tracked independently, if transferred to appropriate parallel hardware, adding targets would not significantly diminish system speed.

  7. Low-cost guaranteed-throughput communication ring for real-time streaming MPSoCs

    NARCIS (Netherlands)

    Dekens, B.H.J.; Kurtin, Philip Sebastian; Bekooij, Marco Jan Gerrit; Smit, Gerardus Johannes Maria

    2013-01-01

    Connection-oriented guaranteed-throughput mesh-based networks on chip have been proposed as a replacement for buses in real-time embedded multiprocessor systems such as software defined radios. Even with attractive features like throughput and latency guarantees they are not always used because

  8. Unsynchronized scanning with a low-cost laser range finder for real-time range imaging

    Science.gov (United States)

    Hatipoglu, Isa; Nakhmani, Arie

    2017-06-01

    Range imaging plays an essential role in many fields: 3D modeling, robotics, heritage, agriculture, forestry, reverse engineering. One of the most popular range-measuring technologies is laser scanner due to its several advantages: long range, high precision, real-time measurement capabilities, and no dependence on lighting conditions. However, laser scanners are very costly. Their high cost prevents widespread use in applications. Due to the latest developments in technology, now, low-cost, reliable, faster, and light-weight 1D laser range finders (LRFs) are available. A low-cost 1D LRF with a scanning mechanism, providing the ability of laser beam steering for additional dimensions, enables to capture a depth map. In this work, we present an unsynchronized scanning with a low-cost LRF to decrease scanning period and reduce vibrations caused by stop-scan in synchronized scanning. Moreover, we developed an algorithm for alignment of unsynchronized raw data and proposed range image post-processing framework. The proposed technique enables to have a range imaging system for a fraction of the price of its counterparts. The results prove that the proposed method can fulfill the need for a low-cost laser scanning for range imaging for static environments because the most significant limitation of the method is the scanning period which is about 2 minutes for 55,000 range points (resolution of 250x220 image). In contrast, scanning the same image takes around 4 minutes in synchronized scanning. Once faster, longer range, and narrow beam LRFs are available, the methods proposed in this work can produce better results.

  9. Gun Launch System: efficient and low-cost means of research and real-time monitoring

    Science.gov (United States)

    Degtyarev, Alexander; Ventskovsky, Oleg; Korostelev, Oleg; Yakovenko, Peter; Kanevsky, Valery; Tselinko, Alexander

    2005-08-01

    The Gun Launch System with a reusable sub-orbital launch vehicle as a central element is proposed by a consortium of several Ukrainian high-tech companies as an effective, fast-response and low-cost means of research and real-time monitoring. The system is described in details, with the emphasis on its most important advantages. Multiple applications of the system are presented, including ones for the purposes of microgravity research; chemical, bacteriological and radiation monitoring and research of atmosphere and ionosphere; operational monitoring of natural and man-made disasters, as well as for some other areas of great practical interest. The current level of the system development is given, and the way ahead towards full system's implementation is prescribed.

  10. Portable low-cost flat panel detectors for real-time digital radiography

    Energy Technology Data Exchange (ETDEWEB)

    Iovea, Mihai; Neagu, Marian; Stefanescu, Bogdan; Mateiasi, Gabriela; Porosnicu, Ioana; Angheluta, Elena [Accent Pro 2000 S.R.L., Bucharest (Romania)

    2015-07-01

    The X-ray inspection is one of the most common used non-destructive testing methods in industry applications, but for the portable X-ray digital solution are not so many accessible, low-cost and versatile detection devices. The efficiency of a non-destructive X-ray portable device is represented by the quality of digital images, by its low acquisition time combined with a high resolution, in condition of low noise and at an affordable cost. The paper presents two X-ray portable imaging systems developed by us, suitable also for aerospace NDT applications, which are also very versatile for being easily adapted for other fields that requires mobile solutions. The first device described in the paper represent a portable large-size (210 mm X 550 mm) and high-resolution (27/54 microns) flat panel detector based on linear translation of a X-Ray TDI detector, destined for various components/parts real-time transmission measurements. The second system it is also a flat panel detectors, with a size of 510 mm X 610 mm, with the detector size from 0.2 mm until 1.5 mm, which can operate by applying the dual-energy method, very useful for discriminating materials by evaluating their Atomic effective number. The high resolution and low-cost of this flat-panels widens their applicability by covering large requirements, from identifying unwanted materials within a structure until detection of very thin cracks in complex components.

  11. Portable low-cost flat panel detectors for real-time digital radiography

    International Nuclear Information System (INIS)

    Iovea, Mihai; Neagu, Marian; Stefanescu, Bogdan; Mateiasi, Gabriela; Porosnicu, Ioana; Angheluta, Elena

    2015-01-01

    The X-ray inspection is one of the most common used non-destructive testing methods in industry applications, but for the portable X-ray digital solution are not so many accessible, low-cost and versatile detection devices. The efficiency of a non-destructive X-ray portable device is represented by the quality of digital images, by its low acquisition time combined with a high resolution, in condition of low noise and at an affordable cost. The paper presents two X-ray portable imaging systems developed by us, suitable also for aerospace NDT applications, which are also very versatile for being easily adapted for other fields that requires mobile solutions. The first device described in the paper represent a portable large-size (210 mm X 550 mm) and high-resolution (27/54 microns) flat panel detector based on linear translation of a X-Ray TDI detector, destined for various components/parts real-time transmission measurements. The second system it is also a flat panel detectors, with a size of 510 mm X 610 mm, with the detector size from 0.2 mm until 1.5 mm, which can operate by applying the dual-energy method, very useful for discriminating materials by evaluating their Atomic effective number. The high resolution and low-cost of this flat-panels widens their applicability by covering large requirements, from identifying unwanted materials within a structure until detection of very thin cracks in complex components.

  12. A Low-Cost Digital Microscope with Real-Time Fluorescent Imaging Capability.

    Science.gov (United States)

    Hasan, Md Mehedi; Alam, Mohammad Wajih; Wahid, Khan A; Miah, Sayem; Lukong, Kiven Erique

    2016-01-01

    This paper describes the development of a prototype of a low-cost digital fluorescent microscope built from commercial off-the-shelf (COTS) components. The prototype was tested to detect malignant tumor cells taken from a living organism in a preclinical setting. This experiment was accomplished by using Alexa Fluor 488 conjugate dye attached to the cancer cells. Our prototype utilizes a torch along with an excitation filter as a light source for fluorophore excitation, a dichroic mirror to reflect the excitation and pass the emitted green light from the sample under test and a barrier filter to permit only appropriate wavelength. The system is designed out of a microscope using its optical zooming property and an assembly of exciter filter, dichroic mirror and transmitter filter. The microscope is connected to a computer or laptop through universal serial bus (USB) that allows real-time transmission of captured florescence images; this also offers real-time control of the microscope. The designed system has comparable features of high-end commercial fluorescent microscopes while reducing cost, power, weight and size.

  13. A Low-Cost Digital Microscope with Real-Time Fluorescent Imaging Capability.

    Directory of Open Access Journals (Sweden)

    Md Mehedi Hasan

    Full Text Available This paper describes the development of a prototype of a low-cost digital fluorescent microscope built from commercial off-the-shelf (COTS components. The prototype was tested to detect malignant tumor cells taken from a living organism in a preclinical setting. This experiment was accomplished by using Alexa Fluor 488 conjugate dye attached to the cancer cells. Our prototype utilizes a torch along with an excitation filter as a light source for fluorophore excitation, a dichroic mirror to reflect the excitation and pass the emitted green light from the sample under test and a barrier filter to permit only appropriate wavelength. The system is designed out of a microscope using its optical zooming property and an assembly of exciter filter, dichroic mirror and transmitter filter. The microscope is connected to a computer or laptop through universal serial bus (USB that allows real-time transmission of captured florescence images; this also offers real-time control of the microscope. The designed system has comparable features of high-end commercial fluorescent microscopes while reducing cost, power, weight and size.

  14. A Low-Cost Digital Microscope with Real-Time Fluorescent Imaging Capability

    Science.gov (United States)

    Hasan, Md. Mehedi; Wahid, Khan A.; Miah, Sayem; Lukong, Kiven Erique

    2016-01-01

    This paper describes the development of a prototype of a low-cost digital fluorescent microscope built from commercial off-the-shelf (COTS) components. The prototype was tested to detect malignant tumor cells taken from a living organism in a preclinical setting. This experiment was accomplished by using Alexa Fluor 488 conjugate dye attached to the cancer cells. Our prototype utilizes a torch along with an excitation filter as a light source for fluorophore excitation, a dichroic mirror to reflect the excitation and pass the emitted green light from the sample under test and a barrier filter to permit only appropriate wavelength. The system is designed out of a microscope using its optical zooming property and an assembly of exciter filter, dichroic mirror and transmitter filter. The microscope is connected to a computer or laptop through universal serial bus (USB) that allows real-time transmission of captured florescence images; this also offers real-time control of the microscope. The designed system has comparable features of high-end commercial fluorescent microscopes while reducing cost, power, weight and size. PMID:27977709

  15. Real-time monitoring for fast deformations using GNSS low-cost receivers

    Directory of Open Access Journals (Sweden)

    T. Bellone

    2016-03-01

    Full Text Available Landslides are one of the major geo-hazards which have constantly affected Italy especially over the last few years. In fact 82% of the Italian territory is affected by this phenomenon which destroys the environment and often causes deaths: therefore it is necessary to monitor these effects in order to detect and prevent these risks. Nowadays, most of this type of monitoring is carried out by using traditional topographic instruments (e.g. total stations or satellite techniques such as global navigation satellite system (GNSS receivers. The level of accuracy obtainable with these instruments is sub-centimetrical in post-processing and centimetrical in real-time; however, the costs are very high (many thousands of euros. The rapid diffusion of GNSS networks has led to an increase of using mass-market receivers for real-time positioning. In this paper, the performances of GNSS mass-market receiver are reported with the aim of verifying if this type of sensor can be used for real-time landslide monitoring: for this purpose a special slide was used for simulating a landslide, since it enabled us to give manual displacements thanks to a micrometre screw. These experiments were also carried out by considering a specific statistical test (a modified Chow test which enabled us to understand if there were any displacements from a statistical point of view in real time. The tests, the algorithm and results are reported in this paper.

  16. A Low Cost GPS System for Real-Time Tracking of Sounding Rockets

    Science.gov (United States)

    Markgraf, M.; Montenbruck, O.; Hassenpflug, F.; Turner, P.; Bull, B.; Bauer, Frank (Technical Monitor)

    2001-01-01

    This paper describes the development as well as the on-ground and the in-flight evaluation of a low cost Global Positioning System (GPS) system for real-time tracking of sounding rockets. The flight unit comprises a modified ORION GPS receiver and a newly designed switchable antenna system composed of a helical antenna in the rocket tip and a dual-blade antenna combination attached to the body of the service module. Aside from the flight hardware a PC based terminal program has been developed to monitor the GPS data and graphically displays the rocket's path during the flight. In addition an Instantaneous Impact Point (IIP) prediction is performed based on the received position and velocity information. In preparation for ESA's Maxus-4 mission, a sounding rocket test flight was carried out at Esrange, Kiruna, on 19 Feb. 2001 to validate existing ground facilities and range safety installations. Due to the absence of a dedicated scientific payload, the flight offered the opportunity to test multiple GPS receivers and assess their performance for the tracking of sounding rockets. In addition to the ORION receiver, an Ashtech G12 HDMA receiver and a BAE (Canadian Marconi) Allstar receiver, both connected to a wrap-around antenna, have been flown on the same rocket as part of an independent experiment provided by the Goddard Space Flight Center. This allows an in-depth verification and trade-off of different receiver and antenna concepts.

  17. Quantification of bovine leukemia virus proviral DNA using a low-cost real-time polymerase chain reaction.

    Science.gov (United States)

    Petersen, M I; Alvarez, I; Trono, K G; Jaworski, J P

    2018-04-11

    The detection of bovine leukemia virus (BLV) proviral DNA is an important tool to address whether an animal is infected with BLV. Compared with serological assays, real-time PCR accounts for greater sensitivity and can serve as a confirmatory test for the clarification of inconclusive or discordant serological test results. However, the high cost related to real-time PCR assays has limited their systematic inclusion in BLV surveillance and eradication programs. The aim of the present study was to validate a low-cost quantitative real-time PCR. Interestingly, by using SYBR Green detection dye, we were able to reduce the cost of a single reaction by a factor of 5 compared with most common assays based on the use of fluorogenic probes (i.e., TaqMan technology). This approach allowed a highly sensitive and specific detection and quantification of BLV proviral DNA from purified peripheral blood leukocytes and a milk matrix. Due to its simplicity and low cost, our in-house BLV SYBR quantitative real-time PCR might be used either as a screening or as a confirmatory test in BLV control programs. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  18. A fast, flexible and low cost real time data acquisition system for nuclear physics experiments

    International Nuclear Information System (INIS)

    Rassool, R.P.; O'Keefe, G.J.; Thompson, M.N.

    1991-01-01

    A system has been developed to permit fast, efficient data collection from a relatively complex nuclear experiment. Incorporated into this system is the communication framework for on-line analysis of the incoming data. The system makes extensive use of readily available low cost Intel based microprocessors. Results from recent measurements of the 16 O(γ,n) cross section made using tagged photons, performed at previously unachievable collection rates are presented. 6 refs., 6 figs

  19. Low-cost HIV-1 diagnosis and quantification in dried blood spots by real time PCR.

    Science.gov (United States)

    Mehta, Nishaki; Trzmielina, Sonia; Nonyane, Bareng A S; Eliot, Melissa N; Lin, Rongheng; Foulkes, Andrea S; McNeal, Kristina; Ammann, Arthur; Eulalievyolo, Vindu; Sullivan, John L; Luzuriaga, Katherine; Somasundaran, Mohan

    2009-06-05

    Rapid and cost-effective methods for HIV-1 diagnosis and viral load monitoring would greatly enhance the clinical management of HIV-1 infected adults and children in limited-resource settings. Recent recommendations to treat perinatally infected infants within the first year of life are feasible only if early diagnosis is routinely available. Dried blood spots (DBS) on filter paper are an easy and convenient way to collect and transport blood samples. A rapid and cost effective method to diagnose and quantify HIV-1 from DBS is urgently needed to facilitate early diagnosis of HIV-1 infection and monitoring of antiretroviral therapy. We have developed a real-time LightCycler (rtLC) PCR assay to detect and quantify HIV-1 from DBS. HIV-1 RNA extracted from DBS was amplified in a one-step, single-tube system using primers specific for long-terminal repeat sequences that are conserved across all HIV-1 clades. SYBR Green dye was used to quantify PCR amplicons and HIV-1 RNA copy numbers were determined from a standard curve generated using serially diluted known copies of HIV-1 RNA. This assay detected samples across clades, has a dynamic range of 5 log(10), and %CV real-time systems demonstrated similar performance. The accuracy, reliability, genotype inclusivity and affordability, along with the small volumes of blood required for the assay suggest that the rtLC DBS assay will be useful for early diagnosis and monitoring of pediatric HIV-1 infection in resource-limited settings.

  20. A low-cost single-board solution for real-time, unsupervised waveform classification of multineuron recordings.

    Science.gov (United States)

    Kreiter, A K; Aertsen, A M; Gerstein, G L

    1989-10-01

    We describe a low-cost single-board system for unsupervised, real-time spike sorting of recordings from a number of neurons on a single microelectrode. The maximum number of spike classes depends on the quality of the recording; it will typically be between 2 and 5. The spike sorter communicates with a conventional microcomputer through a standard serial port (RS232). For typical firing rates as measured in the mammalian central nervous system, this set-up will accommodate up to some 10 parallel spike sorters for as many separate microelectrodes.

  1. Addressing critical environmental data gaps via low-cost, real-time, cellular-based environmental monitoring

    Science.gov (United States)

    Caylor, K. K.; Wolf, A.; Siegfried, B.

    2014-12-01

    Models in the environmental sciences are repositories in a sense of the current state of understanding of critical processes. However, as our understanding of these processes (and their accompanying models) become more granular, the data requirements to parameterize them become more limiting. In addition, as these models become more useful, they are often pressed into service for decision support, meaning that they cannot accept the data latency typical of most environmental observations. Finally, the vast majority of environmental data is generated at highly-instrumented, infrastructure-rich "mega sites" in the US/Europe, while many of the most pressing environmental issues are in rural locales and in the developing world. Cellular-based environmental sensing is a promising means to provide granular data in real time from remote locales to improve model-based forecasting using data assimilation. Applications we are working on include drought forecasting and food security; forest and crop responses to weather and climate change; and rural water usage. Over the past two years, we have developed a suite of integrated hardware, firmware, and backend APIs that accommodates an unlimited variety of sensors, and propagates these data onto the internet over mobile networks. Scientific data holds a unique role for demanding well-characterized information on sensor error and our design attempts to balance error reduction with low costs. The result is a deployment system that undercuts competing commercial products by as much as 90%, allowing more ubiquitous deployment with lower risks associated with sensor loss. Enclosure design and power management are critical ingredients for remote deployments under variable environmental conditions. Sensors push data onto cloud storage and make this data available via public API's via a backend server that accommodates additional metadata essential for interpreting observations, particularly their measurement errors. The data these pods

  2. On Real-Time Systems Using Local Area Networks.

    Science.gov (United States)

    1987-07-01

    87-35 July, 1987 CS-TR-1892 On Real - Time Systems Using Local Area Networks*I VShem-Tov Levi Department of Computer Science Satish K. Tripathit...1892 On Real - Time Systems Using Local Area Networks* Shem-Tov Levi Department of Computer Science Satish K. Tripathit Department of Computer Science...constraints and the clock systems that feed the time to real - time systems . A model for real-time system based on LAN communication is presented in

  3. Real-time implementation of a 1.25-Gbit/s DMT transmitter for robust and low-cost LED-based plastic optical fiber applications

    NARCIS (Netherlands)

    Lee, S.C.J.; Breyer, F.; Cárdenas, D.; Randel, S.; Koonen, A.M.J.

    2009-01-01

    Real-time implementation of a DMT transmitter in FPGA is demonstrated for low-cost, standard 1-mm step-index plastic optical fiber applications based on commercial resonant-cavity LED and large-diameter (540 µm) photodiode.

  4. Real-Time Algebraic Derivative Estimations Using a Novel Low-Cost Architecture Based on Reconfigurable Logic

    Science.gov (United States)

    Morales, Rafael; Rincón, Fernando; Gazzano, Julio Dondo; López, Juan Carlos

    2014-01-01

    Time derivative estimation of signals plays a very important role in several fields, such as signal processing and control engineering, just to name a few of them. For that purpose, a non-asymptotic algebraic procedure for the approximate estimation of the system states is used in this work. The method is based on results from differential algebra and furnishes some general formulae for the time derivatives of a measurable signal in which two algebraic derivative estimators run simultaneously, but in an overlapping fashion. The algebraic derivative algorithm presented in this paper is computed online and in real-time, offering high robustness properties with regard to corrupting noises, versatility and ease of implementation. Besides, in this work, we introduce a novel architecture to accelerate this algebraic derivative estimator using reconfigurable logic. The core of the algorithm is implemented in an FPGA, improving the speed of the system and achieving real-time performance. Finally, this work proposes a low-cost platform for the integration of hardware in the loop in MATLAB. PMID:24859033

  5. Mapping urban air quality in near real-time using observations from low-cost sensors and model information.

    Science.gov (United States)

    Schneider, Philipp; Castell, Nuria; Vogt, Matthias; Dauge, Franck R; Lahoz, William A; Bartonova, Alena

    2017-09-01

    The recent emergence of low-cost microsensors measuring various air pollutants has significant potential for carrying out high-resolution mapping of air quality in the urban environment. However, the data obtained by such sensors are generally less reliable than that from standard equipment and they are subject to significant data gaps in both space and time. In order to overcome this issue, we present here a data fusion method based on geostatistics that allows for merging observations of air quality from a network of low-cost sensors with spatial information from an urban-scale air quality model. The performance of the methodology is evaluated for nitrogen dioxide in Oslo, Norway, using both simulated datasets and real-world measurements from a low-cost sensor network for January 2016. The results indicate that the method is capable of producing realistic hourly concentration fields of urban nitrogen dioxide that inherit the spatial patterns from the model and adjust the prior values using the information from the sensor network. The accuracy of the data fusion method is dependent on various factors including the total number of observations, their spatial distribution, their uncertainty (both in terms of systematic biases and random errors), as well as the ability of the model to provide realistic spatial patterns of urban air pollution. A validation against official data from air quality monitoring stations equipped with reference instrumentation indicates that the data fusion method is capable of reproducing city-wide averaged official values with an R 2 of 0.89 and a root mean squared error of 14.3 μg m -3 . It is further capable of reproducing the typical daily cycles of nitrogen dioxide. Overall, the results indicate that the method provides a robust way of extracting useful information from uncertain sensor data using only a time-invariant model dataset and the knowledge contained within an entire sensor network. Copyright © 2017 The Authors. Published

  6. Fault Tolerant Real-Time Networks

    National Research Council Canada - National Science Library

    Zakhor, Avideh; Henzinger, Thomas; Trevedi, Kishor; Ammar, Mostafa; Lynch, Nancy; Shin, Kang

    2007-01-01

    .... We have focused on multimedia delivery in traditional client-server architectures, both in the case of the Internet and wireless networks, as well as on peer-to-peer content delivery and on mobile ad-hoc networks...

  7. Real-Time Communication Networks Onboard Ships

    DEFF Research Database (Denmark)

    Nielsen, Jens Frederik Dalsgaard; Nielsen, Kirsten Mølgaard; Jørgensen, N.

    1995-01-01

    This paper describes the ATOMOS communication network project carried out within the EU project ATOMOS, to be used for ISC purposes.......This paper describes the ATOMOS communication network project carried out within the EU project ATOMOS, to be used for ISC purposes....

  8. Real-Time Fault Tolerant Networking Protocols

    National Research Council Canada - National Science Library

    Henzinger, Thomas A

    2004-01-01

    We made significant progress in the areas of video streaming, wireless protocols, mobile ad-hoc and sensor networks, peer-to-peer systems, fault tolerant algorithms, dependability and timing analysis...

  9. Wireless Sensor Network Metrics for Real-Time Systems

    Science.gov (United States)

    2009-05-20

    Wireless Sensor Network Metrics for Real-Time Systems Phoebus Wei-Chih Chen Electrical Engineering and Computer Sciences University of California at...3. DATES COVERED 00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE Wireless Sensor Network Metrics for Real-Time Systems 5a. CONTRACT NUMBER 5b... wireless sensor networks (WSNs) is moving from studies of WSNs in isolation toward studies where the WSN is treated as a component of a larger system

  10. TOWARDS A LOW-COST, REAL-TIME PHOTOGRAMMETRIC LANDSLIDE MONITORING SYSTEM UTILISING MOBILE AND CLOUD COMPUTING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    P. Chidburee

    2016-06-01

    Full Text Available Close-range photogrammetric techniques offer a potentially low-cost approach in terms of implementation and operation for initial assessment and monitoring of landslide processes over small areas. In particular, the Structure-from-Motion (SfM pipeline is now extensively used to help overcome many constraints of traditional digital photogrammetry, offering increased user-friendliness to nonexperts, as well as lower costs. However, a landslide monitoring approach based on the SfM technique also presents some potential drawbacks due to the difficulty in managing and processing a large volume of data in real-time. This research addresses the aforementioned issues by attempting to combine a mobile device with cloud computing technology to develop a photogrammetric measurement solution as part of a monitoring system for landslide hazard analysis. The research presented here focusses on (i the development of an Android mobile application; (ii the implementation of SfM-based open-source software in the Amazon cloud computing web service, and (iii performance assessment through a simulated environment using data collected at a recognized landslide test site in North Yorkshire, UK. Whilst the landslide monitoring mobile application is under development, this paper describes experiments carried out to ensure effective performance of the system in the future. Investigations presented here describe the initial assessment of a cloud-implemented approach, which is developed around the well-known VisualSFM algorithm. Results are compared to point clouds obtained from alternative SfM 3D reconstruction approaches considering a commercial software solution (Agisoft PhotoScan and a web-based system (Autodesk 123D Catch. Investigations demonstrate that the cloud-based photogrammetric measurement system is capable of providing results of centimeter-level accuracy, evidencing its potential to provide an effective approach for quantifying and analyzing landslide hazard

  11. Towards a Low-Cost Real-Time Photogrammetric Landslide Monitoring System Utilising Mobile and Cloud Computing Technology

    Science.gov (United States)

    Chidburee, P.; Mills, J. P.; Miller, P. E.; Fieber, K. D.

    2016-06-01

    Close-range photogrammetric techniques offer a potentially low-cost approach in terms of implementation and operation for initial assessment and monitoring of landslide processes over small areas. In particular, the Structure-from-Motion (SfM) pipeline is now extensively used to help overcome many constraints of traditional digital photogrammetry, offering increased user-friendliness to nonexperts, as well as lower costs. However, a landslide monitoring approach based on the SfM technique also presents some potential drawbacks due to the difficulty in managing and processing a large volume of data in real-time. This research addresses the aforementioned issues by attempting to combine a mobile device with cloud computing technology to develop a photogrammetric measurement solution as part of a monitoring system for landslide hazard analysis. The research presented here focusses on (i) the development of an Android mobile application; (ii) the implementation of SfM-based open-source software in the Amazon cloud computing web service, and (iii) performance assessment through a simulated environment using data collected at a recognized landslide test site in North Yorkshire, UK. Whilst the landslide monitoring mobile application is under development, this paper describes experiments carried out to ensure effective performance of the system in the future. Investigations presented here describe the initial assessment of a cloud-implemented approach, which is developed around the well-known VisualSFM algorithm. Results are compared to point clouds obtained from alternative SfM 3D reconstruction approaches considering a commercial software solution (Agisoft PhotoScan) and a web-based system (Autodesk 123D Catch). Investigations demonstrate that the cloud-based photogrammetric measurement system is capable of providing results of centimeter-level accuracy, evidencing its potential to provide an effective approach for quantifying and analyzing landslide hazard at a local-scale.

  12. Real-Time Classification of Patients with Balance Disorders vs. Normal Subjects Using a Low-Cost Small Wireless Wearable Gait Sensor

    Directory of Open Access Journals (Sweden)

    Bhargava Teja Nukala

    2016-11-01

    Full Text Available Gait analysis using wearable wireless sensors can be an economical, convenient and effective way to provide diagnostic and clinical information for various health-related issues. In this work, our custom designed low-cost wireless gait analysis sensor that contains a basic inertial measurement unit (IMU was used to collect the gait data for four patients diagnosed with balance disorders and additionally three normal subjects, each performing the Dynamic Gait Index (DGI tests while wearing the custom wireless gait analysis sensor (WGAS. The small WGAS includes a tri-axial accelerometer integrated circuit (IC, two gyroscopes ICs and a Texas Instruments (TI MSP430 microcontroller and is worn by each subject at the T4 position during the DGI tests. The raw gait data are wirelessly transmitted from the WGAS to a near-by PC for real-time gait data collection and analysis. In order to perform successful classification of patients vs. normal subjects, we used several different classification algorithms, such as the back propagation artificial neural network (BP-ANN, support vector machine (SVM, k-nearest neighbors (KNN and binary decision trees (BDT, based on features extracted from the raw gait data of the gyroscopes and accelerometers. When the range was used as the input feature, the overall classification accuracy obtained is 100% with BP-ANN, 98% with SVM, 96% with KNN and 94% using BDT. Similar high classification accuracy results were also achieved when the standard deviation or other values were used as input features to these classifiers. These results show that gait data collected from our very low-cost wearable wireless gait sensor can effectively differentiate patients with balance disorders from normal subjects in real time using various classifiers, the success of which may eventually lead to accurate and objective diagnosis of abnormal human gaits and their underlying etiologies in the future, as more patient data are being collected.

  13. A Distributed Computing Network for Real-Time Systems.

    Science.gov (United States)

    1980-11-03

    7 ) AU2 o NAVA TUNDEWATER SY$TEMS CENTER NEWPORT RI F/G 9/2 UIS RIBUT E 0 COMPUTIN G N LTWORK FOR REAL - TIME SYSTEMS .(U) UASSIFIED NOV Al 6 1...MORAIS - UT 92 dLEVEL c A Distributed Computing Network for Real - Time Systems . 11 𔃺-1 Gordon E/Morson I7 y tm- ,r - t "en t As J 2 -p .. - 7 I’ cNaval...NUMBER TD 5932 / N 4. TITLE mand SubotI. S. TYPE OF REPORT & PERIOD COVERED A DISTRIBUTED COMPUTING NETWORK FOR REAL - TIME SYSTEMS 6. PERFORMING ORG

  14. Real-Time Communication in Wireless Home Networks

    NARCIS (Netherlands)

    Scholten, Johan; Jansen, P.G.

    This paper describes a medium access protocol for real-time communication in wireless networks. Medium access is controlled by a scheduler, which utilizes a pre-emptive earliest deadline first (PEDF) scheduling algorithm. The scheduler prevents collisions in the network, where normally only

  15. Low cost, robust and real time system for detecting and tracking moving objects to automate cargo handling in port terminals

    NARCIS (Netherlands)

    Vaquero, V.; Repiso, E.; Sanfeliu, A.; Vissers, J.; Kwakkernaat, M.

    2016-01-01

    The presented paper addresses the problem of detecting and tracking moving objects for autonomous cargo handling in port terminals using a perception system which input data is a single layer laser scanner. A computationally low cost and robust Detection and Tracking Moving Objects (DATMO) algorithm

  16. Real Time Monitoring of Children, and Adults with Mental Disabilities Using a Low-Cost Non-Invasive Electronic Device

    Directory of Open Access Journals (Sweden)

    Carlos Polanco

    2017-09-01

    Full Text Available There are a growing number of small children—as well as adults—with mental disabilities (including elderly citizens with Alzheimer’s disease or other forms of age-related dementia that are getting lost in rural and urban areas for various reasons. Establishing their location within the first 72 h is crucial because lost people are exposed to all kinds of adverse conditions and in the case of the elderly, this is further aggravated if prescribed medication is needed. Herein we describe a non-invasive, low-cost electronic device that operates constantly, keeping track of time, the geographical location and the identification of the subject using it. The prototype was made using commercial low-cost electronic components. This electronic device shows high connectivity in open and closed areas and identifies the geographical location of a lost subject. We freely provide the software and technical diagrams of the prototypes.

  17. Performance comparison of next generation controller and MPC in real time for a SISO process with low cost DAQ unit

    Directory of Open Access Journals (Sweden)

    V. Bagyaveereswaran

    2016-09-01

    Full Text Available In this paper, a brief overview of real time implementation of next generation Robust, Tracking, Disturbance rejecting, Aggressive (RTDA controller and Model Predictive Control (MPC is provided. The control algorithm is implemented through MATLAB. The plant model used in controller design is obtained using system identification tool and integral response method. The controller model is developed in Simulink using jMPC tool, which will be executed in real time. The outputs obtained are tested for various constraint values to obtain the desirable results. The implementation of Hardware in Loop is done by interfacing it with MATLAB using Arduino as data acquisition unit. The performance of RTDA is compared with those of MPC and Proportional Integral controller.

  18. An In-Home Digital Network Architecture for Real-Time and Non-Real-Time Communication

    NARCIS (Netherlands)

    Scholten, Johan; Jansen, P.G.; Hanssen, F.T.Y.; Hattink, Tjalling

    2002-01-01

    This paper describes an in-home digital network architecture that supports both real-time and non-real-time communication. The architecture deploys a distributed token mechanism to schedule communication streams and to offer guaranteed quality-ofservice. Essentially, the token mechanism prevents

  19. Comparative study of internet cloud and cloudlet over wireless mesh networks for real-time applications

    Science.gov (United States)

    Khan, Kashif A.; Wang, Qi; Luo, Chunbo; Wang, Xinheng; Grecos, Christos

    2014-05-01

    Mobile cloud computing is receiving world-wide momentum for ubiquitous on-demand cloud services for mobile users provided by Amazon, Google etc. with low capital cost. However, Internet-centric clouds introduce wide area network (WAN) delays that are often intolerable for real-time applications such as video streaming. One promising approach to addressing this challenge is to deploy decentralized mini-cloud facility known as cloudlets to enable localized cloud services. When supported by local wireless connectivity, a wireless cloudlet is expected to offer low cost and high performance cloud services for the users. In this work, we implement a realistic framework that comprises both a popular Internet cloud (Amazon Cloud) and a real-world cloudlet (based on Ubuntu Enterprise Cloud (UEC)) for mobile cloud users in a wireless mesh network. We focus on real-time video streaming over the HTTP standard and implement a typical application. We further perform a comprehensive comparative analysis and empirical evaluation of the application's performance when it is delivered over the Internet cloud and the cloudlet respectively. The study quantifies the influence of the two different cloud networking architectures on supporting real-time video streaming. We also enable movement of the users in the wireless mesh network and investigate the effect of user's mobility on mobile cloud computing over the cloudlet and Amazon cloud respectively. Our experimental results demonstrate the advantages of the cloudlet paradigm over its Internet cloud counterpart in supporting the quality of service of real-time applications.

  20. A Dual-Linear Kalman Filter for Real-Time Orientation Determination System Using Low-Cost MEMS Sensors.

    Science.gov (United States)

    Zhang, Shengzhi; Yu, Shuai; Liu, Chaojun; Yuan, Xuebing; Liu, Sheng

    2016-02-20

    To provide a long-time reliable orientation, sensor fusion technologies are widely used to integrate available inertial sensors for the low-cost orientation estimation. In this paper, a novel dual-linear Kalman filter was designed for a multi-sensor system integrating MEMS gyros, an accelerometer, and a magnetometer. The proposed filter precludes the impacts of magnetic disturbances on the pitch and roll which the heading is subjected to. The filter can achieve robust orientation estimation for different statistical models of the sensors. The root mean square errors (RMSE) of the estimated attitude angles are reduced by 30.6% under magnetic disturbances. Owing to the reduction of system complexity achieved by smaller matrix operations, the mean total time consumption is reduced by 23.8%. Meanwhile, the separated filter offers greater flexibility for the system configuration, as it is possible to switch on or off the second stage filter to include or exclude the magnetometer compensation for the heading. Online experiments were performed on the homemade miniature orientation determination system (MODS) with the turntable. The average RMSE of estimated orientation are less than 0.4° and 1° during the static and low-dynamic tests, respectively. More realistic tests on two-wheel self-balancing vehicle driving and indoor pedestrian walking were carried out to evaluate the performance of the designed MODS when high accelerations and angular rates were introduced. Test results demonstrate that the MODS is applicable for the orientation estimation under various dynamic conditions. This paper provides a feasible alternative for low-cost orientation determination.

  1. Dynamic Web Expression for Near-real-time Sensor Networks

    Science.gov (United States)

    Lindquist, K. G.; Newman, R. L.; Nayak, A.; Vernon, F. L.; Nelson, C.; Hansen, T. S.; Yuen-Wong, R.

    2003-12-01

    As near-real-time sensor grids become more widespread, and processing systems based on them become more powerful, summarizing the raw and derived information products and delivering them to the end user become increasingly important both for ongoing monitoring and as a platform for cross-disciplinary research. We have re-engineered the dbrecenteqs program, which was designed to express real-time earthquake databases into dynamic web pages, with several powerful new technologies. While the application is still most fully developed for seismic data, the infrastructure is extensible (and being extended) to create a real-time information architecture for numerous signal domains. This work provides a practical, lightweight approach suitable for individual seismic and sensor networks, which does not require a full 'web-services' implementation. Nevertheless, the technologies here are extensible to larger applications such as the Storage-Resource-Broker based VORB project. The technologies included in the new system blend real-time relational databases as a focus for processing and data handling; an XML->XSLT architecture as the core of the web mirroring; PHP extensions to Antelope (the environmental monitoring-system context adopted for RoadNET) in order to support complex, user-driven interactivity; and VRML output for expression of information as web-browsable three-dimensional worlds.

  2. Real-Time Alpine Measurement System Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sami A. Malek

    2017-11-01

    Full Text Available Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

  3. Real-Time Alpine Measurement System Using Wireless Sensor Networks.

    Science.gov (United States)

    Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

    2017-11-09

    Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

  4. Efficient Evaluation of Wireless Real-Time Control Networks

    Directory of Open Access Journals (Sweden)

    Peter Horvath

    2015-02-01

    Full Text Available In this paper, we present a system simulation framework for the design and performance evaluation of complex wireless cyber-physical systems. We describe the simulator architecture and the specific developments that are required to simulate cyber-physical systems relying on multi-channel, multihop mesh networks. We introduce realistic and efficient physical layer models and a system simulation methodology, which provides statistically significant performance evaluation results with low computational complexity. The capabilities of the proposed framework are illustrated in the example of WirelessHART, a centralized, real-time, multi-hop mesh network designed for industrial control and monitor applications.

  5. Ref Tek Ultra-low Power Seismic Recorder With Low-cost High Speed Internet Telemetry U An Advanced Real-time Seismological Data Acquisition System

    Science.gov (United States)

    Passmore, P.; Zimakov, L.; Rozhkov, M.

    The 3rd Generation Seismic Recorder, Model 130-01, has been designed to be easier to use - more compact, lighter in weight, lower power, and requires less maintenance than other recorders. Not only is the hardware optimized for field deployments, soft- ware tools as well have been specially developed to support both field and base station operation. The 130's case is a clamshell design, inherently waterproof, with easy access to all user features on the top of the unit. The 130 has 6 input/output connectors, an LCD display, and a removable lid on top of the case. There are two Channel input connectors on a 6-channel unit (only one on a 3-channel unit), a Terminal connector for setup and control, a Net connector combining Ethernet and Serial PPP for network access, a 12 VDC Power connector, and a GPS receiver connector. The LCD display allows the user to monitor the status of various sub systems within the 130 without having a terminal device attached. For storing large amounts of data the IBM MicrodriveTM is offered. User setup, control and status monitoring is done either with a Personal Digital Assistant (PDA) (Palm OS compatible) using our Palm Field Controller (PFC) software or from a PC/workstation using our REF TEK Network Controller (RNC) GUI interface. StarBand VSAT is the premier two-way, always-on, high-speed satellite Internet ser- vice. StarBand means high-speed Internet without the constraints and congestion of land-based cable or telephone networks. StarBand uses a single satellite dish antenna for receiving and for sending dataUno telephone connection is needed. The hardware ° cost is much less than standard VSAT equipment with double or single hop transmis- sion. REF TEK protocol (RTP) provides end-to-end error-correcting data transmission and command/control. StarBandSs low cost VSAT provides two-way, always-on, high speed satellite Internet data availability. REF TEK and StarBand create the most ad- vanced real-time seismological data acquisition

  6. Localized real-time information on outdoor air quality at kindergartens in Oslo, Norway using low-cost sensor nodes.

    Science.gov (United States)

    Castell, Nuria; Schneider, Philipp; Grossberndt, Sonja; Fredriksen, Mirjam F; Sousa-Santos, Gabriela; Vogt, Mathias; Bartonova, Alena

    2018-08-01

    In Norway, children in kindergartens spend significant time outdoors under all weather conditions, and there is thus a natural concern about the quality of outdoor air. It is well known that air pollution is associated with a wide variety of adverse health impacts for children, with greater impact on children with asthma. Especially during winter and spring, kindergartens in Oslo that are situated close to streets with busy traffic, or in areas where wood burning is used for house heating, can experience many days with bad air quality. During these periods, updated information on air quality levels can help the kindergarten teachers to plan appropriate outdoor activities and thus protect children's health. We have installed 17 low-cost air quality nodes in kindergartens in Oslo. These nodes are smaller, cheaper and less complex to use than traditional equipment. Performance evaluation shows that while they are less accurate and suffer from higher uncertainty than reference equipment, they still can provide reliable coarse information about local pollution. The main challenge when using this technology is that calibration parameters might change with time depending on the atmospheric conditions. Thus, even if the sensors are calibrated a priori, once deployed, and especially if they are deployed for a long time, it is not possible to determine if a node is over- or under-estimating the concentration levels. To enhance the data from the sensors, we employed a data fusion technique that allows generating a detailed air quality map merging the data from the sensors and the data from an urban model, thus being able to offer air quality information to any location within Oslo. We arranged a focus group with the participation of local administration, kindergarten staff and parents to understand their opinion and needs related to the air quality information that was provided to the participant kindergartens. They expressed concern about the data quality but agree that

  7. Simulating Real-Time Aspects of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Christian Nastasi

    2010-01-01

    Full Text Available Wireless Sensor Networks (WSNs technology has been mainly used in the applications with low-frequency sampling and little computational complexity. Recently, new classes of WSN-based applications with different characteristics are being considered, including process control, industrial automation and visual surveillance. Such new applications usually involve relatively heavy computations and also present real-time requirements as bounded end-to- end delay and guaranteed Quality of Service. It becomes then necessary to employ proper resource management policies, not only for communication resources but also jointly for computing resources, in the design and development of such WSN-based applications. In this context, simulation can play a critical role, together with analytical models, for validating a system design against the parameters of Quality of Service demanded for. In this paper, we present RTNS, a publicly available free simulation tool which includes Operating System aspects in wireless distributed applications. RTNS extends the well-known NS-2 simulator with models of the CPU, the Real-Time Operating System and the application tasks, to take into account delays due to the computation in addition to the communication. We demonstrate the benefits of RTNS by presenting our simulation study for a complex WSN-based multi-view vision system for real-time event detection.

  8. Deep neural networks to enable real-time multimessenger astrophysics

    Science.gov (United States)

    George, Daniel; Huerta, E. A.

    2018-02-01

    Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field of research, there is a pressing need to increase the depth and speed of the algorithms used to enable these ground-breaking discoveries. We introduce Deep Filtering—a new scalable machine learning method for end-to-end time-series signal processing. Deep Filtering is based on deep learning with two deep convolutional neural networks, which are designed for classification and regression, to detect gravitational wave signals in highly noisy time-series data streams and also estimate the parameters of their sources in real time. Acknowledging that some of the most sensitive algorithms for the detection of gravitational waves are based on implementations of matched filtering, and that a matched filter is the optimal linear filter in Gaussian noise, the application of Deep Filtering using whitened signals in Gaussian noise is investigated in this foundational article. The results indicate that Deep Filtering outperforms conventional machine learning techniques, achieves similar performance compared to matched filtering, while being several orders of magnitude faster, allowing real-time signal processing with minimal resources. Furthermore, we demonstrate that Deep Filtering can detect and characterize waveform signals emitted from new classes of eccentric or spin-precessing binary black holes, even when trained with data sets of only quasicircular binary black hole waveforms. The results presented in this article, and the recent use of deep neural networks for the identification of optical transients in telescope data, suggests that deep learning can facilitate real-time searches of gravitational wave sources and their electromagnetic and astroparticle counterparts. In the subsequent article, the framework introduced herein is directly applied to identify and characterize gravitational wave events in real LIGO data.

  9. Ocean Wireless Networking and Real Time Data Management

    Science.gov (United States)

    Berger, J.; Orcutt, J. A.; Vernon, F. L.; Braun, H. W.; Rajasekar, A.

    2001-12-01

    Recent advances in technology have enabled the exploitation of satellite communications for high-speed (> 64 kbps) duplex communications with oceanographic ships at sea. Furthermore, decreasing costs for high-speed communications have made possible continuous connectivity to the global Internet for delivery of data ashore and communications with scientists and engineers on the ship. Through support from the Office of Naval Research, we have planned a series of tests using the R/V Revelle for real time data delivery of large quantities of underway data (e.g. continuous multibeam profiling) to shore for quality control, archiving, and real-time data availability. The Cecil H. and Ida M. Green Institute of Geophysics and Planetary Physics (IGPP) and the San Diego Supercomputer Center (SDSC) were funded by the NSF Information Technology Research (ITR) Program, the California Institute for Telecommunications and Information Technology [Cal-(IT)2] and the Scripps Institution of Oceanography for research entitled: "Exploring the Environment in Time: Wireless Networks & Real-Time Management." We will describe the technology to be used for the real-time seagoing experiment and the planned expansion of the project through support from the ITR grant. The short-term goal is to exercise the communications system aboard ship in various weather conditions and sea states while testing and developing the real-time data quality control and archiving methodology. The long-term goal is to enable continuous observations in the ocean, specifically supporting the goals of the DEOS (Dynamics of Earth and Ocean Systems) observatory program supported through a NSF Major Research Equipment (MRE) program - a permanent presence in the oceans. The impact on scientific work aboard ships, however, is likely to be fundamental. It will be possible to go to sea in the future with limited engineering capability for scientific operations by allowing shore-based quality control of data collected and

  10. Highly reliable computer network for real time system

    International Nuclear Information System (INIS)

    Mohammed, F.A.; Omar, A.A.; Ayad, N.M.A.; Madkour, M.A.I.; Ibrahim, M.K.

    1988-01-01

    Many of computer networks have been studied different trends regarding the network architecture and the various protocols that govern data transfers and guarantee a reliable communication among all a hierarchical network structure has been proposed to provide a simple and inexpensive way for the realization of a reliable real-time computer network. In such architecture all computers in the same level are connected to a common serial channel through intelligent nodes that collectively control data transfers over the serial channel. This level of computer network can be considered as a local area computer network (LACN) that can be used in nuclear power plant control system since it has geographically dispersed subsystems. network expansion would be straight the common channel for each added computer (HOST). All the nodes are designed around a microprocessor chip to provide the required intelligence. The node can be divided into two sections namely a common section that interfaces with serial data channel and a private section to interface with the host computer. This part would naturally tend to have some variations in the hardware details to match the requirements of individual host computers. fig 7

  11. Aggregated channels network for real-time pedestrian detection

    Science.gov (United States)

    Ghorban, Farzin; Marín, Javier; Su, Yu; Colombo, Alessandro; Kummert, Anton

    2018-04-01

    Convolutional neural networks (CNNs) have demonstrated their superiority in numerous computer vision tasks, yet their computational cost results prohibitive for many real-time applications such as pedestrian detection which is usually performed on low-consumption hardware. In order to alleviate this drawback, most strategies focus on using a two-stage cascade approach. Essentially, in the first stage a fast method generates a significant but reduced amount of high quality proposals that later, in the second stage, are evaluated by the CNN. In this work, we propose a novel detection pipeline that further benefits from the two-stage cascade strategy. More concretely, the enriched and subsequently compressed features used in the first stage are reused as the CNN input. As a consequence, a simpler network architecture, adapted for such small input sizes, allows to achieve real-time performance and obtain results close to the state-of-the-art while running significantly faster without the use of GPU. In particular, considering that the proposed pipeline runs in frame rate, the achieved performance is highly competitive. We furthermore demonstrate that the proposed pipeline on itself can serve as an effective proposal generator.

  12. A low-cost, portable optical sensing system with wireless communication compatible of real-time and remote detection of dissolved ammonia

    Science.gov (United States)

    Deng, Shijie; Doherty, William; McAuliffe, Michael AP; Salaj-Kosla, Urszula; Lewis, Liam; Huyet, Guillaume

    2016-06-01

    A low-cost and portable optical chemical sensor based ammonia sensing system that is capable of detecting dissolved ammonia up to 5 ppm is presented. In the system, an optical chemical sensor is designed and fabricated for sensing dissolved ammonia concentrations. The sensor uses eosin as the fluorescence dye which is immobilized on the glass substrate by a gas-permeable protection layer. A compact module is developed to hold the optical components, and a battery powered micro-controller system is designed to read out and process the data measured. The system operates without the requirement of laboratory instruments that makes it cost effective and highly portable. Moreover, the calculated results in the system can be transmitted to a PC wirelessly, which allows the remote and real-time monitoring of dissolved ammonia.

  13. REAL TIME ANALYSIS OF WIRELESS CONTROLLER AREA NETWORK

    Directory of Open Access Journals (Sweden)

    Gerardine Immaculate Mary

    2014-09-01

    Full Text Available It is widely known that Control Area Networks (CAN are used in real-time, distributed and parallel processing which cover manufacture plants, humanoid robots, networking fields, etc., In applications where wireless conditions are encountered it is convenient to continue the exchange of CAN frames within the Wireless CAN (WCAN. The WCAN considered in this research is based on wireless token ring protocol (WTRP; a MAC protocol for wireless networks to reduce the number of retransmissions due to collision and the wired counterpart CAN attribute on message based communication. WCAN uses token frame method to provide channel access to the nodes in the system. This method allow all the nodes to share common broadcast channel by taken turns in transmitting upon receiving the token frame which is circulating within the network for specified amount of time. This method provides high throughput in bounded latency environment, consistent and predictable delays and good packet delivery ratio. The most important factor to consider when evaluating a control network is the end-to-end time delay between sensors, controllers, and actuators. The correct operation of a control system depends on the timeliness of the data coming over the network, and thus, a control network should be able to guarantee message delivery within a bounded transmission time. The proposed WCAN is modeled and simulated using QualNet, and its average end to end delay and packet delivery ratio (PDR are calculated. The parameters boundaries of WCAN are evaluated to guarantee a maximum throughput and a minimum latency time, in the case of wireless communications, precisely WCAN.

  14. Cellular Neural Network for Real Time Image Processing

    International Nuclear Information System (INIS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-01-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  15. Simplified neural networks for solving linear least squares and total least squares problems in real time.

    Science.gov (United States)

    Cichocki, A; Unbehauen, R

    1994-01-01

    In this paper a new class of simplified low-cost analog artificial neural networks with on chip adaptive learning algorithms are proposed for solving linear systems of algebraic equations in real time. The proposed learning algorithms for linear least squares (LS), total least squares (TLS) and data least squares (DLS) problems can be considered as modifications and extensions of well known algorithms: the row-action projection-Kaczmarz algorithm and/or the LMS (Adaline) Widrow-Hoff algorithms. The algorithms can be applied to any problem which can be formulated as a linear regression problem. The correctness and high performance of the proposed neural networks are illustrated by extensive computer simulation results.

  16. AIRNET: A real-time comunications network for aircraft

    Science.gov (United States)

    Weaver, Alfred C.; Cain, Brendan G.; Colvin, M. Alexander; Simoncic, Robert

    1990-01-01

    A real-time local area network was developed for use on aircraft and space vehicles. It uses token ring technology to provide high throughput, low latency, and high reliability. The system was implemented on PCs and PC/ATs operating on PCbus, and on Intel 8086/186/286/386s operating on Multibus. A standard IEEE 802.2 logical link control interface was provided to (optional) upper layer software; this permits the controls designer to utilize standard communications protocols (e.g., ISO, TCP/IP) if time permits, or to utilize a very fast link level protocol directly if speed is critical. Both unacknowledged datagram and reliable virtual circuit services are supported. A station operating an 8 MHz Intel 286 as a host can generate a sustained load of 1.8 megabits per second per station, and a 100-byte message can be delivered from the transmitter's user memory to the receiver's user memory, including all operating system and network overhead, in under 4 milliseconds.

  17. Real-time services in IP network architectures

    Science.gov (United States)

    Gilardi, Antonella

    1996-12-01

    The worldwide internet system seems to be the success key for the provision of real time multimedia services to both residential and business users and someone says that in such a way broadband networks will have a reason to exist. This new class of applications that use multiple media (voice, video and data) impose constraints to the global network nowadays consisting of subnets with various data links. The attention will be focused on the interconnection of IP non ATM and ATM networks. IETF and ATM forum are currently involved in the developing specifications suited to adapt the connectionless IP protocol to the connection oriented ATM protocol. First of all the link between the ATM and the IP service model has to be set in order to match the QoS and traffic requirements defined in the relative environment. A further significant topic is represented by the mapping of IP resource reservation model onto the ATM signalling and in the end it is necessary to define how the routing works when there are QoS parameters associated. This paper, considering only unicast applications, will examine the above issues taking as a starting point the situation where an host launches as call set up request with the relevant QoS and traffic descriptor and at some point a router at the edge of the ATM network has to decide how forwarding and request in order to establish an end to end link with the right capabilities. The aim is to compare the proposals emerging from different standard bodies to point out convergency or incompatibility.

  18. How to create a very-low cost, very-low-power, credit-card-sized and real-time ready datalogger

    Science.gov (United States)

    Bès de Berc, Maxime; Grunberg, Marc; Engels, Fabien

    2014-05-01

    In some cases a field instrumentalist could have to add some extra sensors in a remote station. Additional ADCs (Analogic Digital Converters) are not always implemented on commercial dataloggers, or may already be used. Adding more ADCs often implies an expensive development, or buy a new datalogger. We present here a very simple way to deploy an embedded ARM computer, use its features and embedded ADCs to create datas in a seismological standard format and integrating it within the real-time data stream from the station. In the past few years, because of the market growth of telephony and mobile applications, the ARM processor from ARM Ltd has become very common and available at a reasonable price. This processor has the particularity to be an excellent compromise between its frequency and its power consumption. That's why most of smartphones and tablets feature nowadays that kind of processor. It is also available on the market as Soc (System on Chip) or complete embedded computer. The most known is probably the Raspberry Pi, but many ohers exist like the BeagleBone or BeagleBoard. This kind of computer can be bought between 35€ for Raspberry Pi and several hundred Euro for more industrial products. Each model often embed some ADCs on its chip or some special buses, allowing additional ADCs to be easily used. Our experiment has been made on a BeagleBone platform, available at 78€. We chose it because its a more mature product than Raspberry Pi, it has all connectors and options needed: seven ADCs, an USB port for local backup, an Ethernet port for real-time streams, and some useful things like GPIO and I2C buses. Our goal was to plug temperature and humidity sensors on the ADCs, read datas, record them in mini-SEED format (Standard for the Exchange of the Earthquake Data), and transmit those datas to a central server as a secondary source for a remote station, by using Seedlink, which is a standard for seismology. Seedlink is a real-time data acquisition

  19. Low-Cost Real-Time Gas Monitoring Using a Laser Plasma Induced by a Third Harmonic Q-Switched Nd-YAG Laser

    Directory of Open Access Journals (Sweden)

    Syahrun Nur Abdulmadjid

    2005-11-01

    Full Text Available A gas plasma induced by a third harmonic Nd-YAG laser with relatively low pulsed energy (about 10 mJ has favorable characteristics for gas analysis due to its low background characteristics, nevertheless a high power fundamental Nd-YAG laser (100-200 mJ is widely used for laser gas breakdown spectroscopy. The air plasma can be used as a low-cost real-time gas monitoring system such that it can be used to detect the local absolute humidity, while a helium plasma can be used for gas analysis with a high level of sensitivity. A new technique using a helium plasma to improve laser ablation emission spectroscopy is proposed. Namely, the third harmonic Nd-YAG laser is focused at a point located some distance from the target in the 1-atm helium surrounding gas. By using this method, the ablated vapor from the target is excited through helium atoms in a metastable state in the helium plasma.

  20. Prototype real-time baseband signal combiner. [deep space network

    Science.gov (United States)

    Howard, L. D.

    1980-01-01

    The design and performance of a prototype real-time baseband signal combiner, used to enhance the received Voyager 2 spacecraft signals during the Jupiter flyby, is described. Hardware delay paths, operating programs, and firmware are discussed.

  1. REAL-TIME CONTROL OF COMBINED SEWER NETWORKS

    Science.gov (United States)

    Real-time control (RTC) is a custom-designed management program for a specific urban sewerage system during a wet-weather event. The function of RTC is to assure efficient operation of the sewerage system and maximum utilization of existing storage capacity, either to fully conta...

  2. RTnet -- A Flexible Hard Real-Time Networking Framework

    NARCIS (Netherlands)

    Kiszka, Jan; Wagner, Bernardo; Zhang, Yuchen; Broenink, Johannes F.

    2005-01-01

    In this paper, the open source project RTnet is presented. RTnet provides a customisable and extensible framework for hard real-time communication over Ethernet and other transport media. The paper describes architecture, core components, and protocols of RTnet. FireWire is introduced as a powerful

  3. Real-time regression analysis with deep convolutional neural networks

    OpenAIRE

    Huerta, E. A.; George, Daniel; Zhao, Zhizhen; Allen, Gabrielle

    2018-01-01

    We discuss the development of novel deep learning algorithms to enable real-time regression analysis for time series data. We showcase the application of this new method with a timely case study, and then discuss the applicability of this approach to tackle similar challenges across science domains.

  4. How to create a very-low-cost, very-low-power, credit-card-sized and real-time-ready datalogger

    Science.gov (United States)

    Bès de Berc, M.; Grunberg, M.; Engels, F.

    2015-03-01

    In order to improve an existing network, a field seismologist would have to add some extra sensors to a remote station. However, additional ADCs (analogue-to-digital converters) are not always implemented on commercial dataloggers, or, if they are, they may already be used. Installing additional ADCs often implies an expensive development, or the purchase of a new datalogger. We present here a simple method to take advantage of the ADCs of an embedded computer in order to create data in a seismological standard format and integrate them within the real-time data stream from the station. Our first goal is to plug temperature and pressure sensors on the ADCs, read data and record them in mini-seed format (seed stands for Standard for the Exchange of the Earthquake Data), and eventually transfer them to a central server together with the seismic data, by using seedlink, since mini-seed and seedlink are standard for seismology.

  5. Real-time resource availability signaling in IP multimedia subsystem networks

    NARCIS (Netherlands)

    Ozcelebi, T.; Radovanovic, I.; Sengupta, D.

    2008-01-01

    IP Multimedia Subsystem (IMS) allows the use of unlicensed, non-dedicated and nondeterministic access networks for delivering IP multimedia services. Providing end-to-end Quality-of-Service (QoS) for resource demanding real-time services (e.g. real-time multimedia) over such networks is a

  6. A Hierarchical Approach to Real-time Activity Recognition in Body Sensor Networks

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Tao, Xianping

    2012-01-01

    Real-time activity recognition in body sensor networks is an important and challenging task. In this paper, we propose a real-time, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network. In this model, we rst use a fast and lightweight al...

  7. Using Streaming Analytics for Effective Real Time Network Visibility -

    Science.gov (United States)

    on in your network right now. Certainly the other thing that we talked about on the big data side was [inaudible] data. So now we'll drill into - so this is all the traffic from the internal network to the taking a streaming analytics approach to network traffic analysis. So we can go to the next - there we go

  8. Wave forecasting in near real time basis by neural network

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, S.; Mandal, S.; Prabaharan, N.

    ., forecasting of waves become an important aspect of marine environment. This paper presents application of the neural network (NN) with better update algorithms, namely rprop, quickprop and superSAB for wave forecasting. Measured waves off Marmagoa, Goa, India...

  9. Neural network real time event selection for the DIRAC experiment

    CERN Document Server

    Kokkas, P; Tauscher, Ludwig; Vlachos, S

    2001-01-01

    The neural network first level trigger for the DIRAC experiment at CERN is presented. Both the neural network algorithm used and its actual hardware implementation are described. The system uses the fast plastic scintillator information of the DIRAC spectrometer. In 210 ns it selects events with two particles having low relative momentum. Such events are selected with an efficiency of more than 0.94. The corresponding rate reduction for background events is a factor of 2.5. (10 refs).

  10. Designing real-time systems based on mono-master Profibus-DP networks

    OpenAIRE

    Monforte, Salvatore; Alves, Mário; Vasques, Francisco; Tovar, Eduardo

    2000-01-01

    Profibus networks are widely used as the communication infrastructure for supporting distributed computer-controlled applications. Most of the times, these applications impose strict real-time requirements. Profibus-DP has gradually become the preferred Profibus application profile. It is usually implemented as a mono-master Profibus network, and is optimised for speed and efficiency. The aim of this paper is to analyse the real-time behaviour of this class of Profibus networks...

  11. Real Time Emulation of Dynamic Tariff for Congestion Management in Distribution Networks

    DEFF Research Database (Denmark)

    Rasmussen, Theis Bo; Wu, Qiuwei; Huang, Shaojun

    2016-01-01

    This paper presents the real time evaluation of the dynamic tariff (DT) method for alleviating congestion in a distribution networks with high penetration of distributed energy resources (DERs). The DT method is implemented in a real time digital testing platform that emulates a real distribution...

  12. Rapid Modeling of and Response to Large Earthquakes Using Real-Time GPS Networks (Invited)

    Science.gov (United States)

    Crowell, B. W.; Bock, Y.; Squibb, M. B.

    2010-12-01

    Real-time GPS networks have the advantage of capturing motions throughout the entire earthquake cycle (interseismic, seismic, coseismic, postseismic), and because of this, are ideal for real-time monitoring of fault slip in the region. Real-time GPS networks provide the perfect supplement to seismic networks, which operate with lower noise and higher sampling rates than GPS networks, but only measure accelerations or velocities, putting them at a supreme disadvantage for ascertaining the full extent of slip during a large earthquake in real-time. Here we report on two examples of rapid modeling of recent large earthquakes near large regional real-time GPS networks. The first utilizes Japan’s GEONET consisting of about 1200 stations during the 2003 Mw 8.3 Tokachi-Oki earthquake about 100 km offshore Hokkaido Island and the second investigates the 2010 Mw 7.2 El Mayor-Cucapah earthquake recorded by more than 100 stations in the California Real Time Network. The principal components of strain were computed throughout the networks and utilized as a trigger to initiate earthquake modeling. Total displacement waveforms were then computed in a simulated real-time fashion using a real-time network adjustment algorithm that fixes a station far away from the rupture to obtain a stable reference frame. Initial peak ground displacement measurements can then be used to obtain an initial size through scaling relationships. Finally, a full coseismic model of the event can be run minutes after the event, given predefined fault geometries, allowing emergency first responders and researchers to pinpoint the regions of highest damage. Furthermore, we are also investigating using total displacement waveforms for real-time moment tensor inversions to look at spatiotemporal variations in slip.

  13. Traffic Analysis for Real-Time Communication Networks onboard Ships

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Jørgensen, N.

    1998-01-01

    The paper presents a novel method for establishing worst case estimates of queue lenghts and transmission delays in networks of interconnected segments each of ring topology as defined by the ATOMOS project for marine automation. A non probalistic model for describing traffic is introduced as well...

  14. Traffic Analysis for Real-Time Communication Networks onboard Ships

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Nielsen, Jens Frederik Dalsgaard; Jørgensen, N.

    The paper presents a novel method for establishing worst case estimates of queue lenghts and transmission delays in networks of interconnected segments each of ring topology as defined by the ATOMOS project for marine automation. A non probalistic model for describing traffic is introduced as well...

  15. Real-time foresight : preparedness for dynamic innovation networks

    NARCIS (Netherlands)

    Weber, C.R.M.

    2016-01-01

    Collaborative innovation processes in unpredictable environments are a challenge for traditional management. But new demands in a global digital society push public and corporate leadership to collaborate ad hoc, without predictable goals and planned working rules. In this study, an actor-network

  16. A restructuring agenda for developing competitive retail electric markets that is based on a low-cost, real-time, smart-kilowatt-hour meter adapter

    International Nuclear Information System (INIS)

    Chasek, N.E.

    1997-01-01

    This paper proposes six agenda items that should expedite a politically smooth transition into a most efficient economically viable market-driven public power system. The agenda would introduce: the virtual marketplace for retail electric power, smart meters, smart meter readers, near-real-time load balancing and load apportionment, advanced supply and demand or commodity-style pricing, and reliability metering

  17. Design of real-time voice over internet protocol system under bandwidth network

    Science.gov (United States)

    Zhang, Li; Gong, Lina

    2017-04-01

    With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

  18. SPEED: A Stateless Protocol for Real-Time Communication in Sensor Networks

    National Research Council Canada - National Science Library

    He, Tian; Stankovic, John A; Lu, Chenyang; Abdelzaher, Tarek

    2003-01-01

    .... End-to-end soft real-time communication is achieved by maintaining a desired delivery speed across the sensor network through a novel combination of feedback control and non-deterministic geographic forwarding...

  19. Real-time stress monitoring of highway bridges with a secured wireless sensor network.

    Science.gov (United States)

    2011-12-01

    "This collaborative research aims to develop a real-time stress monitoring system for highway bridges with a secured wireless sensor network. The near term goal is to collect wireless sensor data under different traffic patterns from local highway br...

  20. Real-time security extensions for EPCglobal networks case study for the pharmaceutical industry

    CERN Document Server

    Schapranow, Matthieu-P

    2014-01-01

    This book reviews the design of real-time security extensions for EPCglobal networks based on in-memory technology, presents authentication protocols for devices with low computational resources and outlines steps for implementing history-based access control.

  1. A Statewide Private Microwave Wide Area Network for Real-time Natural Hazard Monitoring

    Science.gov (United States)

    Williams, M. C.; Kent, G.; Smith, K. D.; Plank, G.; Slater, D.; Torrisi, J.; Presser, R.; Straley, K.

    2013-12-01

    The Nevada Seismological Laboratory (NSL) at the University of Nevada, Reno, operates the Nevada Seismic Network, a collection of ground motion instruments installed throughout Nevada and California, for the purposes of detecting, locating, and notifying the public of earthquakes in the state. To perform these tasks effectively, NSL has designed and built a statewide wireless microwave wide-area network (WAN) in order to receive ground motion data in near real-time. This network consists of radio access points, backhauls, and backbone communication sites transmitting time-series, images, and datalogger diagnostics to our data center servers in Reno. This privately managed communication network greatly reduces the dependence on third-party infrastructure (e.g. commercial cellular networks), and is vital for emergency management response and system uptime. Any individual seismograph or data collection device is networked through a wireless point-to-multipoint connection to a remote access point (AP) using a low-cost radio/routerboard combination. Additional point-to-point connections from AP's to radio backhauls and/or mountaintop backbone sites allow the Data Center in Reno to communicate with and receive data directly from each datalogger. Dataloggers, radios, and routers can be configured using tablets on-site, or via desktop computers at the Data Center. Redundant mountaintop links can be added to the network and facilitate the re-routing of data (similar to a meshed network) in the event of a faulty, failing, or noisy communication site. All routers, radios, and servers, including those at the Data Center, have redundant power and can operate independently in the event of a grid power or public Internet outage. A managed server room at the Data Center processes earthquake data for notifications and acts as a data source for remote users. Consisting of about 500 hosts, and spanning hundreds of miles, this WAN provides network operators access to each router and

  2. 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.

  3. Real Time Eye Detector with Cascaded Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Bin Li

    2018-01-01

    Full Text Available An accurate and efficient eye detector is essential for many computer vision applications. In this paper, we present an efficient method to evaluate the eye location from facial images. First, a group of candidate regions with regional extreme points is quickly proposed; then, a set of convolution neural networks (CNNs is adopted to determine the most likely eye region and classify the region as left or right eye; finally, the center of the eye is located with other CNNs. In the experiments using GI4E, BioID, and our datasets, our method attained a detection accuracy which is comparable to existing state-of-the-art methods; meanwhile, our method was faster and adaptable to variations of the images, including external light changes, facial occlusion, and changes in image modality.

  4. Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

    Directory of Open Access Journals (Sweden)

    Juan Pardo

    2015-04-01

    Full Text Available Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

  5. Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

    Science.gov (United States)

    Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

    2015-01-01

    Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources. PMID:25905698

  6. Online learning algorithm for time series forecasting suitable for low cost wireless sensor networks nodes.

    Science.gov (United States)

    Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

    2015-04-21

    Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

  7. RCNF: Real-time Collaborative Network Forensic Scheme for Evidence Analysis

    OpenAIRE

    Moustafa, Nour; Slay, Jill

    2017-01-01

    Network forensic techniques help in tracking different types of cyber attack by monitoring and inspecting network traffic. However, with the high speed and large sizes of current networks, and the sophisticated philosophy of attackers, in particular mimicking normal behaviour and/or erasing traces to avoid detection, investigating such crimes demands intelligent network forensic techniques. This paper suggests a real-time collaborative network Forensic scheme (RCNF) that can monitor and inves...

  8. Privacy-preserving telecardiology sensor networks: toward a low-cost portable wireless hardware/software codesign.

    Science.gov (United States)

    Hu, Fei; Jiang, Meng; Wagner, Mark; Dong, De-Cun

    2007-11-01

    Recently, a remote-sensing platform based on wireless interconnection of tiny ECG sensors called Telecardiology Sensor Networks (TSN) provided a promising approach to perform low-cost real-time cardiac patient monitoring at any time in community areas (such as elder nursing homes or hospitals). The contribution of this research is the design of a practical TSN hardware/software platform for a typical U.S. healthcare community scenario (such as large nursing homes with many elder patients) to perform real-time healthcare data collections. On the other hand, due to the radio broadcasting nature of MANET, a TSN has the risk of losing the privacy of patients' data. Medical privacy has been highly emphasized by U.S. Department of Health and Human Services. This research also designs a medical security scheme with low communication overhead to achieve confidential electrocardiogram data transmission in wireless medium.

  9. A study on low-cost, high-accuracy, and real-time stereo vision algorithms for UAV power line inspection

    Science.gov (United States)

    Wang, Hongyu; Zhang, Baomin; Zhao, Xun; Li, Cong; Lu, Cunyue

    2018-04-01

    Conventional stereo vision algorithms suffer from high levels of hardware resource utilization due to algorithm complexity, or poor levels of accuracy caused by inadequacies in the matching algorithm. To address these issues, we have proposed a stereo range-finding technique that produces an excellent balance between cost, matching accuracy and real-time performance, for power line inspection using UAV. This was achieved through the introduction of a special image preprocessing algorithm and a weighted local stereo matching algorithm, as well as the design of a corresponding hardware architecture. Stereo vision systems based on this technique have a lower level of resource usage and also a higher level of matching accuracy following hardware acceleration. To validate the effectiveness of our technique, a stereo vision system based on our improved algorithms were implemented using the Spartan 6 FPGA. In comparative experiments, it was shown that the system using the improved algorithms outperformed the system based on the unimproved algorithms, in terms of resource utilization and matching accuracy. In particular, Block RAM usage was reduced by 19%, and the improved system was also able to output range-finding data in real time.

  10. Real-Time-Simulation of IEEE-5-Bus Network on OPAL-RT-OP4510 Simulator

    Science.gov (United States)

    Atul Bhandakkar, Anjali; Mathew, Lini, Dr.

    2018-03-01

    The Real-Time Simulator tools have high computing technologies, improved performance. They are widely used for design and improvement of electrical systems. The advancement of the software tools like MATLAB/SIMULINK with its Real-Time Workshop (RTW) and Real-Time Windows Target (RTWT), real-time simulators are used extensively in many engineering fields, such as industry, education, and research institutions. OPAL-RT-OP4510 is a Real-Time Simulator which is used in both industry and academia. In this paper, the real-time simulation of IEEE-5-Bus network is carried out by means of OPAL-RT-OP4510 with CRO and other hardware. The performance of the network is observed with the introduction of fault at various locations. The waveforms of voltage, current, active and reactive power are observed in the MATLAB simulation environment and on the CRO. Also, Load Flow Analysis (LFA) of IEEE-5-Bus network is computed using MATLAB/Simulink power-gui load flow tool.

  11. Real-time Human Activity Recognition using a Body Sensor Network

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Chen, Hanhua

    2010-01-01

    Real-time activity recognition using body sensor networks is an important and challenging task and it has many potential applications. In this paper, we propose a realtime, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network. In this mo...

  12. Experimental implementation of a real-time token-based network protocol on a microcontroller

    NARCIS (Netherlands)

    Hanssen, F.T.Y.; Krikke, Robert; Baron, Bert; Jansen, P.G.; Scholten, Johan

    The real-time token-based RTnet network protocol has been implemented on a standard Ethernet network to investigate the possibility to use cheap components with strict resource limitations while preserving Quality of Service guarantees. It will be shown that the proposed implementation is feasible

  13. Experimental implementation of a real-time token-based network protocol on a microcontroller

    NARCIS (Netherlands)

    Hanssen, F.T.Y.; Krikke, Robert; Baron, Bert; Jansen, P.G.; Scholten, Johan

    2004-01-01

    The real-time token-based RTnet network protocol has been implemented on a standard Ethernet network to investigate the possibility to use cheap components with strict resource limitations while preserving Quality of Service guarantees. It will be shown that the proposed implementation is feasible

  14. Low-Cost Ground Sensor Network for Intrusion Detection

    Science.gov (United States)

    2017-09-01

    their suitability to our research. 1. Wireless Sensor Networks The backend network infrastructure forms the communication links for the network...were not ideal as they were perpetually turned on. Our research considered the backend communication infrastructure and its power requirements when...7 3. Border Patrol— Mobile Situation Awareness Tool (MSAT

  15. Coarse-grained simulation of a real-time process control network under peak load

    International Nuclear Information System (INIS)

    George, A.D.; Clapp, N.E. Jr.

    1992-01-01

    This paper presents a simulation study on the real-time process control network proposed for the new ANS reactor system at ORNL. A background discussion is provided on networks, modeling, and simulation, followed by an overview of the ANS process control network, its three peak-load models, and the results of a series of coarse-grained simulation studies carried out on these models using implementations of 802.3, 802.4, and 802.5 standard local area networks

  16. Low cost drip irrigation in Burkina Faso : unravelling actors, networks and practices

    NARCIS (Netherlands)

    Wanvoeke, M.J.V.

    2015-01-01

    Title: Low cost drip irrigation in Burkina Faso: Unravelling Actors, Networks and Practices

    In Burkina Faso, there is a lot of enthusiasm about Low Cost Drip Irrigation (LCDI) as a tool to irrigate vegetables, and thus improve food security,

  17. Development of a Low-Cost Stem-Loop Real-Time Quantification PCR Technique for EBV miRNA Expression Analysis.

    Science.gov (United States)

    Bergallo, Massimiliano; Merlino, Chiara; Montin, Davide; Galliano, Ilaria; Gambarino, Stefano; Mareschi, Katia; Fagioli, Franca; Montanari, Paola; Martino, Silvana; Tovo, Pier-Angelo

    2016-09-01

    MicroRNAs (miRNAs) are short, single stranded, non-coding RNA molecules. They are produced by many different species and are key regulators of several physiological processes. miRNAs are also encoded by the genomes of multiple virus families, such as herpesvirus family. In particular, miRNAs from Epstein Barr virus were found at high concentrations in different associated pathologies, such as Burkitt's lymphoma, Hodgkin disease, and nasopharyngeal carcinoma. Thanks to their stability, these molecules could possibly serve as biomarkers for EBV-associated diseases. In this study, a stem-loop real-time PCR for miR-BART2-5p, miR-BART15, and miR-BART22 EBV miRNAs detection and quantification has been developed. Evaluation of these miRNAs in 31 serum samples (12 from patients affected by primary immunodeficiency, 9 from X-linked agammaglobulinemia and 10 from healthy subjects) has been carried out. The amplification performance showed a wide dynamic range (10(8)-10(2) copies/reaction) and sensibility equal to 10(2) copies/reaction for all the target tested. Serum samples analysis, on the other hand, showed a statistical significant higher level of miR-BART22 in primary immunodeficiency patients (P = 0.0001) compared to other groups and targets. The results confirmed the potential use of this assay as a tool for monitoring EBV-associated disease and for miRNAs expression profile analysis.

  18. Low Cost Wireless Sensor Network for Continuous Bridge monitoring

    DEFF Research Database (Denmark)

    Han, Bo; Kalis, A; Tragas, P

    2012-01-01

    Continuous monitoring wireless sensor networks (WSN) are considered as one of the most promising means to harvest information from large structures in order to assist in structural health monitoring and management. At the same time, continuous monitoring WSNs suffer from limited network lifetimes...

  19. Starling flock networks manage uncertainty in consensus at low cost.

    Directory of Open Access Journals (Sweden)

    George F Young

    Full Text Available Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors. We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks.

  20. Starling Flock Networks Manage Uncertainty in Consensus at Low Cost

    Science.gov (United States)

    Young, George F.; Scardovi, Luca; Cavagna, Andrea; Giardina, Irene; Leonard, Naomi E.

    2013-01-01

    Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors). We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks. PMID:23382667

  1. Network Coded Cooperative Communication in a Real-Time Wireless Hospital Sensor Network.

    Science.gov (United States)

    Prakash, R; Balaji Ganesh, A; Sivabalan, Somu

    2017-05-01

    The paper presents a network coded cooperative communication (NC-CC) enabled wireless hospital sensor network architecture for monitoring health as well as postural activities of a patient. A wearable device, referred as a smartband is interfaced with pulse rate, body temperature sensors and an accelerometer along with wireless protocol services, such as Bluetooth and Radio-Frequency transceiver and Wi-Fi. The energy efficiency of wearable device is improved by embedding a linear acceleration based transmission duty cycling algorithm (NC-DRDC). The real-time demonstration is carried-out in a hospital environment to evaluate the performance characteristics, such as power spectral density, energy consumption, signal to noise ratio, packet delivery ratio and transmission offset. The resource sharing and energy efficiency features of network coding technique are improved by proposing an algorithm referred as network coding based dynamic retransmit/rebroadcast decision control (LA-TDC). From the experimental results, it is observed that the proposed LA-TDC algorithm reduces network traffic and end-to-end delay by an average of 27.8% and 21.6%, respectively than traditional network coded wireless transmission. The wireless architecture is deployed in a hospital environment and results are then successfully validated.

  2. Real-Time Tele-Mentored Low Cost "Point-of-Care US" in the Hands of Paediatricians in the Emergency Department: Diagnostic Accuracy Compared to Expert Radiologists.

    Directory of Open Access Journals (Sweden)

    Floriana Zennaro

    Full Text Available The use of point-of-care ultrasonography (POC US in paediatrics is increasing. This study investigated the diagnostic accuracy of POC US in children accessing the emergency department (ED when performed by paediatricians under the remote guidance of radiologists (TELE POC.Children aged 0 to 18 years accessing the ED of a third level research hospital with eight possible clinical scenarios and without emergency/severity signs at the triage underwent three subsequent US tests: by a paediatrician guided remotely by a radiologist (TELE POC; by the same radiologist (UNBLIND RAD; by an independent blinded radiologist (BLIND RAD. Tele-radiology was implemented using low cost "commercial off-the-shelf" (COTS equipment and open-source software. Data were prospectively collected on predefined templates.Fifty-two children were enrolled, for a total of 170 ultrasound findings. Sensitivity, specificity, positive and negative predictive values of TELE POC were: 93.8, 99.7, 96.8, 99.4 when compared to UNBLIND RAD and 88.2, 99.7, 96.8, 98.7 when compared to BLIND RAD. The inter-observers agreement between the paediatricians and either the unblind or blind radiologist was excellent (k = 0.93. The mean duration of TELE POC was 6.3 minutes (95% CI 4.1 to 8.5. Technical difficulties occurred in two (3.8% cases. Quality of the transmission was rated as fair, good, very good and excellent in 7.7%, 15.4%, 42.3% and 34.6% of cases respectively, while in no case was it rated as poor.POC US performed by paediatricians in ED guided via tele-radiology by an expert radiologist (TELE POC produced reliable and timely diagnoses. Findings of this study, especially for the rarer conditions under evaluation, need further confirmation. Future research should investigate the overall benefits and the cost savings of using tele-ultrasound to perform US "at children's bedsides", under remote guidance of expert radiologists.

  3. GTRF: a game theory approach for regulating node behavior in real-time wireless sensor networks.

    Science.gov (United States)

    Lin, Chi; Wu, Guowei; Pirozmand, Poria

    2015-06-04

    The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes' behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime.

  4. Electric space heating scheduling for real-time explicit power control in active distribution networks

    DEFF Research Database (Denmark)

    Costanzo, Giuseppe Tommaso; Bernstein, Andrey; Chamorro, Lorenzo Reyes

    2015-01-01

    This paper presents a systematic approach for abstracting the flexibility of a building space heating system and using it within a composable framework for real-time explicit power control of microgrids and, more in general, active distribution networks. In particular, the proposed approach...... is developed within the context of a previously defined microgrid control framework, called COMMELEC, conceived for the explicit and real-time control of these specific networks. The designed control algorithm is totally independent from the need of a building model and allows exploiting the intrinsic thermal...... inertia for real-time control. The paper first discusses the general approach, then it proves its validity via dedicated simulations performed on specific case study composed by the CIGRE LV microgrid benchmark proposed by the Cigré TF C6.04.02....

  5. Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback.

    Science.gov (United States)

    Ramot, Michal; Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

    2017-09-16

    The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants' awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.

  6. Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

    Science.gov (United States)

    Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

    2017-01-01

    The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns. PMID:28917059

  7. Real-time video streaming in mobile cloud over heterogeneous wireless networks

    Science.gov (United States)

    Abdallah-Saleh, Saleh; Wang, Qi; Grecos, Christos

    2012-06-01

    Recently, the concept of Mobile Cloud Computing (MCC) has been proposed to offload the resource requirements in computational capabilities, storage and security from mobile devices into the cloud. Internet video applications such as real-time streaming are expected to be ubiquitously deployed and supported over the cloud for mobile users, who typically encounter a range of wireless networks of diverse radio access technologies during their roaming. However, real-time video streaming for mobile cloud users across heterogeneous wireless networks presents multiple challenges. The network-layer quality of service (QoS) provision to support high-quality mobile video delivery in this demanding scenario remains an open research question, and this in turn affects the application-level visual quality and impedes mobile users' perceived quality of experience (QoE). In this paper, we devise a framework to support real-time video streaming in this new mobile video networking paradigm and evaluate the performance of the proposed framework empirically through a lab-based yet realistic testing platform. One particular issue we focus on is the effect of users' mobility on the QoS of video streaming over the cloud. We design and implement a hybrid platform comprising of a test-bed and an emulator, on which our concept of mobile cloud computing, video streaming and heterogeneous wireless networks are implemented and integrated to allow the testing of our framework. As representative heterogeneous wireless networks, the popular WLAN (Wi-Fi) and MAN (WiMAX) networks are incorporated in order to evaluate effects of handovers between these different radio access technologies. The H.264/AVC (Advanced Video Coding) standard is employed for real-time video streaming from a server to mobile users (client nodes) in the networks. Mobility support is introduced to enable continuous streaming experience for a mobile user across the heterogeneous wireless network. Real-time video stream packets

  8. AmbientRT - real time system software support for data centric sensor networks

    NARCIS (Netherlands)

    Hofmeijer, T.J.; Dulman, S.O.; Jansen, P.G.; Havinga, Paul J.M.

    We present the architecture and design of a real time operating system for mobile wireless sensor networks. AmbientRT is being developed for environments with very limited resources in order to relieve the burden of the developer and to efficiently use the resources of the node. This paper presents

  9. A real-time networked camera system : a scheduled distributed camera system reduces the latency

    NARCIS (Netherlands)

    Karatoy, H.

    2012-01-01

    This report presents the results of a Real-time Networked Camera System, com-missioned by the SAN Group in TU/e. Distributed Systems are motivated by two reasons, the first reason is the physical environment as a requirement and the second reason is to provide a better Quality of Service (QoS). This

  10. AmbientRT - real time system software support for data centric sensor networks

    NARCIS (Netherlands)

    Hofmeijer, T.J.; Dulman, S.O.; Jansen, P.G.; Havinga, Paul J.M.

    2004-01-01

    We present the architecture and design of a real time operating system for mobile wireless sensor networks. AmbientRT is being developed for environments with very limited resources in order to relieve the burden of the developer and to efficiently use the resources of the node. This paper presents

  11. A Statically Scheduled Time-Division-Multiplexed Network-on-Chip for Real-Time Systems

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Brandner, Florian; Sparsø, Jens

    2012-01-01

    This paper explores the design of a circuit-switched network-on-chip (NoC) based on time-division-multiplexing (TDM) for use in hard real-time systems. Previous work has primarily considered application-specific systems. The work presented here targets general-purpose hardware platforms. We...

  12. Time synchronization for an Ethernet-based real-time token network

    NARCIS (Netherlands)

    Hanssen, F.T.Y.; van den Boom, Joost; Jansen, P.G.; Scholten, Johan

    We present a distributed clock synchronization algorithm. It performs clock synchronization on an Ethernet-based real-time token local area network, without the use of an external clock source. It is used to enable the token schedulers in each node to agree upon a common time. Its intended use is in

  13. Data Centric Sensor Stream Reduction for Real-Time Applications in Wireless Sensor Networks

    Science.gov (United States)

    Aquino, Andre Luiz Lins; Nakamura, Eduardo Freire

    2009-01-01

    This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness. PMID:22303145

  14. Real-Time QoS Routing Protocols in Wireless Multimedia Sensor Networks: Study and Analysis.

    Science.gov (United States)

    Alanazi, Adwan; Elleithy, Khaled

    2015-09-02

    Many routing protocols have been proposed for wireless sensor networks. These routing protocols are almost always based on energy efficiency. However, recent advances in complementary metal-oxide semiconductor (CMOS) cameras and small microphones have led to the development of Wireless Multimedia Sensor Networks (WMSN) as a class of wireless sensor networks which pose additional challenges. The transmission of imaging and video data needs routing protocols with both energy efficiency and Quality of Service (QoS) characteristics in order to guarantee the efficient use of the sensor nodes and effective access to the collected data. Also, with integration of real time applications in Wireless Senor Networks (WSNs), the use of QoS routing protocols is not only becoming a significant topic, but is also gaining the attention of researchers. In designing an efficient QoS routing protocol, the reliability and guarantee of end-to-end delay are critical events while conserving energy. Thus, considerable research has been focused on designing energy efficient and robust QoS routing protocols. In this paper, we present a state of the art research work based on real-time QoS routing protocols for WMSNs that have already been proposed. This paper categorizes the real-time QoS routing protocols into probabilistic and deterministic protocols. In addition, both categories are classified into soft and hard real time protocols by highlighting the QoS issues including the limitations and features of each protocol. Furthermore, we have compared the performance of mobility-aware query based real-time QoS routing protocols from each category using Network Simulator-2 (NS2). This paper also focuses on the design challenges and future research directions as well as highlights the characteristics of each QoS routing protocol.

  15. Low-cost Augmented Reality prototype for controlling network devices

    OpenAIRE

    Nguyen, Anh; Banic, Amy

    2014-01-01

    With the evolution of mobile devices, and smart-phones in particular, comes the ability to create new experiences that enhance the way we see, interact, and manipulate objects, within the world that surrounds us. It is now possible to blend data from our senses and our devices in numerous ways that simply were not possible before using Augmented Reality technology. In a near future, when all of the office devices as well as your personal electronic gadgets are on a common wireless network, op...

  16. Nuclear power plant monitoring using real-time learning neural network

    International Nuclear Information System (INIS)

    Nabeshima, Kunihiko; Tuerkcan, E.; Ciftcioglu, O.

    1994-01-01

    In the present research, artificial neural network (ANN) with real-time adaptive learning is developed for the plant wide monitoring of Borssele Nuclear Power Plant (NPP). Adaptive ANN learning capability is integrated to the monitoring system so that robust and sensitive on-line monitoring is achieved in real-time environment. The major advantages provided by ANN are that system modelling is formed by means of measurement information obtained from a multi-output process system, explicit modelling is not required and the modelling is not restricted to linear systems. Also ANN can respond very fast to anomalous operational conditions. The real-time ANN learning methodology with adaptive real-time monitoring capability is described below for the wide-range and plant-wide data from an operating nuclear power plant. The layered neural network with error backpropagation algorithm for learning has three layers. The network type is auto-associative, inputs and outputs are exactly the same, using 12 plant signals. (author)

  17. Timing System Solution for MedAustron; Real-time Event and Data Distribution Network

    CERN Document Server

    Štefanič, R; Dedič, J; Gutleber, J; Moser, R

    2011-01-01

    MedAustron is an ion beam research and therapy centre under construction in Wiener Neustadt, Austria. The facility features a synchrotron particle accelerator for light ions. The timing system for this class of accelerators has been developed in close collaboration between MedAustron and Cosylab. Mitigating economical and technological risks, we have chosen a proven, widely used Micro Research Finland (MRF) timing equipment and redesigned its FPGA firmware, extending its high-logic services above transport layer, as required by machine specifics. We obtained a generic real-time broadcast network for coordinating actions of a compact, pulse-to-pulse modulation based particle accelerator. High-level services include support for virtual accelerators and a rich selection of event response mechanisms. The system uses a combination of a real-time link for downstream events and a non-real-time link for upstream messaging and non time-critical communication. It comes with National Instruments LabVI...

  18. Real-Time Congestion Management in Distribution Networks by Flexible Demand Swap

    DEFF Research Database (Denmark)

    Huang, Shaojun; Wu, Qiuwei

    2017-01-01

    In addition to the day-ahead congestion management in distribution networks, the real-time congestion management is very important because many unforeseen events can occur at the real operation time, e.g. loss of generation of distributed energy resources (DERs) or inaccurate forecast of energy...... pumps (HPs) for real time congestion management. The swap method can maintain the power balance of the system and avoid the imbalance cost of activating the flexibility service. An algorithm for forming swaps through optimal power flow (OPF) and mixed integer linear programming (MILP) is proposed...... consumption or production. Flexibility service from demand will be a good option to solve the real-time congestions if the cost of activating the flexibility service is fully addressed. This paper proposes a new method, namely “swap”, to employ the flexibility service from electric vehicles (EVs) and heat...

  19. Timing system solution for MedAustron; Real-time event and data distribution network

    International Nuclear Information System (INIS)

    Stefanic, R.; Tavcar, R.; Dedic, J.; Gutleber, J.; Moser, R.

    2012-01-01

    MedAustron is an ion beam research and therapy centre under construction in Wiener Neustadt, Austria. The facility features a synchrotron particle accelerator for light ions. The timing system for this class of accelerators has been developed in close collaboration between MedAustron and Cosylab. Mitigating economical and technological risks, we have chosen a proven, widely used Micro Research Finland (MRF) timing equipment and redesigned its FPGA firmware, extending its high-logic services above transport layer, as required by machine specifics. We obtained a generic real-time broadcast network for coordinating actions of a compact, pulse-to-pulse modulation based particle accelerator. High-level services include support for virtual accelerators and a rich selection of event response mechanisms. The system uses a combination of a real-time link for downstream events and a non-real-time link for upstream messaging and non time-critical communication. It comes with National Instruments LabVIEW-based software support, ready to be integrated into PXIe based front-end controllers. This article explains the high level logic services provided by the real-time link, describes the non-real-time interfaces and presents the software configuration mechanisms. (authors)

  20. Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

    Science.gov (United States)

    Mori, Shinichiro

    2017-08-01

    To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  1. Connection with seismic networks and construction of real time earthquake monitoring system

    International Nuclear Information System (INIS)

    Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S.

    2000-12-01

    It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system

  2. A real-time hybrid neuron network for highly parallel cognitive systems.

    Science.gov (United States)

    Christiaanse, Gerrit Jan; Zjajo, Amir; Galuzzi, Carlo; van Leuken, Rene

    2016-08-01

    For comprehensive understanding of how neurons communicate with each other, new tools need to be developed that can accurately mimic the behaviour of such neurons and neuron networks under `real-time' constraints. In this paper, we propose an easily customisable, highly pipelined, neuron network design, which executes optimally scheduled floating-point operations for maximal amount of biophysically plausible neurons per FPGA family type. To reduce the required amount of resources without adverse effect on the calculation latency, a single exponent instance is used for multiple neuron calculation operations. Experimental results indicate that the proposed network design allows the simulation of up to 1188 neurons on Virtex7 (XC7VX550T) device in brain real-time yielding a speed-up of x12.4 compared to the state-of-the art.

  3. Neural network evaluation of tokamak current profiles for real time control (abstract)

    Science.gov (United States)

    Wróblewski, Dariusz

    1997-01-01

    Active feedback control of the current profile, requiring real-time determination of the current profile parameters, is envisioned for tokamaks operating in enhanced confinement regimes. The distribution of toroidal current in a tokamak is now routinely evaluated based on external (magnetic probes, flux loops) and internal (motional Stark effect) measurements of the poloidal magnetic field. However, the analysis involves reconstruction of magnetohydrodynamic equilibrium and is too intensive computationally to be performed in real time. In the present study, a neural network is used to provide a mapping from the magnetic measurements (internal and external) to selected parameters of the safety factor profile. The single-pass, feedforward calculation of output of a trained neural network is very fast, making this approach particularly suitable for real-time applications. The network was trained on a large set of simulated equilibrium data for the DIII-D tokamak. The database encompasses a large variety of current profiles including the hollow current profiles important for reversed central shear operation. The parameters of safety factor profile (a quantity related to the current profile through the magnetic field tilt angle) estimated by the neural network include central safety factor, q0, minimum value of q, qmin, and the location of qmin. Very good performance of the trained neural network both for simulated test data and for experimental data is demonstrated.

  4. Neural network evaluation of tokamak current profiles for real time control

    Science.gov (United States)

    Wróblewski, Dariusz

    1997-02-01

    Active feedback control of the current profile, requiring real-time determination of the current profile parameters, is envisioned for tokamaks operating in enhanced confinement regimes. The distribution of toroidal current in a tokamak is now routinely evaluated based on external (magnetic probes, flux loops) and internal (motional Stark effect) measurements of the poloidal magnetic field. However, the analysis involves reconstruction of magnetohydrodynamic equilibrium and is too intensive computationally to be performed in real time. In the present study, a neural network is used to provide a mapping from the magnetic measurements (internal and external) to selected parameters of the safety factor profile. The single-pass, feedforward calculation of output of a trained neural network is very fast, making this approach particularly suitable for real-time applications. The network was trained on a large set of simulated equilibrium data for the DIII-D tokamak. The database encompasses a large variety of current profiles including the hollow current profiles important for reversed central shear operation. The parameters of safety factor profile (a quantity related to the current profile through the magnetic field tilt angle) estimated by the neural network include central safety factor, q0, minimum value of q, qmin, and the location of qmin. Very good performance of the trained neural network both for simulated test data and for experimental datais demonstrated.

  5. Neural network evaluation of tokamak current profiles for real time control

    International Nuclear Information System (INIS)

    Wroblewski, D.

    1997-01-01

    Active feedback control of the current profile, requiring real-time determination of the current profile parameters, is envisioned for tokamaks operating in enhanced confinement regimes. The distribution of toroidal current in a tokamak is now routinely evaluated based on external (magnetic probes, flux loops) and internal (motional Stark effect) measurements of the poloidal magnetic field. However, the analysis involves reconstruction of magnetohydrodynamic equilibrium and is too intensive computationally to be performed in real time. In the present study, a neural network is used to provide a mapping from the magnetic measurements (internal and external) to selected parameters of the safety factor profile. The single-pass, feedforward calculation of output of a trained neural network is very fast, making this approach particularly suitable for real-time applications. The network was trained on a large set of simulated equilibrium data for the DIII-D tokamak. The database encompasses a large variety of current profiles including the hollow current profiles important for reversed central shear operation. The parameters of safety factor profile (a quantity related to the current profile through the magnetic field tilt angle) estimated by the neural network include central safety factor, q 0 , minimum value of q, q min , and the location of q min . Very good performance of the trained neural network both for simulated test data and for experimental datais demonstrated. copyright 1997 American Institute of Physics

  6. Neural network evaluation of tokamak current profiles for real time control (abstract)

    International Nuclear Information System (INIS)

    Wroblewski, D.

    1997-01-01

    Active feedback control of the current profile, requiring real-time determination of the current profile parameters, is envisioned for tokamaks operating in enhanced confinement regimes. The distribution of toroidal current in a tokamak is now routinely evaluated based on external (magnetic probes, flux loops) and internal (motional Stark effect) measurements of the poloidal magnetic field. However, the analysis involves reconstruction of magnetohydrodynamic equilibrium and is too intensive computationally to be performed in real time. In the present study, a neural network is used to provide a mapping from the magnetic measurements (internal and external) to selected parameters of the safety factor profile. The single-pass, feedforward calculation of output of a trained neural network is very fast, making this approach particularly suitable for real-time applications. The network was trained on a large set of simulated equilibrium data for the DIII-D tokamak. The database encompasses a large variety of current profiles including the hollow current profiles important for reversed central shear operation. The parameters of safety factor profile (a quantity related to the current profile through the magnetic field tilt angle) estimated by the neural network include central safety factor, q 0 , minimum value of q, q min , and the location of q min . Very good performance of the trained neural network both for simulated test data and for experimental data is demonstrated. copyright 1997 American Institute of Physics

  7. Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

    Science.gov (United States)

    Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

  8. Real-time multiple networked viewer capability of the DIII-D EC data acquisition system

    International Nuclear Information System (INIS)

    Ponce, D.; Gorelov, I.A.; Chiu, H.K.; Baity, F.W.

    2005-01-01

    A data acquisition system (DAS) which permits real-time viewing by multiple locally networked operators is being implemented for the electron cyclotron (EC) heating and current drive system at DIII-D. The DAS is expected to demonstrate performance equivalent to standalone oscilloscopes. Participation by remote viewers, including throughout the greater DIII-D facility, can also be incorporated. The real-time system uses one computer-controlled DAS per gyrotron. The DAS computers send their data to a central data server using individual and dedicated 200 Mbps fully duplexed Ethernet connections. The server has a dedicated 10 krpm hard drive for each gyrotron DAS. Selected channels can then be reprocessed and distributed to viewers over a standard local area network (LAN). They can also be bridged from the LAN to the internet. Calculations indicate that the hardware will support real-time writing of each channel at full resolution to the server hard drives. The data will be re-sampled for distribution to multiple viewers over the LAN in real-time. The hardware for this system is in place. The software is under development. This paper will present the design details and up-to-date performance metrics of the system

  9. Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

    Science.gov (United States)

    Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

    2016-08-01

    This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

  10. An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks.

    Science.gov (United States)

    Pani, Danilo; Meloni, Paolo; Tuveri, Giuseppe; Palumbo, Francesca; Massobrio, Paolo; Raffo, Luigi

    2017-01-01

    In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments.

  11. High reliable and Real-time Data Communication Network Technology for Nuclear Power Plant

    International Nuclear Information System (INIS)

    Jeong, K. I.; Lee, J. K.; Choi, Y. R.; Lee, J. C.; Choi, Y. S.; Cho, J. W.; Hong, S. B.; Jung, J. E.; Koo, I. S.

    2008-03-01

    As advanced digital Instrumentation and Control (I and C) system of NPP(Nuclear Power Plant) are being introduced to replace analog systems, a Data Communication Network(DCN) is becoming the important system for transmitting the data generated by I and C systems in NPP. In order to apply the DCNs to NPP I and C design, DCNs should conform to applicable acceptance criteria and meet the reliability and safety goals of the system. As response time is impacted by the selected protocol, network topology, network performance, and the network configuration of I and C system, DCNs should transmit a data within time constraints and response time required by I and C systems to satisfy response time requirements of I and C system. To meet these requirements, the DCNs of NPP I and C should be a high reliable and real-time system. With respect to high reliable and real-time system, several reports and techniques having influences upon the reliability and real-time requirements of DCNs are surveyed and analyzed

  12. Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System.

    Science.gov (United States)

    Wu, Fan; Rüdiger, Christoph; Yuce, Mehmet Rasit

    2017-02-01

    Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting.

  13. Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System

    Directory of Open Access Journals (Sweden)

    Fan Wu

    2017-02-01

    Full Text Available Wireless sensor networks (WSNs play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT, many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting.

  14. Contribution to the improvement of the performance of wireless mesh networks providing real time services

    OpenAIRE

    Vázquez Rodas, Andrés Marcelo

    2015-01-01

    Nowadays, people expectations for ubiquitous connectivity is continuously growing. Cities are now moving towards the smart city paradigm. Electricity companies aims to become part of smart grids. Internet is no longer exclusive for humans, we now assume the Internet of everything. We consider that Wireless Mesh Networks (WMNs) have a set of valuable features that will make it an important part of such environments. WMNs can also be use in less favored areas thanks to their low-cost deployment...

  15. Neural Network Based Real-time Correction of Transducer Dynamic Errors

    Science.gov (United States)

    Roj, J.

    2013-12-01

    In order to carry out real-time dynamic error correction of transducers described by a linear differential equation, a novel recurrent neural network was developed. The network structure is based on solving this equation with respect to the input quantity when using the state variables. It is shown that such a real-time correction can be carried out using simple linear perceptrons. Due to the use of a neural technique, knowledge of the dynamic parameters of the transducer is not necessary. Theoretical considerations are illustrated by the results of simulation studies performed for the modeled second order transducer. The most important properties of the neural dynamic error correction, when emphasizing the fundamental advantages and disadvantages, are discussed.

  16. Advanced Visualization System for Monitoring the ATLAS TDAQ Network in real-time

    CERN Document Server

    Batraneanu, S M; The ATLAS collaboration; Martin, B; Savu, D O; Stancu, S N; Leahu, L

    2012-01-01

    The trigger and data acquisition (TDAQ) system of the ATLAS experiment at CERN comprises approximately 2500 servers interconnected by three separate Ethernet networks, totaling 250 switches. Due to its real-time nature, there are additional requirements in comparison to conventional networks in terms of speed and performance. A comprehensive monitoring framework has been developed for expert use. However, non experts may experience difficulties in using it and interpreting data. Moreover, specific performance issues, such as single component saturation or unbalanced workload, need to be spotted with ease, in real-time, and understood in the context of the full system view. We addressed these issues by developing an innovative visualization system where the users benefit from the advantages of 3D graphics to visualize the large monitoring parameter space associated with our system. This has been done by developing a hierarchical model of the complete system onto which we overlaid geographical, logical and real...

  17. REAL-TIME VIDEO SCALING BASED ON CONVOLUTION NEURAL NETWORK ARCHITECTURE

    OpenAIRE

    S Safinaz; A V Ravi Kumar

    2017-01-01

    In recent years, video super resolution techniques becomes mandatory requirements to get high resolution videos. Many super resolution techniques researched but still video super resolution or scaling is a vital challenge. In this paper, we have presented a real-time video scaling based on convolution neural network architecture to eliminate the blurriness in the images and video frames and to provide better reconstruction quality while scaling of large datasets from lower resolution frames t...

  18. Memristive Computational Architecture of an Echo State Network for Real-Time Speech Emotion Recognition

    Science.gov (United States)

    2015-05-28

    recognition is simpler and requires less computational resources compared to other inputs such as facial expressions . The Berlin database of Emotional ...Processing Magazine, IEEE, vol. 18, no. 1, pp. 32– 80, 2001. [15] K. R. Scherer, T. Johnstone, and G. Klasmeyer, “Vocal expression of emotion ...Network for Real-Time Speech- Emotion Recognition 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62788F 6. AUTHOR(S) Q

  19. Real-Time Dynamics in U(1 Lattice Gauge Theories with Tensor Networks

    Directory of Open Access Journals (Sweden)

    T. Pichler

    2016-03-01

    Full Text Available Tensor network algorithms provide a suitable route for tackling real-time-dependent problems in lattice gauge theories, enabling the investigation of out-of-equilibrium dynamics. We analyze a U(1 lattice gauge theory in (1+1 dimensions in the presence of dynamical matter for different mass and electric-field couplings, a theory akin to quantum electrodynamics in one dimension, which displays string breaking: The confining string between charges can spontaneously break during quench experiments, giving rise to charge-anticharge pairs according to the Schwinger mechanism. We study the real-time spreading of excitations in the system by means of electric-field and particle fluctuations. We determine a dynamical state diagram for string breaking and quantitatively evaluate the time scales for mass production. We also show that the time evolution of the quantum correlations can be detected via bipartite von Neumann entropies, thus demonstrating that the Schwinger mechanism is tightly linked to entanglement spreading. To present a variety of possible applications of this simulation platform, we show how one could follow the real-time scattering processes between mesons and the creation of entanglement during scattering processes. Finally, we test the quality of quantum simulations of these dynamics, quantifying the role of possible imperfections in cold atoms, trapped ions, and superconducting circuit systems. Our results demonstrate how entanglement properties can be used to deepen our understanding of basic phenomena in the real-time dynamics of gauge theories such as string breaking and collisions.

  20. Use of high performance networks and supercomputers for real-time flight simulation

    Science.gov (United States)

    Cleveland, Jeff I., II

    1993-01-01

    In order to meet the stringent time-critical requirements for real-time man-in-the-loop flight simulation, computer processing operations must be consistent in processing time and be completed in as short a time as possible. These operations include simulation mathematical model computation and data input/output to the simulators. In 1986, in response to increased demands for flight simulation performance, NASA's Langley Research Center (LaRC), working with the contractor, developed extensions to the Computer Automated Measurement and Control (CAMAC) technology which resulted in a factor of ten increase in the effective bandwidth and reduced latency of modules necessary for simulator communication. This technology extension is being used by more than 80 leading technological developers in the United States, Canada, and Europe. Included among the commercial applications are nuclear process control, power grid analysis, process monitoring, real-time simulation, and radar data acquisition. Personnel at LaRC are completing the development of the use of supercomputers for mathematical model computation to support real-time flight simulation. This includes the development of a real-time operating system and development of specialized software and hardware for the simulator network. This paper describes the data acquisition technology and the development of supercomputing for flight simulation.

  1. Flying Real-Time Network to Coordinate Disaster Relief Activities in Urban Areas

    Directory of Open Access Journals (Sweden)

    Matias Micheletto

    2018-05-01

    Full Text Available While there have been important advances within wireless communication technology, the provision of communication support during disaster relief activities remains an open issue. The literature in disaster research reports several major restrictions to conducting first response activities in urban areas, given the limitations of telephone networks and radio systems to provide digital communication in the field. In search-and-rescue operations, the communication requirements are increased, since the first responders need to rely on real-time and reliable communication to perform their activities and coordinate their efforts with other teams. Therefore, these limitations open the door to improvisation during disaster relief efforts. In this paper, we argue that flying ad-hoc networks can provide the communication support needed in these scenarios, and propose a new solution towards that goal. The proposal involves the use of flying witness units, implemented using drones, that act as communication gateways between first responders working at different locations of the affected area. The proposal is named the Flying Real-Time Network, and its feasibility to provide communication in a disaster scenario is shown by presenting both a real-time schedulability analysis of message delivery, as well as simulations of the communication support in a physical scenario inspired by a real incident. The obtained results were highly positive and consistent, therefore this proposal represents a step forward towards the solution of this open issue.

  2. Flying Real-Time Network to Coordinate Disaster Relief Activities in Urban Areas †

    Science.gov (United States)

    Micheletto, Matias; Orozco, Javier; Mosse, Daniel

    2018-01-01

    While there have been important advances within wireless communication technology, the provision of communication support during disaster relief activities remains an open issue. The literature in disaster research reports several major restrictions to conducting first response activities in urban areas, given the limitations of telephone networks and radio systems to provide digital communication in the field. In search-and-rescue operations, the communication requirements are increased, since the first responders need to rely on real-time and reliable communication to perform their activities and coordinate their efforts with other teams. Therefore, these limitations open the door to improvisation during disaster relief efforts. In this paper, we argue that flying ad-hoc networks can provide the communication support needed in these scenarios, and propose a new solution towards that goal. The proposal involves the use of flying witness units, implemented using drones, that act as communication gateways between first responders working at different locations of the affected area. The proposal is named the Flying Real-Time Network, and its feasibility to provide communication in a disaster scenario is shown by presenting both a real-time schedulability analysis of message delivery, as well as simulations of the communication support in a physical scenario inspired by a real incident. The obtained results were highly positive and consistent, therefore this proposal represents a step forward towards the solution of this open issue. PMID:29789458

  3. Performance evaluation of an interactive teleradiology system for real-time teleconsultation in different network environments

    International Nuclear Information System (INIS)

    Lian Ping; Gong Jun; Zhuang Jun; Sun Jianyong; Yang Yuanyuan; Zhang Jianguo; Meng Lili

    2004-01-01

    Objective: Measure the performance of self-developed Interoperable teleradiology system at various communication conditions. Methods: Through three different network media ( satellite network, Asymmetrical Digital Subscriber Loop (ADSL), and Shanghai health system's private broadband WAN), Digital images in radiology were transmitted and experiments on teleradiology consultation were applied. Results such as transmission time were recorded, effects of real-time consultation were evaluated subjectively, and experimental data were analyzed. Results: In satellite network, time spent on the transmission of images is long and effects of consultation is normal; in broadband network, time spent is short and no delay is observed in interoperation. Conclusion: teleconsultation can be hold on image sets composed of small matrix size images and compressed large matrix size images in satellite narrowband network, optimum transmission bandwidth is 192 kbps; original large matrix size images such as CR can be transmitted through broadband network and be used in teleconsultation. Real-time interoperation of the system doesn't require very high bandwidth. It can be implemented at various communication conditions

  4. Packets with deadlines a framework for real-time wireless networks

    CERN Document Server

    Hou, I-Hong

    2013-01-01

    With the explosive increase in the number of mobile devices and applications, it is anticipated that wireless traffic will increase exponentially in the coming years. Moreover, future wireless networks all carry a wide variety of flows, such as video streaming, online gaming, and VoIP, which have various quality of service (QoS) requirements. Therefore, a new mechanism that can provide satisfactory performance to the complete variety of all kinds of flows, in a coherent and unified framework, is needed.In this book, we introduce a framework for real-time wireless networks. This consists of a m

  5. Isochronous wireless network for real-time communication in industrial automation

    CERN Document Server

    Trsek, Henning

    2016-01-01

    This dissertation proposes and investigates an isochronous wireless network for industrial control applications with guaranteed latencies and jitter. Based on a requirements analysis of real industrial applications and the characterisation of the wireless channel, the solution approach is developed. It consists of a TDMA-based medium access control, a dynamic resource allocation and the provision of a global time base for the wired and the wireless network. Due to the global time base, the solution approach allows a seamless and synchronous integration into existing wired Real-time Ethernet systems.

  6. RENEW: a real-time and effective network emulator of windows for IPv6

    Science.gov (United States)

    Zhao, Bing; Jin, Zhigang; Shu, Yantai; Li, Yu; Cen, Dan

    2007-09-01

    Although IPv4 is still working, IPv6 is considered as the backbone and characteristic of the NGI. With the development of Internet, new protocols and network equipments are required to develop. It is necessary to test the new protocols and network equipments extensively before deployment. This paper proposes the design and implementation of RENEW, a useable and accurate network emulator which supports both IPv4 and IPv6 protocols. Besides, it also works on Windows platform. In our IPv6 testbed, we use RENEW to emulate various network characteristics and conditions including bandwidth, delay packet loss and jitter. Compared with the expected values, results are acceptable. Through implementation and experimentation study, we have shown that RENEW does provide the real-time control and change on the parameters of IPv6 network conditions effectively and expediently on Windows. It also gives enough accuracy and more satisfactory convenience to the development and test work for the new protocols.

  7. Architecture for an integrated real-time air combat and sensor network simulation

    Science.gov (United States)

    Criswell, Evans A.; Rushing, John; Lin, Hong; Graves, Sara

    2007-04-01

    An architecture for an integrated air combat and sensor network simulation is presented. The architecture integrates two components: a parallel real-time sensor fusion and target tracking simulation, and an air combat simulation. By integrating these two simulations, it becomes possible to experiment with scenarios in which one or both sides in a battle have very large numbers of primitive passive sensors, and to assess the likely effects of those sensors on the outcome of the battle. Modern Air Power is a real-time theater-level air combat simulation that is currently being used as a part of the USAF Air and Space Basic Course (ASBC). The simulation includes a variety of scenarios from the Vietnam war to the present day, and also includes several hypothetical future scenarios. Modern Air Power includes a scenario editor, an order of battle editor, and full AI customization features that make it possible to quickly construct scenarios for any conflict of interest. The scenario editor makes it possible to place a wide variety of sensors including both high fidelity sensors such as radars, and primitive passive sensors that provide only very limited information. The parallel real-time sensor network simulation is capable of handling very large numbers of sensors on a computing cluster of modest size. It can fuse information provided by disparate sensors to detect and track targets, and produce target tracks.

  8. Incorporating Low-Cost Seismometers into the Central Weather Bureau Seismic Network for Earthquake Early Warning in Taiwan

    Directory of Open Access Journals (Sweden)

    Da-Yi Chen

    2015-01-01

    Full Text Available A dense seismic network can increase Earthquake Early Warning (EEW system capability to estimate earthquake information with higher accuracy. It is also critical for generating fast, robust earthquake alarms before strong-ground shaking hits the target area. However, building a dense seismic network via traditional seismometers is too expensive and may not be practical. Using low-cost Micro-Electro Mechanical System (MEMS accelerometers is a potential solution to quickly deploy a large number of sensors around the monitored region. An EEW system constructed using a dense seismic network with 543 MEMS sensors in Taiwan is presented. The system also incorporates the official seismic network of _ Central Weather Bureau (CWB. The real-time data streams generated by the two networks are integrated using the Earthworm software. This paper illustrates the methods used by the integrated system for estimating earthquake information and evaluates the system performance. We applied the Earthworm picker for the seismograms recorded by the MEMS sensors (Chen et al. 2015 following new picking constraints to accurately detect P-wave arrivals and use a new regression equation for estimating earthquake magnitudes. An off-line test was implemented using 46 earthquakes with magnitudes ranging from ML 4.5 - 6.5 to calibrate the system. The experimental results show that the integrated system has stable source parameter results and issues alarms much faster than the current system run by the CWB seismic network (CWBSN.

  9. An Asynchronous Time-Division-Multiplexed Network-on-Chip for Real-Time Systems

    DEFF Research Database (Denmark)

    Kasapaki, Evangelia

    is an important part of the T-CREST paltform and used in a number of configurations. The flexible timing organization of Argo combines asynchronous routers with mesochronous NIs, which are connected to individually clocked cores, supporting a GALS system organization. The mesochronous NIs operate at the same......Multi-processor architectures using networks-on-chip (NOCs) for communication are becoming the standard approach in the development of embedded systems and general purpose platforms. Typically, multi-processor platforms follow a globally asynchronous locally synchronous (GALS) timing organization....... This thesis focuses on the design of Argo, a NOC targeted at hard real-time multi-processor platforms with a GALS timing organization. To support real-time communication, NOCs establish end-to-end connections and provide latency and throughput guarantees for these connections. Argo uses time division...

  10. A two-hop based adaptive routing protocol for real-time wireless sensor networks.

    Science.gov (United States)

    Rachamalla, Sandhya; Kancherla, Anitha Sheela

    2016-01-01

    One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

  11. Event Based Simulator for Parallel Computing over the Wide Area Network for Real Time Visualization

    Science.gov (United States)

    Sundararajan, Elankovan; Harwood, Aaron; Kotagiri, Ramamohanarao; Satria Prabuwono, Anton

    As the computational requirement of applications in computational science continues to grow tremendously, the use of computational resources distributed across the Wide Area Network (WAN) becomes advantageous. However, not all applications can be executed over the WAN due to communication overhead that can drastically slowdown the computation. In this paper, we introduce an event based simulator to investigate the performance of parallel algorithms executed over the WAN. The event based simulator known as SIMPAR (SIMulator for PARallel computation), simulates the actual computations and communications involved in parallel computation over the WAN using time stamps. Visualization of real time applications require steady stream of processed data flow for visualization purposes. Hence, SIMPAR may prove to be a valuable tool to investigate types of applications and computing resource requirements to provide uninterrupted flow of processed data for real time visualization purposes. The results obtained from the simulation show concurrence with the expected performance using the L-BSP model.

  12. A Wireless Sensor Network Framework for Real-Time Monitoring of Height and Volume Variations on Sandy Beaches and Dunes

    Directory of Open Access Journals (Sweden)

    Alessandro Pozzebon

    2018-04-01

    Full Text Available In this paper, the authors describe the realization and testing of a Wireless Sensor Network (WSN framework aiming at measuring, remotely and in real time, the level variations of the sand layer of sandy beaches or dunes. The proposed framework is based on an innovative low cost sensing structure, able to measure the level variations with a 5-cm degree of precision and to locally transfer the acquired data through the ZigBee protocol. The described sensor is integrated in a wider ZigBee wireless sensor network architecture composed of an array of sensors that, arranged according to a grid layout, can acquire the same data at different points, allowing the definition of a dynamic map of the area under study. The WSN is connected to a local Global System for Mobile Communications (GSM gateway that is in charge of data processing and transmission to a cloud infrastructure through a General Packet Radio Service (GPRS connection. Data are then stored in a MySQL database and made available any time and anywhere through the Internet. The proposed architecture has been tested in a laboratory, to analyze data acquisition, processing timing and power consumption and then in situ to prove the effectiveness of the system. The described infrastructure is expected to be integrated in a wider IoT architecture including different typologies of sensors, in order to create a multi-purpose tool for the study of coastal erosive processes.

  13. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  14. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  15. Low-cost airlines in Europe: Network structures after the enlargement of the European Union

    Directory of Open Access Journals (Sweden)

    Dudas Gabor

    2010-01-01

    Full Text Available The liberalization of the European air opened the strictly regulated European market, and contributed to the appearance and quick spread of the Low-Cost Carriers (LCCs. At the beginning of the 21st century the low cost traffic absolutely concentrated on the Western European market but after the enlargement of the European Union (EU LCCs started their operations in Eastern Europe enlarging and enriching the former evolved network structures. The aim of this paper is to trace the evolution of the route network as a result of EU expansion. During the study we came to the conclusion that in the time period after the EU enlargement the European LCC traffic showed dynamic development, route networks widened and the number of accessible destinations doubled. Comparing the LCCs network structures we defined three main characteristics, which represents the North-South flows, the West-East routes and the mixed network structure.

  16. Real-time community detection in full social networks on a laptop

    Science.gov (United States)

    Chamberlain, Benjamin Paul; Levy-Kramer, Josh; Humby, Clive

    2018-01-01

    For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide

  17. Real-time community detection in full social networks on a laptop.

    Directory of Open Access Journals (Sweden)

    Benjamin Paul Chamberlain

    Full Text Available For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph. As global social networks (e.g., Facebook and Twitter are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to

  18. Real-time community detection in full social networks on a laptop.

    Science.gov (United States)

    Chamberlain, Benjamin Paul; Levy-Kramer, Josh; Humby, Clive; Deisenroth, Marc Peter

    2018-01-01

    For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide

  19. Connection with seismic networks and construction of real time earthquake monitoring system

    Energy Technology Data Exchange (ETDEWEB)

    Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    2000-12-15

    It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system.

  20. UMTS rapid response real-time seismic networks: implementation and strategies at INGV

    Science.gov (United States)

    Govoni, Aladino; Margheriti, Lucia; Moretti, Milena; Lauciani, Valentino; Sensale, Gianpaolo; Bucci, Augusto; Criscuoli, Fabio

    2015-04-01

    The benefits of portable real-time seismic networks are several and well known. During the management of a temporary experiment from the real-time data it is possible to detect and fix rapidly problems with power supply, time synchronization, disk failures and, most important, seismic signal quality degradation due to unexpected noise sources or sensor alignment/tampering. This usually minimizes field maintenance trips and maximizes both the quantity and the quality of the acquired data. When the area of the temporary experiment is not well monitored by the local permanent network, the real-time data from the temporary experiment can be fed to the permanent network monitoring system improving greatly both the real-time hypocentral locations and the final revised bulletin. All these benefits apply also in case of seismic crises when rapid deployment stations can significantly contribute to the aftershock analysis. Nowadays data transmission using meshed radio networks or satellite systems is not a big technological problem for a permanent seismic network where each site is optimized for the device power consumption and is usually installed by properly specialized technicians that can configure transmission devices and align antennas. This is not usually practical for temporary networks and especially for rapid response networks where the installation time is the main concern. These difficulties are substantially lowered using the now widespread UMTS technology for data transmission. A small (but sometimes power hungry) properly configured device with an omnidirectional antenna must be added to the station assembly. All setups are usually configured before deployment and this allows for an easy installation also by untrained personnel. We describe here the implementation of a UMTS based portable seismic network for both temporary experiments and rapid response applications developed at INGV. The first field experimentation of this approach dates back to the 2009 L

  1. Real-time synchronization of wireless sensor network by 1-PPS signal

    Science.gov (United States)

    Giammarini, Marco; Pieralisi, Marco; Isidori, Daniela; Concettoni, Enrico; Cristalli, Cristina; Fioravanti, Matteo

    2015-05-01

    The use of wireless sensor networks with different nodes is desirable in a smart environment, because the network setting up and installation on preexisting structures can be done without a fixed cabled infrastructure. The flexibility of the monitoring system is fundamental where the use of a considerable quantity of cables could compromise the normal exercise, could affect the quality of acquired signal and finally increase the cost of the materials and installation. The network is composed of several intelligent "nodes", which acquires data from different kind of sensors, and then store or transmit them to a central elaboration unit. The synchronization of data acquisition is the core of the real-time wireless sensor network (WSN). In this paper, we present a comparison between different methods proposed by literature for the real-time acquisition in a WSN and finally we present our solution based on 1-Pulse-Per-Second (1-PPS) signal generated by GPS systems. The sensor node developed is a small-embedded system based on ARM microcontroller that manages the acquisition, the timing and the post-processing of the data. The communications between the sensors and the master based on IEEE 802.15.4 protocol and managed by dedicated software. Finally, we present the preliminary results obtained on a 3 floor building simulator with the wireless sensors system developed.

  2. Comparative Analysis of Neural Network Training Methods in Real-time Radiotherapy

    Directory of Open Access Journals (Sweden)

    Nouri S.

    2017-03-01

    Full Text Available Background: The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients. Objective: This study evaluates the accuracy of some artificial intelligence methods including neural network and those of combination with genetic algorithm as well as particle swarm optimization (PSO estimating tumor positions in real-time radiotherapy. Method: One hundred recorded signals of three external markers were used as input data. The signals from 3 markers thorough 10 breathing cycles of a patient treated via a cyber-knife for a lung tumor were used as data input. Then, neural network method and its combination with genetic or PSO algorithms were applied determining the tumor locations using MATLAB© software program. Results: The accuracies were obtained 0.8%, 12% and 14% in neural network, genetic and particle swarm optimization algorithms, respectively. Conclusion: The internal target volume (ITV should be determined based on the applied neural network algorithm on training steps.

  3. Intelligent Stale-Frame Discards for Real-Time Video Streaming over Wireless Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Sheu Tsang-Ling

    2009-01-01

    Full Text Available Abstract This paper presents intelligent early packet discards (I-EPD for real-time video streaming over a multihop wireless ad hoc network. In a multihop wireless ad hoc network, the quality of transferring real-time video streams could be seriously degraded, since every intermediate node (IN functionally like relay device does not possess large buffer and sufficient bandwidth. Even worse, a selected relay node could leave or power off unexpectedly, which breaks the route to destination. Thus, a stale video frame is useless even if it can reach destination after network traffic becomes smooth or failed route is reconfigured. In the proposed I-EPD, an IN can intelligently determine whether a buffered video packet should be early discarded. For the purpose of validation, we implement the I-EPD on Linux-based embedded systems. Via the comparisons of performance metrics (packet/frame discards ratios, PSNR, etc., we demonstrate that video quality over a wireless ad hoc network can be substantially improved and unnecessary bandwidth wastage is greatly reduced.

  4. Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network

    Science.gov (United States)

    Islam, Kh Tohidul; Raj, Ram Gopal

    2017-01-01

    Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications. PMID:28406471

  5. Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network.

    Science.gov (United States)

    Islam, Kh Tohidul; Raj, Ram Gopal

    2017-04-13

    Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are 'traffic light ahead' or 'pedestrian crossing' indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.

  6. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

    Science.gov (United States)

    Abdeljaber, Osama; Avci, Onur; Kiranyaz, Serkan; Gabbouj, Moncef; Inman, Daniel J.

    2017-02-01

    Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.

  7. Implementation of a FPGA-Based Feature Detection and Networking System for Real-time Traffic Monitoring

    OpenAIRE

    Chen, Jieshi; Schafer, Benjamin Carrion; Ho, Ivan Wang-Hei

    2016-01-01

    With the growing demand of real-time traffic monitoring nowadays, software-based image processing can hardly meet the real-time data processing requirement due to the serial data processing nature. In this paper, the implementation of a hardware-based feature detection and networking system prototype for real-time traffic monitoring as well as data transmission is presented. The hardware architecture of the proposed system is mainly composed of three parts: data collection, feature detection,...

  8. Network-Based Real-time Integrated Fire Detection and Alarm (FDA) System with Building Automation

    Science.gov (United States)

    Anwar, F.; Boby, R. I.; Rashid, M. M.; Alam, M. M.; Shaikh, Z.

    2017-11-01

    Fire alarm systems have become increasingly an important lifesaving technology in many aspects, such as applications to detect, monitor and control any fire hazard. A large sum of money is being spent annually to install and maintain the fire alarm systems in buildings to protect property and lives from the unexpected spread of fire. Several methods are already developed and it is improving on a daily basis to reduce the cost as well as increase quality. An integrated Fire Detection and Alarm (FDA) systems with building automation was studied, to reduce cost and improve their reliability by preventing false alarm. This work proposes an improved framework for FDA system to ensure a robust intelligent network of FDA control panels in real-time. A shortest path algorithmic was chosen for series of buildings connected by fiber optic network. The framework shares information and communicates with each fire alarm panels connected in peer to peer configuration and declare the network state using network address declaration from any building connected in network. The fiber-optic connection was proposed to reduce signal noises, thus increasing large area coverage, real-time communication and long-term safety. Based on this proposed method an experimental setup was designed and a prototype system was developed to validate the performance in practice. Also, the distributed network system was proposed to connect with an optional remote monitoring terminal panel to validate proposed network performance and ensure fire survivability where the information is sequentially transmitted. The proposed FDA system is different from traditional fire alarm and detection system in terms of topology as it manages group of buildings in an optimal and efficient manner.Introduction

  9. The new Athens center on data processing from the neutron monitor network in real time

    Directory of Open Access Journals (Sweden)

    Mavromichalaki

    2005-11-01

    Full Text Available The ground-based neutron monitors (NMs record galactic and solar relativistic cosmic rays which can play a useful key role in space weather forecasting, as a result of their interaction with interplanetary disturbances. The Earth's-based neutron monitor network has been used in order to produce a real-time prediction of space weather phenomena. Therefore, the Athens Neutron Monitor Data Processing Center (ANMODAP takes advantage of this unique multi-directional device to solve problems concerning the diagnosis and forecasting of space weather. At this moment there has been a multi-sided use of neutron monitors. On the one hand, a preliminary alert for ground level enhancements (GLEs may be provided due to relativistic solar particles and can be registered around 20 to 30 min before the arrival of the main part of lower energy particles responsible for radiation hazard. To make a more reliable prognosis of these events, real time data from channels of lower energy particles and X-ray intensity from the GOES satellite are involved in the analysis. The other possibility is to search in real time for predictors of geomagnetic storms when they occur simultaneously with Forbush effects, using hourly, on-line accessible neutron monitor data from the worldwide network and applying a special method of processing. This chance of prognosis is only being elaborated and considered here as one of the possible uses of the Neutron Monitor Network for forecasting the arrival of interplanetary disturbance to the Earth. The achievements, the processes and the future results, are discussed in this work.

  10. A smart modules network for real time data acquisition: application to biomedical research.

    Science.gov (United States)

    Logier, R; De jonckheere, J; Dassonneville, A; Chaud, P; Jeanne, M

    2009-01-01

    Healthcare monitoring applications require the measurement and the analysis of multiple physiological data. In the field of biomedical research, these data are issued from different devices involving data centralization and synchronization difficulties. In this paper, we describe a smart hardware modules network for biomedical data real time acquisition. This toolkit, composed of multiple electronic modules, allows users to acquire and transmit all kind of biomedical signals and parameters. These highly efficient hardware modules have been developed and tested especially for biomedical studies and used in a large number of clinical investigations.

  11. UMTS rapid response real-time seismic networks: implementation and strategies at INGV

    Science.gov (United States)

    Govoni, A.; Margheriti, L.; Moretti, M.; Lauciani, V.; Sensale, G.; Bucci, A.; Criscuoli, F.

    2015-12-01

    Universal Mobile Telecommunications System (UMTS) and its evolutions are nowadays the most affordable and widespread data communication infrastructure available almost world wide. Moreover the always growing cellular phone market is pushing the development of new devices with higher performances and lower power consumption. All these characteristics make UMTS really useful for the implementation of an "easy to deploy" temporary real-time seismic station. Despite these remarkable features, there are many drawbacks that must be properly taken in account to effectively transmit the seismic data: Internet security, signal and service availability, power consumption. - Internet security: exposing seismological data services and seismic stations to the Internet is dangerous, attack prone and can lead to downtimes in the services, so we setup a dedicated Virtual Private Network (VPN) service to protect all the connected devices. - Signal and service availability: while for temporary experiment a carefull planning and an accurate site selection can minimize the problem, this is not always the case with rapid response networks. Moreover, as with any other leased line, the availability of the UMTS service during a seismic crisis is basically unpredictable. Nowadays in Italy during a major national emergency a Committee of the Italian Civil Defense ensures unified management and coordination of emergency activities. Inside it the telecom companies are committed to give support to the crisis management improving the standards in their communication networks. - Power consumption: it is at least of the order of that of the seismic station and, being related to data flow and signal quality is largely unpredictable. While the most secure option consists in adding a second independent solar power supply to the seismic station, this is not always a very convenient solution since it doubles the cost and doubles the equipment on site. We found that an acceptable trade-off is to add an

  12. Extended neural network-based scheme for real-time force tracking with magnetorheological dampers

    DEFF Research Database (Denmark)

    Weber, Felix; Bhowmik, Subrata; Høgsberg, Jan Becker

    2014-01-01

    This paper validates numerically and experimentally a new neural network-based real-time force tracking scheme for magnetorheological (MR) dampers on a five-storey shear frame with MR damper. The inverse model is trained with absolute values of measured velocity and force because the targeted...... the pre-yield to the post-yield region. A control-oriented approach is presented to compensate for these drawbacks. The resulting control force tracking scheme is validated for the emulation of viscous damping, clipped viscous damping with negative stiffness, and friction damping with negative stiffness...

  13. Real-Time, Interactive Echocardiography Over High-Speed Networks: Feasibility and Functional Requirements

    Science.gov (United States)

    Bobinsky, Eric A.

    1998-01-01

    Real-time, Interactive Echocardiography Over High Speed Networks: Feasibility and Functional Requirements is an experiment in advanced telemedicine being conducted jointly by the NASA Lewis Research Center, the NASA Ames Research Center, and the Cleveland Clinic Foundation. In this project, a patient undergoes an echocardiographic examination in Cleveland while being diagnosed remotely by a cardiologist in California viewing a real-time display of echocardiographic video images transmitted over the broadband NASA Research and Education Network (NREN). The remote cardiologist interactively guides the sonographer administering the procedure through a two-way voice link between the two sites. Echocardiography is a noninvasive medical technique that applies ultrasound imaging to the heart, providing a "motion picture" of the heart in action. Normally, echocardiographic examinations are performed by a sonographer and cardiologist who are located in the same medical facility as the patient. The goal of telemedicine is to allow medical specialists to examine patients located elsewhere, typically in remote or medically underserved geographic areas. For example, a small, rural clinic might have access to an echocardiograph machine but not a cardiologist. By connecting this clinic to a major metropolitan medical facility through a communications network, a minimally trained technician would be able to carry out the procedure under the supervision and guidance of a qualified cardiologist.

  14. REAL-TIME VIDEO SCALING BASED ON CONVOLUTION NEURAL NETWORK ARCHITECTURE

    Directory of Open Access Journals (Sweden)

    S Safinaz

    2017-08-01

    Full Text Available In recent years, video super resolution techniques becomes mandatory requirements to get high resolution videos. Many super resolution techniques researched but still video super resolution or scaling is a vital challenge. In this paper, we have presented a real-time video scaling based on convolution neural network architecture to eliminate the blurriness in the images and video frames and to provide better reconstruction quality while scaling of large datasets from lower resolution frames to high resolution frames. We compare our outcomes with multiple exiting algorithms. Our extensive results of proposed technique RemCNN (Reconstruction error minimization Convolution Neural Network shows that our model outperforms the existing technologies such as bicubic, bilinear, MCResNet and provide better reconstructed motioning images and video frames. The experimental results shows that our average PSNR result is 47.80474 considering upscale-2, 41.70209 for upscale-3 and 36.24503 for upscale-4 for Myanmar dataset which is very high in contrast to other existing techniques. This results proves our proposed model real-time video scaling based on convolution neural network architecture’s high efficiency and better performance.

  15. Integrated wireless sensor network and real time smart controlling and monitoring system for efficient energy management in standalone photovoltaic systems

    Science.gov (United States)

    Abou-Elnour, Ali; Thabt, A.; Helmy, S.; Kashf, Y.; Hadad, Y.; Tarique, M.; Abo-Elnor, Ossama

    2014-04-01

    In the present work, wireless sensor network and smart real-time controlling and monitoring system are integrated for efficient energy management of standalone photovoltaic system. The proposed system has two main components namely the monitoring and controlling system and the wireless communication system. LabView software has been used in the implementation of the monitoring and controlling system. On the other hand, ZigBee wireless modules have been used to implement the wireless system. The main functions of monitoring and controlling unit is to efficiently control the energy consumption form the photovoltaic system based on accurate determination of the periods of times at which the loads are required to be operated. The wireless communication system send the data from the monitoring and controlling unit to the loads at which desired switching operations are performed. The wireless communication system also continuously feeds the monitoring and controlling unit with updated input data from the sensors and from the photovoltaic module send to calculate and record the generated, the consumed, and the stored energy to apply load switching saving schemes if necessary. It has to be mentioned that our proposed system is a low cost and low power system because and it is flexible to be upgraded to fulfill additional users' requirements.

  16. An energy-efficient transmission scheme for real-time data in wireless sensor networks.

    Science.gov (United States)

    Kim, Jin-Woo; Barrado, José Ramón Ramos; Jeon, Dong-Keun

    2015-05-20

    The Internet of things (IoT) is a novel paradigm where all things or objects in daily life can communicate with other devices and provide services over the Internet. Things or objects need identifying, sensing, networking and processing capabilities to make the IoT paradigm a reality. The IEEE 802.15.4 standard is one of the main communication protocols proposed for the IoT. The IEEE 802.15.4 standard provides the guaranteed time slot (GTS) mechanism that supports the quality of service (QoS) for the real-time data transmission. In spite of some QoS features in IEEE 802.15.4 standard, the problem of end-to-end delay still remains. In order to solve this problem, we propose a cooperative medium access scheme (MAC) protocol for real-time data transmission. We also evaluate the performance of the proposed scheme through simulation. The simulation results demonstrate that the proposed scheme can improve the network performance.

  17. Real-time radionuclide identification in γ-emitter mixtures based on spiking neural network

    International Nuclear Information System (INIS)

    Bobin, C.; Bichler, O.; Lourenço, V.; Thiam, C.; Thévenin, M.

    2016-01-01

    Portal radiation monitors dedicated to the prevention of illegal traffic of nuclear materials at international borders need to deliver as fast as possible a radionuclide identification of a potential radiological threat. Spectrometry techniques applied to identify the radionuclides contributing to γ-emitter mixtures are usually performed using off-line spectrum analysis. As an alternative to these usual methods, a real-time processing based on an artificial neural network and Bayes’ rule is proposed for fast radionuclide identification. The validation of this real-time approach was carried out using γ-emitter spectra ( 241 Am, 133 Ba, 207 Bi, 60 Co, 137 Cs) obtained with a high-efficiency well-type NaI(Tl). The first tests showed that the proposed algorithm enables a fast identification of each γ-emitting radionuclide using the information given by the whole spectrum. Based on an iterative process, the on-line analysis only needs low-statistics spectra without energy calibration to identify the nature of a radiological threat. - Highlights: • A fast radionuclide identification algorithm applicable in spectroscopic portal monitors is presented. • The proposed algorithm combines a Bayesian sequential approach and a spiking neural network. • The algorithm was validated using the mixture of γ-emitter spectra provided by a well-type NaI(Tl) detector. • The radionuclide identification process is implemented using the whole γ-spectrum without energy calibration.

  18. Analysis of several digital network technologies for hard real-time communications in nuclear plant

    International Nuclear Information System (INIS)

    Song, Ki Sang; No, Hee Chun

    1999-01-01

    Applying digital network technology for advanced nuclear plant requires deterministic communication for tight safety requirements, timely and reliable data delivery for operation critical and mission-critical characteristics of nuclear plant. Communication protocols, such as IEEE 802/4 Tiken Bus, IEEE 802/5 Token Ring, FDDI, and ARCnet, which have deterministic communication capability are partially applied to several nuclear power plants. Although digital communication technologies have many advantages, it is necessary to consider the noise immunity form electromagnetic interference (EMI), electrical interference, impulse noise, and heat noise before selecting specific digital network technology for nuclear plant. In this paper, we consider the token frame loss and data frame loss rate due to the link error event, frame size, and link data rate in different protocols, and evaluate the possibility of failure to meet the hard real-time requirement in nuclear plant. (author). 11 refs., 3 figs., 4 tabs

  19. Real-Time Communications in Autonomic Networks: System Implementation and Performance Evaluation

    Directory of Open Access Journals (Sweden)

    C. Tselios

    2012-01-01

    Full Text Available This paper describes the design and prototype implementation of a communication platform aiming to provide voice and video communication in a distributed networking environment. Performance considerations and network characteristics have also been taken into account in order to provide the set of properties dictated by the sensitive nature and the real-time characteristics of the targeted application scenarios. The proposed system has been evaluated both by experimental means as well as subjective tests taken by an extensive number of users. The results show that the proposed platform operates seamlessly in two hops, while in the four hops scenario, audio and video are delivered with marginal distortion. The conducted survey indicates that the user experience in terms of Quality of Service has obtained higher scores in the scenario with the two hops.

  20. Reliable Wireless Broadcast with Linear Network Coding for Multipoint-to-Multipoint Real-Time Communications

    Science.gov (United States)

    Kondo, Yoshihisa; Yomo, Hiroyuki; Yamaguchi, Shinji; Davis, Peter; Miura, Ryu; Obana, Sadao; Sampei, Seiichi

    This paper proposes multipoint-to-multipoint (MPtoMP) real-time broadcast transmission using network coding for ad-hoc networks like video game networks. We aim to achieve highly reliable MPtoMP broadcasting using IEEE 802.11 media access control (MAC) that does not include a retransmission mechanism. When each node detects packets from the other nodes in a sequence, the correctly detected packets are network-encoded, and the encoded packet is broadcasted in the next sequence as a piggy-back for its native packet. To prevent increase of overhead in each packet due to piggy-back packet transmission, network coding vector for each node is exchanged between all nodes in the negotiation phase. Each user keeps using the same coding vector generated in the negotiation phase, and only coding information that represents which user signal is included in the network coding process is transmitted along with the piggy-back packet. Our simulation results show that the proposed method can provide higher reliability than other schemes using multi point relay (MPR) or redundant transmissions such as forward error correction (FEC). We also implement the proposed method in a wireless testbed, and show that the proposed method achieves high reliability in a real-world environment with a practical degree of complexity when installed on current wireless devices.

  1. Study of the full-service and low-cost carriers network configuration

    Directory of Open Access Journals (Sweden)

    Oriol Lordan

    2014-10-01

    Full Text Available Purpose: The network strategies used by airline carriers have been a recurring subject in air transport research. The aim of this paper is to investigate the relationship between the different operational characteristics of the airline and its route network configuration. Design/methodology/approach: The two main airline carrier typologies - Full-Service and Low-Cost carriers – are analysed using empirical models developed on complex network research relating them to the business model of the airlines. Findings and Originality/value: Just in Europe, one can differentiate between Full-Service and Low-Cost Carriers by complex network analyses. In this process, it has been also found that new concept Low-Cost Carriers, such as Vueling, have network properties closer to Full-Service Carriers. Research limitations/implications: This paper has a limited sample, as includes 26 airline case studies from Europe, United States and Asia. Practical implications: The analysis carried out in this research can help to the assessment of the evolution of the strategies of airline carriers, and has also operational implications, since the configuration of an airline route network can determine its resilience to attacks and errors. Social implications: A better understanding of the properties of airline route networks can benefit airlines, passengers and another stakeholders of the air transport industry. Originality/value: Current research on air transport networks has only considered the global or regional level, but few studies have addressed the study of airline transport networks, and its relationship with their business model.

  2. The strategic capability of Asian network airlines to compete with low-cost carriers

    OpenAIRE

    Pearson, James; O'Connell, John F.; Pitfield, David; Ryley, Tim

    2015-01-01

    Never before have network airlines been so exposed and vulnerable to low-cost carriers (LCCs). While LCCs had 26.3% of all world seats in 2013, Southeast Asia had 57.7% and South Asia 58.4% – and these figures will only increase. There are many consequences of LCCs on network airlines, including inadequately meeting the expectations of customers, so increasing dissatisfaction, and not offering sufficient value-for-money. Clearly, it is fundamentally important for Asian network airlines to res...

  3. Real-Time Management of Groundwater Resources Based on Wireless Sensors Networks

    Directory of Open Access Journals (Sweden)

    Qingguo Zhou

    2018-01-01

    Full Text Available Groundwater plays a vital role in the arid inland river basins, in which the groundwater management is critical to the sustainable development of area economy and ecology. Traditional sustainable management approaches are to analyze different scenarios subject to assumptions or to construct simulation–optimization models to obtain optimal strategy. However, groundwater system is time-varying due to exogenous inputs. In this sense, the groundwater management based on static data is relatively outdated. As part of the Heihe River Basin (HRB, which is a typical arid river basin in Northwestern China, the Daman irrigation district was selected as the study area in this paper. First, a simulation–optimization model was constructed to optimize the pumping rates of the study area according to the groundwater level constraints. Three different groundwater level constraints were assigned to explore sustainable strategies for groundwater resources. The results indicated that the simulation–optimization model was capable of identifying the optimal pumping yields and satisfy the given constraints. Second, the simulation–optimization model was integrated with wireless sensors network (WSN technology to provide real-time features for the management. The results showed time-varying feature for the groundwater management, which was capable of updating observations, constraints, and decision variables in real time. Furthermore, a web-based platform was developed to facilitate the decision-making process. This study combined simulation and optimization model with WSN techniques and meanwhile attempted to real-time monitor and manage the scarce groundwater resource, which could be used to support the decision-making related to sustainable management.

  4. Real time data acquisition of a countrywide commercial microwave link network

    Science.gov (United States)

    Chwala, Christian; Keis, Felix; Kunstmann, Harald

    2015-04-01

    Research in recent years has shown that data from commercial microwave link networks can provide very valuable precipitation information. Since these networks comprise the backbone of the cell phone network, they provide countrywide coverage. However acquiring the necessary data from the network operators is still difficult. Data is usually made available for researchers with a large time delay and often at irregular basis. This of course hinders the exploitation of commercial microwave link data in operational applications like QPE forecasts running at national meteorological services. To overcome this, we have developed a custom software in joint cooperation with our industry partner Ericsson. The software is installed on a dedicated server at Ericsson and is capable of acquiring data from the countrywide microwave link network in Germany. In its current first operational testing phase, data from several hundred microwave links in southern Germany is recorded. All data is instantaneously sent to our server where it is stored and organized in an emerging database. Time resolution for the Ericsson data is one minute. The custom acquisition software, however, is capable of processing higher sampling rates. Additionally we acquire and manage 1 Hz data from four microwave links operated by the skiing resort in Garmisch-Partenkirchen. We will present the concept of the data acquisition and show details of the custom-built software. Additionally we will showcase the accessibility and basic processing of real time microwave link data via our database web frontend.

  5. Use of a Real-Time Remote Monitoring Network (RTRM to Characterize the Guadalquivir Estuary (Spain

    Directory of Open Access Journals (Sweden)

    Isabel Caballero

    2012-02-01

    Full Text Available The temporal variability of hydrological variables in the Guadalquivir estuary was examined during three years through a real-time remote monitoring network (RTRM. The network was developed with the aim of studying the influence of hydrodynamical and hydrological features within the estuary on the functioning of the pelagic ecosystem. Completing this data-gathering network, monthly cruises were performed in order to measure biogeochemical variables that are indicative of the trophic status of the aquatic environment. The results showed that several sources of physical forcing, such as wind, tide-associated currents and river discharge were responsible for the spatio-temporal patterns of dissolved oxygen, salinity and turbidity in the estuary. The analysis was conducted under tidal and flood regime, which allowed us to identify river discharge as the main forcing agent of the hydrology inside the estuary. In particular, episodes of elevated turbidity detected by the network, together with episodes of low salinity and dissolved oxygen were closely related to the increase in water supply from a dam located upstream. The network installed provided accurate data that can be rapidly used for research or educational applications and by policy-makers or agencies in charge of the management of the coastal area.

  6. Real-time classification and sensor fusion with a spiking deep belief network.

    Science.gov (United States)

    O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael

    2013-01-01

    Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input.

  7. A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

    Science.gov (United States)

    Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

    2017-01-01

    Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

  8. High-speed railway real-time localization auxiliary method based on deep neural network

    Science.gov (United States)

    Chen, Dongjie; Zhang, Wensheng; Yang, Yang

    2017-11-01

    High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

  9. Effective image differencing with convolutional neural networks for real-time transient hunting

    Science.gov (United States)

    Sedaghat, Nima; Mahabal, Ashish

    2018-06-01

    Large sky surveys are increasingly relying on image subtraction pipelines for real-time (and archival) transient detection. In this process one has to contend with varying point-spread function (PSF) and small brightness variations in many sources, as well as artefacts resulting from saturated stars and, in general, matching errors. Very often the differencing is done with a reference image that is deeper than individual images and the attendant difference in noise characteristics can also lead to artefacts. We present here a deep-learning approach to transient detection that encapsulates all the steps of a traditional image-subtraction pipeline - image registration, background subtraction, noise removal, PSF matching and subtraction - in a single real-time convolutional network. Once trained, the method works lightening-fast and, given that it performs multiple steps in one go, the time saved and false positives eliminated for multi-CCD surveys like Zwicky Transient Facility and Large Synoptic Survey Telescope will be immense, as millions of subtractions will be needed per night.

  10. Real-time flood forecasts & risk assessment using a possibility-theory based fuzzy neural network

    Science.gov (United States)

    Khan, U. T.

    2016-12-01

    Globally floods are one of the most devastating natural disasters and improved flood forecasting methods are essential for better flood protection in urban areas. Given the availability of high resolution real-time datasets for flood variables (e.g. streamflow and precipitation) in many urban areas, data-driven models have been effectively used to predict peak flow rates in river; however, the selection of input parameters for these types of models is often subjective. Additionally, the inherit uncertainty associated with data models along with errors in extreme event observations means that uncertainty quantification is essential. Addressing these concerns will enable improved flood forecasting methods and provide more accurate flood risk assessments. In this research, a new type of data-driven model, a quasi-real-time updating fuzzy neural network is developed to predict peak flow rates in urban riverine watersheds. A possibility-to-probability transformation is first used to convert observed data into fuzzy numbers. A possibility theory based training regime is them used to construct the fuzzy parameters and the outputs. A new entropy-based optimisation criterion is used to train the network. Two existing methods to select the optimum input parameters are modified to account for fuzzy number inputs, and compared. These methods are: Entropy-Wavelet-based Artificial Neural Network (EWANN) and Combined Neural Pathway Strength Analysis (CNPSA). Finally, an automated algorithm design to select the optimum structure of the neural network is implemented. The overall impact of each component of training this network is to replace the traditional ad hoc network configuration methods, with one based on objective criteria. Ten years of data from the Bow River in Calgary, Canada (including two major floods in 2005 and 2013) are used to calibrate and test the network. The EWANN method selected lagged peak flow as a candidate input, whereas the CNPSA method selected lagged

  11. Testing the Feasibility of a Low-Cost Network Performance Measurement Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Chevalier, Scott [Indiana Univ., Bloomington, IN (United States). International Networks; Schopf, Jennifer M. [Indiana Univ., Bloomington, IN (United States). International Networks; Miller, Kenneth [Pennsylvania State Univ., University Park, PA (United States). Telecommunications and Networking Services; Zurawski, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Sciences Network

    2016-07-01

    Todays science collaborations depend on reliable, high performance networks, but monitoring the end-to-end performance of a network can be costly and difficult. The most accurate approaches involve using measurement equipment in many locations, which can be both expensive and difficult to manage due to immobile or complicated assets. The perfSONAR framework facilitates network measurement making management of the tests more reasonable. Traditional deployments have used over-provisioned servers, which can be expensive to deploy and maintain. As scientific network uses proliferate, there is a desire to instrument more facets of a network to better understand trends. This work explores low cost alternatives to assist with network measurement. Benefits include the ability to deploy more resources quickly, and reduced capital and operating expenditures. Finally, we present candidate platforms and a testing scenario that evaluated the relative merits of four types of small form factor equipment to deliver accurate performance measurements.

  12. Real-time camera-based face detection using a modified LAMSTAR neural network system

    Science.gov (United States)

    Girado, Javier I.; Sandin, Daniel J.; DeFanti, Thomas A.; Wolf, Laura K.

    2003-03-01

    This paper describes a cost-effective, real-time (640x480 at 30Hz) upright frontal face detector as part of an ongoing project to develop a video-based, tetherless 3D head position and orientation tracking system. The work is specifically targeted for auto-stereoscopic displays and projection-based virtual reality systems. The proposed face detector is based on a modified LAMSTAR neural network system. At the input stage, after achieving image normalization and equalization, a sub-window analyzes facial features using a neural network. The sub-window is segmented, and each part is fed to a neural network layer consisting of a Kohonen Self-Organizing Map (SOM). The output of the SOM neural networks are interconnected and related by correlation-links, and can hence determine the presence of a face with enough redundancy to provide a high detection rate. To avoid tracking multiple faces simultaneously, the system is initially trained to track only the face centered in a box superimposed on the display. The system is also rotationally and size invariant to a certain degree.

  13. An electronic system for simulation of neural networks with a micro-second real time constraint

    International Nuclear Information System (INIS)

    Chorti, Arsenia; Granado, Bertrand; Denby, Bruce; Garda, Patrick

    2001-01-01

    Neural networks implemented in hardware can perform pattern recognition very quickly, and as such have been used to advantage in the triggering systems of certain high energy physics experiments. Typically, time constants of the order of a few microseconds are required. In this paper, we present a new system. MAHARADJA, for evaluating MLP and RBF neural network paradigms in real time. The system is tested on a possible ATLAS muon triggering application suggested by the Tel Aviv ATLAS group, consisting of a 4-8-8-4 MLP which must be evaluated in 10 microseconds. The inputs to the net are dx/dz, x(z=0), dy/dz, and y(z=0), whereas the outputs give pt, tan(phi), sin(theta), and q, the charge. With a 10 MHz clock, MAHARADJA calculates the result in 6.8 microseconds; at 20 MHz, which is readily attainable, this would be reduced to only 3.4 microseconds. The system can also handle RBF networks with 3 different distance metrics (Euclidean, Manhattan and Mahalanobis), and can simulate any MLP of 10 hidden layers or less. The electronic implementation is with FPGA's, which can be optimized for a specific neural network because the number of processing elements can be modified

  14. Experiences from Implementing a Mobile Multiplayer Real-Time Game for Wireless Networks with High Latency

    Directory of Open Access Journals (Sweden)

    Alf Inge Wang

    2009-01-01

    Full Text Available This paper describes results and experiences from designing, implementing, and testing a multiplayer real-time game over mobile networks with high latency. The paper reports on network latency and bandwidth measurements from playing the game live over GPRS, EDGE, UMTS, and WLAN using the TCP and the UDP protocols. These measurements describe the practical constraints of various wireless networks and protocols when used for mobile multiplayer game purposes. Further, the paper reports on experiences from implementing various approaches to minimize issues related to high latency. Specifically, the paper focuses on a discussion about how much of the game should run locally on the client versus on the server to minimize the load on the mobile device and obtain sufficient consistency in the game. The game was designed to reveal all kinds of implementation issues of mobile network multiplayer games. The goal of the game is for a player to push other players around and into traps where they loose their lives. The game relies heavily on collision detection between the players and game objects. The paper presents experiences from experimenting with various approaches that can be used to handle such collisions, and highlights the advantages and disadvantages of the various approaches.

  15. STAR: a local network system for real-time management of imagery data

    Energy Technology Data Exchange (ETDEWEB)

    Chuan-lin Wu; Tse-yun Feng; Min-chang Lin

    1982-10-01

    Overall architecture of a local computer network, STAR, is described. The objective is to accomplish a cost-effective system which provides multiple users a real-time service of manipulating very large volume imagery information and data. STAR consists of a reconfigurable communication subnet (starnet), heterogeneous resource units, and distributed-control software entities. Architectural aspects of a fault-tolerant communication subnet, distributed database management, and a distributed scheduling strategy for configuring desirable computation topology are exploited. A model for comparing cost-effectiveness among starnet, crossbar, and multiple buses is included. It is concluded that starnet outperforms the other two when the number of units to be connected is larger than 64. This project serves as a research tool for using current and projected technology to innovate better schemes for parallel image processing. 30 references.

  16. Determining Methane Leak Locations and Rates with a Wireless Network Composed of Low-Cost, Printed Sensors

    Science.gov (United States)

    Smith, C. J.; Kim, B.; Zhang, Y.; Ng, T. N.; Beck, V.; Ganguli, A.; Saha, B.; Daniel, G.; Lee, J.; Whiting, G.; Meyyappan, M.; Schwartz, D. E.

    2015-12-01

    We will present our progress on the development of a wireless sensor network that will determine the source and rate of detected methane leaks. The targeted leak detection threshold is 2 g/min with a rate estimation error of 20% and localization error of 1 m within an outdoor area of 100 m2. The network itself is composed of low-cost, high-performance sensor nodes based on printed nanomaterials with expected sensitivity below 1 ppmv methane. High sensitivity to methane is achieved by modifying high surface-area-to-volume-ratio single-walled carbon nanotubes (SWNTs) with materials that adsorb methane molecules. Because the modified SWNTs are not perfectly selective to methane, the sensor nodes contain arrays of variously-modified SWNTs to build diversity of response towards gases with adsorption affinity. Methane selectivity is achieved through advanced pattern-matching algorithms of the array's ensemble response. The system is low power and designed to operate for a year on a single small battery. The SWNT sensing elements consume only microwatts. The largest power consumer is the wireless communication, which provides robust, real-time measurement data. Methane leak localization and rate estimation will be performed by machine-learning algorithms built with the aid of computational fluid dynamics simulations of gas plume formation. This sensor system can be broadly applied at gas wells, distribution systems, refineries, and other downstream facilities. It also can be utilized for industrial and residential safety applications, and adapted to other gases and gas combinations.

  17. Real-time distributed scheduling algorithm for supporting QoS over WDM networks

    Science.gov (United States)

    Kam, Anthony C.; Siu, Kai-Yeung

    1998-10-01

    Most existing or proposed WDM networks employ circuit switching, typically with one session having exclusive use of one entire wavelength. Consequently they are not suitable for data applications involving bursty traffic patterns. The MIT AON Consortium has developed an all-optical LAN/MAN testbed which provides time-slotted WDM service and employs fast-tunable transceivers in each optical terminal. In this paper, we explore extensions of this service to achieve fine-grained statistical multiplexing with different virtual circuits time-sharing the wavelengths in a fair manner. In particular, we develop a real-time distributed protocol for best-effort traffic over this time-slotted WDM service with near-optical fairness and throughput characteristics. As an additional design feature, our protocol supports the allocation of guaranteed bandwidths to selected connections. This feature acts as a first step towards supporting integrated services and quality-of-service guarantees over WDM networks. To achieve high throughput, our approach is based on scheduling transmissions, as opposed to collision- based schemes. Our distributed protocol involves one MAN scheduler and several LAN schedulers (one per LAN) in a master-slave arrangement. Because of propagation delays and limits on control channel capacities, all schedulers are designed to work with partial, delayed traffic information. Our distributed protocol is of the `greedy' type to ensure fast execution in real-time in response to dynamic traffic changes. It employs a hybrid form of rate and credit control for resource allocation. We have performed extensive simulations, which show that our protocol allocates resources (transmitters, receivers, wavelengths) fairly with high throughput, and supports bandwidth guarantees.

  18. NetPICOmag: A low-cost networked magnetometer and its applications

    Science.gov (United States)

    Schofield, I.; Connors, M.; Russell, C. T.

    2012-03-01

    NetPICOmag (NPM) is the culmination of a design effort to build a compact, low-cost, laboratory-grade, networked magnetometer designed for remote autonomous operation, suited for research and education. NPM allows wide placement of magnetometers sensitive enough to detect auroral activity and the daily variation, and is suitable for education projects and a range of geophysical applications. The use of networked microcontrollers and GPS timing is applicable to other small instruments for field or local deployment, and an onboard data logging capability has also been demonstrated. We illustrate the value of the placement of low-cost magnetometers to increase coverage in an area through the study of a Pc 5 pulsation event which took place on September 4, 2010. By combining results with those from auroral zone magnetometers supporting the THEMIS project, we find that the phase velocity of these morning sector pulsations was northward on the ground. The event took place under very quiet solar wind conditions, and credible mapping associates it with the inner magnetosphere. Another aspect beyond increasing areal coverage is increasing density of coverage, which becomes feasible with instruments of very low cost. We examine aspects of the April 5, 2010 space weather event which are possible to deduce from closely spaced magnetometers.

  19. Development of high-reliable real-time communication network protocol for SMART

    Energy Technology Data Exchange (ETDEWEB)

    Song, Ki Sang; Kim, Young Sik [Korea National University of Education, Chongwon (Korea); No, Hee Chon [Korea Advanced Institute of Science and Technology, Taejon (Korea)

    1999-04-01

    In this research, we first define protocol subsets for SMART(System-integrated Modular Advanced Reactor) communication network based on the requirement of SMART MMIS transmission delay and traffic requirements and OSI(Open System Interconnection) 7 layers' network protocol functions. Also, current industrial purpose LAN protocols are analyzed and the applicability of commercialized protocols are checked. For the suitability test, we have applied approximated SMART data traffic and maximum allowable transmission delay requirement. With the simulation results, we conclude that IEEE 802.5 and FDDI which is an ANSI standard, is the most suitable for SMART. We further analyzed the FDDI and token ring protocols for SMART and nuclear plant network environment including IEEE 802.4, IEEE 802.5, and ARCnet. The most suitable protocol for SMART is FDDI and FDDI MAC and RMT protocol specifications have been verified with LOTOS and the verification results show that FDDI MAC and RMT satisfy the reachability and liveness, but does not show deadlock and livelock. Therefore, we conclude that FDDI MAC and RMT is highly reliable protocol for SMART MMIS network. After that, we consider the stacking fault of IEEE 802.5 token ring protocol and propose a fault tolerant MAM(Modified Active Monitor) protocol. The simulation results show that the MAM protocol improves lower priority traffic service rate when stacking fault occurs. Therefore, proposed MAM protocol can be applied to SMART communication network for high reliability and hard real-time communication purpose in data acquisition and inter channel network. (author). 37 refs., 79 figs., 39 tabs.

  20. Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

    Science.gov (United States)

    Aulov, O.; Halem, M.; Lary, D. J.

    2011-12-01

    We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly

  1. Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks

    Science.gov (United States)

    Avci, Onur; Abdeljaber, Osama; Kiranyaz, Serkan; Hussein, Mohammed; Inman, Daniel J.

    2018-06-01

    Being an alternative to conventional wired sensors, wireless sensor networks (WSNs) are extensively used in Structural Health Monitoring (SHM) applications. Most of the Structural Damage Detection (SDD) approaches available in the SHM literature are centralized as they require transferring data from all sensors within the network to a single processing unit to evaluate the structural condition. These methods are found predominantly feasible for wired SHM systems; however, transmission and synchronization of huge data sets in WSNs has been found to be arduous. As such, the application of centralized methods with WSNs has been a challenge for engineers. In this paper, the authors are presenting a novel application of 1D Convolutional Neural Networks (1D CNNs) on WSNs for SDD purposes. The SDD is successfully performed completely wireless and real-time under ambient conditions. As a result of this, a decentralized damage detection method suitable for wireless SHM systems is proposed. The proposed method is based on 1D CNNs and it involves training an individual 1D CNN for each wireless sensor in the network in a format where each CNN is assigned to process the locally-available data only, eliminating the need for data transmission and synchronization. The proposed damage detection method operates directly on the raw ambient vibration condition signals without any filtering or preprocessing. Moreover, the proposed approach requires minimal computational time and power since 1D CNNs merge both feature extraction and classification tasks into a single learning block. This ability is prevailingly cost-effective and evidently practical in WSNs considering the hardware systems have been occasionally reported to suffer from limited power supply in these networks. To display the capability and verify the success of the proposed method, large-scale experiments conducted on a laboratory structure equipped with a state-of-the-art WSN are reported.

  2. Development of a Laboratory Synchrophasor Network and an Application to Estimate Transmission Line Parameters in Real Time

    Science.gov (United States)

    Almiron Bonnin, Rubens Eduardo

    The development of an experimental synchrophasors network and application of synchrophasors for real-time transmission line parameter monitoring are presented in this thesis. In the laboratory setup, a power system is simulated in a RTDS real-time digital simulator, and the simulated voltages and currents are input to hardware phasor measurement units (PMUs) through the analog outputs of the simulator. Time synchronizing signals for the PMU devices are supplied from a common GPS clock. The real time data collected from PMUs are sent to a phasor data concentrator (PDC) through Ethernet using the TCP/IP protocol. A real-time transmission line parameter monitoring application program that uses the synchrophasor data provided by the PDC is implemented and validated. The experimental synchrophasor network developed in this thesis is expected to be used in research on synchrophasor applications as well as in graduate and undergraduate teaching.

  3. Sandwich node architecture for agile wireless sensor networks for real-time structural health monitoring applications

    Science.gov (United States)

    Wang, Zi; Pakzad, Shamim; Cheng, Liang

    2012-04-01

    In recent years, wireless sensor network (WSN), as a powerful tool, has been widely applied to structural health monitoring (SHM) due to its low cost of deployment. Several commercial hardware platforms of wireless sensor networks (WSN) have been developed and used for structural monitoring applications [1,2]. A typical design of a node includes a sensor board and a mote connected to it. Sensing units, analog filters and analog-to-digital converters (ADCs) are integrated on the sensor board and the mote consists of a microcontroller and a wireless transceiver. Generally, there are a set of sensor boards compatible with the same model of mote and the selection of the sensor board depends on the specific applications. A WSN system based on this node lacks the capability of interrupting its scheduled task to start a higher priority task. This shortcoming is rooted in the hardware architecture of the node. The proposed sandwich-node architecture is designed to remedy the shortcomings of the existing one for task preemption. A sandwich node is composed of a sensor board and two motes. The first mote is dedicated to managing the sensor board and processing acquired data. The second mote controls the first mote via commands. A prototype has been implemented using Imote2 and verified by an emulation in which one mote is triggered by a remote base station and then preempts the running task at the other mote for handling an emergency event.

  4. Squeezeposenet: Image Based Pose Regression with Small Convolutional Neural Networks for Real Time Uas Navigation

    Science.gov (United States)

    Müller, M. S.; Urban, S.; Jutzi, B.

    2017-08-01

    The number of unmanned aerial vehicles (UAVs) is increasing since low-cost airborne systems are available for a wide range of users. The outdoor navigation of such vehicles is mostly based on global navigation satellite system (GNSS) methods to gain the vehicles trajectory. The drawback of satellite-based navigation are failures caused by occlusions and multi-path interferences. Beside this, local image-based solutions like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) can e.g. be used to support the GNSS solution by closing trajectory gaps but are computationally expensive. However, if the trajectory estimation is interrupted or not available a re-localization is mandatory. In this paper we will provide a novel method for a GNSS-free and fast image-based pose regression in a known area by utilizing a small convolutional neural network (CNN). With on-board processing in mind, we employ a lightweight CNN called SqueezeNet and use transfer learning to adapt the network to pose regression. Our experiments show promising results for GNSS-free and fast localization.

  5. An energy saving mechanism of EPON networks for real time video transmission

    Science.gov (United States)

    Liu, Chien-Ping; Wu, Ho-Ting; Chiang, Yun-Ting; Chien, Shieh-Chieh; Ke, Kai-Wei

    2015-07-01

    Modern access networks are constructed widely by passive optical networks (PONs) to meet the growing bandwidth demand. However, higher bandwidth means more energy consumption. To save energy, a few research works propose the dual-mode energy saving mechanism that allows the ONU to operate between active and sleep modes periodically. However, such dual-mode energy saving design may induce unnecessary power consumption or packet delay increase in the case where only downstream data exist for most of the time. In this paper, we propose a new tri-mode energy saving scheme for Ethernet PON (EPON). The new tri-mode energy saving design, combining the dual-mode saving mechanism with the doze mode, allows the ONU to switch among these three modes alternatively. In the doze mode, the ONU may receive downstream data while keeping its transmitter close. Such scenario is often observed for real time video downstream transmission. Furthermore, the low packet delay of high priority upstream data can be attained through the use of early wake-up mechanism employed in both energy saving modes. The energy saving and system efficiency can thus be achieved jointly while maintaining the differentiated QoS for data with various priorities. Performance results via simulation have demonstrated the effectiveness of such mechanism.

  6. Real-time video streaming of sonographic clips using domestic internet networks and free videoconferencing software.

    Science.gov (United States)

    Liteplo, Andrew S; Noble, Vicki E; Attwood, Ben H C

    2011-11-01

    As the use of point-of-care sonography spreads, so too does the need for remote expert over-reading via telesonogrpahy. We sought to assess the feasibility of using familiar, widespread, and cost-effective existent technology to allow remote over-reading of sonograms in real time and to compare 4 different methods of transmission and communication for both the feasibility of transmission and image quality. Sonographic video clips were transmitted using 2 different connections (WiFi and 3G) and via 2 different videoconferencing modalities (iChat [Apple Inc, Cupertino, CA] and Skype [Skype Software Sàrl, Luxembourg]), for a total of 4 different permutations. The clips were received at a remote location and recorded and then scored by expert reviewers for image quality, resolution, and detail. Wireless transmission of sonographic clips was feasible in all cases when WiFi was used and when Skype was used over a 3G connection. Images transmitted via a WiFi connection were statistically superior to those transmitted via 3G in all parameters of quality (average P = .031), and those sent by iChat were superior to those sent by Skype but not statistically so (average P = .057). Wireless transmission of sonographic video clips using inexpensive hardware, free videoconferencing software, and domestic Internet networks is feasible with retention of image quality sufficient for interpretation. WiFi transmission results in greater image quality than transmission by a 3G network.

  7. Heterogeneous network epidemics: real-time growth, variance and extinction of infection.

    Science.gov (United States)

    Ball, Frank; House, Thomas

    2017-09-01

    Recent years have seen a large amount of interest in epidemics on networks as a way of representing the complex structure of contacts capable of spreading infections through the modern human population. The configuration model is a popular choice in theoretical studies since it combines the ability to specify the distribution of the number of contacts (degree) with analytical tractability. Here we consider the early real-time behaviour of the Markovian SIR epidemic model on a configuration model network using a multitype branching process. We find closed-form analytic expressions for the mean and variance of the number of infectious individuals as a function of time and the degree of the initially infected individual(s), and write down a system of differential equations for the probability of extinction by time t that are numerically fast compared to Monte Carlo simulation. We show that these quantities are all sensitive to the degree distribution-in particular we confirm that the mean prevalence of infection depends on the first two moments of the degree distribution and the variance in prevalence depends on the first three moments of the degree distribution. In contrast to most existing analytic approaches, the accuracy of these results does not depend on having a large number of infectious individuals, meaning that in the large population limit they would be asymptotically exact even for one initial infectious individual.

  8. Real-time networked control of an industrial robot manipulator via discrete-time second-order sliding modes

    Science.gov (United States)

    Massimiliano Capisani, Luca; Facchinetti, Tullio; Ferrara, Antonella

    2010-08-01

    This article presents the networked control of a robotic anthropomorphic manipulator based on a second-order sliding mode technique, where the control objective is to track a desired trajectory for the manipulator. The adopted control scheme allows an easy and effective distribution of the control algorithm over two networked machines. While the predictability of real-time tasks execution is achieved by the Soft Hard Real-Time Kernel (S.Ha.R.K.) real-time operating system, the communication is established via a standard Ethernet network. The performances of the control system are evaluated under different experimental system configurations using, to perform the experiments, a COMAU SMART3-S2 industrial robot, and the results are analysed to put into evidence the robustness of the proposed approach against possible network delays, packet losses and unmodelled effects.

  9. Seamless Data Services for Real Time Communication in a Heterogeneous Networks using Network Tracking and Management

    OpenAIRE

    T, Adiline Macriga.; Kumar, Dr. P. Anandha

    2010-01-01

    Heterogeneous Networks is the integration of all existing networks under a single environment with an understanding between the functional operations and also includes the ability to make use of multiple broadband transport technologies and to support generalized mobility. It is a challenging feature for Heterogeneous networks to integrate several IP-based access technologies in a seamless way. The focus of this paper is on the requirements of a mobility management scheme for multimedia real-...

  10. Low-cost autonomous perceptron neural network inspired by quantum computation

    Science.gov (United States)

    Zidan, Mohammed; Abdel-Aty, Abdel-Haleem; El-Sadek, Alaa; Zanaty, E. A.; Abdel-Aty, Mahmoud

    2017-11-01

    Achieving low cost learning with reliable accuracy is one of the important goals to achieve intelligent machines to save time, energy and perform learning process over limited computational resources machines. In this paper, we propose an efficient algorithm for a perceptron neural network inspired by quantum computing composite from a single neuron to classify inspirable linear applications after a single training iteration O(1). The algorithm is applied over a real world data set and the results are outer performs the other state-of-the art algorithms.

  11. 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.

  12. Real-Time Support on IEEE 802.11 Wireless Ad-Hoc Networks: Reality vs. Theory

    Science.gov (United States)

    Kang, Mikyung; Kang, Dong-In; Suh, Jinwoo

    The usable throughput of an IEEE 802.11 system for an application is much less than the raw bandwidth. Although 802.11b has a theoretical maximum of 11Mbps, more than half of the bandwidth is consumed by overhead leaving at most 5Mbps of usable bandwidth. Considering this characteristic, this paper proposes and analyzes a real-time distributed scheduling scheme based on the existing IEEE 802.11 wireless ad-hoc networks, using USC/ISI's Power Aware Sensing Tracking and Analysis (PASTA) hardware platform. We compared the distributed real-time scheduling scheme with the real-time polling scheme to meet deadline, and compared a measured real bandwidth with a theoretical result. The theoretical and experimental results show that the distributed scheduling scheme can guarantee real-time traffic and enhances the performance up to 74% compared with polling scheme.

  13. MAC-Layer Active Dropping for Real-Time Video Streaming in 4G Access Networks

    KAUST Repository

    She, James

    2010-12-01

    This paper introduces a MAC-layer active dropping scheme to achieve effective resource utilization, which can satisfy the application-layer delay for real-time video streaming in time division multiple access based 4G broadband wireless access networks. When a video frame is not likely to be reconstructed within the application-layer delay bound at a receiver for the minimum decoding requirement, the MAC-layer protocol data units of such video frame will be proactively dropped before the transmission. An analytical model is developed to evaluate how confident a video frame can be delivered within its application-layer delay bound by jointly considering the effects of time-varying wireless channel, minimum decoding requirement of each video frame, data retransmission, and playback buffer. Extensive simulations with video traces are conducted to prove the effectiveness of the proposed scheme. When compared to conventional cross-layer schemes using prioritized-transmission/retransmission, the proposed scheme is practically implementable for more effective resource utilization, avoiding delay propagation, and achieving better video qualities under certain conditions.

  14. Real-time identification of vehicle motion-modes using neural networks

    Science.gov (United States)

    Wang, Lifu; Zhang, Nong; Du, Haiping

    2015-01-01

    A four-wheel ground vehicle has three body-dominated motion-modes, that is, bounce, roll, and pitch motion-modes. Real-time identification of these motion-modes can make vehicle suspensions, in particular, active suspensions, target on the dominant motion-mode and apply appropriate control strategies to improve its performance with less power consumption. Recently, a motion-mode energy method (MEM) was developed to identify the vehicle body motion-modes. However, this method requires the measurement of full vehicle states and road inputs, which are not always available in practice. This paper proposes an alternative approach to identify vehicle primary motion-modes with acceptable accuracy by employing neural networks (NNs). The effectiveness of the trained NNs is verified on a 10-DOF full-car model under various types of excitation inputs. The results confirm that the proposed method is effective in determining vehicle primary motion-modes with comparable accuracy to the MEM method. Experimental data is further used to validate the proposed method.

  15. Surveying multidisciplinary aspects in real-time distributed coding for Wireless Sensor Networks.

    Science.gov (United States)

    Braccini, Carlo; Davoli, Franco; Marchese, Mario; Mongelli, Maurizio

    2015-01-27

    Wireless Sensor Networks (WSNs), where a multiplicity of sensors observe a physical phenomenon and transmit their measurements to one or more sinks, pertain to the class of multi-terminal source and channel coding problems of Information Theory. In this category, "real-time" coding is often encountered for WSNs, referring to the problem of finding the minimum distortion (according to a given measure), under transmission power constraints, attainable by encoding and decoding functions, with stringent limits on delay and complexity. On the other hand, the Decision Theory approach seeks to determine the optimal coding/decoding strategies or some of their structural properties. Since encoder(s) and decoder(s) possess different information, though sharing a common goal, the setting here is that of Team Decision Theory. A more pragmatic vision rooted in Signal Processing consists of fixing the form of the coding strategies (e.g., to linear functions) and, consequently, finding the corresponding optimal decoding strategies and the achievable distortion, generally by applying parametric optimization techniques. All approaches have a long history of past investigations and recent results. The goal of the present paper is to provide the taxonomy of the various formulations, a survey of the vast related literature, examples from the authors' own research, and some highlights on the inter-play of the different theories.

  16. All-IP wireless sensor networks for real-time patient monitoring.

    Science.gov (United States)

    Wang, Xiaonan; Le, Deguang; Cheng, Hongbin; Xie, Conghua

    2014-12-01

    This paper proposes the all-IP WSNs (wireless sensor networks) for real-time patient monitoring. In this paper, the all-IP WSN architecture based on gateway trees is proposed and the hierarchical address structure is presented. Based on this architecture, the all-IP WSN can perform routing without route discovery. Moreover, a mobile node is always identified by a home address and it does not need to be configured with a care-of address during the mobility process, so the communication disruption caused by the address change is avoided. Through the proposed scheme, a physician can monitor the vital signs of a patient at any time and at any places, and according to the IPv6 address he can also obtain the location information of the patient in order to perform effective and timely treatment. Finally, the proposed scheme is evaluated based on the simulation, and the simulation data indicate that the proposed scheme might effectively reduce the communication delay and control cost, and lower the packet loss rate. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Wireless Sensor Networks and Real-Time Locating Systems to Fight against Maritime Piracy

    Directory of Open Access Journals (Sweden)

    Óscar García

    2012-06-01

    Full Text Available There is a wide range of military and civil applications where Wireless Sensor Networks (WSNs and Multi-Agent Systems (MASs can be used for providing context-awareness for troops and special corps. On the one hand, WSNs comprise an ideal technology to develop Real-Time Locating Systems (RTLSs aimed at indoor environments, where existing global navigation satellite systems do not work properly. On the other hand, agent-based architectures allow building autonomous and robust systems that are capable of working on highly dynamic scenarios. This paper presents two piracy scenarios where the n-Core platform can be applied. n-Core is a hardware and software platform intended for developing and deploying easily and quickly a wide variety of WSNs applications based on the ZigBee standard. In the first scenario a RTLS is deployed to support boarding and rescue operations. In the second scenario a multi-agent system is proposed to detect the unloading of illegal traffic of merchandise at ports.

  18. Real-time parameter optimization based on neural network for smart injection molding

    Science.gov (United States)

    Lee, H.; Liau, Y.; Ryu, K.

    2018-03-01

    The manufacturing industry has been facing several challenges, including sustainability, performance and quality of production. Manufacturers attempt to enhance the competitiveness of companies by implementing CPS (Cyber-Physical Systems) through the convergence of IoT(Internet of Things) and ICT(Information & Communication Technology) in the manufacturing process level. Injection molding process has a short cycle time and high productivity. This features have been making it suitable for mass production. In addition, this process is used to produce precise parts in various industry fields such as automobiles, optics and medical devices. Injection molding process has a mixture of discrete and continuous variables. In order to optimized the quality, variables that is generated in the injection molding process must be considered. Furthermore, Optimal parameter setting is time-consuming work to predict the optimum quality of the product. Since the process parameter cannot be easily corrected during the process execution. In this research, we propose a neural network based real-time process parameter optimization methodology that sets optimal process parameters by using mold data, molding machine data, and response data. This paper is expected to have academic contribution as a novel study of parameter optimization during production compare with pre - production parameter optimization in typical studies.

  19. A Human Sensor Network Framework in Support of Near Real Time Situational Geophysical Modeling

    Science.gov (United States)

    Aulov, O.; Price, A.; Smith, J. A.; Halem, M.

    2013-12-01

    The area of Disaster Management is well established among Federal Agencies such as FEMA, EPA, NOAA and NASA. These agencies have well formulated frameworks for response and mitigation based on near real time satellite and conventional observing networks for assimilation into geophysical models. Forecasts from these models are used to communicate with emergency responders and the general public. More recently, agencies have started using social media to broadcast warnings and alerts to potentially affected communities. In this presentation, we demonstrate the added benefits of mining and assimilating the vast amounts of social media data available from heterogeneous hand held devices and social networks into established operational geophysical modeling frameworks as they apply to the five cornerstones of disaster management - Prevention, Mitigation, Preparedness, Response and Recovery. Often, in situations of extreme events, social media provide the earliest notification of adverse extreme events. However, various forms of social media data also can provide useful geolocated and time stamped in situ observations, complementary to directly sensed conventional observations. We use the concept of a Human Sensor Network where one views social media users as carrying field deployed "sensors" whose posts are the remotely "sensed instrument measurements.' These measurements can act as 'station data' providing the resolution and coverage needed for extreme event specific modeling and validation. Here, we explore the use of social media through the use of a Human Sensor Network (HSN) approach as another data input source for assimilation into geophysical models. Employing the HSN paradigm can provide useful feedback in near real-time, but presents software challenges for rapid access, quality filtering and transforming massive social media data into formats consistent with the operational models. As a use case scenario, we demonstrate the value of HSN for disaster management

  20. Validation of real-time zenith tropospheric delay estimation with TOMION software within WAGNSS networks

    OpenAIRE

    Graffigna, Victoria

    2017-01-01

    The TOmographic Model of the IONospheric electron content (TOMION) software implements a simultaneous precise geodetic and ionospheric modeling, which can be used to test new approaches for real-time precise GNSS modeling (positioning, ionospheric and tropospheric delays, clock errors, among others). In this work, the software is used to estimate the Zenith Tropospheric Delay (ZTD) emulating real time and its performance is evaluated through a comparative analysis with a built-in GIPSY estima...

  1. Development of real-time voltage stability monitoring tool for power system transmission network using Synchrophasor data

    Science.gov (United States)

    Pulok, Md Kamrul Hasan

    Intelligent and effective monitoring of power system stability in control centers is one of the key issues in smart grid technology to prevent unwanted power system blackouts. Voltage stability analysis is one of the most important requirements for control center operation in smart grid era. With the advent of Phasor Measurement Unit (PMU) or Synchrophasor technology, real time monitoring of voltage stability of power system is now a reality. This work utilizes real-time PMU data to derive a voltage stability index to monitor the voltage stability related contingency situation in power systems. The developed tool uses PMU data to calculate voltage stability index that indicates relative closeness of the instability by producing numerical indices. The IEEE 39 bus, New England power system was modeled and run on a Real-time Digital Simulator that stream PMU data over the Internet using IEEE C37.118 protocol. A Phasor data concentrator (PDC) is setup that receives streaming PMU data and stores them in Microsoft SQL database server. Then the developed voltage stability monitoring (VSM) tool retrieves phasor measurement data from SQL server, performs real-time state estimation of the whole network, calculate voltage stability index, perform real-time ranking of most vulnerable transmission lines, and finally shows all the results in a graphical user interface. All these actions are done in near real-time. Control centers can easily monitor the systems condition by using this tool and can take precautionary actions if needed.

  2. Real-time Geomagnetic Data from a Raspberry Pi Magnetometer Network in the United Kingdom

    Science.gov (United States)

    Case, N.; Beggan, C.; Marple, S. R.

    2017-12-01

    In 2014, BGS and the University of Lancaster won an STFC Public Engagement grant to build and deploy 10 Raspberry Pi magnetometers to secondary schools across the UK to enable citizen science. The system uses a Raspberry Pi computer as a logging and data transfer device, connected to a set of three orthogonal miniature fluxgate magnetometers. The system has a nominal sensitivity of around 1 nanoTesla (nT), in each component direction (North, East and Down). This is around twenty times less sensitive than a current scientific-level instrument, but given its relatively low-cost, at about £250 ($325) per unit, this is an excellent price-to-performance ratio given we could not improve the sensitivity unless we spent a lot more money. The magnetic data are sampled at a 5 second cadence and sent to the AuroraWatch website at Lancaster University every 2 minutes. The data are freely available to view and download. The primary aim of the project is to encourage students from 14-18 years old to look at how sensors can be used to collect geophysical data and integrate it together to give a wider understanding of physical phenomena. A second aim is to provide useful data on the spatial variation of the magnetic field for analysis of geomagnetic storms, alongside data from the BGS observatory and University of Lancaster's SAMNET variometer network. We show results from the build, testing and running of the sensors including some recent storms and we reflect on our experiences in engaging schools and the general public with information about the magnetic field. The information to build the system and logging and analysis software for the Raspberry Pi is all freely available, allowing those interested to participate in the project as citizen scientists.

  3. An efficient solution of real-time data processing for multi-GNSS network

    Science.gov (United States)

    Gong, Xiaopeng; Gu, Shengfeng; Lou, Yidong; Zheng, Fu; Ge, Maorong; Liu, Jingnan

    2017-12-01

    Global navigation satellite systems (GNSS) are acting as an indispensable tool for geodetic research and global monitoring of the Earth, and they have been rapidly developed over the past few years with abundant GNSS networks, modern constellations, and significant improvement in mathematic models of data processing. However, due to the increasing number of satellites and stations, the computational efficiency becomes a key issue and it could hamper the further development of GNSS applications. In this contribution, this problem is overcome from the aspects of both dense linear algebra algorithms and GNSS processing strategy. First, in order to fully explore the power of modern microprocessors, the square root information filter solution based on the blocked QR factorization employing as many matrix-matrix operations as possible is introduced. In addition, the algorithm complexity of GNSS data processing is further decreased by centralizing the carrier-phase observations and ambiguity parameters, as well as performing the real-time ambiguity resolution and elimination. Based on the QR factorization of the simulated matrix, we can conclude that compared to unblocked QR factorization, the blocked QR factorization can greatly improve processing efficiency with a magnitude of nearly two orders on a personal computer with four 3.30 GHz cores. Then, with 82 globally distributed stations, the processing efficiency is further validated in multi-GNSS (GPS/BDS/Galileo) satellite clock estimation. The results suggest that it will take about 31.38 s per epoch for the unblocked method. While, without any loss of accuracy, it only takes 0.50 and 0.31 s for our new algorithm per epoch for float and fixed clock solutions, respectively.

  4. On the Correctness of Real-Time Modular Computer Systems Modeling with Stopwatch Automata Networks

    Directory of Open Access Journals (Sweden)

    Alevtina B. Glonina

    2018-01-01

    Full Text Available In this paper, we consider a schedulability analysis problem for real-time modular computer systems (RT MCS. A system configuration is called schedulable if all the jobs finish within their deadlines. The authors propose a stopwatch automata-based general model of RT MCS operation. A model instance for a given RT MCS configuration is a network of stopwatch automata (NSA and it can be built automatically using the general model. A system operation trace, which is necessary for checking the schedulability criterion, can be obtained from the corresponding NSA trace. The paper substantiates the correctness of the proposed approach. A set of correctness requirements to models of system components and to the whole system model were derived from RT MCS specifications. The authors proved that if all models of system components satisfy the corresponding requirements, the whole system model built according to the proposed approach satisfies its correctness requirements and is deterministic (i.e. for a given configuration a trace generated by the corresponding model run is uniquely determined. The model determinism implies that any model run can be used for schedulability analysis. This fact is crucial for the approach efficiency, as the number of possible model runs grows exponentially with the number of jobs in a system. Correctness requirements to models of system components models can be checked automatically by a verifier using observer automata approach. The authors proved by using UPPAAL verifier that all the developed models of system components satisfy the corresponding requirements. User-defined models of system components can be also used for system modeling if they satisfy the requirements.

  5. An Interactive Real-Time Locating System Based on Bluetooth Low-Energy Beacon Network †.

    Science.gov (United States)

    Lin, You-Wei; Lin, Chi-Yi

    2018-05-21

    The ubiquity of Bluetooth-enabled smartphones and peripherals has brought tremendous convenience to our daily life. In recent years, Bluetooth beacons have also been gaining popularity in implementing a variety of innovative location-based services such as self-guided systems in exhibition centers. However, the broadcast-based beacon technology can only provide unidirectional communication. In case smartphone users would like to respond to the beacon messages, they have to rely on their own mobile Internet connections to send the information back to the backend system. Nevertheless, mobile Internet services may not be always available or too costly. In this work, we develop a real-time locating system based only on the Bluetooth low energy (BLE) technology to support interactive communications by combining the broadcast and mesh topology options to extend the applicability of beacon solutions. Specifically, we turn the smartphone into a beacon device and augment the beacon devices with the capability of forming a mesh network. The implementation result shows that our beacon devices can detect the presence of specific users at specific locations, and then the presence state can be sent to the application server via the relay of beacon devices. Moreover, the application server can send personalized location-based messages to the users, again via the relay of beacon devices. With the capability of relaying messages between the beacon devices, it would be convenient for developers to implement a variety of interactive applications such as tracking VIP customers at the airport, or tracking an elder with Alzheimer’s disease in the neighborhood.

  6. An Interactive Real-Time Locating System Based on Bluetooth Low-Energy Beacon Network

    Directory of Open Access Journals (Sweden)

    You-Wei Lin

    2018-05-01

    Full Text Available The ubiquity of Bluetooth-enabled smartphones and peripherals has brought tremendous convenience to our daily life. In recent years, Bluetooth beacons have also been gaining popularity in implementing a variety of innovative location-based services such as self-guided systems in exhibition centers. However, the broadcast-based beacon technology can only provide unidirectional communication. In case smartphone users would like to respond to the beacon messages, they have to rely on their own mobile Internet connections to send the information back to the backend system. Nevertheless, mobile Internet services may not be always available or too costly. In this work, we develop a real-time locating system based only on the Bluetooth low energy (BLE technology to support interactive communications by combining the broadcast and mesh topology options to extend the applicability of beacon solutions. Specifically, we turn the smartphone into a beacon device and augment the beacon devices with the capability of forming a mesh network. The implementation result shows that our beacon devices can detect the presence of specific users at specific locations, and then the presence state can be sent to the application server via the relay of beacon devices. Moreover, the application server can send personalized location-based messages to the users, again via the relay of beacon devices. With the capability of relaying messages between the beacon devices, it would be convenient for developers to implement a variety of interactive applications such as tracking VIP customers at the airport, or tracking an elder with Alzheimer’s disease in the neighborhood.

  7. A Tree Based Broadcast Scheme for (m, k)-firm Real-Time Stream in Wireless Sensor Networks.

    Science.gov (United States)

    Park, HoSung; Kim, Beom-Su; Kim, Kyong Hoon; Shah, Babar; Kim, Ki-Il

    2017-11-09

    Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new ( m , k )-firm-based Real-time Broadcast Protocol (FRBP) by constructing a broadcast tree to satisfy the ( m , k )-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured ( m , k )-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption.

  8. A reliable and real-time aggregation aware data dissemination in a chain-based wireless sensor network

    NARCIS (Netherlands)

    Taghikhaki, Zahra; Meratnia, Nirvana; Havinga, Paul J.M.

    2012-01-01

    Time-critical applications of Wireless Sensor Networks (WSNs) demand timely data delivery for fast identification of out-of-ordinary situations and fast and reliable delivery of notification and warning messages. Due to the low reliable links in WSNs, achieving real-time guarantees and providing

  9. Global TIE Observatories: Real Time Observational Astronomy Through a Robotic Telescope Network

    Science.gov (United States)

    Clark, G.; Mayo, L. A.

    2001-12-01

    Astronomy in grades K-12 is traditionally taught (if at all) using textbooks and a few simple hands-on activities. Teachers are generally not trained in observational astronomy techniques and are unfamiliar with the most basic astronomical concepts. In addition, most students, by High School graduation, will never have even looked through the eyepiece of a telescope. The problem becomes even more challenging in inner cities, remote rural areas and low socioeconomic communities where educational emphasis on topics in astronomy as well as access to observing facilities is limited or non existent. Access to most optical telescope facilities is limited to monthly observing nights that cater to a small percentage of the general public living near the observatory. Even here, the observing experience is a one-time event detached from the process of scientific enquiry and sustained educational application. Additionally, a number of large, "research grade" observatory facilities are largely unused, partially due to the slow creep of light pollution around the facilities as well as the development of newer, more capable telescopes. Though cutting edge science is often no longer possible at these sights, real research opportunities in astronomy remain numerous for these facilities as educational tools. The possibility now exists to establish a network of research grade telescopes, no longer useful to the professional astronomical community, that can be made accessible through classrooms, after school, and community based programs all across the country through existing IT technologies and applications. These telescopes could provide unparalleled research and educational opportunities for a broad spectrum of students and turns underutilized observatory facilities into valuable, state-of-the-art teaching centers. The NASA sponsored Telescopes In Education project has been wildly successful in engaging the K-12 education community in real-time, hands-on, interactive astronomy

  10. A Portable Low-Cost High Density Sensor Network for Air Quality at London Heathrow Airport

    Science.gov (United States)

    Popoola, Olalekan; Mead, Iq; Bright, Vivien; Baron, Ronan; Saffell, John; Stewart, Gregor; Kaye, Paul; Jones, Roderic

    2013-04-01

    Outdoor air quality and its impact on human health and the environment have been well studied and it has been projected that poor air quality will surpass poor sanitation as the major course of environmental premature mortality by 2050 (IGAC / IGBP, release statement, 2012). Transport-related pollution has been regulated at various levels by enactment of legislations at local, national, regional and global stages. As part of the mitigation measures, routine measurements of atmospheric pollutants such as carbon monoxide (CO), nitric oxide (NO) and nitrogen dioxide (NO2) have to be established in areas where air quality problems are identified. In addition, emission inventories are also generated for different atmospheric environments including urban areas and airport environments required for air quality models. Whilst recognising that most of the existing sparse monitoring networks provide high temporal measurements, spatial data of these highly variable pollutants are not captured, making it difficult to adequately characterise the highly heterogeneous air quality. Spatial information is often obtained from model data which can only be constrained using measurements from the sparse monitoring networks. The work presented here shows the application of low-cost sensor networks aimed at addressing this missing spatial information. We have shown in previous studies the application of low-cost electrochemical sensor network instruments in monitoring road transport pollutants including CO, NO and NO2 in an urban environment (Mead et. al. 2012, accepted Atmospheric Environment). Modified versions of these instruments which include additional species such as O3, SO2, VOCs and CO2 are currently deployed at London Heathrow Airport (LHR) as part of the Sensor Network for Air Quality (SNAQ) project. Meteorology data such as temperature, relative humidity, wind speed and direction are also measured as well as size-speciated particulates (0.38 to 17.4 µm). A network of 50

  11. Assessing the Performance of a Network of Low Cost Particulate Matter Sensors Deployed in Sacramento, California

    Science.gov (United States)

    Mukherjee, A. D.; Brown, S. G.; McCarthy, M. C.

    2017-12-01

    A new generation of low cost air quality sensors have the potential to provide valuable information on the spatial-temporal variability of air pollution - if the measurements have sufficient quality. This study examined the performance of a particulate matter sensor model, the AirBeam (HabitatMap Inc., Brooklyn, NY), over a three month period in the urban environment of Sacramento, California. Nineteen AirBeam sensors were deployed at a regulatory air monitoring site collocated with meteorology measurements and as a local network over an 80 km2 domain in Sacramento, CA. This study presents the methodology to evaluate the precision, accuracy, and reliability of the sensors over a range of meteorological and aerosol conditions. The sensors demonstrated a robust degree of precision during collocated measurement periods (R2 = 0.98 - 0.99) and a moderate degree of correlation against a Beta Attenuation Monitor PM2.5 monitor (R2 0.6). A normalization correction is applied during the study period so that each AirBeam sensor in the network reports a comparable value. The role of the meteorological environment on the accuracy of the sensor measurements is investigated, along with the possibility of improving the measurements through a meteorology weighted correction. The data quality of the network of sensors is examined, and the spatial variability of particulate matter through the study domain derived from the sensor network is presented.

  12. A Web service-based architecture for real-time hydrologic sensor networks

    Science.gov (United States)

    Wong, B. P.; Zhao, Y.; Kerkez, B.

    2014-12-01

    Recent advances in web services and cloud computing provide new means by which to process and respond to real-time data. This is particularly true of platforms built for the Internet of Things (IoT). These enterprise-scale platforms have been designed to exploit the IP-connectivity of sensors and actuators, providing a robust means by which to route real-time data feeds and respond to events of interest. While powerful and scalable, these platforms have yet to be adopted by the hydrologic community, where the value of real-time data impacts both scientists and decision makers. We discuss the use of one such IoT platform for the purpose of large-scale hydrologic measurements, showing how rapid deployment and ease-of-use allows scientists to focus on their experiment rather than software development. The platform is hardware agnostic, requiring only IP-connectivity of field devices to capture, store, process, and visualize data in real-time. We demonstrate the benefits of real-time data through a real-world use case by showing how our architecture enables the remote control of sensor nodes, thereby permitting the nodes to adaptively change sampling strategies to capture major hydrologic events of interest.

  13. Network Reduction Algorithm for Developing Distribution Feeders for Real-Time Simulators: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Nagarajan, Adarsh; Nelson, Austin; Prabakar, Kumaraguru; Hoke, Andy; Asano, Marc; Ueda, Reid; Nepal, Shaili

    2017-06-15

    As advanced grid-support functions (AGF) become more widely used in grid-connected photovoltaic (PV) inverters, utilities are increasingly interested in their impacts when implemented in the field. These effects can be understood by modeling feeders in real-time systems and testing PV inverters using power hardware-in-the-loop (PHIL) techniques. This paper presents a novel feeder model reduction algorithm using a Monte Carlo method that enables large feeders to be solved and operated on real-time computing platforms. Two Hawaiian Electric feeder models in Synergi Electric's load flow software were converted to reduced order models in OpenDSS, and subsequently implemented in the OPAL-RT real-time digital testing platform. Smart PV inverters were added to the real-time model with AGF responses modeled after characterizing commercially available hardware inverters. Finally, hardware inverters were tested in conjunction with the real-time model using PHIL techniques so that the effects of AGFs on the choice feeders could be analyzed.

  14. Applications of neural networks to real-time data processing at the Environmental and Molecular Sciences Laboratory (EMSL)

    International Nuclear Information System (INIS)

    Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

    1993-06-01

    Detailed design of the Environmental and Molecular Sciences Laboratory (EMSL) at the Pacific Northwest Laboratory (PNL) is nearing completion and construction is scheduled to begin later this year. This facility will assist in the environmental restoration and waste management mission at the Hanford Site. This paper identifies several real-time data processing applications within the EMSL where neural networks can potentially be beneficial. These applications include real-time sensor data acquisition and analysis, spectral analysis, process control, theoretical modeling, and data compression

  15. W-Band Real-Time Transmission Utilizing a Reconfigurable RAU for NG-PON Networks

    DEFF Research Database (Denmark)

    Chorchos, Łukasz; Turkiewicz, Jarosław P.; Rommel, Simon

    2016-01-01

    In this article, we propose and test a reconfigurable Remote Access Unit (RAU) to interface optical and W-band wireless communication links (75–110 GHz), utilizing optical heterodyne signal upconversion. The RAU is composed of a tunable local oscillator, narrow optical filter and a control unit....... The RAU can be software-reconfigured to select a specific dense wavelength division multiplexed (DWDM) channel. Real-time tests with 100 GHz spaced DWDM signals have been performed. Real-time 2.5 Gbit/s error free radio transmission in the 75 GHz to 95 GHz range of the W-band was achieved after 15 km...

  16. PAVENET OS: A Compact Hard Real-Time Operating System for Precise Sampling in Wireless Sensor Networks

    Science.gov (United States)

    Saruwatari, Shunsuke; Suzuki, Makoto; Morikawa, Hiroyuki

    The paper shows a compact hard real-time operating system for wireless sensor nodes called PAVENET OS. PAVENET OS provides hybrid multithreading: preemptive multithreading and cooperative multithreading. Both of the multithreading are optimized for two kinds of tasks on wireless sensor networks, and those are real-time tasks and best-effort ones. PAVENET OS can efficiently perform hard real-time tasks that cannot be performed by TinyOS. The paper demonstrates the hybrid multithreading realizes compactness and low overheads, which are comparable to those of TinyOS, through quantitative evaluation. The evaluation results show PAVENET OS performs 100 Hz sensor sampling with 0.01% jitter while performing wireless communication tasks, whereas optimized TinyOS has 0.62% jitter. In addition, PAVENET OS has a small footprint and low overheads (minimum RAM size: 29 bytes, minimum ROM size: 490 bytes, minimum task switch time: 23 cycles).

  17. Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.

    Science.gov (United States)

    Gopalakrishnan, Ravichandran C; Karunakaran, Manivannan

    2014-01-01

    Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

  18. Southern California Seismic Network: New Design and Implementation of Redundant and Reliable Real-time Data Acquisition Systems

    Science.gov (United States)

    Saleh, T.; Rico, H.; Solanki, K.; Hauksson, E.; Friberg, P.

    2005-12-01

    The Southern California Seismic Network (SCSN) handles more than 2500 high-data rate channels from more than 380 seismic stations distributed across southern California. These data are imported real-time from dataloggers, earthworm hubs, and partner networks. The SCSN also exports data to eight different partner networks. Both the imported and exported data are critical for emergency response and scientific research. Previous data acquisition systems were complex and difficult to operate, because they grew in an ad hoc fashion to meet the increasing needs for distributing real-time waveform data. To maximize reliability and redundancy, we apply best practices methods from computer science for implementing the software and hardware configurations for import, export, and acquisition of real-time seismic data. Our approach makes use of failover software designs, methods for dividing labor diligently amongst the network nodes, and state of the art networking redundancy technologies. To facilitate maintenance and daily operations we seek to provide some separation between major functions such as data import, export, acquisition, archiving, real-time processing, and alarming. As an example, we make waveform import and export functions independent by operating them on separate servers. Similarly, two independent servers provide waveform export, allowing data recipients to implement their own redundancy. The data import is handled differently by using one primary server and a live backup server. These data import servers, run fail-over software that allows automatic role switching in case of failure from primary to shadow. Similar to the classic earthworm design, all the acquired waveform data are broadcast onto a private network, which allows multiple machines to acquire and process the data. As we separate data import and export away from acquisition, we are also working on new approaches to separate real-time processing and rapid reliable archiving of real-time data

  19. Real-time visual communication to aid disaster recovery in a multi-segment hybrid wireless networking system

    Science.gov (United States)

    Al Hadhrami, Tawfik; Wang, Qi; Grecos, Christos

    2012-06-01

    When natural disasters or other large-scale incidents occur, obtaining accurate and timely information on the developing situation is vital to effective disaster recovery operations. High-quality video streams and high-resolution images, if available in real time, would provide an invaluable source of current situation reports to the incident management team. Meanwhile, a disaster often causes significant damage to the communications infrastructure. Therefore, another essential requirement for disaster management is the ability to rapidly deploy a flexible incident area communication network. Such a network would facilitate the transmission of real-time video streams and still images from the disrupted area to remote command and control locations. In this paper, a comprehensive end-to-end video/image transmission system between an incident area and a remote control centre is proposed and implemented, and its performance is experimentally investigated. In this study a hybrid multi-segment communication network is designed that seamlessly integrates terrestrial wireless mesh networks (WMNs), distributed wireless visual sensor networks, an airborne platform with video camera balloons, and a Digital Video Broadcasting- Satellite (DVB-S) system. By carefully integrating all of these rapidly deployable, interworking and collaborative networking technologies, we can fully exploit the joint benefits provided by WMNs, WSNs, balloon camera networks and DVB-S for real-time video streaming and image delivery in emergency situations among the disaster hit area, the remote control centre and the rescue teams in the field. The whole proposed system is implemented in a proven simulator. Through extensive simulations, the real-time visual communication performance of this integrated system has been numerically evaluated, towards a more in-depth understanding in supporting high-quality visual communications in such a demanding context.

  20. Research overview of real-time monitoring system for micro leak of three-dimensional pipe network

    Directory of Open Access Journals (Sweden)

    Shaofeng WANG

    2016-04-01

    Full Text Available Aiming at the key technical problems encountered by domestic and foreign scholars in building the real-time monitoring system for the micro leak of three-dimensional pipe networks, the paper classifies the problems into three aspects: 1 in the extraction of fault signal frequency, how to avoid the effect of the mixed echo stack and improve the delay estimation accuracy of the correlation; 2 in network bifurcation structure, how to discern the signal propagation path, and how to locate the leak source; 3 under the uncertainly delay in transmitting and receiving information data, how to ensure the time synchronization accuracy of the real-time monitoring system for the three-dimensional pipe network leakage. Through the comparison of the monitoring technologies for the pipe network leakage at home and abroad, it shows that the acoustic emission sensor network based three-dimensional pipeline leak real-time monitoring has great advantages in detecting the weak leakage of flammable and explosive gas/liquid transportation pipelines.

  1. 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

    Short-term forecasts of current high-resolution numerical weather prediction models still have large deficits in forecasting the exact temporal and spatial location of severe, locally influenced weather such as summer-time convective storms or cool season lifted stratus or ground fog. Often, the thermodynamic instability - especially in the boundary layer - plays an essential role in the evolution of weather events. While the thermodynamic state of the atmosphere is well measured close to the surface (i.e. 2 m) by in-situ sensors and in the upper troposphere by satellite sounders, the planetary boundary layer remains a largely under-sampled region of the atmosphere where only sporadic information from radiosondes or aircraft observations is available. The major objective of the presented DWD-funded project ARON (Extramural Research Programme) is to overcome this observational gap and to design an optimized network of ground based microwave radiometers (MWR) and compact Differential Absorption Lidars (DIAL) for a continuous, near-real-time monitoring of temperature and humidity in the atmospheric boundary layer in order to monitor thermodynamic (in)stability. Previous studies showed, that microwave profilers are well suited for continuously monitoring the temporal development of atmospheric stability (i.e. Cimini et al., 2015) before the initiation of deep convection, especially in the atmospheric boundary layer. However, the vertical resolution of microwave temperature profiles is best in the lowest kilometer above the surface, decreasing rapidly with increasing height. In addition, humidity profile retrievals typically cannot be resolved with more than two degrees of freedom for signal, resulting in a rather poor vertical resolution throughout the troposphere. Typical stability indices used to assess the potential of convection rely on temperature and humidity values not only in the region of the boundary layer but also in the layers above. Therefore, satellite

  2. Bridging the Gap - Networking Educators using Real-Time Seismic Data

    Science.gov (United States)

    Ortiz, A. M.; Renwald, M. D.; Baldwin, T. K.; Hall, M. K.

    2004-12-01

    After nearly a decade, the seismology community has made critical advances in identifying what is effective and what is needed for success in incorporating real-time seismic data in the classroom. Today's K-16 classroom teachers have many options and opportunities for incorporating short- and long-term inquiry activities for monitoring earthquakes and analyzing seismic data in their daily instruction. Through the SpiNet program, we are providing web-based tools that support educators working with real-time seismic data (http://www.scieds.com/spinet/). Our site includes a Recent Seismicity section, which allows users to share seismic data in real-time, and provides near real-time information about global seismicity. Our Activities section provides data and lessons to assist educators who wish to integrate seismology into their classroom. The Research section, currently under development, will allow educators to share general information about how they teach seismology in their classroom through a discussion board and by posting lesson plans. In addition, we are developing a user-friendly tool for students to post results of their research projects. Designing a website which targets a range of users requires a working knowledge of both user needs and website programming and design. User needs include providing a logical navigational structure and accounting for differences in browser functionality, internet access, and users' abilities. Using website development tools, such as PHP, MySQL, RDF feeds, and specialized geoscience applications, we are automating site maintenance; incorporating databases for information storage and retrieval; and providing accessibility for users with a range of skills and physical limitations. By incorporating these features, we have built a dynamic interface for a broad range of users interested in educational seismology.

  3. Improved UUV Positioning Using Acoustic Communications and a Potential for Real-Time Networking and Collaboration

    Science.gov (United States)

    2017-06-01

    model the environment is proposed for real-time applications . To be able to establish the submersible vehicle’s position, a tracking algorithm ...approximation, which in certain cases can lead to coarse accuracy in the results. In high frequency applications , however, ray tracing algorithms are very...intelligence techniques, as in the genetic algorithms or simulated annealing algorithms . START Initial Choice for Run UKF for  , , , ,  x R Q

  4. A Wireless and Real-Time Monitoring System Design for Car Networking Applications

    Directory of Open Access Journals (Sweden)

    Li Wenjun

    2013-01-01

    Full Text Available We described a wireless and monitoring system to obtain several classes of vehicle data and send them to the server via General Packet Radio Service (GPRS in real-time. These data are consisted by on-board diagnostic (OBD which get from the vehicle’s OBD interface, Tire-Pressure Monitoring system (TPMS and Global Positioning System (GPS. The main content of this paper is the hardware design of the system, especially RF modules and antennas.

  5. Acquisition of Real Time Simulator for Intelligent Power Networks in Operational Energy Applications

    Science.gov (United States)

    2017-12-05

    and fixed power installations to enhance DoD mission effectiveness. The long term goal of this effort is to create a strong research and education ...effort is to create a strong research and education center at UTSA focused on innovative technologies and solutions for Energy-Systems Management...in Real-Time. , Grid Low voltage dc = ~ Dual Active Bridge (DAB) With 3-Level NPC HV bridge and High frequency transformer High voltage dc

  6. Synchronous Databus Network in ITER: Open source real-time network for the next nuclear fusion experiment

    International Nuclear Information System (INIS)

    Boncagni, L.; Centioli, C.; Iannone, F.; Neri, C.; Panella, M.; Pangione, L.; Riva, M.; Scappaticci, M.; Vitale, V.; Zaccarian, L.

    2008-01-01

    The next nuclear fusion experiment, ITER, is providing the infrastructure for the optimal operation of a burning plasma, requiring feedback control of discharge parameters and on-line evaluation of computationally intensive models running in a cluster of controller nodes. Thus, the synchronization of the available information on the plasma and plant state variables among the controller nodes is a key issue for ITER. The ITER conceptual design aims to perform feedback control on a cluster of distributed controllers connected by a Synchronous Databus Network (SDN). Therefore it is mandatory to achieve a deterministic data exchange among the controller nodes with a refresh rate of at least 1 kHz and a jitter of at least 50 μs. Thus, a conservative estimate of the data flow within the controller network can be 3 kSample/ms. In this paper the open source RTnet project is evaluated to meet the requirements of the SDN of ITER. A testbed involving a cluster of eight nodes connected over a standard ethernet network has been set up to simulate a distributed real-time control system. The main goal of the test is to verify the compliance of the performance with the ITER SDN requirements

  7. Automated observatory in Antarctica: real-time data transfer on constrained networks in practice

    Directory of Open Access Journals (Sweden)

    S. Bracke

    2017-08-01

    Full Text Available In 2013 a project was started by the geophysical centre in Dourbes to install a fully automated magnetic observatory in Antarctica. This isolated place comes with specific requirements: unmanned station during 6 months, low temperatures with extreme values down to −50 °C, minimum power consumption and satellite bandwidth limited to 56 Kbit s−1. The ultimate aim is to transfer real-time magnetic data every second: vector data from a LEMI-25 vector magnetometer, absolute F measurements from a GEM Systems scalar proton magnetometer and absolute magnetic inclination–declination (DI measurements (five times a day with an automated DI-fluxgate magnetometer. Traditional file transfer protocols (for instance File Transfer Protocol (FTP, email, rsync show severe limitations when it comes to real-time capability. After evaluation of pro and cons of the available real-time Internet of things (IoT protocols and seismic software solutions, we chose to use Message Queuing Telemetry Transport (MQTT and receive the 1 s data with a negligible latency cost and no loss of data. Each individual instrument sends the magnetic data immediately after capturing, and the data arrive approximately 300 ms after being sent, which corresponds with the normal satellite latency.

  8. Automated observatory in Antarctica: real-time data transfer on constrained networks in practice

    Science.gov (United States)

    Bracke, Stephan; Gonsette, Alexandre; Rasson, Jean; Poncelet, Antoine; Hendrickx, Olivier

    2017-08-01

    In 2013 a project was started by the geophysical centre in Dourbes to install a fully automated magnetic observatory in Antarctica. This isolated place comes with specific requirements: unmanned station during 6 months, low temperatures with extreme values down to -50 °C, minimum power consumption and satellite bandwidth limited to 56 Kbit s-1. The ultimate aim is to transfer real-time magnetic data every second: vector data from a LEMI-25 vector magnetometer, absolute F measurements from a GEM Systems scalar proton magnetometer and absolute magnetic inclination-declination (DI) measurements (five times a day) with an automated DI-fluxgate magnetometer. Traditional file transfer protocols (for instance File Transfer Protocol (FTP), email, rsync) show severe limitations when it comes to real-time capability. After evaluation of pro and cons of the available real-time Internet of things (IoT) protocols and seismic software solutions, we chose to use Message Queuing Telemetry Transport (MQTT) and receive the 1 s data with a negligible latency cost and no loss of data. Each individual instrument sends the magnetic data immediately after capturing, and the data arrive approximately 300 ms after being sent, which corresponds with the normal satellite latency.

  9. Prospects of real-time ion temperature and rotation profiles based on neural-network charge exchange analysis

    Energy Technology Data Exchange (ETDEWEB)

    Koenig, R W.T.; Von Hellermann, M [Commission of the European Communities, Abingdon (United Kingdom). JET Joint Undertaking; Svensson, J [Royal Inst. of Tech., Stockholm (Sweden)

    1994-07-01

    A back-propagation neural network technique is used at JET to extract plasma parameters like ion temperature, rotation velocities or spectral line intensities from charge exchange (CX) spectra. It is shown that in the case of the C VI CX spectra, neural networks can give a good estimation (better than +-20% accuracy) for the main plasma parameters (Ti, V{sub rot}). Since the neural network approach involves no iterations or initial guesses the speed with which a spectrum is processed is so high (0.2 ms/spectrum) that real time analysis will be achieved in the near future. 4 refs., 8 figs.

  10. Prospects of real-time ion temperature and rotation profiles based on neural-network charge exchange analysis

    International Nuclear Information System (INIS)

    Koenig, R.W.T.; Von Hellermann, M.

    1994-01-01

    A back-propagation neural network technique is used at JET to extract plasma parameters like ion temperature, rotation velocities or spectral line intensities from charge exchange (CX) spectra. It is shown that in the case of the C VI CX spectra, neural networks can give a good estimation (better than +-20% accuracy) for the main plasma parameters (Ti, V rot ). Since the neural network approach involves no iterations or initial guesses the speed with which a spectrum is processed is so high (0.2 ms/spectrum) that real time analysis will be achieved in the near future. 4 refs., 8 figs

  11. Providing strong Security and high privacy in low-cost RFID networks

    DEFF Research Database (Denmark)

    David, Mathieu; Prasad, Neeli R.

    2009-01-01

    Since the dissemination of Radio Frequency IDentification (RFID) tags is getting larger and larger, the requirement for strong security and privacy is also increasing. Low-cost and ultra-low-cost tags are being implemented on everyday products, and their limited resources constraints the security...

  12. A Tree Based Broadcast Scheme for (m, k-firm Real-Time Stream in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    HoSung Park

    2017-11-01

    Full Text Available Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new (m, k-firm-based Real-time Broadcast Protocol (FRBP by constructing a broadcast tree to satisfy the (m, k-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured (m, k-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption.

  13. Optimal Throughput and Self-adaptability of Robust Real-Time IEEE 802.15.4 MAC for AMI Mesh Network

    International Nuclear Information System (INIS)

    Shabani, Hikma; Ahmed, Musse Mohamud; Khan, Sheroz; Hameed, Shahab Ahmed; Habaebi, Mohamed Hadi

    2013-01-01

    A smart grid refers to a modernization of the electricity system that brings intelligence, reliability, efficiency and optimality to the power grid. To provide an automated and widely distributed energy delivery, the smart grid will be branded by a two-way flow of electricity and information system between energy suppliers and their customers. Thus, the smart grid is a power grid that integrates data communication networks which provide the collected and analysed data at all levels in real time. Therefore, the performance of communication systems is so vital for the success of smart grid. Merit to the ZigBee/IEEE802.15.4std low cost, low power, low data rate, short range, simplicity and free licensed spectrum that makes wireless sensor networks (WSNs) the most suitable wireless technology for smart grid applications. Unfortunately, almost all ZigBee channels overlap with wireless local area network (WLAN) channels, resulting in severe performance degradation due to interference. In order to improve the performance of communication systems, this paper proposes an optimal throughput and self-adaptability of ZigBee/IEEE802.15.4std for smart grid

  14. A real-time and closed-loop control algorithm for cascaded multilevel inverter based on artificial neural network.

    Science.gov (United States)

    Wang, Libing; Mao, Chengxiong; Wang, Dan; Lu, Jiming; Zhang, Junfeng; Chen, Xun

    2014-01-01

    In order to control the cascaded H-bridges (CHB) converter with staircase modulation strategy in a real-time manner, a real-time and closed-loop control algorithm based on artificial neural network (ANN) for three-phase CHB converter is proposed in this paper. It costs little computation time and memory. It has two steps. In the first step, hierarchical particle swarm optimizer with time-varying acceleration coefficient (HPSO-TVAC) algorithm is employed to minimize the total harmonic distortion (THD) and generate the optimal switching angles offline. In the second step, part of optimal switching angles are used to train an ANN and the well-designed ANN can generate optimal switching angles in a real-time manner. Compared with previous real-time algorithm, the proposed algorithm is suitable for a wider range of modulation index and results in a smaller THD and a lower calculation time. Furthermore, the well-designed ANN is embedded into a closed-loop control algorithm for CHB converter with variable direct voltage (DC) sources. Simulation results demonstrate that the proposed closed-loop control algorithm is able to quickly stabilize load voltage and minimize the line current's THD (<5%) when subjecting the DC sources disturbance or load disturbance. In real design stage, a switching angle pulse generation scheme is proposed and experiment results verify its correctness.

  15. A Real-Time and Closed-Loop Control Algorithm for Cascaded Multilevel Inverter Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Libing Wang

    2014-01-01

    Full Text Available In order to control the cascaded H-bridges (CHB converter with staircase modulation strategy in a real-time manner, a real-time and closed-loop control algorithm based on artificial neural network (ANN for three-phase CHB converter is proposed in this paper. It costs little computation time and memory. It has two steps. In the first step, hierarchical particle swarm optimizer with time-varying acceleration coefficient (HPSO-TVAC algorithm is employed to minimize the total harmonic distortion (THD and generate the optimal switching angles offline. In the second step, part of optimal switching angles are used to train an ANN and the well-designed ANN can generate optimal switching angles in a real-time manner. Compared with previous real-time algorithm, the proposed algorithm is suitable for a wider range of modulation index and results in a smaller THD and a lower calculation time. Furthermore, the well-designed ANN is embedded into a closed-loop control algorithm for CHB converter with variable direct voltage (DC sources. Simulation results demonstrate that the proposed closed-loop control algorithm is able to quickly stabilize load voltage and minimize the line current’s THD (<5% when subjecting the DC sources disturbance or load disturbance. In real design stage, a switching angle pulse generation scheme is proposed and experiment results verify its correctness.

  16. Low-Cost Ultrasonic Distance Sensor Arrays with Networked Error Correction

    Directory of Open Access Journals (Sweden)

    Tianzhou Chen

    2013-09-01

    Full Text Available Distance has been one of the basic factors in manufacturing and control fields, and ultrasonic distance sensors have been widely used as a low-cost measuring tool. However, the propagation of ultrasonic waves is greatly affected by environmental factors such as temperature, humidity and atmospheric pressure. In order to solve the problem of inaccurate measurement, which is significant within industry, this paper presents a novel ultrasonic distance sensor model using networked error correction (NEC trained on experimental data. This is more accurate than other existing approaches because it uses information from indirect association with neighboring sensors, which has not been considered before. The NEC technique, focusing on optimization of the relationship of the topological structure of sensor arrays, is implemented for the compensation of erroneous measurements caused by the environment. We apply the maximum likelihood method to determine the optimal fusion data set and use a neighbor discovery algorithm to identify neighbor nodes at the top speed. Furthermore, we adopt the NEC optimization algorithm, which takes full advantage of the correlation coefficients for neighbor sensors. The experimental results demonstrate that the ranging errors of the NEC system are within 2.20%; furthermore, the mean absolute percentage error is reduced to 0.01% after three iterations of this method, which means that the proposed method performs extremely well. The optimized method of distance measurement we propose, with the capability of NEC, would bring a significant advantage for intelligent industrial automation.

  17. The effect of destination linked feature selection in real-time network intrusion detection

    CSIR Research Space (South Africa)

    Mzila, P

    2013-07-01

    Full Text Available techniques in the network intrusion detection system (NIDS) is the feature selection technique. The ability of NIDS to accurately identify intrusion from the network traffic relies heavily on feature selection, which describes the pattern of the network...

  18. Real-Time Management and Control of a Bus Public Transport Network: The STCP Experience

    Directory of Open Access Journals (Sweden)

    Jorge Freire Sousa

    2009-11-01

    Full Text Available STCP is the main bus operator in the Porto Metropolitan Area. The experimental phase of using fleet tracking and management systems fitted on public transport vehicles began in the late eighties, but only in 2002 the current system (SAEI covered all the buses of the company. Nowadays, these systems are integral company management systems. In this paper, the experience of the past six years or so is presented. The main reasons for the use of such systems are detailed, the architecture and functionalities are described and the importance of accessing real-time information together with subsequent analysis of the data obtained is underlined.

  19. Human perception of the measurement of a network attack taxonomy in near real-time

    CSIR Research Space (South Africa)

    van Heerden, R

    2014-07-01

    Full Text Available apparent long after an attack and even then it is sometimes only speculation. For example, the Aggressor can not be determined in a near real-time environment and for some attacks the real power behind the attack is never determined or proven. 2.1 Actor...- tigating the accuracy of various assessment methods. We classify each class as either defined, high, low or not quantifiable. For example, it may not be possi- ble to determine the instigator of an attack (Aggressor), but only that the attack has been...

  20. Development of real time monitor system displaying seismic waveform data observed at seafloor seismic network, DONET, for disaster management information

    Science.gov (United States)

    Horikawa, H.; Takaesu, M.; Sueki, K.; Takahashi, N.; Sonoda, A.; Miura, S.; Tsuboi, S.

    2014-12-01

    Mega-thrust earthquakes are anticipated to occur in the Nankai Trough in southwest Japan. In the source areas, we have deployed seafloor seismic network, DONET (Dense Ocean-floor Network System for Earthquake and Tsunamis), in 2010 in order to monitor seismicity, crustal deformations, and tsunamis. DONET system consists of totally 20 stations, which is composed of six kinds of sensors, including strong-motion seismometers and quartz pressure gauges. Those stations are densely distributed with an average spatial interval of 15-20 km and cover near the trench axis to coastal areas. Observed data are transferred to a land station through a fiber-optical cable and then to JAMSTEC (Japan Agency for Marine-Earth Science and Technology) data management center through a private network in real time. After 2011 off the Pacific coast of Tohoku Earthquake, each local government close to Nankai Trough try to plan disaster prevention scheme. JAMSTEC will disseminate DONET data combined with research accomplishment so that they will be widely recognized as important earthquake information. In order to open DONET data observed for research to local government, we have developed a web application system, REIS (Real-time Earthquake Information System). REIS is providing seismic waveform data to some local governments close to Nankai Trough as a pilot study. As soon as operation of DONET is ready, REIS will start full-scale operation. REIS can display seismic waveform data of DONET in real-time, users can select strong motion and pressure data, and configure the options of trace view arrangement, time scale, and amplitude. In addition to real-time monitoring, REIS can display past seismic waveform data and show earthquake epicenters on the map. In this presentation, we briefly introduce DONET system and then show our web application system. We also discuss our future plans for further developments of REIS.

  1. Reorganization of functional brain networks mediates the improvement of cognitive performance following real-time neurofeedback training of working memory.

    Science.gov (United States)

    Zhang, Gaoyan; Yao, Li; Shen, Jiahui; Yang, Yihong; Zhao, Xiaojie

    2015-05-01

    Working memory (WM) is essential for individuals' cognitive functions. Neuroimaging studies indicated that WM fundamentally relied on a frontoparietal working memory network (WMN) and a cinguloparietal default mode network (DMN). Behavioral training studies demonstrated that the two networks can be modulated by WM training. Different from the behavioral training, our recent study used a real-time functional MRI (rtfMRI)-based neurofeedback method to conduct WM training, demonstrating that WM performance can be significantly improved after successfully upregulating the activity of the target region of interest (ROI) in the left dorsolateral prefrontal cortex (Zhang et al., [2013]: PloS One 8:e73735); however, the neural substrate of rtfMRI-based WM training remains unclear. In this work, we assessed the intranetwork and internetwork connectivity changes of WMN and DMN during the training, and their correlations with the change of brain activity in the target ROI as well as with the improvement of post-training behavior. Our analysis revealed an "ROI-network-behavior" correlation relationship underlying the rtfMRI training. Further mediation analysis indicated that the reorganization of functional brain networks mediated the effect of self-regulation of the target brain activity on the improvement of cognitive performance following the neurofeedback training. The results of this study enhance our understanding of the neural basis of real-time neurofeedback and suggest a new direction to improve WM performance by regulating the functional connectivity in the WM related networks. © 2014 Wiley Periodicals, Inc.

  2. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

    OpenAIRE

    Ren, Shaoqing; He, Kaiming; Girshick, Ross; Sun, Jian

    2015-01-01

    State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet and Fast R-CNN have reduced the running time of these detection networks, exposing region proposal computation as a bottleneck. In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals. An RPN is a fully convolutional network that simultan...

  3. Design of Networks-on-Chip for Real-Time Multi-Processor Systems-on-Chip

    DEFF Research Database (Denmark)

    Sparsø, Jens

    2012-01-01

    This paper addresses the design of networks-on-chips for use in multi-processor systems-on-chips - the hardware platforms used in embedded systems. These platforms typically have to guarantee real-time properties, and as the network is a shared resource, it has to provide service guarantees...... (bandwidth and/or latency) to different communication flows. The paper reviews some past work in this field and the lessons learned, and the paper discusses ongoing research conducted as part of the project "Time-predictable Multi-Core Architecture for Embedded Systems" (T-CREST), supported by the European...

  4. Characteristics of DNA-AuNP networks on cell membranes and real-time movies for viral infection.

    Science.gov (United States)

    Li, Chunmei; Zheng, Linling; Yang, Xiaoxi; Wan, Xiaoyan; Wu, Wenbi; Zhen, Shujun; Li, Yuanfang; Luo, Lingfei; Huang, Chengzhi

    2016-03-01

    This data article provides complementary data for the article entitled "DNA-AuNP networks on cell membranes as a protective barrier to inhibit viral attachment, entry and budding" Li et al. (2016) [1]. The experimental methods for the preparation and characterization of DNA-conjugated nanoparticle networks on cell membranes were described. Confocal fluorescence images, agarose gel electrophoresis images and hydrodynamic diameter of DNA-conjugated gold nanoparticle (DNA-AuNP) networks were presented. In addition, we have prepared QDs-labeled RSV (QDs-RSV) to real-time monitor the RSV infection on HEp-2 cells in the absence and presence of DNA-AuNP networks. Finally, the cell viability of HEp-2 cells coated by six types of DNA-nanoparticle networks was determined after RSV infection.

  5. A Novel Low-Cost Dual-Wavelength Precipitation Radar Sensor Network, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Remote Sensing Solutions, Inc. (RSS) has developed a novel, practical design that will produce a low-cost precipitation radar / radiometer sensor. Operating in a...

  6. Real-time object tracking system based on field-programmable gate array and convolution neural network

    Directory of Open Access Journals (Sweden)

    Congyi Lyu

    2016-12-01

    Full Text Available Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit- or graphics processing unit-based computers are not good choices due to the high weight and power consumption. To address the problem, this article proposed a real-time object tracking system based on field-programmable gate array, convolution neural network, and visual servo technology. The time-consuming image processing algorithms, such as distortion correction, color space convertor, and Sobel edge, Harris corner features detector, and convolution neural network were redesigned using the programmable gates in field-programmable gate array. Based on the field-programmable gate array-based image processing, an image-based visual servo controller was designed to drive a two degree of freedom manipulator to track the target in real time. Finally, experiments on the proposed system were performed to illustrate the effectiveness of the real-time object tracking system.

  7. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    OpenAIRE

    Xerxes D. Arsiwalla; Riccardo eZucca; Alberto eBetella; Enrique eMartinez; David eDalmazzo; Pedro eOmedas; Gustavo eDeco; Gustavo eDeco; Paul F.M.J. Verschure; Paul F.M.J. Verschure

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

  8. Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

    OpenAIRE

    Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martínez, Enrique, 1961-; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

  9. Low-cost RAU with Optical Power Supply Used in a Hybrid RoF IEEE 802.11 Network

    Science.gov (United States)

    Kowalczyk, M.; Siuzdak, J.

    2014-09-01

    The paper presents design and implementation of a low-cost RAU (Remote Antenna Unit) device. It was designed to work in a hybrid Wi-Fi/optical network based on the IEEE 802.11b/g standard. An unique feature of the device is the possibility of optical power supply.

  10. An optimized compression algorithm for real-time ECG data transmission in wireless network of medical information systems.

    Science.gov (United States)

    Cho, Gyoun-Yon; Lee, Seo-Joon; Lee, Tae-Ro

    2015-01-01

    Recent medical information systems are striving towards real-time monitoring models to care patients anytime and anywhere through ECG signals. However, there are several limitations such as data distortion and limited bandwidth in wireless communications. In order to overcome such limitations, this research focuses on compression. Few researches have been made to develop a specialized compression algorithm for ECG data transmission in real-time monitoring wireless network. Not only that, recent researches' algorithm is not appropriate for ECG signals. Therefore this paper presents a more developed algorithm EDLZW for efficient ECG data transmission. Results actually showed that the EDLZW compression ratio was 8.66, which was a performance that was 4 times better than any other recent compression method widely used today.

  11. Teacher Directed Design: Content Knowledge, Pedagogy and Assessment under the Nevada K-12 Real-Time Seismic Network

    Science.gov (United States)

    Cantrell, P.; Ewing-Taylor, J.; Crippen, K. J.; Smith, K. D.; Snelson, C. M.

    2004-12-01

    Education professionals and seismologists under the emerging SUN (Shaking Up Nevada) program are leveraging the existing infrastructure of the real-time Nevada K-12 Seismic Network to provide a unique inquiry based science experience for teachers. The concept and effort are driven by teacher needs and emphasize rigorous content knowledge acquisition coupled with the translation of that knowledge into an integrated seismology based earth sciences curriculum development process. We are developing a pedagogical framework, graduate level coursework, and materials to initiate the SUN model for teacher professional development in an effort to integrate the research benefits of real-time seismic data with science education needs in Nevada. A component of SUN is to evaluate teacher acquisition of qualified seismological and earth science information and pedagogy both in workshops and in the classroom and to assess the impact on student achievement. SUN's mission is to positively impact earth science education practices. With the upcoming EarthScope initiative, the program is timely and will incorporate EarthScope real-time seismic data (USArray) and educational materials in graduate course materials and teacher development programs. A number of schools in Nevada are contributing real-time data from both inexpensive and high-quality seismographs that are integrated with Nevada regional seismic network operations as well as the IRIS DMC. A powerful and unique component of the Nevada technology model is that schools can receive "stable" continuous live data feeds from 100's seismograph stations in Nevada, California and world (including live data from Earthworm systems and the IRIS DMC BUD - Buffer of Uniform Data). Students and teachers see their own networked seismograph station within a global context, as participants in regional and global monitoring. The robust real-time Internet communications protocols invoked in the Nevada network provide for local data acquisition

  12. Real-time method for establishing a detection map for a network of sensors

    Science.gov (United States)

    Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

    2012-09-11

    A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

  13. Real-time resource availability signalling in IMS-based networks

    NARCIS (Netherlands)

    Ozcelebi, T.; Radovanovic, I.; Lukkien, J.J.

    2007-01-01

    The emerging converged IP multimedia subsystem (IMS) allows the use of unlicensed, nondedicated and nondeterministic computer access networks for delivering IP multimedia services. To provide end-to-end quality-of-service (QoS) over such networks combined with the IMS core network, for resource

  14. Low-cost coherent receiver for long-reach optical access network using single-ended detection.

    Science.gov (United States)

    Zhang, Xuebing; Li, Zhaohui; Li, Jianping; Yu, Changyuan; Lau, Alan Pak Tao; Lu, Chao

    2014-09-15

    A low-cost coherent receiver using two 2×3 optical hybrids and single-ended detection is proposed for long-reach optical access network. This structure can detect the two polarization components of polarization division multiplexing (PDM) signals. Polarization de-multiplexing and signal-to-signal beat interference (SSBI) cancellation are realized by using only three photodiodes. Simulation results for 40 Gb/s PDM-OFDM transmissions indicate that the low-cost coherent receiver has 3.2 dB optical signal-to-noise ratio difference compared with the theoretical value.

  15. Development of a Real-Time Radiological Area Monitoring Network for Emergency Response at Lawrence Livermore National Laboratory

    International Nuclear Information System (INIS)

    Bertoldo, N; Hunter, S; Fertig, R; Laguna, G; MacQueen, D

    2004-01-01

    A real-time radiological sensor network for emergency response was developed and deployed at the Lawrence Livermore National Laboratory (LLNL). The Real-Time Radiological Area Monitoring (RTRAM) network is comprised of 16 Geiger-Mueller (GM) sensors positioned on the LLNL Livermore site perimeter to continuously monitor for a radiological condition resulting from a terrorist threat to site security and the health and safety of LLNL personnel. The RTRAM network sensor locations coincide with wind sector directions to provide thorough coverage of the one square mile site. These loW--power sensors are supported by a central command center (CCC) and transmit measurement data back to the CCC computer through the LLNL telecommunications infrastructure. Alarm conditions are identified by comparing current data to predetermined threshold parameters and are validated by comparison with plausible dispersion modeling scenarios and prevailing meteorological conditions. Emergency response personnel are notified of alarm conditions by automatic radio and computer based notifications. A secure intranet provides emergency response personnel with current condition assessment data that enable them to direct field response efforts remotely. The RTRAM network has proven to be a reliable system since initial deployment in August 2001 and maintains stability during inclement weather conditions

  16. Interaction of multiple networks modulated by the working memory training based on real-time fMRI

    Science.gov (United States)

    Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

    2015-03-01

    Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

  17. Collaborative Science: Human Sensor Networks for Real-time Natural Disaster Prediction

    Science.gov (United States)

    Halem, M.; Yesha, Y.; Aulov, O.; Martineau, J.; Brown, S.; Conte, T.; CenterHybrid Multicore Productivity Research

    2010-12-01

    We have implemented a ‘Human Sensor Network’ as a real time collaborative science data observing system by collecting and integrating the vast untapped information potential of digital social media data sources occurring during the oil spill situation arising from the Macondo well in the Gulf of Mexico. We collected, and archived blogs, Twitter status updates (aka tweets), photographs posted to Flicker, and videos posted to YouTube related to the Gulf oil spill and processed the meta data, text, and photos to extract quantitative physical data such as locations and estimates of the severity and dispersion of oil being collected on the beaches and marshes, frequencies of observations of tar ball sightings, correlations of sightings from different media, numbers of dead or distressed animals, trends, etc. These data were then introduced into the NOAA operational Gnome oil spill predictive model as time dependent boundary conditions employing a 2-D variational data assimilation scheme. The three participating institutions employed a distributed cloud computing system for the processing and model executions. In this presentation, we conducted preliminary forecast impact tests of the Gnome model with and without the use of social media data using a 2-D variational data assimilation technique. The 2-D VAR is used to adjust the state variables of the model by recursively minimizing the differences between oil spill predictions reaching locations across the entire coastlines of the Gulf of Mexico and the estimated positions of oil derived from analyzed social media data. Ensemble forecasts will be performed to provide estimates of the rates of oil and surface oil distributions emanating from the Deepwater Horizon. We display the derived predictions from the photos and animations from Flicker, YouTube, and extracted content from tweets and blogs in a dynamic representation on very large tiled walls of LCDs at the UCSD Cal IT2 visualization facility. We describe the

  18. Experimental validation of concept for real-time wavelength monitoring and tracking in densely populated WDM networks

    Science.gov (United States)

    Vukovic, Alex; Savoie, Michel; Hua, Heng; Campbell, Scott; Nguyen, Thao

    2005-10-01

    As the telecom industry responds with technological innovations to requests for higher data rates, increased number of wavelengths at higher densities, longer transmission distances and more intelligence for next generation optical networks, new monitoring schemes based on monitoring and tracking of each wavelength need to be developed and deployed. An optical layer monitoring scheme, based on tracking key optical parameters per each wavelength, is considered to be one of enablers for the transformation of today's opaque networks to dynamic, agile future networks. Ever-tighter network monitoring and control will be required to fulfill customer Service Level Agreements (SLAs). A wavelength monitoring and tracking concept was developed as a three-step approach. It started with the identification of all critical parameters required to obtain sufficient information about each wavelength; followed by the deployment of a cost-efficient device to provide simultaneous, accurate measurements in real-time of all critical parameters; and finally, the formulation of a specification for wavelength monitoring and tracking devices for real-time, simultaneous measurements and processing the data. A prototype solution based on a commercially available integrated modular spectrometer within a testbed environment associated with the all-optical network (AON) demonstrator program was used to verify and validate the wavelength monitoring and tracking concept. The developed concept verified that it can manage tracking of 32 wavelengths within a wavelength division multiplexing network. The developed concept presented in this paper can be used inside the transparent domains of networks to detect, identify and locate signal degradations in real-time, even sometimes to recognize the cause of the failure. Aside from the reduction of operational expenses due to the elimination of the need for operators at every site and skilled field technicians to isolate and repair faults, the developed

  19. Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai

    Directory of Open Access Journals (Sweden)

    Young-Ji Byon

    2017-09-01

    Full Text Available Traditionally, departments of transportation (DOTs have dispatched probe vehicles with dedicated vehicles and drivers for monitoring traffic conditions. Emerging assisted GPS (AGPS and accelerometer-equipped smartphones offer new sources of raw data that arise from voluntarily-traveling smartphone users provided that their modes of transportation can correctly be identified. By introducing additional raster map layers that indicate the availability of each mode, it is possible to enhance the accuracy of mode detection results. Even in its simplest form, an artificial neural network (ANN excels at pattern recognition with a relatively short processing timeframe once it is properly trained, which is suitable for real-time mode identification purposes. Dubai is one of the major cities in the Middle East and offers unique environments, such as a high density of extremely high-rise buildings that may introduce multi-path errors with GPS signals. This paper develops real-time mode identification ANNs enhanced with proposed mode availability geographic information system (GIS layers, firstly for a universal mode detection and, secondly for an auto mode detection for the particular intelligent transportation system (ITS application of traffic monitoring, and compares the results with existing approaches. It is found that ANN-based real-time mode identification, enhanced by mode availability GIS layers, significantly outperforms the existing methods.

  20. Development of real-time monitoring system using wired and wireless networks in a full-scale ship

    Directory of Open Access Journals (Sweden)

    Bu-Geun Paik

    2010-09-01

    Full Text Available In the present study, the real-time monitoring system is developed based on the wireless sensor network (WSN and power line communication (PLC employed in the 3,000-ton-class training ship. The WSN consists of sensor nodes, router, gateway and middleware. The PLC is composed of power lines, modems, Ethernet gateway and phase-coupler. The basic tests show that the ship has rather good environments for the wired and wireless communications. The developed real-time monitoring system is applied to recognize the thermal environments of main-engine room and one cabin in the ship. The main-engine room has lots of heat sources and needs careful monitoring to satisfy safe operation condition or detect any human errors beforehand. The monitoring is performed in two regions near the turbocharger and cascade tank, considered as heat sources. The cabin on the second deck is selected to monitor the thermal environments because it is close to the heat source of main engine. The monitoring results of the cabin show the thermal environment is varied by the human activity. The real-time monitoring for the thermal environment would be useful for the planning of the ventilation strategy based on the traces of the human activity against inconvenient thermal environments as well as the recognizing the temperature itself in each cabin.

  1. A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion.

    Science.gov (United States)

    Liu, Qingshan; Dang, Chuangyin; Huang, Tingwen

    2013-02-01

    This paper presents a decision-making model described by a recurrent neural network for dynamic portfolio optimization. The portfolio-optimization problem is first converted into a constrained fractional programming problem. Since the objective function in the programming problem is not convex, the traditional optimization techniques are no longer applicable for solving this problem. Fortunately, the objective function in the fractional programming is pseudoconvex on the feasible region. It leads to a one-layer recurrent neural network modeled by means of a discontinuous dynamic system. To ensure the optimal solutions for portfolio optimization, the convergence of the proposed neural network is analyzed and proved. In fact, the neural network guarantees to get the optimal solutions for portfolio-investment advice if some mild conditions are satisfied. A numerical example with simulation results substantiates the effectiveness and illustrates the characteristics of the proposed neural network.

  2. Real time track finding in a drift chamber with a VLSI neural network

    International Nuclear Information System (INIS)

    Lindsey, C.S.; Denby, B.; Haggerty, H.; Johns, K.

    1992-01-01

    In a test setup, a hardware neural network determined track parameters of charged particles traversing a drift chamber. Voltages proportional to the drift times in 6 cells of the 3-layer chamber were inputs to the Intel ETANN neural network chip which had been trained to give the slope and intercept of tracks. We compare network track parameters to those obtained from off-line track fits. To our knowledge this is the first on-line application of a VLSI neural network to a high energy physics detector. This test explored the potential of the chip and the practical problems of using it in a real world setting. We compare the chip performance to a neural network simulation on a conventional computer. We discuss possible applications of the chip in high energy physics detector triggers. (orig.)

  3. Development of Real-time Tsunami Inundation Forecast Using Ocean Bottom Tsunami Networks along the Japan Trench

    Science.gov (United States)

    Aoi, S.; Yamamoto, N.; Suzuki, W.; Hirata, K.; Nakamura, H.; Kunugi, T.; Kubo, T.; Maeda, T.

    2015-12-01

    In the 2011 Tohoku earthquake, in which huge tsunami claimed a great deal of lives, the initial tsunami forecast based on hypocenter information estimated using seismic data on land were greatly underestimated. From this lesson, NIED is now constructing S-net (Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench) which consists of 150 ocean bottom observatories with seismometers and pressure gauges (tsunamimeters) linked by fiber optic cables. To take full advantage of S-net, we develop a new methodology of real-time tsunami inundation forecast using ocean bottom observation data and construct a prototype system that implements the developed forecasting method for the Pacific coast of Chiba prefecture (Sotobo area). We employ a database-based approach because inundation is a strongly non-linear phenomenon and its calculation costs are rather heavy. We prepare tsunami scenario bank in advance, by constructing the possible tsunami sources, and calculating the tsunami waveforms at S-net stations, coastal tsunami heights and tsunami inundation on land. To calculate the inundation for target Sotobo area, we construct the 10-m-mesh precise elevation model with coastal structures. Based on the sensitivities analyses, we construct the tsunami scenario bank that efficiently covers possible tsunami scenarios affecting the Sotobo area. A real-time forecast is carried out by selecting several possible scenarios which can well explain real-time tsunami data observed at S-net from tsunami scenario bank. An advantage of our method is that tsunami inundations are estimated directly from the actual tsunami data without any source information, which may have large estimation errors. In addition to the forecast system, we develop Web services, APIs, and smartphone applications and brush them up through social experiments to provide the real-time tsunami observation and forecast information in easy way to understand toward urging people to evacuate.

  4. High speed network for real-time data acquisition and control with lossless and balanced self-routing

    International Nuclear Information System (INIS)

    Ofek, Y.; Hicks, S.E.

    1990-01-01

    The authors present a gigabit network architecture for interconnecting the on-line and off-line data acquisition and processing farms for future detector facilities at the SSC (Superconducting Super Collider). In the solution they concentrate on how to interconnect the front-end (ADCs and leve 1 and 2 triggers) with the on-line (real-time) computer farm. They propose that the on-line solution be extended into the off-line data processing and mass-storage. As a result, this solution provides a single uniform structure which will simplify the overall system

  5. Real-time Railway Traffic Management : Dispatching in complex, large and busy railway networks

    NARCIS (Netherlands)

    Corman, F.

    2010-01-01

    Railway is an important and sustainable transportation mode, which despite good potentials results in a limited attractiveness, mostly due to the perceived consequences of unreliability. In fact, busy railway networks with frequent and heterogeneous services are highly sensitive to delay

  6. Real-time-service-based Distributed Scheduling Scheme for IEEE 802.16j Networks

    OpenAIRE

    Kuo-Feng Huang; Shih-Jung Wu

    2013-01-01

    Supporting Quality of Service (QoS) guarantees for diverse multimedia services is the primary concern for IEEE802.16j networks. A scheduling scheme that satisfies the QoS requirements has become more important for wireless communications. We proposed an adaptive nontransparent-based distributed scheduling scheme (ANDS) for IEEE 802.16j networks. ANDS comprises three major components: Priority Assignment, Resource Allocation, Preserved Bandwidth Adjustment. Different service-type connections p...

  7. Extending the coverage of the internet of things with low-cost nanosatellite networks

    Science.gov (United States)

    Almonacid, Vicente; Franck, Laurent

    2017-09-01

    Recent technology advances have made CubeSats not only an affordable means of access to space, but also promising platforms to develop a new variety of space applications. In this paper, we explore the idea of using nanosatellites as access points to provide extended coverage to the Internet of Things (IoT) and Machine-to-Machine (M2M) communications. This study is mainly motivated by two facts: on the one hand, it is already obvious that the number of machine-type devices deployed globally will experiment an exponential growth over the forthcoming years. This trend is pushed by the available terrestrial cellular infrastructure, which allows adding support for M2M connectivity at marginal costs. On the other hand, the same growth is not observed in remote areas that must rely on space-based connectivity. In such environments, the demand for M2M communications is potentially large, yet it is challenged by the lack of cost-effective service providers. The traffic characteristics of typical M2M applications translate into the requirement for an extremely low cost per transmitted message. Under these strong economical constraints, we expect that nanosatellites in the low Earth orbit will play a fundamental role in overcoming what we may call the IoT digital divide. The objective of this paper is therefore to provide a general analysis of a nanosatellite-based, global IoT/M2M network. We put emphasis in the engineering challenges faced in designing the Earth-to-Space communication link, where the adoption of an efficient multiple-access scheme is paramount for ensuring connectivity to a large number of terminal nodes. In particular, the trade-offs energy efficiency-access delay and energy efficiency-throughput are discussed, and a novel access approach suitable for delay-tolerant applications is proposed. Thus, by keeping a system-level standpoint, we identify key issues and discuss perspectives towards energy efficient and cost-effective solutions.

  8. Compact holographic optical neural network system for real-time pattern recognition

    Science.gov (United States)

    Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

    1996-08-01

    One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

  9. A One-Pass Real-Time Decoder Using Memory-Efficient State Network

    Science.gov (United States)

    Shao, Jian; Li, Ta; Zhang, Qingqing; Zhao, Qingwei; Yan, Yonghong

    This paper presents our developed decoder which adopts the idea of statically optimizing part of the knowledge sources while handling the others dynamically. The lexicon, phonetic contexts and acoustic model are statically integrated to form a memory-efficient state network, while the language model (LM) is dynamically incorporated on the fly by means of extended tokens. The novelties of our approach for constructing the state network are (1) introducing two layers of dummy nodes to cluster the cross-word (CW) context dependent fan-in and fan-out triphones, (2) introducing a so-called “WI layer” to store the word identities and putting the nodes of this layer in the non-shared mid-part of the network, (3) optimizing the network at state level by a sufficient forward and backward node-merge process. The state network is organized as a multi-layer structure for distinct token propagation at each layer. By exploiting the characteristics of the state network, several techniques including LM look-ahead, LM cache and beam pruning are specially designed for search efficiency. Especially in beam pruning, a layer-dependent pruning method is proposed to further reduce the search space. The layer-dependent pruning takes account of the neck-like characteristics of WI layer and the reduced variety of word endings, which enables tighter beam without introducing much search errors. In addition, other techniques including LM compression, lattice-based bookkeeping and lattice garbage collection are also employed to reduce the memory requirements. Experiments are carried out on a Mandarin spontaneous speech recognition task where the decoder involves a trigram LM and CW triphone models. A comparison with HDecode of HTK toolkits shows that, within 1% performance deviation, our decoder can run 5 times faster with half of the memory footprint.

  10. Multiscale Methods, Parallel Computation, and Neural Networks for Real-Time Computer Vision.

    Science.gov (United States)

    Battiti, Roberto

    1990-01-01

    This thesis presents new algorithms for low and intermediate level computer vision. The guiding ideas in the presented approach are those of hierarchical and adaptive processing, concurrent computation, and supervised learning. Processing of the visual data at different resolutions is used not only to reduce the amount of computation necessary to reach the fixed point, but also to produce a more accurate estimation of the desired parameters. The presented adaptive multiple scale technique is applied to the problem of motion field estimation. Different parts of the image are analyzed at a resolution that is chosen in order to minimize the error in the coefficients of the differential equations to be solved. Tests with video-acquired images show that velocity estimation is more accurate over a wide range of motion with respect to the homogeneous scheme. In some cases introduction of explicit discontinuities coupled to the continuous variables can be used to avoid propagation of visual information from areas corresponding to objects with different physical and/or kinematic properties. The human visual system uses concurrent computation in order to process the vast amount of visual data in "real -time." Although with different technological constraints, parallel computation can be used efficiently for computer vision. All the presented algorithms have been implemented on medium grain distributed memory multicomputers with a speed-up approximately proportional to the number of processors used. A simple two-dimensional domain decomposition assigns regions of the multiresolution pyramid to the different processors. The inter-processor communication needed during the solution process is proportional to the linear dimension of the assigned domain, so that efficiency is close to 100% if a large region is assigned to each processor. Finally, learning algorithms are shown to be a viable technique to engineer computer vision systems for different applications starting from

  11. Near Real Time Analytics of Human Sensor Networks in the Realm of Big Data

    Science.gov (United States)

    Aulov, O.; Halem, M.

    2012-12-01

    With the prolific development of social media, emergency responders have an increasing interest in harvesting social media from outlets such as Flickr, Twitter, and Facebook, in order to assess the scale and specifics of extreme events including wild fires, earthquakes, terrorist attacks, oil spills, etc. A number of experimental platforms have successfully been implemented to demonstrate the utilization of social media data in extreme events, including Twitter Earthquake Detector, which relied on tweets for earthquake monitoring; AirTwitter, which used tweets for air quality reporting; and our previous work, using Flickr data as boundary value forcings to improve the forecast of oil beaching in the aftermath of the Deepwater Horizon oil spill. The majority of these platforms addressed a narrow, specific type of emergency and harvested data from a particular outlet. We demonstrate an interactive framework for monitoring, mining and analyzing a plethora of heterogeneous social media sources for a diverse range of extreme events. Our framework consists of three major parts: a real time social media aggregator, a data processing and analysis engine, and a web-based visualization and reporting tool. The aggregator gathers tweets, Facebook comments from fan pages, Google+ posts, forum discussions, blog posts (such as LiveJournal and Blogger.com), images from photo-sharing platforms (such as Flickr, Picasa), videos from video-sharing platforms (youtube, Vimeo), and so forth. The data processing and analysis engine pre-processes the aggregated information and annotates it with geolocation and sentiment information. In many cases, the metadata of the social media posts does not contain geolocation information—-however, a human reader can easily guess from the body of the text what location is discussed. We are automating this task by use of Named Entity Recognition (NER) algorithms and a gazetteer service. The visualization and reporting tool provides a web-based, user

  12. Development of A Low-Cost FPGA-Based Measurement System for Real-Time Processing of Acoustic Emission Data: Proof of Concept Using Control of Pulsed Laser Ablation in Liquids.

    Science.gov (United States)

    Wirtz, Sebastian F; Cunha, Adauto P A; Labusch, Marc; Marzun, Galina; Barcikowski, Stephan; Söffker, Dirk

    2018-06-01

    Today, the demand for continuous monitoring of valuable or safety critical equipment is increasing in many industrial applications due to safety and economical requirements. Therefore, reliable in-situ measurement techniques are required for instance in Structural Health Monitoring (SHM) as well as process monitoring and control. Here, current challenges are related to the processing of sensor data with a high data rate and low latency. In particular, measurement and analyses of Acoustic Emission (AE) are widely used for passive, in-situ inspection. Advantages of AE are related to its sensitivity to different micro-mechanical mechanisms on the material level. However, online processing of AE waveforms is computationally demanding. The related equipment is typically bulky, expensive, and not well suited for permanent installation. The contribution of this paper is the development of a Field Programmable Gate Array (FPGA)-based measurement system using ZedBoard devlopment kit with Zynq-7000 system on chip for embedded implementation of suitable online processing algorithms. This platform comprises a dual-core Advanced Reduced Instruction Set Computer Machine (ARM) architecture running a Linux operating system and FPGA fabric. A FPGA-based hardware implementation of the discrete wavelet transform is realized to accelerate processing the AE measurements. Key features of the system are low cost, small form factor, and low energy consumption, which makes it suitable to serve as field-deployed measurement and control device. For verification of the functionality, a novel automatically realized adjustment of the working distance during pulsed laser ablation in liquids is established as an example. A sample rate of 5 MHz is achieved at 16 bit resolution.

  13. Improved Image Encryption for Real-Time Application over Wireless Communication Networks using Hybrid Cryptography Technique

    Directory of Open Access Journals (Sweden)

    Kazeem B. Adedeji

    2016-12-01

    Full Text Available Advances in communication networks have enabled organization to send confidential data such as digital images over wireless networks. However, the broadcast nature of wireless communication channel has made it vulnerable to attack from eavesdroppers. We have developed a hybrid cryptography technique, and we present its application to digital images as a means of improving the security of digital image for transmission over wireless communication networks. The hybrid technique uses a combination of a symmetric (Data Encryption Standard and asymmetric (Rivest Shamir Adleman cryptographic algorithms to secure data to be transmitted between different nodes of a wireless network. Three different image samples of type jpeg, png and jpg were tested using this technique. The results obtained showed that the hybrid system encrypt the images with minimal simulation time, and high throughput. More importantly, there is no relation or information between the original images and their encrypted form, according to Shannon’s definition of perfect security, thereby making the system much more secure.

  14. Real Time Synchronization of Live Broadcast Streams with User Generated Content and Social Network Streams

    NARCIS (Netherlands)

    Stokking, H.M.; Kaptein, A.M.; Veenhuizen, A.T.; Spitters4, M.M.; Niamut, O.A.

    2013-01-01

    This paper describes the work in the FP7 STEER project on augmenting a live broadcast with live user generated content. This user generated content consists of both video content, captured with mobile devices, and social network content, such as Facebook or Twitter messages. To enable multi-source

  15. Hardware realization of a fast neural network algorithm for real-time tracking in HEP experiments

    International Nuclear Information System (INIS)

    Leimgruber, F.R.; Pavlopoulos, P.; Steinacher, M.; Tauscher, L.; Vlachos, S.; Wendler, H.

    1995-01-01

    A fast pattern recognition system for HEP experiments, based on artificial neural network algorithms (ANN), has been realized with standard electronics. The multiplicity and location of tracks in an event are determined in less than 75 ns. Hardware modules of this first level trigger were extensively tested for performance and reliability with data from the CPLEAR experiment. (orig.)

  16. Ethernet Networks for Real-Time Use in the ATLAS Experiment

    CERN Document Server

    Meirosu, C; Martin, B

    2005-01-01

    Ethernet became today's de-facto standard technology for local area networks. Defined by the IEEE 802.3 and 802.1 working groups, the Ethernet standards cover technologies deployed at the first two layers of the OSI protocol stack. The architecture of modern Ethernet networks is based on switches. The switches are devices usually built using a store-and-forward concept. At the highest level, they can be seen as a collection of queues and mathematically modelled by means of queuing theory. However, the traffic profiles on modern Ethernet networks are rather different from those assumed in classical queuing theory. The standard recommendations for evaluating the performance of network devices define the values that should be measured but do not specify a way of reconciling these values with the internal architecture of the switches. The introduction of the 10 Gigabit Ethernet standard provided a direct gateway from the LAN to the WAN by the means of the WAN PHY. Certain aspects related to the actual use of WAN ...

  17. Secure Real-Time Monitoring and Management of Smart Distribution Grid using Shared Cellular Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen; Ganem, Hervé; Jorguseski, Ljupco

    2017-01-01

    capabilities. Thanks to the advanced measurement devices, management framework, and secure communication infrastructure developed in the FP7 SUNSEED project, the Distribution System Operator (DSO) now has full observability of the energy flows at the medium/low voltage grid. Furthermore, the prosumers are able......, where the smart grid ICT solutions are provided through shared cellular LTE networks....

  18. Real-Time Analysis of an Active Distribution Network - Coordinated Frequency Control for Islanding Operation

    DEFF Research Database (Denmark)

    Cha, Seung-Tae

    distribution networks makes it possible to operate the distribution networks independently which is called islanding operation. However, it is a challenge to ensure secure and reliable operation of the islanded system due to a num-ber of reasons, e.g. low inertia in the islanded system, intermittency of some...... of the DERs, etc. Particularly during islanding operation, with relatively few DG units, the frequency and voltage control of the islanded system is not straightforward. DG units, specially based on renewable energy sources (RESs), i.e. wind and solar, have an inter-mittent nature and intrinsic...... system (BESS) and two secondary frequency control scenarios with BESS and DG units. During the island-ing transition, the frequency is regulated by the fast-acting primary control of the BESS. The secondary control of the main management system (MMS) detects the status of the BESS and tries to return...

  19. Distributed radar network for real-time tracking of bullet trajectory

    Science.gov (United States)

    Zhang, Yimin; Li, Xin; Jin, Yuanwei; Amin, Moeness G.; Eydgahi, Ali

    2009-05-01

    Gunshot detection, sniper localization, and bullet trajectory prediction are of significant importance in military and homeland security applications. While the majority of existing work is based on acoustic and electro-optical sensors, this paper develops a framework of networked radar systems that uses distributed radar sensor networks to achieve the aforementioned objectives. The use of radio frequency radar systems allows the achievement of subtime- of-flight tracking response, enabling to response before the bullet reaches its target and, as such, effectively leading to the reduction of injuries and casualties in military and homeland security operations. The focus of this paper is to examine the MIMO radar concept with concurrent transmission of low-correlation waveforms from multiple radar sets to ensure wide surveillance coverage and maintain a high waveform repetition frequency for long coherent time interval required to achieve return signal concentration.

  20. Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control

    Directory of Open Access Journals (Sweden)

    RATOI, M.

    2010-05-01

    Full Text Available In this paper an experimental model with a distributed control system of a hybrid electrical vehicle is presented. A communication CAN network of high speed (1 Mbps assures a distributed control of the all components. The modeling and the control of different operating regimes are realized on an experimental test-bench of a hybrid electrical vehicle. The experimental results concerning the variations of the mains variables (currents, torques, speeds are presented.

  1. Instantly decodable network coding for real-time device-to-device communications

    KAUST Repository

    Douik, Ahmed

    2016-01-04

    This paper studies the delay reduction problem for instantly decodable network coding (IDNC)-based device-to-device (D2D) communication-enabled networks. Unlike conventional point-to-multipoint (PMP) systems in which the wireless base station has the sufficient computation abilities, D2D networks rely on battery-powered operations of the devices. Therefore, a particular emphasis on the computation complexity needs to be addressed in the design of delay reduction algorithms for D2D networks. While most of the existing literature on IDNC directly extend the delay reduction PMP schemes, known to be NP-hard, to the D2D setting, this paper proposes to investigate and minimize the complexity of such algorithms for battery-powered devices. With delay minimization problems in IDNC-based systems being equivalent to a maximum weight clique problems in the IDNC graph, the presented algorithms, in this paper, can be applied to different delay aspects. This paper introduces and focuses on the reduction of the maximum value of the decoding delay as it represents the most general solution. The complexity of the solution is reduced by first proposing efficient methods for the construction, the update, and the dimension reduction of the IDNC graph. The paper, further, shows that, under particular scenarios, the problem boils down to a maximum clique problem. Due to the complexity of discovering such maximum clique, the paper presents a fast selection algorithm. Simulation results illustrate the performance of the proposed schemes and suggest that the proposed fast selection algorithm provides appreciable complexity gain as compared to the optimal selection one, with a negligible degradation in performance. In addition, they indicate that the running time of the proposed solution is close to the random selection algorithm.

  2. Modeling real time CBTC operation in mixed traffic networks: A simulation-based approach

    OpenAIRE

    De Martinis, Valerio; Toletti, Ambra; Weidmann, Ulrich; Nash, Andrew

    2017-01-01

    Vehicle automation and continuous connection with communication networks are the key innovations currently redefining transport systems. Just as autonomous cars are rapidly changing road transport, increasing railway automation will help to maximize the use of infrastructure, increase schedule reliability, improve safety, and increase energy efficiency. However, railway operations are fundamentally different from road-based transport systems and automation must be specifically tailored to rai...

  3. Calibration of low-cost gas sensors for an urban air quality monitoring network

    Science.gov (United States)

    Scott, A.; Kelley, C.; He, C.; Ghugare, P.; Lehman, A.; Benish, S.; Stratton, P.; Dickerson, R. R.; Zuidema, C.; Azdoud, Y.; Ren, X.

    2017-12-01

    In a warming world, environmental pollution may be exacerbated by anthropogenic activities, such as climate change and the urban heat island effect, as well as natural phenomena such as heat waves. However, monitoring air pollution at federal reference standards (approximately 1 part per billion or ppb for ambient ozone) is cost-prohibitive in heterogeneous urban areas as many expensive devices are required to fully capture a region's geo-spatial variability. Innovation in low-cost sensors provide a potential solution, yet technical challenges remain to overcome possible imprecision in the data. We present the calibrations of ozone and nitrous dioxide from a low-cost air quality monitoring device designed for the Baltimore Open Air Project. The sensors used in this study are commercially available thin film electrochemical sensors from SPEC Sensor, which are amperometric, meaning they generate current proportional to volumetric fraction of gas. The results of sensor calibrations in the laboratory and field are presented.

  4. Real-time dynamic hydraulic model for water distribution networks: steady state modelling

    CSIR Research Space (South Africa)

    Osman, Mohammad S

    2016-09-01

    Full Text Available equipment (pipes, reservoirs, pumps, valves, etc.) was used as a pilot WDN. Further information of the various other DHM components has been published [1]. The steady-state hydraulic model calculates the network hydraulic variables at a particular... from the abstraction point to the two low-level concrete reservoirs. On this pipeline there is a 2” tie-off to an alternate consumer as well as another 2” tie-off (5 m length) to the pump station sump. Water from the pump station is pumped to two...

  5. Need of a disaster alert system for India through a network of real-time monitoring of sea-level and other meteorological events

    Digital Repository Service at National Institute of Oceanography (India)

    Joseph, A.; Desai, R.G.P.

    Need of a disaster alert system (DAS) capable of online transmission of real-time integrated sea-level and surface meteorological data is discussed. In addition to INSAT platform transmit terminal, VHF, etc., the ubiquitous cellular phone network...

  6. Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays

    National Research Council Canada - National Science Library

    Yang, Kyoung

    2005-01-01

    This final report summarizes the progress during the Phase I SBIR project entitled "Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays...

  7. Real-time prediction of acute cardiovascular events using hardware-implemented Bayesian networks.

    Science.gov (United States)

    Tylman, Wojciech; Waszyrowski, Tomasz; Napieralski, Andrzej; Kamiński, Marek; Trafidło, Tamara; Kulesza, Zbigniew; Kotas, Rafał; Marciniak, Paweł; Tomala, Radosław; Wenerski, Maciej

    2016-02-01

    This paper presents a decision support system that aims to estimate a patient׳s general condition and detect situations which pose an immediate danger to the patient׳s health or life. The use of this system might be especially important in places such as accident and emergency departments or admission wards, where a small medical team has to take care of many patients in various general conditions. Particular stress is laid on cardiovascular and pulmonary conditions, including those leading to sudden cardiac arrest. The proposed system is a stand-alone microprocessor-based device that works in conjunction with a standard vital signs monitor, which provides input signals such as temperature, blood pressure, pulseoxymetry, ECG, and ICG. The signals are preprocessed and analysed by a set of artificial intelligence algorithms, the core of which is based on Bayesian networks. The paper focuses on the construction and evaluation of the Bayesian network, both its structure and numerical specification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting.

    Science.gov (United States)

    Werner, Thilo; Vianello, Elisa; Bichler, Olivier; Garbin, Daniele; Cattaert, Daniel; Yvert, Blaise; De Salvo, Barbara; Perniola, Luca

    2016-01-01

    In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM) as easy to program and low energy (Spike Timing Dependent Plasticity. Real spiking data have been recorded both intra- and extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

  9. Real-time clock and orbit calculation of the GPS satellite constellation based on observation data of RTIGS-station network

    International Nuclear Information System (INIS)

    Thaler, G.

    2011-01-01

    Due to the development of faster communication networks and improving computer technology beside postprocessing techniques real-time applications and services are more and more created and used in the eld of precise positioning and navigation using global navigation satellite systems (GNSS) like GPS. Data formats like RTCM (NTRIP) or RTIGS serve in this manner as basic tool to transmit real-time GNSS observation data to a eld of users. To handle this trend to real-time, the International GNSS Service (IGS) or more precisely the Real-Time Working Group (RTWG) of the IGS started to establish a global GNSS station network several years ago. These reference stations (RTIGS stations) transmit their observation data in real-time via the open internet to registerd users to support the development of potential new real-time products and services. One example for such a new real-time application based on the observations of the RTIGS network is the software RTIGU-Control developed within this PHD thesis. RTIGU-Control fulls 2 main tasks. The rst task is the monitoring (integrity) of the predicted IGS orbit and clock products (IGU products) using real-time observations from the station network. The second task deals with calculating more precise satellite and station clock corrections compared to the predicted values of the IGU solutions based on the already very precise IGU orbit solutions. In a rst step RTIGU-Control calculates based on the IGU orbit predictions together with code-smoothed station observations precise values for the satellite and station clock corrections.The code-smoothed observations are additionally corrected for several corrections eecting the GNSS observations (for example the delay of the signal propagation time due to the atmosphere, relativistic eects, etc.). The second calculation step deals with monitoring the IGU predicted orbits using the calculated clock solution in the calculation step before and again the corrected real-time observations

  10. Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks.

    Science.gov (United States)

    Zhang, Qiushi; Zhang, Gaoyan; Yao, Li; Zhao, Xiaojie

    2015-01-01

    Working memory (WM) refers to the temporary holding and manipulation of information during the performance of a range of cognitive tasks, and WM training is a promising method for improving an individual's cognitive functions. Our previous work demonstrated that WM performance can be improved through self-regulation of dorsal lateral prefrontal cortex (PFC) activation using real-time functional magnetic resonance imaging (rtfMRI), which enables individuals to control local brain activities volitionally according to the neurofeedback. Furthermore, research concerning large-scale brain networks has demonstrated that WM training requires the engagement of several networks, including the central executive network (CEN), the default mode network (DMN) and the salience network (SN), and functional connectivity within the CEN and DMN can be changed by WM training. Although a switching role of the SN between the CEN and DMN has been demonstrated, it remains unclear whether WM training can affect the interactions between the three networks and whether a similar mechanism also exists during the training process. In this study, we investigated the dynamic functional connectivity between the three networks during the rtfMRI feedback training using independent component analysis (ICA) and correlation analysis. The results indicated that functional connectivity within and between the three networks were significantly enhanced by feedback training, and most of the changes were associated with the insula and correlated with behavioral improvements. These findings suggest that the insula plays a critical role in the reorganization of functional connectivity among the three networks induced by rtfMRI training and in WM performance, thus providing new insights into the mechanisms of high-level functions and the clinical treatment of related functional impairments.

  11. Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network.

    Science.gov (United States)

    Cordes, Kristina M; Cookson, Susan T; Boyd, Andrew T; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad; Husain, Farah

    2017-11-01

    Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security.

  12. Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS Networks with Ensuring the Fairness for Other Traffics.

    Directory of Open Access Journals (Sweden)

    Mohammed A Al-Shargabi

    Full Text Available Optical burst switching (OBS networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS' QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50-60%, 30-40%, and 10-20% for high, normal, and low traffic loads respectively.

  13. Secure real-time wireless video streaming in the aeronautical telecommunications network

    Science.gov (United States)

    Czernik, Pawel; Olszyna, Jakub

    2010-09-01

    As Air Traffic Control Systems move from a voice only environment to one in which clearances are issued via data link, there is a risk that an unauthorized entity may attempt to masquerade as either the pilot or controller. In order to protect against this and related attacks, air-ground communications must be secured. The challenge is to add security in an environment in which bandwidth is limited. The Aeronautical Telecommunications Network (ATN) is an enabling digital network communications technology that addresses capacity and efficiency issues associated with current aeronautical voice communication systems. Equally important, the ATN facilitates migration to free flight, where direct computer-to-computer communication will automate air traffic management, minimize controller and pilot workload, and improve overall aircraft routing efficiency. Protecting ATN communications is critical since safety-of-flight is seriously affected if an unauthorized entity, a hacker for example, is able to penetrate an otherwise reliable communications system and accidentally or maliciously introduce erroneous information that jeopardizes the overall safety and integrity of a given airspace. However, an ATN security implementation must address the challenges associated with aircraft mobility, limited bandwidth communication channels, and uninterrupted operation across organizational and geopolitical boundaries. This paper provides a brief overview of the ATN, the ATN security concept, and begins a basic introduction to the relevant security concepts of security threats, security services and security mechanisms. Security mechanisms are further examined by presenting the fundamental building blocks of symmetric encipherment, asymmetric encipherment, and hash functions. The second part of this paper presents the project of cryptographiclly secure wireless communication between Unmanned Aerial Vehicles (UAV) and the ground station in the ATM system, based on the ARM9 processor

  14. Real-time systems

    OpenAIRE

    Badr, Salah M.; Bruztman, Donald P.; Nelson, Michael L.; Byrnes, Ronald Benton

    1992-01-01

    This paper presents an introduction to the basic issues involved in real-time systems. Both real-time operating sys and real-time programming languages are explored. Concurrent programming and process synchronization and communication are also discussed. The real-time requirements of the Naval Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real-time operating system, real-time programming language, real-time sy...

  15. Real-time neural network-based self-tuning control of a nonlinear electro-hydraulic servomotor

    Energy Technology Data Exchange (ETDEWEB)

    Canelon, J.I.; Ortega, A.G. [Univ. del Zulia, Maracaibo, Zulia (Venezuela, Bolivarian Republic of). School of Electrical Engineering; Shieh, L.S. [Houston Univ., Houston, TX (United States). Dept. of Electrical and Computer Engineering; Bastidas, J.I. [Univ. del Zulia, Maracaibo, Zulia (Venezuela, Bolivarian Republic of). School of Mechanical Engineering; Zhang, Y.; Akujuobi, C.M. [Prairie View A and M Univ., Prairie View, TX (United States). Center of Excellence for Communication Systems Technology Research and Dept. of Engineering Technology

    2010-08-13

    For high power applications, hydraulic actuators offer many advantages over electromagnetic actuators, including higher torque/mass ratios; smaller control gains; excellent torque capability; filtered high frequency noise; better heat transfer characteristics; smaller size; higher speed of response of the servomechanism; cheaper hardware; and higher reliability. Therefore, any application that requires a large force applied smoothly by an actuator is a candidate for hydraulic power. Examples of such applications include vehicle steering and braking systems; roll mills; drilling rigs; heavy duty crane and presses; and industrial robots and actuators for aircraft control surfaces such as ailerons and flaps. It is extremely important to create effective control strategies for hydraulic systems. This paper outlined the real-time implementation of a neural network-based approach, for self-tuning control of the angular position of a nonlinear electro-hydraulic servomotor. Using an online training algorithm, a neural network autoregressive moving-average model with exogenous input (ARMAX) model of the system was identified and continuously updated and an optimal linear ARMAX model was determined. The paper briefly depicted the neural network-based self-tuning control approach and a description of the experimental equipment (hardware and software) was presented including the implementation details. The experimental results were discussed and conclusions were summarized. It was found that the approach proved to be very effective in the control of this fast dynamics system, outperforming a fine tuned PI controller. Therefore, although the self-tuning approach was computationally demanding, it was feasible for real-time implementation. 22 refs., 6 figs.

  16. Networks of VTA Neurons Encode Real-Time Information about Uncertain Numbers of Actions Executed to Earn a Reward

    Directory of Open Access Journals (Sweden)

    Jesse Wood

    2017-08-01

    Full Text Available Multiple and unpredictable numbers of actions are often required to achieve a goal. In order to organize behavior and allocate effort so that optimal behavioral policies can be selected, it is necessary to continually monitor ongoing actions. Real-time processing of information related to actions and outcomes is typically assigned to the prefrontal cortex and basal ganglia, but also depends on midbrain regions, especially the ventral tegmental area (VTA. We were interested in how individual VTA neurons, as well as networks within the VTA, encode salient events when an unpredictable number of serial actions are required to obtain a reward. We recorded from ensembles of putative dopamine and non-dopamine neurons in the VTA as animals performed multiple cued trials in a recording session where, in each trial, serial actions were randomly rewarded. While averaging population activity did not reveal a response pattern, we observed that different neurons were selectively tuned to low, medium, or high numbered actions in a trial. This preferential tuning of putative dopamine and non-dopamine VTA neurons to different subsets of actions in a trial allowed information about binned action number to be decoded from the ensemble activity. At the network level, tuning curve similarity was positively associated with action-evoked noise correlations, suggesting that action number selectivity reflects functional connectivity within these networks. Analysis of phasic responses to cue and reward revealed that the requirement to execute multiple and uncertain numbers of actions weakens both cue-evoked responses and cue-reward response correlation. The functional connectivity and ensemble coding scheme that we observe here may allow VTA neurons to cooperatively provide a real-time account of ongoing behavior. These computations may be critical to cognitive and motivational functions that have long been associated with VTA dopamine neurons.

  17. Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network

    Directory of Open Access Journals (Sweden)

    Mehmet Şimşir

    2016-01-01

    Full Text Available Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure. Such systems driven by hub motors (in wheel motors encounter previously defined and undefined faults under operation. It may inevitably lead to the interruption of the electromechanical system operation; hence, economic losses take place at certain times. Therefore, in order to maintain system operation sustainability, the motor should be precisely monitored and the faults are diagnosed considering various significant motor parameters. In this study, the artificial feedforward backpropagation neural network approach is proposed to real-time monitor and diagnose the faults of the hub motor by measuring seven main system parameters. So as to construct a necessary model, we trained the model, using a data set consisting of 4160 samples where each has 7 parameters, by the MATLAB environment until the best model is obtained. The results are encouraging and meaningful for the specific motor and the developed model may be applicable to other types of hub motors. The prosperous model of the whole system was embedded into Arduino Due microcontroller card and the mobile real-time monitoring and fault diagnosis system prototype for hub motor was designed and manufactured.

  18. A Novel Real-Time Coal Miner Localization and Tracking System Based on Self-Organized Sensor Networks

    Directory of Open Access Journals (Sweden)

    Wang Yang

    2010-01-01

    Full Text Available With the development of information technology, we envision that the key of improving coal mine safety is how to get real-time positions of miners. In this paper, we propose a prototype system for real-time coal miner localization and tracking based on self-organized sensor networks. The system is composed of hardware and software platform. We develop a set of localization hardware devices with the Safety Certificate of Approval for Mining Products include miner node, wired fixed access station, and base with optical port. On the software side, we develop a layered software architecture of node application, server management, and information dissemination and broadcasting. We also develop three key localization technologies: an underground localization algorithm using received signal strength indication- (RSSI- verifying algorithm to reduce the influence of the severe environment in a coal mine; a robust fault-tolerant localization mechanism to improve the inherent defect of instability of RSSI localization; an accurate localization algorithm based on Monte Carlo localization (MCL to adapt to the underground tunnel structure. In addition, we conduct an experimental evaluation based on a real prototype implementation using MICA2 motes. The results show that our system is more accurate and more adaptive in general than traditional localization algorithms.

  19. A wireless telecommunications network for real-time monitoring of greenhouse microclimate

    Directory of Open Access Journals (Sweden)

    Giuliano Vox

    2014-10-01

    Full Text Available An innovative wireless monitoring system for measuring greenhouse climatic parameters was developed to overcome the problems related to wires cabling such as presence of a dense net of wires hampering the cultivation practices, wires subjected to high temperature and relative humidity, rodents that can damage wires. The system exploits battery-powered environmental sensors, such as air temperature and relative humidity sensors, wind speed and direction, and solar radiation sensors, integrated in the contest of an 802.15.4-based wireless sensors network. Besides, a fruit diameter measurement sensor was integrated into the system. This approach guarantees flexibility, ease of deployment and low power consumption. Data collected from the greenhouse are then sent to a remote server via a general packet radio service link. The proposed solution has been implemented in a real environment. The test of the communication system showed that 0.3% of the sent data packed were lost; the climatic parameters measured with the wireless system were compared with data collected by the wired system showing a mean value of the absolute difference equal to 0.6°C for the value of the greenhouse air temperature. The wireless climate monitoring system showed a good reliability, while the sensor node batteries showed a lifetime of 530 days.

  20. Surveying Multidisciplinary Aspects in Real-Time Distributed Coding for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Carlo Braccini

    2015-01-01

    Full Text Available Wireless Sensor Networks (WSNs, where a multiplicity of sensors observe a physical phenomenon and transmit their measurements to one or more sinks, pertain to the class of multi-terminal source and channel coding problems of Information Theory. In this category, “real-time” coding is often encountered for WSNs, referring to the problem of finding the minimum distortion (according to a given measure, under transmission power constraints, attainable by encoding and decoding functions, with stringent limits on delay and complexity. On the other hand, the Decision Theory approach seeks to determine the optimal coding/decoding strategies or some of their structural properties. Since encoder(s and decoder(s possess different information, though sharing a common goal, the setting here is that of Team Decision Theory. A more pragmatic vision rooted in Signal Processing consists of fixing the form of the coding strategies (e.g., to linear functions and, consequently, finding the corresponding optimal decoding strategies and the achievable distortion, generally by applying parametric optimization techniques. All approaches have a long history of past investigations and recent results. The goal of the present paper is to provide the taxonomy of the various formulations, a survey of the vast related literature, examples from the authors’ own research, and some highlights on the inter-play of the different theories.

  1. Development and evaluation of an open-source, low-cost distributed sensor network for environmental monitoring applications

    Science.gov (United States)

    Gunawardena, N.; Pardyjak, E. R.; Stoll, R.; Khadka, A.

    2018-02-01

    Over the last decade there has been a proliferation of low-cost sensor networks that enable highly distributed sensor deployments in environmental applications. The technology is easily accessible and rapidly advancing due to the use of open-source microcontrollers. While this trend is extremely exciting, and the technology provides unprecedented spatial coverage, these sensors and associated microcontroller systems have not been well evaluated in the literature. Given the large number of new deployments and proposed research efforts using these technologies, it is necessary to quantify the overall instrument and microcontroller performance for specific applications. In this paper, an Arduino-based weather station system is presented in detail. These low-cost energy-budget measurement stations, or LEMS, have now been deployed for continuous measurements as part of several different field campaigns, which are described herein. The LEMS are low-cost, flexible, and simple to maintain. In addition to presenting the technical details of the LEMS, its errors are quantified in laboratory and field settings. A simple artificial neural network-based radiation-error correction scheme is also presented. Finally, challenges and possible improvements to microcontroller-based atmospheric sensing systems are discussed.

  2. TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks

    Science.gov (United States)

    Song, W.-Z.; Huang, R.; Shirazi, B.; Husent, R.L.

    2009-01-01

    Earlier sensor network MAC protocols focus on energy conservation in low-duty cycle applications, while some recent applications involve real-time high-data-rate signals. This motivates us to design an innovative localized TDMA MAC protocol to achieve high throughput and low congestion in data collection sensor networks, besides energy conservation. TreeMAC divides a time cycle into frames and frame into slots. Parent determines children's frame assigmnent based on their relative bandwidth demand, and each node calculates its own slot assignment based on its hop-count to the sink. This innovative 2-dimensional frame-slot assignment algorithm has the following nice theory properties. Firstly, given any node, at any time slot, there is at most one active sender in its neighborhood (includ ing itself). Secondly, the packet scheduling with TreelMAC is bufferless, which therefore minimizes the probability of network congestion. Thirdly, the data throughput to gateway is at least 1/3 of the optimum assuming reliable links. Our experiments on a 24 node test bed demonstrate that TreeMAC protocol significantly improves network throughput and energy efficiency, by comparing to the TinyOS's default CSMA MAC protocol and a recent TDMA MAC protocol Funneling-MAC[8]. ?? 2009 IEEE.

  3. Implementation of a Low-Cost Energy and Environment Monitoring System Based on a Hybrid Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Dong Sik Kim

    2017-01-01

    Full Text Available A low-cost hybrid wireless sensor network (WSN that utilizes the 917 MHz band Wireless Smart Utility Network (Wi-SUN and a 447 MHz band narrow bandwidth communication network is implemented for electric metering and room temperature, humidity, and CO2 gas measurements. A mesh network connection that is commonly utilized for the Internet of Things (IoT is used for the Wi-SUN under the Contiki OS, and a star connection is used for the narrow bandwidth network. Both a duty-cycling receiver algorithm and a digitally controlled temperature-compensated crystal oscillator algorithm for frequency reference are implemented at the physical layer of the receiver to accomplish low-power and low-cost wireless sensor node design. A two-level temperature-compensation approach, in which first a fixed third-order curve and then a sample-based first-order curve are applied, is proposed using a conventional AT-cut quartz crystal resonator. The developed WSN is installed in a home and provides reliable data collection with low construction complexity and power consumption.

  4. Flexible automated systems of real time mining operation management: concepts, architecture, models of network engineering for data transmission and processing

    Energy Technology Data Exchange (ETDEWEB)

    Markhasin, A.B.

    1987-11-01

    Since the mid 1960's considerable effort has been invested by the mining industry and its research institutions and by universities to create real time mining management automation systems. Some of the shortcomings which still persist in realizing the efficiency such systems can offer are due to objective and subjective factors within and outside the management systems: the creation of the component base, automation equipment, and computer technology, on the one hand, and the organization, process, engineering, and coordination of mining work on the other. This review addresses several of these shortcomings with recommendations for their solution in a primary and systematic way and suggests methods for the implementation of microprocessors and a network of flexible data transmission and processing facilities for both surface and underground mining.

  5. Real-time distributed simulation using the Modular Modeling System interfaced to a Bailey NETWORK 90 system

    International Nuclear Information System (INIS)

    Edwards, R.M.; Turso, J.A.; Garcia, H.E.; Ghie, M.H.; Dharap, S.; Lee, S.

    1991-01-01

    The Modular Modeling System was adapted for real-time simulation testing of diagnostic expert systems in 1987. The early approach utilized an available general purpose mainframe computer which operated the simulation and diagnostic program in the multitasking environment of the mainframe. That research program was subsequently expanded to intelligent distributed control applications incorporating microprocessor based controllers with the aid of an equipment grant from the National Science Foundation (NSF). The Bailey NETWORK 90 microprocessor-based control system, acquired with the NSF grant, has been operational since April of 1990 and has been interfaced to both VAX mainframe and PC simulations of power plant processes in order to test and demonstrate advanced control and diagnostic concepts. This paper discusses the variety of techniques that have been used and which are under development to interface simulations and other distributed control functions to the Penn State Bailey system

  6. A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

    Science.gov (United States)

    Qu, Jianfeng; Chai, Yi; Yang, Simon X.

    2009-01-01

    A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS) gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors. PMID:22399946

  7. Development of the Real Time Situation Identification Model for Adaptive Service Support in Vehicular Communication Networks Domain

    Directory of Open Access Journals (Sweden)

    Mindaugas Kurmis

    2013-01-01

    Full Text Available The article discusses analyses and assesses the key proposals how to deal with the situation identification for the heterogeneous service support in vehicular cooperation environment. This is one of the most important topics of the pervasive computing. Without the solution it is impossible to adequately respond to the user's needs and to provide needed services in the right place at the right moment and in the right way. In this work we present our developed real time situation identification model for adaptive service support in vehicular communication networks domain. Our solution is different from the others as it uses additional virtual context information source - information from other vehicles which for our knowledge is not addressed in the past. The simulation results show the promising context exchange rate between vehicles. The other vehicles provided additional context source in our developed model helps to increase situations identification level.

  8. A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Yi Chai

    2009-02-01

    Full Text Available A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors.

  9. VADASE: a new approach for real-time fast displacement detection - First application to Taiwan High-Rate GNSS Network

    Science.gov (United States)

    Hung, Huang-Kai; Rau, Ruey-Juin; Colosimo, Gabriele; Benedetti, Elisa; Branzanti, Mara; Crespi, Mattia; Mazzoni, Augusto

    2014-05-01

    The aim of this work is to show new possibilities for GNSS Permanent Network data processing offered by VADASE (Variometric Approach for Displacements Analysis Standalone Engine) to retrieve waveforms and coseismic displacements in real-time when an earthquake occurs. The main advantage of using GNSS receiver, in a complementary way with traditional seismic network, is that it can work without being affected by saturation, which commonly influence seismometers and accelerometers close to strong earthquake epicenters. VADASE was originally proposed in 2010 ([4],[5]) as the third way in GPS Seismology (in addition to Precise Point Positioning and Instantaneous Differential Positioning). The approach is based on time single differences of carrier phase observations continuously collected at high rate (1 Hz or higher) using a standalone GPS receiver and standard GPS broadcast products (orbits and clocks) that are available in real-time. Hence, one receiver works in standalone mode and the epoch-by-epoch displacements (equivalent to velocities) are estimated. Then, they are summed over the time interval when the earthquake occurred to retrieve coseismic displacements and waveforms. Considering time intervals limited to few minutes, the receiver displacements can be ascertained at a few centimeters accuracy level in real-time. The effectiveness of this approach was recognized by DLR (German Aerospace Agency), and VADASE was awarded the DLR Special Topic Prize and the Audience Award at the European Satellite Navigation Competition 2010. Moreover, VADASE potential was proven in the dramatic occasion of the Japanese earthquake occurred on March 11, 2011 ([3]-[6]); in fact VADASE was able to provide the first estimates of the displacements suffered at the IGS sites of MIZU and USUD [7], as soon as the data of these stations were available. The results were then confirmed by several other solutions based on the renown (DP, PPP) approaches. More recently, VADASE was applied

  10. Development of real-time core monitoring system models with accuracy-enhanced neural network and its application

    International Nuclear Information System (INIS)

    Koo, Bon Hyun

    1994-02-01

    In a complicated system like pressurized water reactor, a number of key safety parameters need to be selected to represent the reactor systems safety. It could be more effective for the reactor safety to make the key safety parameters in real-time available directly to the reactor operator. Direct representation of key safety parameters is also desirable in the view of reactor core design since it could reduce unnecessary margins for various components of uncertainties. In this thesis, real-time core monitoring system models have been developed with use of artificial neural networks for the prediction of nuclear hot channel factor (HCF) and core departure from nucleate boiling ratio (DNBR) which are known to be the fundamental core safety parameters for pressurized water reactors. Artificial neural network algorithm, has been shown to be successful for the conservative and accurate prediction of the HCF and DNBR. For the development of system models, training patterns were generated using the FLAIR and COBRAIV-i computer codes for the HCF and DNBR. The selected input variables were the core power, reactor coolant flow, temperature, pressure, power distribution, boron concentration, and rod position. The developed system models could replace the existing core monitoring systems and then afford a better efficiency by using the additional margin which otherwise needs to be reserved for various unidentified uncertainties. Several variations of the neural network technique have been proposed and compared based on numerical experiments. The neural network can be augmented by use of a functional link to improve the performance of the network model. The functional link is found to be very effective especially when the relationship between the input parameters and the output parameters is overly complicated such as in the core HCF and DNBR. For the further enhancement of DNBR accuracy, two-fold weight sets were used. The coarse weight set can provide a quick and

  11. Monitoring urban air quality using a high-density network of low-cost sensor nodes in Oslo, Norway.

    Science.gov (United States)

    Castell, Nuria; Schneider, Philipp; Vogt, Matthias; Dauge, Franck R.; Lahoz, William; Bartonova, Alena

    2017-04-01

    Urban air quality represents a major public health burden and is a long-standing concern to citizens. Air pollution is associated with a range of diseases, symptoms and conditions that impair health and quality of life. In Oslo, traffic, especially exhaust from heavy-duty and private diesel vehicles and dust resuspension from studded tyres, together with wood burning in winter, are the main sources of pollution. Norway, as part of the European Economic Area, is obliged to comply with the European air quality regulations and ensure clean air. Despite this, Oslo has exceeded both the NO2 and PM10 thresholds for health protection defined in the Directive 2008/50/EC. The air quality in the Oslo area is continuously monitored in 12 compliance monitoring stations. These stations provide reliable and accurate data but their density is too low to provide a detailed spatial distribution of air quality. The emergence of low-cost nodes enables observations at high spatial resolution, providing the opportunity to enhance existing monitoring systems. However, the data generated by these nodes is significantly less accurate and precise than the data provided by reference equipment. We have conducted an evaluation of low-cost nodes to monitor NO2 and PM10, comparing the data collected with low-cost nodes against CEN (European Standardization Organization) reference analysers. During January and March 2016, a network of 24 nodes was deployed in Oslo. During January, high NO2 levels were observed for several days in a row coinciding with the formation of a thermal inversion. During March, we observed an episode with high PM10 levels due to road dust resuspension. Our results show that there is a major technical challenge associated with current commercial low-cost sensors, regarding the sensor robustness and measurement repeatability. Despite this, low-cost sensor nodes are able to reproduce the NO2 and PM10 variability. The data from the sensors was employed to generate detailed

  12. Low-cost design of next generation SONET/SDH networks with multiple constraints

    CSIR Research Space (South Africa)

    Karem, TR

    2007-07-01

    Full Text Available on constraints programming satisfaction technology is proposed. The algorithm is tested in OPNET simulation environment using different network models derived from a hypothetical case study of an optical network design for Bellville area in Cape Town, South...

  13. The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors

    Science.gov (United States)

    Kim, Jinsol; Shusterman, Alexis A.; Lieschke, Kaitlyn J.; Newman, Catherine; Cohen, Ronald C.

    2018-04-01

    The newest generation of air quality sensors is small, low cost, and easy to deploy. These sensors are an attractive option for developing dense observation networks in support of regulatory activities and scientific research. They are also of interest for use by individuals to characterize their home environment and for citizen science. However, these sensors are difficult to interpret. Although some have an approximately linear response to the target analyte, that response may vary with time, temperature, and/or humidity, and the cross-sensitivity to non-target analytes can be large enough to be confounding. Standard approaches to calibration that are sufficient to account for these variations require a quantity of equipment and labor that negates the attractiveness of the sensors' low cost. Here we describe a novel calibration strategy for a set of sensors, including CO, NO, NO2, and O3, that makes use of (1) multiple co-located sensors, (2) a priori knowledge about the chemistry of NO, NO2, and O3, (3) an estimate of mean emission factors for CO, and (4) the global background of CO. The strategy requires one or more well calibrated anchor points within the network domain, but it does not require direct calibration of any of the individual low-cost sensors. The procedure nonetheless accounts for temperature and drift, in both the sensitivity and zero offset. We demonstrate this calibration on a subset of the sensors comprising BEACO2N, a distributed network of approximately 50 sensor nodes, each measuring CO2, CO, NO, NO2, O3 and particulate matter at 10 s time resolution and approximately 2 km spacing within the San Francisco Bay Area.

  14. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    Directory of Open Access Journals (Sweden)

    Xerxes D. Arsiwalla

    2015-02-01

    Full Text Available BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for real-time exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably, due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  15. Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks

    OpenAIRE

    de Paz Santana, Juan F.; Tapia Martínez, Dante I.; Alonso Rincón, Ricardo S.; Pinzón, Cristian; Bajo Pérez, Javier; Corchado Rodríguez, Juan M.

    2017-01-01

    Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the ...

  16. Real-Time Emulation of Heterogeneous Wireless Networks with End-to-Edge Quality of Service Guarantees: The AROMA Testbed

    Directory of Open Access Journals (Sweden)

    Anna Umbert

    2010-01-01

    Full Text Available This work presents and describes the real-time testbed for all-IP Beyond 3G (B3G heterogeneous wireless networks that has been developed in the framework of the European IST AROMA project. The main objective of the AROMA testbed is to provide a highly accurate and realistic framework where the performance of algorithms, policies, protocols, services, and applications for a complete heterogeneous wireless network can be fully assessed and evaluated before bringing them to a real system. The complexity of the interaction between all-IP B3G systems and user applications, while dealing with the Quality of Service (QoS concept, motivates the development of this kind of emulation platform where different solutions can be tested in realistic conditions that could not be achieved by means of simple offline simulations. This work provides an in-depth description of the AROMA testbed, emphasizing many interesting implementation details and lessons learned during the development of the tool that may result helpful to other researchers and system engineers in the development of similar emulation platforms. Several case studies are also presented in order to illustrate the full potential and capabilities of the presented emulation platform.

  17. A Real-Time Smooth Weighted Data Fusion Algorithm for Greenhouse Sensing Based on Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Tengyue Zou

    2017-11-01

    Full Text Available 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.

  18. Real-Time Multifault Rush Repairing Strategy Based on Utility Theory and Multiagent System in Distribution Networks

    Directory of Open Access Journals (Sweden)

    Zhao Hao

    2016-01-01

    Full Text Available The problem of multifault rush repair in distribution networks (DNs is a multiobjective dynamic combinatorial problem with topology constraints. The problem consists of archiving an optimal faults’ allocation strategy to squads and an admissible multifault rush repairing strategy with coordinating switch operations. In this article, the utility theory is introduced to solve the first problem and a new discrete bacterial colony chemotaxis (DBCC algorithm is proposed for the second problem to determine the optimal sequence for each squad to repair faults and the corresponding switch operations. The above solution is called the two-stage approach. Additionally, a double mathematical optimization model based on the fault level is proposed in the second stage to minimize the outage loss and total repairing time. The real-time adjustment multiagent system (RA-MAS is proposed to provide facility to achieve online multifault rush repairing strategy in DNs when there are emergencies after natural disasters. The two-stage approach is illustrated with an example from a real urban distribution network and the simulation results show the effectiveness of the two-stage approach.

  19. Performance of data acceptance criteria over 50 months from an automatic real-time environmental radiation surveillance network

    International Nuclear Information System (INIS)

    Casanovas, R.; Morant, J.J.; Lopez, M.; Hernandez-Giron, I.; Batalla, E.; Salvado, M.

    2011-01-01

    The automatic real-time environmental radiation surveillance network of Catalonia (Spain) comprises two subnetworks; one with 9 aerosol monitors and the other with 8 Geiger monitors together with 2 water monitors located in the Ebre river. Since September 2006, several improvements were implemented in order to get better quality and quantity of data, allowing a more accurate data analysis. However, several causes (natural causes, equipment failure, artificial external causes and incidents in nuclear power plants) may produce radiological measured values mismatched with the own station background, whether spurious without significance or true radiological values. Thus, data analysis for a 50-month period was made and allowed to establish an easily implementable statistical criterion to find those values that require special attention. This criterion proved a very useful tool for creating a properly debugged database and to give a quick response to equipment failures or possible radiological incidents. This paper presents the results obtained from the criterion application, including the figures for the expected, raw and debugged data, percentages of missing data grouped by causes and radiological measurements from the networks. Finally, based on the discussed information, recommendations for the improvement of the network are identified to obtain better radiological information and analysis capabilities. - Highlights: → Causes producing data mismatching with the own stations background are described. → Causes may be natural, equipment failure, external or nuclear plants incidents. → These causes can produce either spurious or true radiological data. → A criterion to find these data was implemented and tested for a 50-month period. → Recommendations for the improvement of the network are identified.

  20. The Inverse Contagion Problem (ICP) vs.. Predicting site contagion in real time, when network links are not observable

    Science.gov (United States)

    Mushkin, I.; Solomon, S.

    2017-10-01

    We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires "only" the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types. The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the "false link difficulty". By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the "false link difficulty" of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure. We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it

  1. Transforming Ordinary Buildings into Smart Buildings via Low-Cost, Self-Powering Wireless Sensors & Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Feng, Philip [Case Western Reserve Univ., Cleveland, OH (United States)

    2017-06-09

    The research objective of this project is to design and demonstrate a low-cost, compact, easy-to-deploy, maintenance-free sensor node technology, and a network of such sensors, which enable the monitoring of multiphysical parameters and can transform today’s ordinary buildings into smart buildings with environmental awareness. We develop the sensor node and network via engineering and integration of existing technologies, including high-efficiency mechanical energy harvesting, and ultralow-power integrated circuits (ICs) for sensing and wireless communication. Through integration and innovative power management via specifically designed low-power control circuits for wireless sensing applications, and tailoring energy-harvesting components to indoor applications, the target products will have smaller volume, higher efficiency, and much lower cost (in both manufacturing and maintenance) than the baseline technology. Our development and commercialization objective is to create prototypes for our target products under the CWRU-Intwine collaboration.

  2. Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves

    Science.gov (United States)

    Chang, Ya-Ting; Chang, Li-Chiu; Chang, Fi-John

    2005-04-01

    To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network-based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M-5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input-output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M-5 curves in real-time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved.

  3. A 181 GOPS AKAZE Accelerator Employing Discrete-Time Cellular Neural Networks for Real-Time Feature Extraction.

    Science.gov (United States)

    Jiang, Guangli; Liu, Leibo; Zhu, Wenping; Yin, Shouyi; Wei, Shaojun

    2015-09-04

    This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network) that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures.

  4. A 181 GOPS AKAZE Accelerator Employing Discrete-Time Cellular Neural Networks for Real-Time Feature Extraction

    Directory of Open Access Journals (Sweden)

    Guangli Jiang

    2015-09-01

    Full Text Available This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures.

  5. SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

    Science.gov (United States)

    Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi

    2018-01-01

    Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. The aquatic real-time monitoring network; in-situ optical sensors for monitoring the nation's water quality

    Science.gov (United States)

    Pellerin, Brian A.; Bergamaschi, Brian A.; Murdoch, Peter S.; Downing, Bryan D.; Saraceno, John Franco; Aiken, George R.; Striegl, Robert G.

    2011-01-01

    Floods, hurricanes, and longer-term changes in climate and land use can have profound effects on water quality due to shifts in hydrologic flow paths, water residence time, precipitation patterns, connectivity between rivers and uplands, and many other factors. In order to understand and respond to changes in hydrology and water quality, resource managers and policy makers have a need for accurate and early indicators, as well as the ability to assess possible mechanisms and likely outcomes. In-situ optical sensors-those making continuous measurements of constituents by absorbance or fluorescence properties in the environment at timescales of minutes to years-have a long history in oceanography for developing highly resolved concentrations and fluxes, but are not commonly used in freshwater systems. The United States Geological Survey (USGS) has developed the Aquatic Real-Time Monitoring Network, with high-resolution optical data collection for organic carbon, nutrients, and sediment in large coastal rivers, along with continuous measurements of discharge, water temperature, and dissolved inorganic carbon. The collecting of continuous water-quality data in the Nation?s waterways has revealed temporal trends and spatial patterns in constituents that traditional sampling approaches fail to capture, and will serve a critical role in monitoring, assessment and decision-making in a rapidly changing landscape.

  7. Implementation of an RBF neural network on embedded systems: real-time face tracking and identity verification.

    Science.gov (United States)

    Yang, Fan; Paindavoine, M

    2003-01-01

    This paper describes a real time vision system that allows us to localize faces in video sequences and verify their identity. These processes are image processing techniques based on the radial basis function (RBF) neural network approach. The robustness of this system has been evaluated quantitatively on eight video sequences. We have adapted our model for an application of face recognition using the Olivetti Research Laboratory (ORL), Cambridge, UK, database so as to compare the performance against other systems. We also describe three hardware implementations of our model on embedded systems based on the field programmable gate array (FPGA), zero instruction set computer (ZISC) chips, and digital signal processor (DSP) TMS320C62, respectively. We analyze the algorithm complexity and present results of hardware implementations in terms of the resources used and processing speed. The success rates of face tracking and identity verification are 92% (FPGA), 85% (ZISC), and 98.2% (DSP), respectively. For the three embedded systems, the processing speeds for images size of 288 /spl times/ 352 are 14 images/s, 25 images/s, and 4.8 images/s, respectively.

  8. Low cost fabrication and assembly process for re-usable 3D polydimethylsiloxane (PDMS) microfluidic networks

    CSIR Research Space (South Africa)

    Land, K

    2011-09-01

    Full Text Available and assembly process for re-usable 3D polydimethylsiloxane (PDMS) microfluidic networks Kevin J. Land, Mesuli B. Mbanjwa, Klariska Govindasamy, and Jan G. Korvink Citation: Biomicrofluidics 5, 036502 (2011); doi: 10.1063/1.3641859 View online: http... polydimethylsiloxane (PDMS) microfluidic networks Kevin J. Land,1,2,a) Mesuli B. Mbanjwa,1,3 Klariska Govindasamy,1 and Jan G. Korvink2,4 1Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa 2University of Freiburg, Department...

  9. Performance in wireless networks and industrial wireless networks on control processes in real time under industrial environments

    Directory of Open Access Journals (Sweden)

    Juan F. Monsalve-Posada

    2015-01-01

    Full Text Available The growing use of Ethernet networks on the industrial automation pyramid has led many companies to develop new devices to operate in requirements of this level, nowadays it is called Industrial Ethernet network, on the market there are various sensors and actuators to industrial scale equipped with this technology, many of these devices are very expensive. In this paper, the performance of two wireless networks is evaluated, the first network has conventional Ethernet devices, and the second network has Industrial Ethernet devices. For the process we vary four parameters such as distance, number of bytes, the signal to noise ratio, and the packet error rate, and then we measure delays and compare with metric statistics results, Box Plot graphs were used for the analysis. Finally, we conclude that under the parameters and conditions tested, wireless networks can serve as a communication system in control applications with allowable delays of up to 50 ms, in addition, the results show a better performance of Industrial Ethernet networks over conventional networks, with differences in the RTT of milliseconds. Therefore, it is recommended to establish what risk is for the process to control these delays to determine if the equipment conventional applies, since under certain features like humidity and temperature can operate properly for a considerable time and at lower cost than devices to Industrial Ethernet.

  10. A Low-Cost Maximum Power Point Tracking System Based on Neural Network Inverse Model Controller

    Directory of Open Access Journals (Sweden)

    Carlos Robles Algarín

    2018-01-01

    Full Text Available This work presents the design, modeling, and implementation of a neural network inverse model controller for tracking the maximum power point of a photovoltaic (PV module. A nonlinear autoregressive network with exogenous inputs (NARX was implemented in a serial-parallel architecture. The PV module mathematical modeling was developed, a buck converter was designed to operate in the continuous conduction mode with a switching frequency of 20 KHz, and the dynamic neural controller was designed using the Neural Network Toolbox from Matlab/Simulink (MathWorks, Natick, MA, USA, and it was implemented on an open-hardware Arduino Mega board. To obtain the reference signals for the NARX and determine the 65 W PV module behavior, a system made of a 0.8 W PV cell, a temperature sensor, a voltage sensor and a static neural network, was used. To evaluate performance a comparison with the P&O traditional algorithm was done in terms of response time and oscillations around the operating point. Simulation results demonstrated the superiority of neural controller over the P&O. Implementation results showed that approximately the same power is obtained with both controllers, but the P&O controller presents oscillations between 7 W and 10 W, in contrast to the inverse controller, which had oscillations between 1 W and 2 W.

  11. D-MSR: A Distributed Network Management Scheme for Real-Time Monitoring and Process Control Applications in Wireless Industrial Automation

    Science.gov (United States)

    Zand, Pouria; Dilo, Arta; Havinga, Paul

    2013-01-01

    Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot cope with dynamicity/disturbance in large-scale networks in a real-time manner and it incurs a high communication overhead and latency for exchanging management traffic. In this paper, we therefore propose a distributed network management scheme, D-MSR. It enables the network devices to join the network, schedule their communications, establish end-to-end connections by reserving the communication resources for addressing real-time requirements, and cope with network dynamicity (e.g., node/edge failures) in a distributed manner. According to our knowledge, this is the first distributed management scheme based on IEEE 802.15.4e standard, which guides the nodes in different phases from joining until publishing their sensor data in the network. We demonstrate via simulation that D-MSR can address real-time and reliable communication as well as the high throughput requirements of industrial automation wireless networks, while also achieving higher efficiency in network management than WirelessHART, in terms of delay and overhead. PMID:23807687

  12. D-MSR: a distributed network management scheme for real-time monitoring and process control applications in wireless industrial automation.

    Science.gov (United States)

    Zand, Pouria; Dilo, Arta; Havinga, Paul

    2013-06-27

    Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot cope with dynamicity/disturbance in large-scale networks in a real-time manner and it incurs a high communication overhead and latency for exchanging management traffic. In this paper, we therefore propose a distributed network management scheme, D-MSR. It enables the network devices to join the network, schedule their communications, establish end-to-end connections by reserving the communication resources for addressing real-time requirements, and cope with network dynamicity (e.g., node/edge failures) in a distributed manner. According to our knowledge, this is the first distributed management scheme based on IEEE 802.15.4e standard, which guides the nodes in different phases from joining until publishing their sensor data in the network. We demonstrate via simulation that D-MSR can address real-time and reliable communication as well as the high throughput requirements of industrial automation wireless networks, while also achieving higher efficiency in network management than WirelessHART, in terms of delay and overhead.

  13. Network dynamics with BrainX(3): a large-scale simulation of the human brain network with real-time interaction.

    Science.gov (United States)

    Arsiwalla, Xerxes D; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F M J

    2015-01-01

    BrainX(3) is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX(3) in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX(3) can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  14. Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

    Science.gov (United States)

    Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas. PMID:25759649

  15. Emerging adults' use of alcohol and social networking sites during a large street festival: A real-time interview study.

    Science.gov (United States)

    Whitehill, Jennifer M; Pumper, Megan A; Moreno, Megan A

    2015-05-20

    Emerging adults have high rates of heavy episodic drinking (binge drinking) and related risks including alcohol-impaired driving. To understand whether social networking sites (SNSs) used on mobile devices represent a viable platform for real-time interventions, this study measured emerging adults' use of two popular SNSs (Facebook and Twitter) during the Mifflin Street Block Party. This annual festival is held in Madison, Wisconsin and is known for high alcohol consumption. Event attendees ages 18-23 years were recruited by young adult research assistants (>21 years). Participants completed a brief in-person interview assessing drinking intensity, use of SNSs, and use of SNSs to plan transportation. Analyses included t-tests, chi-squared tests, and Fisher's exact tests. At the event, nearly all of the 200 participants (97 %) consumed alcohol and 18 % met criteria for heavy episodic drinking. Approximately one-third of participants had used Facebook or Twitter on the day of the event. Facebook use (23 %) was more prevalent than Twitter use (18 %), especially among heavy episodic drinkers. Use of either SNS was 41 % among females and 24 % among males (χ (2)=6.01; df=1; p=0.01). Plans to use a SNS to arrange transportation were relatively uncommon (4 %), but this was more frequent among heavy episodic drinkers (11 %) compared to non-heavy episodic drinkers (2 %) (Fisher's exact p=0.02). These results indicate that SNSs are used during alcohol consumption and warrant exploration as a way to facilitate connections to resources like safe ride services.

  16. Scalable Real-Time Negotiation Toolkit

    National Research Council Canada - National Science Library

    Lesser, Victor

    2004-01-01

    ... to implement an adaptive distributed sensor network. These activities involved the development of a distributed soft, real-time heuristic resource allocation protocol, the development of a domain-independent soft, real time agent architecture...

  17. Monitoring meteorological spatial variability in viticulture using a low-cost Wireless Sensor Network

    Science.gov (United States)

    Matese, Alessandro; Crisci, Alfonso; Di Gennaro, Filippo; Primicerio, Jacopo; Tomasi, Diego; Guidoni, Silvia

    2014-05-01

    In a long-term perspective, the current global agricultural scenario will be characterize by critical issues in terms of water resource management and environmental protection. The concept of sustainable agriculture would become crucial at reducing waste, optimizing the use of pesticides and fertilizers to crops real needs. This can be achieved through a minimum-scale monitoring of the crop physiologic status and the environmental parameters that characterize the microclimate. Viticulture is often subject to high variability within the same vineyard, thus becomes important to monitor this heterogeneity to allow a site-specific management and maximize the sustainability and quality of production. Meteorological variability expressed both at vineyard scale (mesoclimate) and at single plant level (microclimate) plays an important role during the grape ripening process. The aim of this work was to compare temperature, humidity and solar radiation measurements at different spatial scales. The measurements were assessed for two seasons (2011, 2012) in two vineyards of the Veneto region (North-East Italy), planted with Pinot gris and Cabernet Sauvignon using a specially designed and developed Wireless Sensor Network (WSN). The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering. Nodes level is based on a network of peripheral nodes consisting of a sensor board equipped with sensors and wireless module. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity. Different sources of spatial variation were studied, from meso-scale to micro-scale. A widespread investigation was conducted, building a factorial design able to evidence the role played by any factor influencing the physical environment in the vineyard, such as the surrounding climate

  18. Research on High-Precision, Low Cost Piezoresistive MEMS-Array Pressure Transmitters Based on Genetic Wavelet Neural Networks for Meteorological Measurements

    Directory of Open Access Journals (Sweden)

    Jiahong Zhang

    2015-05-01

    Full Text Available This paper provides a novel and effective compensation method by improving the hardware design and software algorithm to achieve optimization of piezoresistive pressure sensors and corresponding measurement systems in order to measure pressure more accurately and stably, as well as to meet the application requirements of the meteorological industry. Specifically, GE NovaSensor MEMS piezoresistive pressure sensors within a thousandth of accuracy are selected to constitute an array. In the versatile compensation method, the hardware utilizes the array of MEMS pressure sensors to reduce random error caused by sensor creep, and the software adopts the data fusion technique based on the wavelet neural network (WNN which is improved by genetic algorithm (GA to analyze the data of sensors for the sake of obtaining accurate and complete information over the wide temperature and pressure ranges. The GA-WNN model is implemented in hardware by using the 32-bit STMicroelectronics (STM32 microcontroller combined with an embedded real-time operating system µC/OS-II to make the output of the array of MEMS sensors be a direct digital readout. The results of calibration and test experiments clearly show that the GA-WNN technique can be effectively applied to minimize the sensor errors due to the temperature drift, the hysteresis effect and the long-term drift because of aging and environmental changes. The maximum error of the low cost piezoresistive MEMS-array pressure transmitter proposed by us is within 0.04% of its full-scale value, and it can satisfy the meteorological pressure measurement.

  19. Real-time estimation of free spaces in regulated on-street parking spaces using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Magaña Suarez, M.

    2016-07-01

    In this paper we will develop a methodology for estimating the percentage of free parking spaces available in the area of the city where a user is interested through a real-time query in a mobile app. The smartphone screen will provide a colour-coded map of the requested area that indicates the saturation state of the parking spaces. (Author)

  20. Low-cost fused taper polymer optical fiber (LFT-POF) splitters for environmental and home-networking solution

    Science.gov (United States)

    Supian, L. S.; Ab-Rahman, Mohammad Syuhaimi; Harun, Mohd Hazwan; Gunab, Hadi; Sulaiman, Malik; Naim, Nani Fadzlina

    2017-08-01

    In visible optical communication over the multimode PMMA fibers, the overall cost of optical network can be reduced by deploying economical splitters for distributing the optical data signals from a point to multipoint in transmission network. The low-cost splitters shall have two main characteristics; good uniformity and high power efficiency. The most cost-effective and environmental friendly optical splitter having those characteristics have been developed. The device material is 100% purely based on the multimode step-index PMMA Polymer Optical Fiber (POF). The region which all fibers merged as single fiber is called as fused-taper POF. This ensures that all fibers are melted and fused properly. The results for uniformity and power efficiency of all splitters have been revealed by injecting red LED transmitter with 650 nm wavelength into input port while each end of output fibers measured by optical power meter. Final analysis shows our fused-taper splitter has low excess loss 0.53 dB and each of the output port has low insertion loss, which the average value is below 7 dB. In addition, the splitter has good uniformity that is 32:37:31% in which it is suitably used for demultiplexer fabrication.

  1. UNAVCO GPS High-Rate and Real-Time Products and Services: Building a next generation geodetic network.

    Science.gov (United States)

    Mencin, David; Meertens, Charles; Mattioli, Glen; Feaux, Karl; Looney, Sara; Sievers, Charles; Austin, Ken

    2013-04-01

    Recent advances in GPS technology and data processing are providing position estimates with centimeter-level precision at high-rate (1-5 Hz) and low latency (transforming rapid event characterization, early warning, as well as hazard mitigation and response. Other scientific and operational applications for high-rate GPS also include glacier and ice sheet motions, tropospheric modeling, and better constraints on the dynamics of space weather. UNAVCO, through community input and the recent Plate Boundary Observatory (PBO) NSF-ARRA Cascadia initiative, has nearly completed the process of upgrading a total of 373 PBO GPS sites to real-time high-rate capability and these streams are now being archived in the UNAVCO data center. Further, through the UNAVCO core proposal (GAGE), currently under review at NSF, UNAVCO has proposed upgrading a significant portion of the ~1100 GPS stations that PBO currently operates to real-time high-rate capability to address community science and operational needs. In addition, in collaboration with NOAA, 74 of these stations will provide meteorological data in real-time, primarily to support watershed and flood analyses for regional early-warning systems related to NOAA's work with California Department of Water Resources. In preparation for this increased emphasis on high-rate GPS data, UNAVCO hosted an NSF funded workshop in Boulder, CO on March 26-28, 2012, which brought together 70 participants representing a spectrum of research fields with a goal to develop a community plan for the use of real-time GPS data products within the UNAVCO and EarthScope communities. These data products are expected to improve and expand the use of real-time, high-rate GPS data over the next decade.

  2. UNAVCO Geodetic HIgh-Rate and Real-Time Products and Services: A next generation geodetic network

    Science.gov (United States)

    Mattioli, G. S.; Mencin, D.; Meertens, C. M.; Feaux, K.; Looney, S.

    2012-12-01

    Recent advances in GPS technology and data processing are providing position estimates with centimeter-level precision at high-rate (1 Hz) and low latency (transforming rapid event characterization, early warning, as well as hazard mitigation and response. Other scientific and operational applications for high-rate GPS also include glacier and ice sheet motions, tropospheric modeling, and better constraints on the dynamics of space weather. UNAVCO, through community input and the recent Plate Boundary Observatory (PBO) NSF-ARRA Cascadia initiative, has nearly completed the process of upgrading a total of 373 PBO GPS sites to real-time high-rate capability and these streams are now being archived in our data center. In addition, UNAVCO hosted an NSF funded workshop in Boulder, CO on March 26-28, which brought together 70 participants representing a spectrum of research fields with a goal to develop a community plan for the use of real-time GPS data products within the UNAVCO and EarthScope communities. These data products are expected to improve and expand the use of real-time GPS data over the next decade. Additionally, in collaboration with NOAA, 74 of these stations will provide meteorological data in real-time, primarily to support watershed and flood analyses for regional early-warning systems related to NOAA's work with California Department of Water Resources. As part of this upgrade UNAVCO is also exploring making the 75 PBO borehole strainmeter sites, whose data are now collected with a latency of 24 hours, available in SEED format in real-time in the near future, providing an opportunity to combine high-rate surface positioning and strain data together.

  3. Real Time Revisited

    Science.gov (United States)

    Allen, Phillip G.

    1985-12-01

    The call for abolishing photo reconnaissance in favor of real time is once more being heard. Ten years ago the same cries were being heard with the introduction of the Charge Coupled Device (CCD). The real time system problems that existed then and stopped real time proliferation have not been solved. The lack of an organized program by either DoD or industry has hampered any efforts to solve the problems, and as such, very little has happened in real time in the last ten years. Real time is not a replacement for photo, just as photo is not a replacement for infra-red or radar. Operational real time sensors can be designed only after their role has been defined and improvements made to the weak links in the system. Plodding ahead on a real time reconnaissance suite without benefit of evaluation of utility will allow this same paper to be used ten years from now.

  4. Embedded XML DOM Parser: An Approach for XML Data Processing on Networked Embedded Systems with Real-Time Requirements

    Directory of Open Access Journals (Sweden)

    Cavia Soto MAngeles

    2008-01-01

    Full Text Available Abstract Trends in control and automation show an increase in data processing and communication in embedded automation controllers. The eXtensible Markup Language (XML is emerging as a dominant data syntax, fostering interoperability, yet little is still known about how to provide predictable real-time performance in XML processing, as required in the domain of industrial automation. This paper presents an XML processor that is designed with such real-time performance in mind. The publication attempts to disclose insight gained in applying techniques such as object pooling and reuse, and other methods targeted at avoiding dynamic memory allocation and its consequent memory fragmentation. Benchmarking tests are reported in order to illustrate the benefits of the approach.

  5. Orchestrating utility supply and demand in real-time via the Internet, home networks, and smart appliances

    Energy Technology Data Exchange (ETDEWEB)

    Cruickshank, R.F. III [Power Networks, Big Indian, NY (United States)

    2008-07-01

    This paper presented a model to illustrate the efficient coordination between the supply-side and demand-side of household electricity use and the magnitude of demand that can be managed using real-time pricing. In real-time supply and demand side management, a variable price for service is sent via Internet from the supply-side to the demand-side. The 3 benefits to this type of demand-side management are that traditional fossil-fuelled electrical capacity can operate less of the time and more efficiently; renewable electrical capacity such as wind and solar power can be put to use more efficiently when it becomes available; and additional means are available to protect the transmission and distribution infrastructure of the utility. A critical requirement is that pricing should change frequently throughout the day so that budget conscious consumers do not have to wait too long for favourable pricing to use their appliances. 12 refs., 9 figs.

  6. Estimation of stress distribution in ferromagnetic tensile specimens using low cost eddy current stress measurement system and BP neural network.

    Directory of Open Access Journals (Sweden)

    Jianwei Li

    Full Text Available Estimation of the stress distribution in ferromagnetic components is very important for evaluating the working status of mechanical equipment and implementing preventive maintenance. Eddy current testing technology is a promising method in this field because of its advantages of safety, no need of coupling agent, etc. In order to reduce the cost of eddy current stress measurement system, and obtain the stress distribution in ferromagnetic materials without scanning, a low cost eddy current stress measurement system based on Archimedes spiral planar coil was established, and a method based on BP neural network to obtain the stress distribution using the stress of several discrete test points was proposed. To verify the performance of the developed test system and the validity of the proposed method, experiment was implemented using structural steel (Q235 specimens. Standard curves of sensors at each test point were achieved, the calibrated data were used to establish the BP neural network model for approximating the stress variation on the specimen surface, and the stress distribution curve of the specimen was obtained by interpolating with the established model. The results show that there is a good linear relationship between the change of signal modulus and the stress in most elastic range of the specimen, and the established system can detect the change in stress with a theoretical average sensitivity of -0.4228 mV/MPa. The obtained stress distribution curve is well consonant with the theoretical analysis result. At last, possible causes and improving methods of problems appeared in the results were discussed. This research has important significance for reducing the cost of eddy current stress measurement system, and advancing the engineering application of eddy current stress testing.

  7. Estimation of stress distribution in ferromagnetic tensile specimens using low cost eddy current stress measurement system and BP neural network.

    Science.gov (United States)

    Li, Jianwei; Zhang, Weimin; Zeng, Weiqin; Chen, Guolong; Qiu, Zhongchao; Cao, Xinyuan; Gao, Xuanyi

    2017-01-01

    Estimation of the stress distribution in ferromagnetic components is very important for evaluating the working status of mechanical equipment and implementing preventive maintenance. Eddy current testing technology is a promising method in this field because of its advantages of safety, no need of coupling agent, etc. In order to reduce the cost of eddy current stress measurement system, and obtain the stress distribution in ferromagnetic materials without scanning, a low cost eddy current stress measurement system based on Archimedes spiral planar coil was established, and a method based on BP neural network to obtain the stress distribution using the stress of several discrete test points was proposed. To verify the performance of the developed test system and the validity of the proposed method, experiment was implemented using structural steel (Q235) specimens. Standard curves of sensors at each test point were achieved, the calibrated data were used to establish the BP neural network model for approximating the stress variation on the specimen surface, and the stress distribution curve of the specimen was obtained by interpolating with the established model. The results show that there is a good linear relationship between the change of signal modulus and the stress in most elastic range of the specimen, and the established system can detect the change in stress with a theoretical average sensitivity of -0.4228 mV/MPa. The obtained stress distribution curve is well consonant with the theoretical analysis result. At last, possible causes and improving methods of problems appeared in the results were discussed. This research has important significance for reducing the cost of eddy current stress measurement system, and advancing the engineering application of eddy current stress testing.

  8. Real Time Systems

    DEFF Research Database (Denmark)

    Christensen, Knud Smed

    2000-01-01

    Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems.......Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems....

  9. A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

    Science.gov (United States)

    Hossain, Moinul; Muromachi, Yasunori

    2012-03-01

    The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. Validation of low-cost ozone measurement instruments suitable for use in an air-quality monitoring network

    International Nuclear Information System (INIS)

    Williams, David E; Henshaw, Geoff S; Bart, Mark; Laing, Greer; Wagner, John; Naisbitt, Simon; Salmond, Jennifer A

    2013-01-01

    This paper presents a novel low-cost instrument that uses a sensor based on conductivity changes of heated tungstic oxide, which is capable of accurately measuring ambient concentrations of ozone. A combination of temperature steps and air flow-rate steps is used to continually reset and re-zero the sensor. A two-stage calibration procedure is presented, in which a nonlinear transformation converts sensor resistance to a signal linear in ozone concentration, then a linear correlation is used to align the calibration with a reference instrument. The required calibration functions specific for the sensor, and control system for air flow rate and sensor temperature, are housed with the sensor in a compact, simple-to-exchange assembly. The instrument can be operated on solar power and uses cell phone technology to enable monitoring in remote locations. Data from field trials are presented here to demonstrate that both the accuracy and the stability of the instrument over periods of months are within a few parts-per-billion by volume. We show that common failure modes can be detected through measurement of signals available from the instrument. The combination of long-term stability, self-diagnosis, and simple, inexpensive repair means that the cost of operation and calibration of the instruments is significantly reduced in comparison with traditional reference instrumentation. These instruments enable the economical construction and operation of ozone monitoring networks of accuracy, time resolution and spatial density sufficient to resolve the local gradients that are characteristic of urban air pollution. (paper)

  11. Embedded Artificial Neuval Network-Based Real-Time Half-Wave Dynamic Resistance Estimation during the A.C. Resistance Spot Welding Process

    Directory of Open Access Journals (Sweden)

    Liang Gong

    2013-01-01

    Full Text Available Online monitoring of the instantaneous resistance variation during the A.C. resistance spot welding is of paramount importance for the weld quality control. On the basis of the welding transformer circuit model, a new method is proposed to measure the transformer primary-side signal for estimating the secondary-side resistance in each 1/4 cycle. The tailored computing system ensures that the measuring method possesses a real-time computational capacity with satisfying accuracy. Since the dynamic resistance cannot be represented via an explicit function with respect to measurable parameters from the primary side of the welding transformer, an offline trained embedded artificial neural network (ANN successfully realizes the real-time implicit function calculation or estimation. A DSP-based resistance spot welding monitoring system is developed to perform ANN computation. Experimental results indicate that the proposed method is applicable for measuring the dynamic resistance in single-phase, half-wave controlled rectifier circuits.

  12. Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

    Science.gov (United States)

    Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

    2016-08-04

    Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

  13. Real-time shadows

    CERN Document Server

    Eisemann, Elmar; Assarsson, Ulf; Wimmer, Michael

    2011-01-01

    Important elements of games, movies, and other computer-generated content, shadows are crucial for enhancing realism and providing important visual cues. In recent years, there have been notable improvements in visual quality and speed, making high-quality realistic real-time shadows a reachable goal. Real-Time Shadows is a comprehensive guide to the theory and practice of real-time shadow techniques. It covers a large variety of different effects, including hard, soft, volumetric, and semi-transparent shadows.The book explains the basics as well as many advanced aspects related to the domain

  14. Real-time parallel processing of grammatical structure in the fronto-striatal system: a recurrent network simulation study using reservoir computing.

    Science.gov (United States)

    Hinaut, Xavier; Dominey, Peter Ford

    2013-01-01

    Sentence processing takes place in real-time. Previous words in the sentence can influence the processing of the current word in the timescale of hundreds of milliseconds. Recent neurophysiological studies in humans suggest that the fronto-striatal system (frontal cortex, and striatum--the major input locus of the basal ganglia) plays a crucial role in this process. The current research provides a possible explanation of how certain aspects of this real-time processing can occur, based on the dynamics of recurrent cortical networks, and plasticity in the cortico-striatal system. We simulate prefrontal area BA47 as a recurrent network that receives on-line input about word categories during sentence processing, with plastic connections between cortex and striatum. We exploit the homology between the cortico-striatal system and reservoir computing, where recurrent frontal cortical networks are the reservoir, and plastic cortico-striatal synapses are the readout. The system is trained on sentence-meaning pairs, where meaning is coded as activation in the striatum corresponding to the roles that different nouns and verbs play in the sentences. The model learns an extended set of grammatical constructions, and demonstrates the ability to generalize to novel constructions. It demonstrates how early in the sentence, a parallel set of predictions are made concerning the meaning, which are then confirmed or updated as the processing of the input sentence proceeds. It demonstrates how on-line responses to words are influenced by previous words in the sentence, and by previous sentences in the discourse, providing new insight into the neurophysiology of the P600 ERP scalp response to grammatical complexity. This demonstrates that a recurrent neural network can decode grammatical structure from sentences in real-time in order to generate a predictive representation of the meaning of the sentences. This can provide insight into the underlying mechanisms of human cortico

  15. Real-time communication protocols: an overview

    NARCIS (Netherlands)

    Hanssen, F.T.Y.; Jansen, P.G.

    2003-01-01

    This paper describes several existing data link layer protocols that provide real-time capabilities on wired networks, focusing on token-ring and Carrier Sense Multiple Access based networks. Existing modifications to provide better real-time capabilities and performance are also described. Finally

  16. Real time expert systems

    International Nuclear Information System (INIS)

    Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

    1992-01-01

    Recently, aiming at the application to the plant control for nuclear reactors and traffic and communication control, the research and the practical use of the expert system suitable to real time processing have become conspicuous. In this report, the condition for the required function to control the object that dynamically changes within a limited time is presented, and the technical difference between the real time expert system developed so as to satisfy it and the expert system of conventional type is explained with the actual examples and from theoretical aspect. The expert system of conventional type has the technical base in the problem-solving equipment originating in STRIPS. The real time expert system is applied to the fields accompanied by surveillance and control, to which conventional expert system is hard to be applied. The requirement for the real time expert system, the example of the real time expert system, and as the techniques of realizing real time processing, the realization of interruption processing, dispersion processing, and the mechanism of maintaining the consistency of knowledge are explained. (K.I.)

  17. Real time recording system of radioisotopes by local area network (LAN) computer system and user input processing

    International Nuclear Information System (INIS)

    Shinohara, Kunio; Ito, Atsushi; Kawaguchi, Hajime; Yanase, Makoto; Uno, Kiyoshi.

    1991-01-01

    A computer-assisted real time recording system was developed for management of radioisotopes. The system composed of two personal computers forming LAN, identification-card (ID-card) reader, and electricity-operating door-lock. One computer is operated by radiation safety staffs and stores the records of radioisotopes. The users of radioisotopes are registered in this computer. Another computer is installed in front of the storage room for radioisotopes. This computer is ready for operation by a registered ID-card and is input data by the user. After the completion of data input, the door to the storage room is unlocked. The present system enables us the following merits: Radiation safety staffs can easily keep up with the present states of radioisotopes in the storage room and save much labor. Radioactivity is always corrected. The upper limit of radioactivities in use per day is automatically checked and users are regulated when they input the amounts to be used. Users can obtain storage records of radioisotopes any time. In addition, the system is applicable to facilities which have more than two storage rooms. (author)

  18. Real-time radiography

    International Nuclear Information System (INIS)

    Bossi, R.H.; Oien, C.T.

    1981-01-01

    Real-time radiography is used for imaging both dynamic events and static objects. Fluorescent screens play an important role in converting radiation to light, which is then observed directly or intensified and detected. The radiographic parameters for real-time radiography are similar to conventional film radiography with special emphasis on statistics and magnification. Direct-viewing fluoroscopy uses the human eye as a detector of fluorescent screen light or the light from an intensifier. Remote-viewing systems replace the human observer with a television camera. The remote-viewing systems have many advantages over the direct-viewing conditions such as safety, image enhancement, and the capability to produce permanent records. This report reviews real-time imaging system parameters and components

  19. Graduation Report : Directional relay coordination in ungrounded medium voltage networks using a real-time digital simulator

    NARCIS (Netherlands)

    Van der Meer, A.A.

    2009-01-01

    The thesis describes a comprehensive protection relay coordination study in ungrounded 10 kV distribution networks. Until now, single phase-toground faults (also: earth-faults) were never interrupted because resulting fault currents were relatively small. Since the earth-fault current amplitude is

  20. Using YOLO based deep learning network for real time detection and localization of lung nodules from low dose CT scans

    Science.gov (United States)

    Ramachandran S., Sindhu; George, Jose; Skaria, Shibon; V. V., Varun

    2018-02-01

    Lung cancer is the leading cause of cancer related deaths in the world. The survival rate can be improved if the presence of lung nodules are detected early. This has also led to more focus being given to computer aided detection (CAD) and diagnosis of lung nodules. The arbitrariness of shape, size and texture of lung nodules is a challenge to be faced when developing these detection systems. In the proposed work we use convolutional neural networks to learn the features for nodule detection, replacing the traditional method of handcrafting features like geometric shape or texture. Our network uses the DetectNet architecture based on YOLO (You Only Look Once) to detect the nodules in CT scans of lung. In this architecture, object detection is treated as a regression problem with a single convolutional network simultaneously predicting multiple bounding boxes and class probabilities for those boxes. By performing training using chest CT scans from Lung Image Database Consortium (LIDC), NVIDIA DIGITS and Caffe deep learning framework, we show that nodule detection using this single neural network can result in reasonably low false positive rates with high sensitivity and precision.

  1. D-MHR: A Distributed Management Scheme for Hybrid Networks to Provide Real-time Industrial Wireless Automation

    NARCIS (Netherlands)

    Zand, P.; Das, Kallol; Mathews, E.; Havinga, Paul J.M.

    Current wireless technologies for industrial application, such as WirelessHART and ISA100.11a, use a centralized management approach which makes it difficult and costly for harvester-powered I/O devices to re-join the network in case of power failure. The communication overhead and delay to cope

  2. A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi'an, China

    International Nuclear Information System (INIS)

    Gao, Meiling; Cao, Junji; Seto, Edmund

    2015-01-01

    Fine particulate matter (PM2.5) is a growing public health concern especially in industrializing countries but existing monitoring networks are unable to properly characterize human exposures due to low resolution spatiotemporal data. Low-cost portable monitors can supplement existing networks in both developed and industrializing regions to increase density of sites and data. This study tests the performance of a low-cost sensor in high concentration urban environments. Seven Portable University of Washington Particle (PUWP) monitors were calibrated with optical and gravimetric PM2.5 reference monitors in Xi'an, China in December 2013. Pairwise correlations between the raw PUWP and the reference monitors were high (R 2  = 0.86–0.89). PUWP monitors were also simultaneously deployed at eight sites across Xi'an alongside gravimetric PM2.5 monitors (R 2  = 0.53). The PUWP monitors were able to identify the High-technology Zone site as a potential PM2.5 hotspot with sustained high concentrations compared to the city average throughout the day. - Highlights: • A $15 portable PM sensor demonstrated high correlations with reference monitors. • The sensor can be deployed in high PM2.5 urban environments. • The sensor can improve spatiotemporal resolution of data from existing monitoring networks. - This reliable low-cost portable PM sensor could help improve monitoring and management of urban air pollution to help protect public health in both developed and developing areas

  3. Real-time monitoring and control of the oil pipeline networks; Monitoramento e controle inteligentes e em tempo real de redes de escoamento de petroleo

    Energy Technology Data Exchange (ETDEWEB)

    Brasileiro, F.; Galvao, C.; Brasileiro, E.; Catao, B.; Souto, C.; Machado, E.; Muniz, M.; Souza, A.; Gomes, A. [Universidade Federal de Campina Grande, PB (Brazil)]. E-mail: fubica@dsc.ufcg.edu.br; Aloise, D. [Universidade Federal do Rio Grande do Norte, Natal, RN (Brazil); Oliveira, A.; Gomes, C.; Rolim, T.; Boquimpani, C. [PETROBRAS S.A. (Brazil)

    2003-07-01

    Real-time monitoring and control of complex and large-scale oil pipeline networks is complicated by several requirements, among them: reliability of data acquisition and communication systems; strict time limits between data acquisition and decision of control action; operational constraints of a large number of pipeline devices and multi-objective control, involving economic, operational, environmental and institutional objectives and constraints. The MDTP system was designed for meeting such requirements. A simulation-optimization approach is the strategy adopted for the network state prediction and control. The simulation module is based on the quasi-steady state hydraulics of oil-water flow. The control is centered on the pumping systems, respecting operational constraints of tanks and pipes, without reducing the oil production targets. For real-time control, an optimization scheme generates multiple operational scenarios, the optimum of them being selected by means of a meta-heuristics approach. To meet the strict time limits for deciding the control strategy, a grid computing architecture was adopted, instead of conventional dedicated high-performance computers. (author)

  4. Optical chaos and hybrid WDM/TDM based large capacity quasi-distributed sensing network with real-time fiber fault monitoring.

    Science.gov (United States)

    Luo, Yiyang; Xia, Li; Xu, Zhilin; Yu, Can; Sun, Qizhen; Li, Wei; Huang, Di; Liu, Deming

    2015-02-09

    An optical chaos and hybrid wavelength division multiplexing/time division multiplexing (WDM/TDM) based large capacity quasi-distributed sensing network with real-time fiber fault monitoring is proposed. Chirped fiber Bragg grating (CFBG) intensity demodulation is adopted to improve the dynamic range of the measurements. Compared with the traditional sensing interrogation methods in time, radio frequency and optical wavelength domains, the measurand sensing and the precise locating of the proposed sensing network can be simultaneously interrogated by the relative amplitude change (RAC) and the time delay of the correlation peak in the cross-correlation spectrum. Assisted with the WDM/TDM technology, hundreds of sensing units could be potentially multiplexed in the multiple sensing fiber lines. Based on the proof-of-concept experiment for axial strain measurement with three sensing fiber lines, the strain sensitivity up to 0.14% RAC/με and the precise locating of the sensors are achieved. Significantly, real-time fiber fault monitoring in the three sensing fiber lines is also implemented with a spatial resolution of 2.8 cm.

  5. THE ORIGINS OF THE CASHLESS SOCIETY: CASH DISPENSERS, DIRECT TO ACCOUNT PAYMENTS AND THE DEVELOPMENT OF ON-LINE REAL-TIME NETWORKS, C.1965-1985

    Directory of Open Access Journals (Sweden)

    Bernardo Bátiz-Lazo

    2014-07-01

    Full Text Available This article explores the technological choices made at the dawn of the massification of retail finance. We describe and analyze the early development of electronic banking and the foundations of the cashless society through the experiences of organizations with similar governance in two different competitive environments — Swedish and British savings banks. We document how the adoption of direct-to-account wage deposits and the subsequent deployment of networks of cash dispensers interacted with the adoption of on-line real-time (OLRT computing, and distinguish on- line and OLRT communication as distinct stages in the evolution of computer networks. We emphasize the role of middle managers in the selection of alternative technologies and show how delivering a cashless society proved more difficult than anticipated.

  6. Enabling Real-Time Video Services over Ad-Hoc Networks Opens the Gates for E-learning in Areas Lacking Infrastructure

    Directory of Open Access Journals (Sweden)

    Johannes Karlsson

    2009-10-01

    Full Text Available In this paper we suggest a promising solution to come over the problems of delivering e-learning to areas with lack or deficiencies in infrastructure for Internet and mobile communication. We present a simple, reasonably priced and efficient communication platform for providing e-learning. This platform is based on wireless ad-hoc networks. We also present a preemptive routing protocol suitable for real-time video communication over wireless ad-hoc networks. Our results show that this routing protocol can significantly improve the quality of the received video. This makes our suggested system not only good to overcome the infrastructure barrier but even capable of delivering a high quality e-learning material.

  7. An Implementation of Parallel and Networked Computing Schemes for the Real-Time Image Reconstruction Based on Electrical Tomography

    International Nuclear Information System (INIS)

    Park, Sook Hee

    2001-02-01

    This thesis implements and analyzes the parallel and networked computing libraries based on the multiprocessor computer architecture as well as networked computers, aiming at improving the computation speed of ET(Electrical Tomography) system which requires enormous CPU time in reconstructing the unknown internal state of the target object. As an instance of the typical tomography technology, ET partitions the cross-section of the target object into the tiny elements and calculates the resistivity of them with signal values measured at the boundary electrodes surrounding the surface of the object after injecting the predetermined current pattern through the object. The number of elements is determined considering the trade-off between the accuracy of the reconstructed image and the computation time. As the elements become more finer, the number of element increases, and the system can get the better image. However, the reconstruction time increases polynomially with the number of partitioned elements since the procedure consists of a number of time consuming matrix operations such as multiplication, inverse, pseudo inverse, Jacobian and so on. Consequently, the demand for improving computation speed via multiple processor grows indispensably. Moreover, currently released PCs can be stuffed with up to 4 CPUs interconnected to the shared memory while some operating systems enable the application process to benefit from such computer by allocating the threaded job to each CPU, resulting in concurrent processing. In addition, a networked computing or cluster computing environment is commonly available to almost every computer which contains communication protocol and is connected to local or global network. After partitioning the given job(numerical operation), each CPU or computer calculates the partial result independently, and the results are merged via common memory to produce the final result. It is desirable to adopt the commonly used library such as Matlab to

  8. Cross-layer protocol design for QoS optimization in real-time wireless sensor networks

    Science.gov (United States)

    Hortos, William S.

    2010-04-01

    The metrics of quality of service (QoS) for each sensor type in a wireless sensor network can be associated with metrics for multimedia that describe the quality of fused information, e.g., throughput, delay, jitter, packet error rate, information correlation, etc. These QoS metrics are typically set at the highest, or application, layer of the protocol stack to ensure that performance requirements for each type of sensor data are satisfied. Application-layer metrics, in turn, depend on the support of the lower protocol layers: session, transport, network, data link (MAC), and physical. The dependencies of the QoS metrics on the performance of the higher layers of the Open System Interconnection (OSI) reference model of the WSN protocol, together with that of the lower three layers, are the basis for a comprehensive approach to QoS optimization for multiple sensor types in a general WSN model. The cross-layer design accounts for the distributed power consumption along energy-constrained routes and their constituent nodes. Following the author's previous work, the cross-layer interactions in the WSN protocol are represented by a set of concatenated protocol parameters and enabling resource levels. The "best" cross-layer designs to achieve optimal QoS are established by applying the general theory of martingale representations to the parameterized multivariate point processes (MVPPs) for discrete random events occurring in the WSN. Adaptive control of network behavior through the cross-layer design is realized through the parametric factorization of the stochastic conditional rates of the MVPPs. The cross-layer protocol parameters for optimal QoS are determined in terms of solutions to stochastic dynamic programming conditions derived from models of transient flows for heterogeneous sensor data and aggregate information over a finite time horizon. Markov state processes, embedded within the complex combinatorial history of WSN events, are more computationally

  9. Image processing with cellular nonlinear networks implemented on field-programmable gate arrays for real-time applications in nuclear fusion

    International Nuclear Information System (INIS)

    Palazzo, S.; Vagliasindi, G.; Arena, P.; Murari, A.; Mazon, D.; De Maack, A.

    2010-01-01

    In the past years cameras have become increasingly common tools in scientific applications. They are now quite systematically used in magnetic confinement fusion, to the point that infrared imaging is starting to be used systematically for real-time machine protection in major devices. However, in order to guarantee that the control system can always react rapidly in case of critical situations, the time required for the processing of the images must be as predictable as possible. The approach described in this paper combines the new computational paradigm of cellular nonlinear networks (CNNs) with field-programmable gate arrays and has been tested in an application for the detection of hot spots on the plasma facing components in JET. The developed system is able to perform real-time hot spot recognition, by processing the image stream captured by JET wide angle infrared camera, with the guarantee that computational time is constant and deterministic. The statistical results obtained from a quite extensive set of examples show that this solution approximates very well an ad hoc serial software algorithm, with no false or missed alarms and an almost perfect overlapping of alarm intervals. The computational time can be reduced to a millisecond time scale for 8 bit 496x560-sized images. Moreover, in our implementation, the computational time, besides being deterministic, is practically independent of the number of iterations performed by the CNN - unlike software CNN implementations.

  10. Improvements of Real Time First Motion Focal Mechanism and Noise Characteristics of New Sites at the Puerto Rico Seismic Network

    Science.gov (United States)

    Williams, D. M.; Lopez, A. M.; Huerfano, V.; Lugo, J.; Cancel, J.

    2011-12-01

    Seismic networks need quick and efficient ways to obtain information related to seismic events for the purposes of seismic activity monitoring, risk assessment, and scientific knowledge among others. As part of an IRIS summer internship program, two projects were performed to provide a tool for quick faulting mechanism and improve seismic data at the Puerto Rico Seismic Network (PRSN). First, a simple routine to obtain a focal mechanisms, the geometry of the fault, based on first motions was developed and implemented for data analysts routine operations at PRSN. The new tool provides the analyst a quick way to assess the probable faulting mechanism that occurred while performing the interactive earthquake location procedure. The focal mechanism is generated on-the-fly when data analysts pick P wave arrivals onsets and motions. Once first motions have been identified, an in-house PRSN utility is employed to obtain the double couple representation and later plotted using GMT's psmeca utility. Second, we addressed the issue of seismic noise related to thermal fluctuations inside seismic vaults. Seismic sites can be extremely noisy due to proximity to cultural activities and unattended thermal fluctuations inside sensor housings, thus resulting in skewed readings. In the past, seismologists have used different insulation techniques to reduce the amount of unwanted noise that a seismometers experience due to these thermal changes with items such as Styrofoam, and fiber glass among others. PRSN traditionally uses Styrofoam boxes to cover their seismic sensors, however, a proper procedure to test how these method compare to other new techniques has never been approached. The deficiency of properly testing these techniques in the Caribbean and especially Puerto Rico is that these thermal fluctuations still happen because of the intense sun and humidity. We conducted a test based on the methods employed by the IRIS Transportable Array, based on insulation by sand burial of

  11. Route around real time

    International Nuclear Information System (INIS)

    Terrier, Francois

    1996-01-01

    The greater and greater autonomy and complexity asked to the control and command systems lead to work on introducing techniques such as Artificial Intelligence or concurrent object programming in industrial applications. However, while the critical feature of these systems impose to control the dynamics of the proposed solutions, their complexity often imposes a high adaptability to a partially modelled environment. The studies presented start from low level control and command systems to more complex applications at higher levels, such as 'supervision systems'. Techniques such as temporal reasoning and uncertainty management are proposed for the first studies, while the second are tackled with programming techniques based on the real time object paradigm. The outcomes of this itinerary crystallize on the ACCORD project which targets to manage - on the whole life cycle of a real time application - these two problematics, sometimes antagonistic: control of the dynamics and adaptivity. (author) [fr

  12. A Wireless Sensor Network for the Real-Time Remote Measurement of Aeolian Sand Transport on Sandy Beaches and Dunes.

    Science.gov (United States)

    Pozzebon, Alessandro; Cappelli, Irene; Mecocci, Alessandro; Bertoni, Duccio; Sarti, Giovanni; Alquini, Fernanda

    2018-03-08

    Direct measurements of aeolian sand transport on coastal dunes and beaches is of paramount importance to make correct decisions about coast management. As most of the existing studies are mainly based on a statistical approach, the solution presented in this paper proposes a sensing structure able to orient itself according to wind direction and directly calculate the amount of wind-transported sand by collecting it and by measuring its weight. Measurements are performed remotely without requiring human action because the structure is equipped with a ZigBee radio module, which periodically sends readings to a local gateway. Here data are processed by a microcontroller and then transferred to a remote data collection centre, through GSM technology. The ease of installation, the reduced power consumption and the low maintenance required, make the proposed solution able to work independently, limiting human intervention, for all the duration of the expected experimental campaign. In order to analyze the cause-effect relationship between the transported sand and the wind, the sensing structure is integrated with a multi-layer anemoscope-anemometer structure. The overall sensor network has been developed and tested in the laboratory, and its operation has been validated in field through a 48 h measurement campaign.

  13. A Real-Time Construction Safety Monitoring System for Hazardous Gas Integrating Wireless Sensor Network and Building Information Modeling Technologies.

    Science.gov (United States)

    Cheung, Weng-Fong; Lin, Tzu-Hsuan; Lin, Yu-Cheng

    2018-02-02

    In recent years, many studies have focused on the application of advanced technology as a way to improve management of construction safety management. A Wireless Sensor Network (WSN), one of the key technologies in Internet of Things (IoT) development, enables objects and devices to sense and communicate environmental conditions; Building Information Modeling (BIM), a revolutionary technology in construction, integrates database and geometry into a digital model which provides a visualized way in all construction lifecycle management. This paper integrates BIM and WSN into a unique system which enables the construction site to visually monitor the safety status via a spatial, colored interface and remove any hazardous gas automatically. Many wireless sensor nodes were placed on an underground construction site and to collect hazardous gas level and environmental condition (temperature and humidity) data, and in any region where an abnormal status is detected, the BIM model will alert the region and an alarm and ventilator on site will start automatically for warning and removing the hazard. The proposed system can greatly enhance the efficiency in construction safety management and provide an important reference information in rescue tasks. Finally, a case study demonstrates the applicability of the proposed system and the practical benefits, limitations, conclusions, and suggestions are summarized for further applications.

  14. Optimizing Transmission and Shutdown for Energy-Efficient Real-time Packet Scheduling in Clustered Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Rajkumar Ragunathan

    2005-01-01

    Full Text Available Energy efficiency is imperative to enable the deployment of ad hoc networks. Conventional power management focuses independently on the physical or MAC layer and approaches differ depending on the abstraction level. At the physical layer, the fundamental tradeoff between transmission rate and energy is exploited, which leads to transmit as slow as possible. At MAC level, power reduction techniques aim to transmit as fast as possible to maximize the radios power-off interval. The two approaches seem conflicting and it is not obvious which one is the most appropriate. We propose a transmission strategy that optimally mixes both techniques in a multiuser context. We present a cross-layer solution considering the transceiver power characteristics, the varying system load, and the dynamic channel constraints. Based on this, we derive a low-complexity online scheduling algorithm. Results considering an -ary quadrature amplitude modulation radio show that for a range of scenarios a large power reduction is achieved, compared to the case where only scaling or shutdown is considered.

  15. A Wireless Sensor Network for the Real-Time Remote Measurement of Aeolian Sand Transport on Sandy Beaches and Dunes

    Science.gov (United States)

    Cappelli, Irene; Mecocci, Alessandro; Alquini, Fernanda

    2018-01-01

    Direct measurements of aeolian sand transport on coastal dunes and beaches is of paramount importance to make correct decisions about coast management. As most of the existing studies are mainly based on a statistical approach, the solution presented in this paper proposes a sensing structure able to orient itself according to wind direction and directly calculate the amount of wind-transported sand by collecting it and by measuring its weight. Measurements are performed remotely without requiring human action because the structure is equipped with a ZigBee radio module, which periodically sends readings to a local gateway. Here data are processed by a microcontroller and then transferred to a remote data collection centre, through GSM technology. The ease of installation, the reduced power consumption and the low maintenance required, make the proposed solution able to work independently, limiting human intervention, for all the duration of the expected experimental campaign. In order to analyze the cause-effect relationship between the transported sand and the wind, the sensing structure is integrated with a multi-layer anemoscope-anemometer structure. The overall sensor network has been developed and tested in the laboratory, and its operation has been validated in field through a 48 h measurement campaign. PMID:29518060

  16. Real time falling leaves

    OpenAIRE

    Vázquez Alcocer, Pere Pau; Balsa, Marcos

    2007-01-01

    There is a growing interest in simulating natural phenomena in computer graphics applications. Animating natural scenes in real time is one of the most challenging problems due to the inherent complexity of their structure, formed by millions of geometric entities, and the interactions that happen within. An example of natural scenario that is needed for games or simulation programs are forests. Forests are difficult to render because the huge amount of geometric entities and the large amount...

  17. Real Time Strategy Language

    OpenAIRE

    Hayes, Roy; Beling, Peter; Scherer, William

    2014-01-01

    Real Time Strategy (RTS) games provide complex domain to test the latest artificial intelligence (AI) research. In much of the literature, AI systems have been limited to playing one game. Although, this specialization has resulted in stronger AI gaming systems it does not address the key concerns of AI researcher. AI researchers seek the development of AI agents that can autonomously interpret learn, and apply new knowledge. To achieve human level performance, current AI systems rely on game...

  18. Real Time Processing

    CERN Multimedia

    CERN. Geneva; ANDERSON, Dustin James; DOGLIONI, Caterina

    2015-01-01

    The LHC provides experiments with an unprecedented amount of data. Experimental collaborations need to meet storage and computing requirements for the analysis of this data: this is often a limiting factor in the physics program that would be achievable if the whole dataset could be analysed. In this talk, I will describe the strategies adopted by the LHCb, CMS and ATLAS collaborations to overcome these limitations and make the most of LHC data: data parking, data scouting, and real-time analysis.

  19. Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks

    Directory of Open Access Journals (Sweden)

    Reinhold Decker

    2014-11-01

    Full Text Available In the recent past, the quantitative analysis of online product reviews (OPRs has become a popular manifestation of marketing intelligence activities focusing on products that are frequently subject to electronic word-of-mouth (eWOM. Typical elements of OPRs are overall star ratings, product at- tribute scores, recommendations, pros and cons, and free texts. The first three elements are of pa r- ticular interest because they provide an aggregate view of reviewers’ opinions about the products of interest. However, the significance of individual product attributes in the overall evaluation pro c- ess  can  vary  in  the  course  of  time.  Accordingly,  ad  hoc  analyses  of  OPRs  that  have  been downloaded at a certain point in time are of limited value for dynamic eWOM monitoring because of their snapshot character. On the other hand, opinion platforms can increase the meaningfulness of the OPRs posted there and, therewith, the usefulness of the platform as a whole, by directing eWOM activities to those product attributes that really matter at present. This paper therefore in- troduces a neural network-based approach that allows the dynamic tracking of the influence the posted scores of product attributes have on the overall star ratings of the concerning products. By using an elasticity measure, this approach supports the identification of those attributes that tend to lose or gain significance in the product evaluation process over time. The usability of this ap- proach is demonstrated using real OPR data on digital cameras and hotels.

  20. Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces

    Science.gov (United States)

    Dethier, Julie; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.; Boahen, Kwabena

    2013-06-01

    Objective. Cortically-controlled motor prostheses aim to restore functions lost to neurological disease and injury. Several proof of concept demonstrations have shown encouraging results, but barriers to clinical translation still remain. In particular, intracortical prostheses must satisfy stringent power dissipation constraints so as not to damage cortex. Approach. One possible solution is to use ultra-low power neuromorphic chips to decode neural signals for these intracortical implants. The first step is to explore in simulation the feasibility of translating decoding algorithms for brain-machine interface (BMI) applications into spiking neural networks (SNNs). Main results. Here we demonstrate the validity of the approach by implementing an existing Kalman-filter-based decoder in a simulated SNN using the Neural Engineering Framework (NEF), a general method for mapping control algorithms onto SNNs. To measure this system’s robustness and generalization, we tested it online in closed-loop BMI experiments with two rhesus monkeys. Across both monkeys, a Kalman filter implemented using a 2000-neuron SNN has comparable performance to that of a Kalman filter implemented using standard floating point techniques. Significance. These results demonstrate the tractability of SNN implementations of statistical signal processing algorithms on different monkeys and for several tasks, suggesting that a SNN decoder, implemented on a neuromorphic chip, may be a feasible computational platform for low-power fully-implanted prostheses. The validation of this closed-loop decoder system and the demonstration of its robustness and generalization hold promise for SNN implementations on an ultra-low power neuromorphic chip using the NEF.

  1. Development of a Real-Time Thermal Performance Diagnostic Monitoring system Using Self-Organizing Neural Network for Kori-2 Nuclear Power Unit

    International Nuclear Information System (INIS)

    Kang, Hyun Gook; Seong, Poong Hyun

    1996-01-01

    In this work, a PC-based thermal performance monitoring system is developed for the nuclear power plants. the system performs real-time thermal performance monitoring and diagnosis during plant operation. Specifically, a prototype for the Kori-2 nuclear power unit is developed and examined is very difficult because the system structure is highly complex and the components are very much inter-related. In this study, some major diagnostic performance parameters are selected in order to represent the thermal cycle effectively and to reduce the computing time. The Fuzzy ARTMAP, a self-organizing neural network, is used to recognize the characteristic pattern change of the performance parameters in abnormal situation. By examination, the algorithm is shown to be ale to detect abnormality and to identify the fault component or the change of system operation condition successfully. For the convenience of operators, a graphical user interface is also constructed in this work. 5 figs., 3 tabs., 11 refs. (Author)

  2. A Low Cost Bluetooth Low Energy Transceiver for Wireless Sensor Network Applications with a Front-end Receiver-Matching Network-Reusing Power Amplifier Load Inductor.

    Science.gov (United States)

    Liang, Zhen; Li, Bin; Huang, Mo; Zheng, Yanqi; Ye, Hui; Xu, Ken; Deng, Fangming

    2017-04-19

    In this work, a low cost Bluetooth Low Energy (BLE) transceiver for wireless sensor network (WSN) applications, with a receiver (RX)-matching network-reusing power amplifier (PA) load inductor, is presented. In order to decrease the die area, only two inductors were used in this work. Besides the one used in the voltage control oscillator (VCO), the PA load inductor was reused as the RX impedance matching component in the front-end. Proper controls have been applied to achieve high transmitter (TX) input impedance when the transceiver is in the receiving mode, and vice versa. This allows the TRX-switch/matching network integration without significant performance degradation. The RX adopted a low-IF structure and integrated a single-ended low noise amplifier (LNA), a current bleeding mixer, a 4th complex filter and a delta-sigma continuous time (CT) analog-to-digital converter (ADC). The TX employed a two-point PLL-based architecture with a non-linear PA. The RX achieved a sensitivity of -93 dBm and consumes 9.7 mW, while the TX achieved a 2.97% error vector magnitude (EVM) with 9.4 mW at 0 dBm output power. This design was fabricated in a 0.11 μm complementary metal oxide semiconductor (CMOS) technology and the front-end circuit only occupies 0.24 mm². The measurement results verify the effectiveness and applicability of the proposed BLE transceiver for WSN applications.

  3. Real-time specifications

    DEFF Research Database (Denmark)

    David, A.; Larsen, K.G.; Legay, A.

    2015-01-01

    A specification theory combines notions of specifications and implementations with a satisfaction relation, a refinement relation, and a set of operators supporting stepwise design. We develop a specification framework for real-time systems using Timed I/O Automata as the specification formalism......, with the semantics expressed in terms of Timed I/O Transition Systems. We provide constructs for refinement, consistency checking, logical and structural composition, and quotient of specifications-all indispensable ingredients of a compositional design methodology. The theory is implemented in the new tool Ecdar...

  4. Real Time Text Analysis

    Science.gov (United States)

    Senthilkumar, K.; Ruchika Mehra Vijayan, E.

    2017-11-01

    This paper aims to illustrate real time analysis of large scale data. For practical implementation we are performing sentiment analysis on live Twitter feeds for each individual tweet. To analyze sentiments we will train our data model on sentiWordNet, a polarity assigned wordNet sample by Princeton University. Our main objective will be to efficiency analyze large scale data on the fly using distributed computation. Apache Spark and Apache Hadoop eco system is used as distributed computation platform with Java as development language

  5. Real time Faraday spectrometer

    Science.gov (United States)

    Smith, Jr., Tommy E.; Struve, Kenneth W.; Colella, Nicholas J.

    1991-01-01

    This invention uses a dipole magnet to bend the path of a charged particle beam. As the deflected particles exit the magnet, they are spatially dispersed in the bend-plane of the magnet according to their respective momenta and pass to a plurality of chambers having Faraday probes positioned therein. Both the current and energy distribution of the particles is then determined by the non-intersecting Faraday probes located along the chambers. The Faraday probes are magnetically isolated from each other by thin metal walls of the chambers, effectively providing real time current-versus-energy particle measurements.

  6. Real time Faraday spectrometer

    International Nuclear Information System (INIS)

    Smith, T.E.; Struve, K.W.; Colella, N.J.

    1991-01-01

    This patent describes an invention which uses a dipole magnet to bend the path of a charged particle beam. As the deflected particles exit the magnet, they are spatially dispersed in the bend-plane of the magnet according to their respective momenta and pass to a plurality of chambers having Faraday probes positioned therein. Both the current and energy distribution of the particles is then determined by the non-intersecting Faraday probes located along the chambers. The Faraday probes are magnetically isolated from each other by thin metal walls of the chambers, effectively providing real time current-versus-energy particle measurements

  7. Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

    Science.gov (United States)

    Adams, Matthew D; Kanaroglou, Pavlos S

    2016-03-01

    Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved

  8. Hourly Comparison of GPM-IMERG-Final-Run and IMERG-Real-Time (V-03) over a Dense Surface Network in Northeastern Austria

    Science.gov (United States)

    Sharifi, Ehsan; Steinacker, Reinhold; Saghafian, Bahram

    2017-04-01

    Accurate quantitative daily precipitation estimation is key to meteorological and hydrological applications in hazards forecast and management. In-situ observations over mountainous areas are mostly limited, however, currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. Over the years, blended methods that use multi-satellites and multi-sensors have been developed for estimating of global precipitation. One of the latest satellite precipitation products is GPM-IMERG (Global Precipitation Measurement with 30-minute temporal and 0.1-degree spatial resolutions) which consists of three products: Final-Run (aimed for research), Real-Time early run, and Real-Time late run. The Integrated Multisatellite Retrievals for GPM (IMERG) products built upon the success of TRMM's Multisatellite Precipitation Analysis (TMPA) products continue to make improvements in spatial and temporal resolutions and snowfall estimates. Recently, researchers who evaluated IMERG-Final-Run V-03 and other precipitation products indicated better performance for IMERG-Final-Run against other similar products. In this study two GPM-IMERG products, namely final run and real time-late run, were evaluated against a dense synoptic stations network (62 stations) over Northeastern Austria for mid-March 2015 to end of January 2016 period at hourly time-scale. Both products were examined against the reference data (stations) in capturing the occurrence of precipitation and statistical characteristics of precipitation intensity. Both satellite precipitation products underestimated precipitation events of 0.1 mm/hr to 0.4 mm/hr in intensity. For precipitations 0.4 mm/hr and greater, the trend was reversed and both satellite products overestimated than station recorded data. IMERG-RT outperformed IMERG-FR for precipitation intensity in the range of 0.1 mm/hr to 0.4 mm/hr while in the range of 1.1 to 1.8 mm

  9. Real-time estimation of lesion depth and control of radiofrequency ablation within ex vivo animal tissues using a neural network.

    Science.gov (United States)

    Wang, Yearnchee Curtis; Chan, Terence Chee-Hung; Sahakian, Alan Varteres

    2018-01-04

    Radiofrequency ablation (RFA), a method of inducing thermal ablation (cell death), is often used to destroy tumours or potentially cancerous tissue. Current techniques for RFA estimation (electrical impedance tomography, Nakagami ultrasound, etc.) require long compute times (≥ 2 s) and measurement devices other than the RFA device. This study aims to determine if a neural network (NN) can estimate ablation lesion depth for control of bipolar RFA using complex electrical impedance - since tissue electrical conductivity varies as a function of tissue temperature - in real time using only the RFA therapy device's electrodes. Three-dimensional, cubic models comprised of beef liver, pork loin or pork belly represented target tissue. Temperature and complex electrical impedance from 72 data generation ablations in pork loin and belly were used for training the NN (403 s on Xeon processor). NN inputs were inquiry depth, starting complex impedance and current complex impedance. Training-validation-test splits were 70%-0%-30% and 80%-10%-10% (overfit test). Once the NN-estimated lesion depth for a margin reached the target lesion depth, RFA was stopped for that margin of tissue. The NN trained to 93% accuracy and an NN-integrated control ablated tissue to within 1.0 mm of the target lesion depth on average. Full 15-mm depth maps were calculated in 0.2 s on a single-core ARMv7 processor. The results show that a NN could make lesion depth estimations in real-time using less in situ devices than current techniques. With the NN-based technique, physicians could deliver quicker and more precise ablation therapy.

  10. Low Cost Benefit Suggestions.

    Science.gov (United States)

    Doyel, Hoyt W.; McMillan, John D.

    1980-01-01

    Outlines eight low-cost employee benefits and summarizes their relative advantages. The eight include a stock ownership program, a sick leave pool, flexible working hours, production incentives, and group purchase plans. (IRT)

  11. Homogeneous and Heterogeneous MPSoC Architectures with Network-On-Chip Connectivity for Low-Power and Real-Time Multimedia Signal Processing

    Directory of Open Access Journals (Sweden)

    Sergio Saponara

    2012-01-01

    Full Text Available Two multiprocessor system-on-chip (MPSoC architectures are proposed and compared in the paper with reference to audio and video processing applications. One architecture exploits a homogeneous topology; it consists of 8 identical tiles, each made of a 32-bit RISC core enhanced by a 64-bit DSP coprocessor with local memory. The other MPSoC architecture exploits a heterogeneous-tile topology with on-chip distributed memory resources; the tiles act as application specific processors supporting a different class of algorithms. In both architectures, the multiple tiles are interconnected by a network-on-chip (NoC infrastructure, through network interfaces and routers, which allows parallel operations of the multiple tiles. The functional performances and the implementation complexity of the NoC-based MPSoC architectures are assessed by synthesis results in submicron CMOS technology. Among the large set of supported algorithms, two case studies are considered: the real-time implementation of an H.264/MPEG AVC video codec and of a low-distortion digital audio amplifier. The heterogeneous architecture ensures a higher power efficiency and a smaller area occupation and is more suited for low-power multimedia processing, such as in mobile devices. The homogeneous scheme allows for a higher flexibility and easier system scalability and is more suited for general-purpose DSP tasks in power-supplied devices.

  12. Experience with low-cost telemedicine in three different settings. Recommendations based on a proposed framework for network performance evaluation

    Science.gov (United States)

    Wootton, Richard; Vladzymyrskyy, Anton; Zolfo, Maria; Bonnardot, Laurent

    2011-01-01

    Background Telemedicine has been used for many years to support doctors in the developing world. Several networks provide services in different settings and in different ways. However, to draw conclusions about which telemedicine networks are successful requires a method of evaluating them. No general consensus or validated framework exists for this purpose. Objective To define a basic method of performance measurement that can be used to improve and compare teleconsultation networks; to employ the proposed framework in an evaluation of three existing networks; to make recommendations about the future implementation and follow-up of such networks. Methods Analysis based on the experience of three telemedicine networks (in operation for 7–10 years) that provide services to doctors in low-resource settings and which employ the same basic design. Findings Although there are many possible indicators and metrics that might be relevant, five measures for each of the three user groups appear to be sufficient for the proposed framework. In addition, from the societal perspective, information about clinical- and cost-effectiveness is also required. The proposed performance measurement framework was applied to three mature telemedicine networks. Despite their differences in terms of activity, size and objectives, their performance in certain respects is very similar. For example, the time to first reply from an expert is about 24 hours for each network. Although all three networks had systems in place to collect data from the user perspective, none of them collected information about the coordinator's time required or about ease of system usage. They had only limited information about quality and cost. Conclusion Measuring the performance of a telemedicine network is essential in understanding whether the network is working as intended and what effect it is having. Based on long-term field experience, the suggested framework is a practical tool that will permit

  13. Experience with low-cost telemedicine in three different settings. Recommendations based on a proposed framework for network performance evaluation

    Directory of Open Access Journals (Sweden)

    Richard Wootton

    2011-12-01

    Full Text Available Telemedicine has been used for many years to support doctors in the developing world. Several networks provide services in different settings and in different ways. However, to draw conclusions about which telemedicine networks are successful requires a method of evaluating them. No general consensus or validated framework exists for this purpose.To define a basic method of performance measurement that can be used to improve and compare teleconsultation networks; to employ the proposed framework in an evaluation of three existing networks; to make recommendations about the future implementation and follow-up of such networks.Analysis based on the experience of three telemedicine networks (in operation for 7–10 years that provide services to doctors in low-resource settings and which employ the same basic design.Although there are many possible indicators and metrics that might be relevant, five measures for each of the three user groups appear to be sufficient for the proposed framework. In addition, from the societal perspective, information about clinical- and cost-effectiveness is also required. The proposed performance measurement framework was applied to three mature telemedicine networks. Despite their differences in terms of activity, size and objectives, their performance in certain respects is very similar. For example, the time to first reply from an expert is about 24 hours for each network. Although all three networks had systems in place to collect data from the user perspective, none of them collected information about the coordinator's time required or about ease of system usage. They had only limited information about quality and cost.Measuring the performance of a telemedicine network is essential in understanding whether the network is working as intended and what effect it is having. Based on long-term field experience, the suggested framework is a practical tool that will permit organisations to assess the performance of

  14. Real time spectrum analysis

    International Nuclear Information System (INIS)

    Blunden, A.; O'Prey, D.G.; Tait, W.H.

    1983-01-01

    A method is described for the separation of a composite pulse-height spectrum into its unresolved component parts, which belong to a set of measured library spectra. The method allows real-time estimation giving running estimates during acquisition of the spectrum, minimises computation space, especially for a number of parallel calculations, estimates in advance the rms errors, and produces a significance measure for the hypothesis that the composite contains only the library spectra. Least squares curve-fitting, and other methods, can be compared, with the formalism developed, allowing analytical comparison of the effect of detector energy resolution and detection efficiency. A rational basis for the choice between the various methods of spectrum analysis follows from the theory, minimising rms estimation errors. The method described is applicable for very low numbers of counts and poor resolution. (orig.)

  15. Real time production optimization

    Energy Technology Data Exchange (ETDEWEB)

    Saputelli, Luigi; Otavio, Joao; Araujo, Turiassu; Escorcia, Alvaro [Halliburton, Houston, TX (United States). Landmark Division

    2004-07-01

    Production optimization encompasses various activities of measuring, analyzing, modeling, prioritizing and implementing actions to enhance productivity of a field. We present a state-of-the-art framework for optimizing production on a continuous basis as new sensor data is acquired in real time. Permanently acquired data is modeled and analyzed in order to create predictive models. A model based control strategy is used to regulate well and field instrumentation. The optimum field operating point, which changes with time, satisfies the maximum economic return. This work is a starting point for further development in automatic, intelligent reservoir technologies which get the most out of the abilities of permanent, instrumented wells and remotely activated downhole completions. The strategy, tested with history-matched data from a compartmentalised giant field, proved to reduce operating costs while increasing oil recovery by 27% in this field. (author)

  16. Real time urbanism

    Directory of Open Access Journals (Sweden)

    Ana Ruiz Varona

    2012-12-01

    Full Text Available Nowadays, given the technological revolution of the society of information, the administrative management of the cities faces a new problem not as related to the projection of the urban space as to the capacity of controlling and measuring the process of direct and centralized production of the cities by part of some non-homogeneous social multitudes, in a hyper-accelerated time towards instantaneity. Against libertarian apologies of the new “participative urbanisms”, the article puts forward a discourse that shows the lost associated to the new problem of temporal instantaneity. In this regard we claim new process of mediation that allow administrations and urbanist monitoring the production of the city. To that end, a previous and necessary step will be the redefinition of the role of a new real time urbanist.

  17. Earthquake Early Warning: Real-time Testing of an On-site Method Using Waveform Data from the Southern California Seismic Network

    Science.gov (United States)

    Solanki, K.; Hauksson, E.; Kanamori, H.; Wu, Y.; Heaton, T.; Boese, M.

    2007-12-01

    We have implemented an on-site early warning algorithm using the infrastructure of the Caltech/USGS Southern California Seismic Network (SCSN). We are evaluating the real-time performance of the software system and the algorithm for rapid assessment of earthquakes. In addition, we are interested in understanding what parts of the SCSN need to be improved to make early warning practical. Our EEW processing system is composed of many independent programs that process waveforms in real-time. The codes were generated by using a software framework. The Pd (maximum displacement amplitude of P wave during the first 3sec) and Tau-c (a period parameter during the first 3 sec) values determined during the EEW processing are being forwarded to the California Integrated Seismic Network (CISN) web page for independent evaluation of the results. The on-site algorithm measures the amplitude of the P-wave (Pd) and the frequency content of the P-wave during the first three seconds (Tau-c). The Pd and the Tau-c values make it possible to discriminate between a variety of events such as large distant events, nearby small events, and potentially damaging nearby events. The Pd can be used to infer the expected maximum ground shaking. The method relies on data from a single station although it will become more reliable if readings from several stations are associated. To eliminate false triggers from stations with high background noise level, we have created per station Pd threshold configuration for the Pd/Tau-c algorithm. To determine appropriate values for the Pd threshold we calculate Pd thresholds for stations based on the information from the EEW logs. We have operated our EEW test system for about a year and recorded numerous earthquakes in the magnitude range from M3 to M5. Two recent examples are a M4.5 earthquake near Chatsworth and a M4.7 earthquake near Elsinore. In both cases, the Pd and Tau-c parameters were determined successfully within 10 to 20 sec of the arrival of the

  18. Results of Geoenvironmental Studies (2013-2014) Applied to a Monitoring Water Quality Network in Real Time in the Atoyac River (upstream) Puebla, Mexico.

    Science.gov (United States)

    Rodriguez-Espinosa, P. F.; Tavera, E. M.; Morales-Garcia, S. S.; Muñoz-Sevilla, N. P.

    2014-12-01

    Results of geoenvironment studies, referents to geochemistry, weathering, size, mineral composition, and metals contained in sediments and physicochemical parameters of water in urban rivers associated with dam are presented. Emphasis on the interpretation of these results, was detect environmental susceptibility areas associated at the water quality in Upper basin of Atoyac River, Puebla, Mexico. The environmental sub secretary of the state government of Puebla, Mexico has initiated actions to clean up the urban Atoyac River, with measurements of physicochemical parameters associated of the water quality in real-time monitoring and sampling network along the river. The results identified an important role in the rivers, not only to receive and transport the contaminants associated with sedimentological and geochemical conditions, but magnified the effects of pollutant discharges. A significant concentration of hazardous metals in sediments of the dam, reflecting the geo-environmental conditions of anthropogenic Valsequillo Dam induction was determined. For example, a moderately contaminated Pb contaminated extreme class, and Cu and Zn contaminated with moderate to heavy contaminated under geoenvironment class index. Large concentration of clay minerals with larger surface areas was found there in the study, the minerals are definitely the fittest in nature to accept on their surfaces constitution of metals, metalloids and other contaminants which were reflected in the Geoenvironmental index. The results of the studies performed here enable us to locate monitoring stations and sampling network to physicochemical parameters in real time, in the areas of higher contamination found in geoenvironmental studies Atoyac High River Basin. Similarly, we can elucidate the origin of pollutants and monitoring agents reflected in BOD5 (223 mg / l) and COD (610 mg / l), suspended solids totals (136 mg / l) and dissolved solids totals (840 mg / l), in others. Recent hydrometric

  19. Ovation Prime Real-Time

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Ovation Prime Real-Time (OPRT) product is a real-time forecast and nowcast model of auroral power and is an operational implementation of the work by Newell et...

  20. Low-cost Cognitive Electronics Technology for Enhanced Communications and Situational Awareness for Networks of Small Unmanned Aerial Vehicles (UAV)

    Science.gov (United States)

    2013-03-01

    series of checkpoints in a complex route network,” while observing standard traffic etiquette and regulations [17]. The rules for the 2012 RoboCup...structure or protocols above the PHY. To support AVEP operation, we developed a packet structure based on the transmission control protocol (TCP...Control Protocol .” 1981. [37] F. Ge, Q. Chen, Y. Wang, C. W. Bostian, T. W. Rondeau, and B. Le, “Cognitive radio: from spectrum sharing to adaptive

  1. The Role of Telematic Practices in Computer Engineering: A Low-cost Remote Power Control in a Network Lab

    Directory of Open Access Journals (Sweden)

    Tomas Mateo Sanguino

    2012-05-01

    Full Text Available The present paper describes a practical solution of e-learning laboratory devoted to the study of computer networks. This laboratory has been proven with two groups of students from the University of Huelva (Spain during two academic years. In order to achieve this objective, it has been necessary to create an entire network infrastructure that includes both the telematic access to the laboratory equipment and the remote power control. The interest of this work lies in an economical and simple system of remote control and telematic access with a twofold objective. On the one hand, to develop distance practices with attendance appearance by means of real hardware systems, not simulated. On the other hand, to reduce the power consumption regarding other proposals of remote labs with permanent power connection, providing herein an on demand connection only when required. As a result, a versatile and flexible laboratory has been put into practice whose basic network topology allows transferring traditional practices to telematic practices in a natural way and without harsh changes

  2. Moball-Buoy Network: A Near-Real-Time Ground-Truth Distributed Monitoring System to Map Ice, Weather, Chemical Species, and Radiations, in the Arctic

    Science.gov (United States)

    Davoodi, F.; Shahabi, C.; Burdick, J.; Rais-Zadeh, M.; Menemenlis, D.

    2014-12-01

    control system. This control system will ensure arctic-wide coverage, will optimize Moball-buoys monitoring efforts according to their available resources and the priority of local areas of high scientific value within the Arctic region. Moball-buoy Network is expected to be the first robust and persistent Arctic-wide environment monitoring system capable of providing reliable readings in near real time

  3. Real Time Structured Light and Applications

    DEFF Research Database (Denmark)

    Wilm, Jakob

    Structured light scanning is a versatile method for 3D shape acquisition. While much faster than most competing measurement techniques, most high-end structured light scans still take in the order of seconds to complete. Low-cost sensors such as Microsoft Kinect and time of flight cameras have made......, increased processing power, and methods presented in this thesis, it is possible to perform structured light scans in real time with 20 depth measurements per second. This offers new opportunities for studying dynamic scenes, quality control, human-computer interaction and more. This thesis discusses...... several aspects of real time structured light systems and presents contributions within calibration, scene coding and motion correction aspects. The problem of reliable and fast calibration of such systems is addressed with a novel calibration scheme utilising radial basis functions [Contribution B...

  4. An Improved Approach for RSSI-Based only Calibration-Free Real-Time Indoor Localization on IEEE 802.11 and 802.15.4 Wireless Networks

    Directory of Open Access Journals (Sweden)

    Marco Passafiume

    2017-03-01

    Full Text Available Assuming a reliable and responsive spatial contextualization service is a must-have in IEEE 802.11 and 802.15.4 wireless networks, a suitable approach consists of the implementation of localization capabilities, as an additional application layer to the communication protocol stack. Considering the applicative scenario where satellite-based positioning applications are denied, such as indoor environments, and excluding data packet arrivals time measurements due to lack of time resolution, received signal strength indicator (RSSI measurements, obtained according to IEEE 802.11 and 802.15.4 data access technologies, are the unique data sources suitable for indoor geo-referencing using COTS devices. In the existing literature, many RSSI based localization systems are introduced and experimentally validated, nevertheless they require periodic calibrations and significant information fusion from different sensors that dramatically decrease overall systems reliability and their effective availability. This motivates the work presented in this paper, which introduces an approach for an RSSI-based calibration-free and real-time indoor localization. While switched-beam array-based hardware (compliant with IEEE 802.15.4 router functionality has already been presented by the author, the focus of this paper is the creation of an algorithmic layer for use with the pre-existing hardware capable to enable full localization and data contextualization over a standard 802.15.4 wireless sensor network using only RSSI information without the need of lengthy offline calibration phase. System validation reports the localization results in a typical indoor site, where the system has shown high accuracy, leading to a sub-metrical overall mean error and an almost 100% site coverage within 1 m localization error.

  5. An Improved Approach for RSSI-Based only Calibration-Free Real-Time Indoor Localization on IEEE 802.11 and 802.15.4 Wireless Networks.

    Science.gov (United States)

    Passafiume, Marco; Maddio, Stefano; Cidronali, Alessandro

    2017-03-29

    Assuming a reliable and responsive spatial contextualization service is a must-have in IEEE 802.11 and 802.15.4 wireless networks, a suitable approach consists of the implementation of localization capabilities, as an additional application layer to the communication protocol stack. Considering the applicative scenario where satellite-based positioning applications are denied, such as indoor environments, and excluding data packet arrivals time measurements due to lack of time resolution, received signal strength indicator (RSSI) measurements, obtained according to IEEE 802.11 and 802.15.4 data access technologies, are the unique data sources suitable for indoor geo-referencing using COTS devices. In the existing literature, many RSSI based localization systems are introduced and experimentally validated, nevertheless they require periodic calibrations and significant information fusion from different sensors that dramatically decrease overall systems reliability and their effective availability. This motivates the work presented in this paper, which introduces an approach for an RSSI-based calibration-free and real-time indoor localization. While switched-beam array-based hardware (compliant with IEEE 802.15.4 router functionality) has already been presented by the author, the focus of this paper is the creation of an algorithmic layer for use with the pre-existing hardware capable to enable full localization and data contextualization over a standard 802.15.4 wireless sensor network using only RSSI information without the need of lengthy offline calibration phase. System validation reports the localization results in a typical indoor site, where the system has shown high accuracy, leading to a sub-metrical overall mean error and an almost 100% site coverage within 1 m localization error.

  6. Technical features of a low-cost earthquake alert system

    International Nuclear Information System (INIS)

    Harben, P.

    1991-01-01

    The concept and features of an Earthquake Alert System (EAS) involving a distributed network of strong motion sensors is discussed. The EAS analyzes real-time data telemetered to a central facility and issues an areawide warning of a large earthquake in advance of the spreading elastic wave energy. A low-cost solution to high-cost estimates for installation and maintenance of a dedicated EAS is presented that makes use of existing microseismic stations. Using the San Francisco Bay area as an example, we show that existing US Geological Survey microseismic monitoring stations are of sufficient density to form the elements of a prototype EAS. By installing strong motion instrumentation and a specially developed switching device, strong ground motion can be telemetered in real-time to the central microseismic station on the existing communication channels. When a large earthquake occurs, a dedicated real-time central processing unit at the central microseismic station digitizes and analyzes the incoming data and issues a warning containing location and magnitude estimations. A 50-station EAS of this type in the San Francisco Bay area should cost under $70,000 to install and less than $5,000 annually to maintain

  7. Integrated Coastal Observation Network (ICON) for real-time monitoring of sea-level, sea-state, and surface-meteorological data

    Digital Repository Service at National Institute of Oceanography (India)

    Desai, R.G.P.; Joseph, A.; Agarvadekar, Y.; Mehra, P.; VijayKumar, K.; Luis, R.

    ). Real-time reporting capability of ICON yields several benefits, such as (i) remote monitoring of proper working condition of individual stations; (ii) implementation of repair/maintenance in the shortest possible time, thereby minimizing break...

  8. Designing a low-cost effective network for monitoring large scale regional seismicity in a soft-soil region (Alsace, France)

    Science.gov (United States)

    Bès de Berc, M.; Doubre, C.; Wodling, H.; Jund, H.; Hernandez, A.; Blumentritt, H.

    2015-12-01

    The Seismological Observatory of the North-East of France (ObSNEF) is developing its monitoring network within the framework of several projects. Among these project, RESIF (Réseau sismologique et géodésique français) allows the instrumentation of broad-band seismic stations, separated by 50-100 km. With the recent and future development of geothermal industrial projects in the Alsace region, the ObSNEF is responsible for designing, building and operating a dense regional seismic network in order to detect and localize earthquakes with both a completeness magnitude of 1.5 and no clipping for M6.0. The realization of the project has to be done prior to the summer 2016Several complex technical and financial constraints constitute such a projet. First, most of the Alsace Région (150x150 km2), particularly the whole Upper Rhine Graben, is a soft-soil plain where seismic signals are dominated by a high frequency noise level. Second, all the signals have to be transmitted in near real-time. And finally, the total cost of the project must not exceed $450,000.Regarding the noise level in Alsace, in order to make a reduction of 40 dB for frequencies above 1Hz, we program to instrument into 50m deep well with post-hole sensor for 5 stations out of 8 plane new stations. The 3 remaining would be located on bedrock along the Vosges piedmont. In order to be sensitive to low-magnitude regional events, we plan to install a low-noise short-period post-hole velocimeter. In order to avoid saturation for high potentiel local events (M6.0 at 10km), this velocimeter will be coupled with a surface strong-motion sensor. Regarding the connectivity, these stations will have no wired network, which reduces linking costs and delays. We will therefore use solar panels and a 3G/GPRS network. The infrastructure will be minimal and reduced to an outdoor box on a secured parcel of land. In addition to the data-logger, we will use a 12V ruggedized computer, hosting a seed-link server for near

  9. Evaluation of technologies of parallel computers. Communication networks for a real-time triggering application for a high-energy physics experiment at CERN

    International Nuclear Information System (INIS)

    Hoertnagl, Ch.

    1997-12-01

    Experiments at the future Large Hadron Collider (LHC) at CERN will be faced with an extraordinary challenge of event selection in real time. The primary event rate, equal to the bunch crossing frequency of 40 MHz, will have to be reduced by a factor of almost one-in-a-million in order to reveal traces of rare physics processes from an abundant background. This work presents various contributions to ongoing feasibility studies concerning the possible use of commercial technologies from the proximities of parallel computers and their communication networks for the second trigger stage, which faces an average data input rate of 100 kHz. Studies in this thesis apply a combination of methodologies, namely the build-up of lab-scale prototype implementations (including their exposition to test beam runs), algorithm development, technology tracking and benchmarking, as well as discrete event simulation. The main contribution consists of several technology case studies, which are based on the exploration of a set of standard benchmark programs for revealing simple parameters for characterizing delays during communication. Studied technologies include the communication sub-system of the Meiko CS-2, Asynchronous Transfer Mode (ATM), MEMORY CHANNEL, and Scalable Coherent Interface (SCI); all could be considered typical for candidate technologies. The discussion sheds light on the relative benefits and costs associated with different parallel programming models, in general, and with the use of message-passing libraries, such as Message Passing Interface (MPI), in particular. Best observed end-user-to-end-user latencies were ∼ 10 μs, best asymptotic bandwidths were ∼ 70 MByte/s. Typical sub-patterns of communication that have to be applied in the second trigger stage were sustained at ∼ 13 kHz, using today's technologies in realistic embeddings. (author)

  10. Real time stagger of electric network advanced analysis functions of a modern control center; Escalonamento em tempo real das funcoes avancadas de analise de rede eletrica de um moderno centro de controle

    Energy Technology Data Exchange (ETDEWEB)

    Zagari, Eduardo Nicola Ferraz

    1996-02-01

    This work presents two models for implementation of staggers for network analysis functions in real time for a control center. The methodology is described. Tests were performed in a electric power system of Campinas region, Sao Paulo sate - Southeast Brazil. Results are presented.

  11. Dependable Real-Time Systems

    Science.gov (United States)

    1991-09-30

    0196 or 413 545-0720 PI E-mail Address: krithi@nirvan.cs.umass.edu, stankovic(ocs.umass.edu Grant or Contract Title: Dependable Real - Time Systems Grant...Dependable Real - Time Systems " Grant or Contract Number: N00014-85-k-0398 L " Reporting Period: 1 Oct 87 - 30 Sep 91 , 2. Summary of Accomplishments ’ 2.1 Our...in developing a sound approach to scheduling tasks in complex real - time systems , (2) developed a real-time operating system kernel, a preliminary

  12. Hardware Algorithms For Tile-Based Real-Time Rendering

    NARCIS (Netherlands)

    Crisu, D.

    2012-01-01

    In this dissertation, we present the GRAphics AcceLerator (GRAAL) framework for developing embedded tile-based rasterization hardware for mobile devices, meant to accelerate real-time 3-D graphics (OpenGL compliant) applications. The goal of the framework is a low-cost, low-power, high-performance

  13. Real-time gigabit DMT transmission over plastic optical fibre

    NARCIS (Netherlands)

    Lee, S.C.J.; Breyer, F.; Cárdenas, D.; Randel, S.; Koonen, A.M.J.

    2009-01-01

    For the first time, a real-time 1.25 Gbit/s discrete multitone (DMT) transmitter implemented in a field-programmable gate array is demonstrated for use in low-cost, standard 1 mm step-index plastic optical fibre applications based on a commercial resonant-cavity LED and a large-diameter

  14. Low cost submarine robot

    Directory of Open Access Journals (Sweden)

    Ponlachart Chotikarn

    2010-10-01

    Full Text Available A submarine robot is a semi-autonomous submarine robot used mainly for marine environmental research. We aim todevelop a low cost, semi-autonomous submarine robot which is able to travel underwater. The robot’s structure was designedand patented using a novel idea of the diving system employing a volume adjustment mechanism to vary the robot’s density.A light weight, flexibility and small structure provided by PVC can be used to construct the torpedo-liked shape robot.Hydraulic seal and O-ring rubbers are used to prevent water leaking. This robot is controlled by a wired communicationsystem.

  15. Real-time prediction and gating of respiratory motion in 3D space using extended Kalman filters and Gaussian process regression network

    Science.gov (United States)

    Bukhari, W.; Hong, S.-M.

    2016-03-01

    The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the radiation treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting respiratory motion in 3D space and realizing a gating function without pre-specifying a particular phase of the patient’s breathing cycle. The algorithm, named EKF-GPRN+ , first employs an extended Kalman filter (EKF) independently along each coordinate to predict the respiratory motion and then uses a Gaussian process regression network (GPRN) to correct the prediction error of the EKF in 3D space. The GPRN is a nonparametric Bayesian algorithm for modeling input-dependent correlations between the output variables in multi-output regression. Inference in GPRN is intractable and we employ variational inference with mean field approximation to compute an approximate predictive mean and predictive covariance matrix. The approximate predictive mean is used to correct the prediction error of the EKF. The trace of the approximate predictive covariance matrix is utilized to capture the uncertainty in EKF-GPRN+ prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification enables us to pause the treatment beam over such instances. EKF-GPRN+ implements a gating function by using simple calculations based on the trace of the predictive covariance matrix. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPRN+ . The experimental results show that the EKF-GPRN+ algorithm reduces the patient-wise prediction error to 38%, 40% and 40% in root-mean-square, compared to no prediction, at lookahead lengths of 192 ms, 384 ms and 576 ms, respectively. The EKF-GPRN+ algorithm can further reduce the prediction error by employing the gating function, albeit

  16. Real-time prediction and gating of respiratory motion in 3D space using extended Kalman filters and Gaussian process regression network

    International Nuclear Information System (INIS)

    Bukhari, W; Hong, S-M

    2016-01-01

    The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the radiation treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting respiratory motion in 3D space and realizing a gating function without pre-specifying a particular phase of the patient’s breathing cycle. The algorithm, named EKF-GPRN +  , first employs an extended Kalman filter (EKF) independently along each coordinate to predict the respiratory motion and then uses a Gaussian process regression network (GPRN) to correct the prediction error of the EKF in 3D space. The GPRN is a nonparametric Bayesian algorithm for modeling input-dependent correlations between the output variables in multi-output regression. Inference in GPRN is intractable and we employ variational inference with mean field approximation to compute an approximate predictive mean and predictive covariance matrix. The approximate predictive mean is used to correct the prediction error of the EKF. The trace of the approximate predictive covariance matrix is utilized to capture the uncertainty in EKF-GPRN + prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification enables us to pause the treatment beam over such instances. EKF-GPRN + implements a gating function by using simple calculations based on the trace of the predictive covariance matrix. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPRN +  . The experimental results show that the EKF-GPRN + algorithm reduces the patient-wise prediction error to 38%, 40% and 40% in root-mean-square, compared to no prediction, at lookahead lengths of 192 ms, 384 ms and 576 ms, respectively. The EKF-GPRN + algorithm can further reduce the prediction error by employing the gating function

  17. Studying Complex Interactions in Real Time

    DEFF Research Database (Denmark)

    Mønster, Dan

    2017-01-01

    The study of human behavior must take into account the social context, and real-time, networked experiments with multiple participants is one increasingly popular way to achieve this. In this paper a framework based on Python and XMPP is presented that aims to make it easy to develop...

  18. Testing Real-Time Systems Using UPPAAL

    DEFF Research Database (Denmark)

    Hessel, Anders; Larsen, Kim Guldstrand; Mikucionis, Marius

    2008-01-01

    This chapter presents principles and techniques for model-based black-box conformance testing of real-time systems using the Uppaal model-checking tool-suite. The basis for testing is given as a network of concurrent timed automata specified by the test engineer. Relativized input...

  19. Hybrid Design Tools in a Social Virtual Reality Using Networked Oculus Rift: A Feasibility Study in Remote Real-Time Interaction

    NARCIS (Netherlands)

    Wendrich, Robert E.; Chambers, Kris-Howard; Al-Halabi, Wadee; Seibel, Eric J.; Grevenstuk, Olaf; Ullman, David; Hoffman, Hunter G.

    2016-01-01

    Hybrid Design Tool Environments (HDTE) allow designers and engineers to use real tangible tools and physical objects and/or artifacts to make and create real-time virtual representations and presentations on-the-fly. Manipulations of the real tangible objects (e.g., real wire mesh, clay, sketches,

  20. Real-time computational photon-counting LiDAR

    Science.gov (United States)

    Edgar, Matthew; Johnson, Steven; Phillips, David; Padgett, Miles

    2018-03-01

    The availability of compact, low-cost, and high-speed MEMS-based spatial light modulators has generated widespread interest in alternative sampling strategies for imaging systems utilizing single-pixel detectors. The development of compressed sensing schemes for real-time computational imaging may have promising commercial applications for high-performance detectors, where the availability of focal plane arrays is expensive or otherwise limited. We discuss the research and development of a prototype light detection and ranging (LiDAR) system via direct time of flight, which utilizes a single high-sensitivity photon-counting detector and fast-timing electronics to recover millimeter accuracy three-dimensional images in real time. The development of low-cost real time computational LiDAR systems could have importance for applications in security, defense, and autonomous vehicles.

  1. Telepositional portable real time radiation monitoring system

    International Nuclear Information System (INIS)

    Talpalariu, Jeni; Matei, Corina; Popescu, Oana

    2010-01-01

    Technology development for complex portable networks is on going to meet the area dosimetry challenge, improving the basic design using new telepositional GPS satellite methods and GSM terrestrial civil radio transmission networks. The system and devices proposed overcome the limitations of fixed and portable dosimeters, providing wireless real time radiations data and geospatial information's means, using many portable dosimeter stations and a mobile dosimeter computerised central console. (authors)

  2. Real-Time Parameter Identification

    Data.gov (United States)

    National Aeronautics and Space Administration — Armstrong researchers have implemented in the control room a technique for estimating in real time the aerodynamic parameters that describe the stability and control...

  3. Prototyping real-time systems

    OpenAIRE

    Clynch, Gary

    1994-01-01

    The traditional software development paradigm, the waterfall life cycle model, is defective when used for developing real-time systems. This thesis puts forward an executable prototyping approach for the development of real-time systems. A prototyping system is proposed which uses ESML (Extended Systems Modelling Language) as a prototype specification language. The prototyping system advocates the translation of non-executable ESML specifications into executable LOOPN (Language of Object ...

  4. Real-time vision systems

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, R.; Hernandez, J.E.; Lu, Shin-yee [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    Many industrial and defence applications require an ability to make instantaneous decisions based on sensor input of a time varying process. Such systems are referred to as `real-time systems` because they process and act on data as it occurs in time. When a vision sensor is used in a real-time system, the processing demands can be quite substantial, with typical data rates of 10-20 million samples per second. A real-time Machine Vision Laboratory (MVL) was established in FY94 to extend our years of experience in developing computer vision algorithms to include the development and implementation of real-time vision systems. The laboratory is equipped with a variety of hardware components, including Datacube image acquisition and processing boards, a Sun workstation, and several different types of CCD cameras, including monochrome and color area cameras and analog and digital line-scan cameras. The equipment is reconfigurable for prototyping different applications. This facility has been used to support several programs at LLNL, including O Division`s Peacemaker and Deadeye Projects as well as the CRADA with the U.S. Textile Industry, CAFE (Computer Aided Fabric Inspection). To date, we have successfully demonstrated several real-time applications: bullet tracking, stereo tracking and ranging, and web inspection. This work has been documented in the ongoing development of a real-time software library.

  5. An open real-time tele-stethoscopy system.

    Science.gov (United States)

    Foche-Perez, Ignacio; Ramirez-Payba, Rodolfo; Hirigoyen-Emparanza, German; Balducci-Gonzalez, Fernando; Simo-Reigadas, Francisco-Javier; Seoane-Pascual, Joaquin; Corral-Peñafiel, Jaime; Martinez-Fernandez, Andres

    2012-08-23

    Acute respiratory infections are the leading cause of childhood mortality. The lack of physicians in rural areas of developing countries makes difficult their correct diagnosis and treatment. The staff of rural health facilities (health-care technicians) may not be qualified to distinguish respiratory diseases by auscultation. For this reason, the goal of this project is the development of a tele-stethoscopy system that allows a physician to receive real-time cardio-respiratory sounds from a remote auscultation, as well as video images showing where the technician is placing the stethoscope on the patient's body. A real-time wireless stethoscopy system was designed. The initial requirements were: 1) The system must send audio and video synchronously over IP networks, not requiring an Internet connection; 2) It must preserve the quality of cardiorespiratory sounds, allowing to adapt the binaural pieces and the chestpiece of standard stethoscopes, and; 3) Cardiorespiratory sounds should be recordable at both sides of the communication. In order to verify the diagnostic capacity of the system, a clinical validation with eight specialists has been designed. In a preliminary test, twelve patients have been auscultated by all the physicians using the tele-stethoscopy system, versus a local auscultation using traditional stethoscope. The system must allow listen the cardiac (systolic and diastolic murmurs, gallop sound, arrhythmias) and respiratory (rhonchi, rales and crepitations, wheeze, diminished and bronchial breath sounds, pleural friction rub) sounds. The design, development and initial validation of the real-time wireless tele-stethoscopy system are described in detail. The system was conceived from scratch as open-source, low-cost and designed in such a way that many universities and small local companies in developing countries may manufacture it. Only free open-source software has been used in order to minimize manufacturing costs and look for alliances to

  6. An open real-time tele-stethoscopy system

    Directory of Open Access Journals (Sweden)

    Foche-Perez Ignacio

    2012-08-01

    Full Text Available Abstract Background Acute respiratory infections are the leading cause of childhood mortality. The lack of physicians in rural areas of developing countries makes difficult their correct diagnosis and treatment. The staff of rural health facilities (health-care technicians may not be qualified to distinguish respiratory diseases by auscultation. For this reason, the goal of this project is the development of a tele-stethoscopy system that allows a physician to receive real-time cardio-respiratory sounds from a remote auscultation, as well as video images showing where the technician is placing the stethoscope on the patient’s body. Methods A real-time wireless stethoscopy system was designed. The initial requirements were: 1 The system must send audio and video synchronously over IP networks, not requiring an Internet connection; 2 It must preserve the quality of cardiorespiratory sounds, allowing to adapt the binaural pieces and the chestpiece of standard stethoscopes, and; 3 Cardiorespiratory sounds should be recordable at both sides of the communication. In order to verify the diagnostic capacity of the system, a clinical validation with eight specialists has been designed. In a preliminary test, twelve patients have been auscultated by all the physicians using the tele-stethoscopy system, versus a local auscultation using traditional stethoscope. The system must allow listen the cardiac (systolic and diastolic murmurs, gallop sound, arrhythmias and respiratory (rhonchi, rales and crepitations, wheeze, diminished and bronchial breath sounds, pleural friction rub sounds. Results The design, development and initial validation of the real-time wireless tele-stethoscopy system are described in detail. The system was conceived from scratch as open-source, low-cost and designed in such a way that many universities and small local companies in developing countries may manufacture it. Only free open-source software has been used in order to

  7. The experience of the LIGHT (Light and Power Company of Rio de Janeiro State, Brazil), in low cost energy networks for rural electrification; A experiencia da LIGHT na implantacao de redes de baixo custo para eletrificacao rural

    Energy Technology Data Exchange (ETDEWEB)

    Macedo, Fernando F; Andre, Oswaldo P [Light Servicos de Eletricidade SA, Rio de Janeiro, RJ (Brazil)

    1987-12-31

    This paper shows the experience of LIGHT (Light and Power Company of Rio de Janeiro State, Brazil), in planning and implementation of low cost energy networks in rural electrification. Were also showed guidelines for consumer`s orientation, viability of installations and wiring options. 4 figs., 16 tabs., 12 refs.

  8. Exploring Earthquakes in Real-Time

    Science.gov (United States)

    Bravo, T. K.; Kafka, A. L.; Coleman, B.; Taber, J. J.

    2013-12-01

    Earthquakes capture the attention of students and inspire them to explore the Earth. Adding the ability to view and explore recordings of significant and newsworthy earthquakes in real-time makes the subject even more compelling. To address this opportunity, the Incorporated Research Institutions for Seismology (IRIS), in collaboration with Moravian College, developed ';jAmaSeis', a cross-platform application that enables students to access real-time earthquake waveform data. Students can watch as the seismic waves are recorded on their computer, and can be among the first to analyze the data from an earthquake. jAmaSeis facilitates student centered investigations of seismological concepts using either a low-cost educational seismograph or streamed data from other educational seismographs or from any seismic station that sends data to the IRIS Data Management System. After an earthquake, students can analyze the seismograms to determine characteristics of earthquakes such as time of occurrence, distance from the epicenter to the station, magnitude, and location. The software has been designed to provide graphical clues to guide students in the analysis and assist in their interpretations. Since jAmaSeis can simultaneously record up to three stations from anywhere on the planet, there are numerous opportunities for student driven investigations. For example, students can explore differences in the seismograms from different distances from an earthquake and compare waveforms from different azimuthal directions. Students can simultaneously monitor seismicity at a tectonic plate boundary and in the middle of the plate regardless of their school location. This can help students discover for themselves the ideas underlying seismic wave propagation, regional earthquake hazards, magnitude-frequency relationships, and the details of plate tectonics. The real-time nature of the data keeps the investigations dynamic, and offers students countless opportunities to explore.

  9. Towards Real-Time Argumentation

    Directory of Open Access Journals (Sweden)

    Vicente JULIÁN

    2016-07-01

    Full Text Available In this paper, we deal with the problem of real-time coordination with the more general approach of reaching real-time agreements in MAS. Concretely, this work proposes a real-time argumentation framework in an attempt to provide agents with the ability of engaging in argumentative dialogues and come with a solution for their underlying agreement process within a bounded period of time. The framework has been implemented and evaluated in the domain of a customer support application. Concretely, we consider a society of agents that act on behalf of a group of technicians that must solve problems in a Technology Management Centre (TMC within a bounded time. This centre controls every process implicated in the provision of technological and customer support services to private or public organisations by means of a call centre. The contract signed between the TCM and the customer establishes penalties if the specified time is exceeded.

  10. Real-time digital signal processing fundamentals, implementations and applications

    CERN Document Server

    Kuo, Sen M; Tian, Wenshun

    2013-01-01

    Combines both the DSP principles and real-time implementations and applications, and now updated with the new eZdsp USB Stick, which is very low cost, portable and widely employed at many DSP labs. Real-Time Digital Signal Processing introduces fundamental digital signal processing (DSP) principles and will be updated to include the latest DSP applications, introduce new software development tools and adjust the software design process to reflect the latest advances in the field. In the 3rd edition of the book, the key aspect of hands-on experiments will be enhanced to make the DSP principle

  11. Evaluation of RTKLIB's Positioning Accuracy Using low-cost GNSS Receiver and ASG-EUPOS

    Directory of Open Access Journals (Sweden)

    Bartosz Wisniewski

    2013-03-01

    Full Text Available The paper focuses on a comparison of different positioning methods provided by free and open source software (FOSS package called RTKLIB. The RTKLIB supports real-time and post-processed positioning. The most important modes of operation tested by the authors are Kinematic, Static, Fixed and Precise Point Positioning (PPP. The data for evaluation were obtained from low-cost Global Navigation Satellite System (GNSS receiver. The tested receiver was based on the u-blox's LEA-6T GNSS module. This receiver provides different types of information including raw carrier phase measurements. It gives the possibility for centimeter-level precision of positioning. As the supporting source of data ASG-EUPOS system was used. ASG-EUPOS is a Polish network of GNSS reference stations providing the real-time corrections and post processing services for the entire territory of Poland.

  12. Development and implementation of the quality control panel of RT-PCR and real-time RT-PCR for avian influenza A (H5N1 surveillance network in mainland China

    Directory of Open Access Journals (Sweden)

    Wang Wei

    2011-03-01

    Full Text Available Abstract Background Reverse transcription PCR (RT-PCR and real time RT-PCR (rRT-PCR have been indispensable methods for influenza surveillance, especially for determination of avian influenza. The movement of testing beyond reference lab introduced the need of quality control, including the implementation of an evaluation system for validating personal training and sample proficiency testing. Methods We developed a panel with lysates of seasonal influenza virus (H1N1, H3N2 and B, serials of diluted H5N1 virus lysates, and in-vitro transcribed H5 hemaglutinin (HA and an artificial gene RNAs for RT-PCR and rRT-PCR quality control assessment. The validations of stability and reproducibility were performed on the panel. Additionally, the panel was implemented to assess the detection capability of Chinese human avian influenza networks. Results The panel has relatively high stability and good reproducibility demonstrated by kappa's tests. In the implementation of panel on Chinese human avian influenza networks, the results suggested that there were a relatively low number of discrepancies for both concise and reproducibility in Chinese avian influenza virus net works. Conclusions A quality control panel of RT-PCR and real-time RT-PCR for avian influenza A (H5N1 surveillance network was developed. An availably statistical data, which are used to assess the detection capability of networks on avian influenza virus (H5N1, can be obtained relatively easily through implementation of the panel on networks.

  13. Design and implementation of a telemedicine system using Bluetooth protocol and GSM/GPRS network, for real time remote patient monitoring.

    Science.gov (United States)

    Jasemian, Yousef; Nielsen, Lars Arendt

    2005-01-01

    This paper introduces the design and implementation of a generic wireless and Real-time Multi-purpose Health Care Telemedicine system applying Bluetooth protocol, Global System for Mobile Communications (GSM) and General Packet Radio Service (GPRS). The paper explores the factors that should be considered when evaluating different technologies for application in telemedicine system. The design and implementation of an embedded wireless communication platform utilising Bluetooth protocol is described, and the implementation problems and limitations are investigated. The system is tested and its telecommunication general aspects are verified. The results showed that the system has (97.9 +/- 1.3)% Up-time, 2.5 x 10(-5) Bit Error Rate, 1% Dropped Call Rate, 97.4% Call Success Rate, 5 second transmission delay in average, (3.42 +/- 0.11) kbps throughput, and the system may have application in electrocardiography.

  14. Real time automatic scene classification

    NARCIS (Netherlands)

    Verbrugge, R.; Israël, Menno; Taatgen, N.; van den Broek, Egon; van der Putten, Peter; Schomaker, L.; den Uyl, Marten J.

    2004-01-01

    This work has been done as part of the EU VICAR (IST) project and the EU SCOFI project (IAP). The aim of the first project was to develop a real time video indexing classification annotation and retrieval system. For our systems, we have adapted the approach of Picard and Minka [3], who categorized

  15. Real time freeway incident detection.

    Science.gov (United States)

    2014-04-01

    The US Department of Transportation (US-DOT) estimates that over half of all congestion : events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time : incident detection on freeways is an important part of any mo...

  16. Real Time Conference 2016 Overview

    Science.gov (United States)

    Luchetta, Adriano

    2017-06-01

    This is a special issue of the IEEE Transactions on Nuclear Science containing papers from the invited, oral, and poster presentation of the 20th Real Time Conference (RT2016). The conference was held June 6-10, 2016, at Centro Congressi Padova “A. Luciani,” Padova, Italy, and was organized by Consorzio RFX (CNR, ENEA, INFN, Università di Padova, Acciaierie Venete SpA) and the Istituto Nazionale di Fisica Nucleare. The Real Time Conference is multidisciplinary and focuses on the latest developments in real-time techniques in high-energy physics, nuclear physics, astrophysics and astroparticle physics, nuclear fusion, medical physics, space instrumentation, nuclear power instrumentation, general radiation instrumentation, and real-time security and safety. Taking place every second year, it is sponsored by the Computer Application in Nuclear and Plasma Sciences technical committee of the IEEE Nuclear and Plasma Sciences Society. RT2016 attracted more than 240 registrants, with a large proportion of young researchers and engineers. It had an attendance of 67 students from many countries.

  17. Designing Real Time Assistive Technologies

    DEFF Research Database (Denmark)

    Sonne, Tobias; Obel, Carsten; Grønbæk, Kaj

    2015-01-01

    activities and assists the child in maintaining attention. From a preliminary evaluation of CASTT with 20 children in several schools, we and found that: 1) it is possible to create a wearable sensor system for children with ADHD that monitors physical and physiological activities in real time; and that 2...

  18. ISTTOK real-time architecture

    Energy Technology Data Exchange (ETDEWEB)

    Carvalho, Ivo S., E-mail: ivoc@ipfn.ist.utl.pt; Duarte, Paulo; Fernandes, Horácio; Valcárcel, Daniel F.; Carvalho, Pedro J.; Silva, Carlos; Duarte, André S.; Neto, André; Sousa, Jorge; Batista, António J.N.; Hekkert, Tiago; Carvalho, Bernardo B.

    2014-03-15

    Highlights: • All real-time diagnostics and actuators were integrated in the same control platform. • A 100 μs control cycle was achieved under the MARTe framework. • Time-windows based control with several event-driven control strategies implemented. • AC discharges with exception handling on iron core flux saturation. • An HTML discharge configuration was developed for configuring the MARTe system. - Abstract: The ISTTOK tokamak was upgraded with a plasma control system based on the Advanced Telecommunications Computing Architecture (ATCA) standard. This control system was designed to improve the discharge stability and to extend the operational space to the alternate plasma current (AC) discharges as part of the ISTTOK scientific program. In order to accomplish these objectives all ISTTOK diagnostics and actuators relevant for real-time operation were integrated in the control system. The control system was programmed in C++ over the Multi-threaded Application Real-Time executor (MARTe) which provides, among other features, a real-time scheduler, an interrupt handler, an intercommunications interface between code blocks and a clearly bounded interface with the external devices. As a complement to the MARTe framework, the BaseLib2 library provides the foundations for the data, code introspection and also a Hypertext Transfer Protocol (HTTP) server service. Taking advantage of the modular nature of MARTe, the algorithms of each diagnostic data processing, discharge timing, context switch, control and actuators output reference generation, run on well-defined blocks of code named Generic Application Module (GAM). This approach allows reusability of the code, simplified simulation, replacement or editing without changing the remaining GAMs. The ISTTOK control system GAMs run sequentially each 100 μs cycle on an Intel{sup ®} Q8200 4-core processor running at 2.33 GHz located in the ATCA crate. Two boards (inside the ATCA crate) with 32 analog

  19. ISTTOK real-time architecture

    International Nuclear Information System (INIS)

    Carvalho, Ivo S.; Duarte, Paulo; Fernandes, Horácio; Valcárcel, Daniel F.; Carvalho, Pedro J.; Silva, Carlos; Duarte, André S.; Neto, André; Sousa, Jorge; Batista, António J.N.; Hekkert, Tiago; Carvalho, Bernardo B.

    2014-01-01

    Highlights: • All real-time diagnostics and actuators were integrated in the same control platform. • A 100 μs control cycle was achieved under the MARTe framework. • Time-windows based control with several event-driven control strategies implemented. • AC discharges with exception handling on iron core flux saturation. • An HTML discharge configuration was developed for configuring the MARTe system. - Abstract: The ISTTOK tokamak was upgraded with a plasma control system based on the Advanced Telecommunications Computing Architecture (ATCA) standard. This control system was designed to improve the discharge stability and to extend the operational space to the alternate plasma current (AC) discharges as part of the ISTTOK scientific program. In order to accomplish these objectives all ISTTOK diagnostics and actuators relevant for real-time operation were integrated in the control system. The control system was programmed in C++ over the Multi-threaded Application Real-Time executor (MARTe) which provides, among other features, a real-time scheduler, an interrupt handler, an intercommunications interface between code blocks and a clearly bounded interface with the external devices. As a complement to the MARTe framework, the BaseLib2 library provides the foundations for the data, code introspection and also a Hypertext Transfer Protocol (HTTP) server service. Taking advantage of the modular nature of MARTe, the algorithms of each diagnostic data processing, discharge timing, context switch, control and actuators output reference generation, run on well-defined blocks of code named Generic Application Module (GAM). This approach allows reusability of the code, simplified simulation, replacement or editing without changing the remaining GAMs. The ISTTOK control system GAMs run sequentially each 100 μs cycle on an Intel ® Q8200 4-core processor running at 2.33 GHz located in the ATCA crate. Two boards (inside the ATCA crate) with 32 analog

  20. Implementing a low cost distributed architecture for real-time behavioural modelling and simulation

    CSIR Research Space (South Africa)

    Le Roux, WH

    2006-06-01

    Full Text Available at different levels of which some are: 1. Comprehensiveness (completeness) – Are the sun and moon positions accurate for the time of day and time of year in the flight simulator? Are wind gusts taken into account for the projectile trajectory? 2... system, referred to as the Virtual GBADS Demonstrator (VGD), to the first GBADS acquisition phase. The GBADS procurement programme follows a phased approach of which acquisition of the SABLE2 Air Defence System forms the first phase [1...

  1. Low cost time to digital converter in real time with +-1 ns resolution

    Energy Technology Data Exchange (ETDEWEB)

    Lenzi, G; Podini, P; Reverberi, R [Parma Univ. (Italy). Istituto di Fisica; Pernestaal, K [Uppsala Univ. (Sweden). Fysiska Institutionen

    1977-04-15

    A time to digital converter (TDC) with a time resolution of 1 ns has been designed. The deadtime is T+0.6 ..mu..s where T is the measured time. The time range can be preselected between 0.3 and 10 ..mu..s. The TDC has one START and three mutually exclusive STOP inputs which accept standard pulses (-16 mA). The time information is presented as a bit binary word, including the activated stop input address. The instrument has been successfully used in ..mu../sup +/SR (muon spin rotation) measurements and has proven itself advantageous over the more common TAC+ADC combination.

  2. Community Air Sensor Network (CAIRSENSE) project: Evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

    Science.gov (United States)

    Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring n...

  3. Verifying real-time systems against scenario-based requirements

    DEFF Research Database (Denmark)

    Larsen, Kim Guldstrand; Li, Shuhao; Nielsen, Brian

    2009-01-01

    We propose an approach to automatic verification of real-time systems against scenario-based requirements. A real-time system is modeled as a network of Timed Automata (TA), and a scenario-based requirement is specified as a Live Sequence Chart (LSC). We define a trace-based semantics for a kernel...... subset of the LSC language. By equivalently translating an LSC chart into an observer TA and then non-intrusively composing this observer with the original system model, the problem of verifying a real-time system against a scenario-based requirement reduces to a classical real-time model checking...

  4. A Cross-Layer Wireless Sensor Network Energy-Efficient Communication Protocol for Real-Time Monitoring of the Long-Distance Electric Transmission Lines

    Directory of Open Access Journals (Sweden)

    Jun Yu

    2015-01-01

    Full Text Available Optimization of energy consumption in Wireless Sensor Network (WSN nodes has become a critical link that constrains the engineering application of the smart grid due to the fact that the smart grid is characterized by long-distance transmission in a special environment. The paper proposes a linear hierarchical network topological structure specific to WSN energy conservation in environmental monitoring of the long-distance electric transmission lines in the smart grid. Based on the topological structural characteristics and optimization of network layers, the paper also proposes a Topological Structure be Layered Configurations (TSLC routing algorithm to improve the quality of WSN data transmission performance. Coprocessing of the network layer and the media access control (MAC layer is achieved by using the cross-layer design method, accessing the status for the nodes in the network layer and obtaining the status of the network nodes of the MAC layer. It efficiently saves the energy of the whole network, improves the quality of the network service performance, and prolongs the life cycle of the network.

  5. Real time automatic discriminating of ultrasonic flaws

    International Nuclear Information System (INIS)

    Suhairy Sani; Mohd Hanif Md Saad; Marzuki Mustafa; Mohd Redzwan Rosli

    2009-01-01

    This paper is concerned with the real time automatic discriminating of flaws from two categories; i. cracks (planar defect) and ii. Non-cracks (volumetric defect such as cluster porosity and slag) using pulse-echo ultrasound. The raw ultrasonic flaws signal were collected from a computerized robotic plane scanning system over the whole of each reflector as the primary source of data. The signal is then filtered and the analysis in both time and frequency domain were executed to obtain the selected feature. The real time feature analysis techniques measured the number of peaks, maximum index, pulse duration, rise time and fall time. The obtained features could be used to distinguish between quantitatively classified flaws by using various tools in artificial intelligence such as neural networks. The proposed algorithm and complete system were implemented in a computer software developed using Microsoft Visual BASIC 6.0 (author)

  6. Application of Real-Time Automated Traffic Incident Response Plan Management System: A Web Structure for the Regional Highway Network in China

    Directory of Open Access Journals (Sweden)

    Yongfeng Ma

    2014-01-01

    Full Text Available Traffic incidents, caused by various factors, may lead to heavy traffic delay and be harmful to traffic capacity of downstream sections. Traffic incident management (TIM systems have been developed widely to respond to traffic incidents intelligently and reduce the losses. Traffic incident response plans, as an important component of TIM, can effectively guide responders as to what and how to do in traffic incidents. In the paper, a real-time automated traffic incident response plan management system was developed, which could generate and manage traffic incident response plans timely and automatically. A web application structure and a physical structure were designed to implement and show these functions. A standard framework of data storage was also developed to save information about traffic incidents and generated response plans. Furthermore, a conformation survey and case-based reasoning (CBR were introduced to identify traffic incident and generate traffic incident response plans automatically, respectively. Twenty-three traffic crash-related incidents were selected and three indicators were used to measure the system performance. Results showed that 20 of 23 cases could be retrieved effectively and accurately. The system is practicable to generate traffic incident response plans and has been implemented in China.

  7. An agent-based signal processing in-node environment for real-time human activity monitoring based on wireless body sensor networks

    NARCIS (Netherlands)

    Aiello, F.; Bellifemine, F.L.; Fortino, G.; Galzarano, S.; Gravina, R.

    2011-01-01

    Nowadays wireless body sensor networks (WBSNs) have great potential to enable a broad variety of assisted living applications such as human biophysical/biochemical control and activity monitoring for health care, e-fitness, emergency detection, emotional recognition for social networking, security,

  8. D-MSR: A Distributed Network Management Scheme for Real-Time Monitoring and Process Control Applications in Wireless Industrial Automation

    NARCIS (Netherlands)

    Zand, P.; Dilo, Arta; Havinga, Paul J.M.

    2013-01-01

    Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot

  9. Developing infrared array controller with software real time operating system

    Science.gov (United States)

    Sako, Shigeyuki; Miyata, Takashi; Nakamura, Tomohiko; Motohara, Kentaro; Uchimoto, Yuka Katsuno; Onaka, Takashi; Kataza, Hirokazu

    2008-07-01

    Real-time capabilities are required for a controller of a large format array to reduce a dead-time attributed by readout and data transfer. The real-time processing has been achieved by dedicated processors including DSP, CPLD, and FPGA devices. However, the dedicated processors have problems with memory resources, inflexibility, and high cost. Meanwhile, a recent PC has sufficient resources of CPUs and memories to control the infrared array and to process a large amount of frame data in real-time. In this study, we have developed an infrared array controller with a software real-time operating system (RTOS) instead of the dedicated processors. A Linux PC equipped with a RTAI extension and a dual-core CPU is used as a main computer, and one of the CPU cores is allocated to the real-time processing. A digital I/O board with DMA functions is used for an I/O interface. The signal-processing cores are integrated in the OS kernel as a real-time driver module, which is composed of two virtual devices of the clock processor and the frame processor tasks. The array controller with the RTOS realizes complicated operations easily, flexibly, and at a low cost.

  10. Passive low-cost inkjet-printed smart skin sensor for structural health monitoring

    KAUST Repository

    Cook, Benjamin Stassen; Shamim, Atif; Tentzeris, Manos

    2012-01-01

    presents a step towards fully integrated, low-cost, conformal and environmentally friendly smart skins for real-time monitoring of large structures. © The Institution of Engineering and Technology 2012.

  11. Quantitative (real-time) PCR

    International Nuclear Information System (INIS)

    Denman, S.E.; McSweeney, C.S.

    2005-01-01

    Many nucleic acid-based probe and PCR assays have been developed for the detection tracking of specific microbes within the rumen ecosystem. Conventional PCR assays detect PCR products at the end stage of each PCR reaction, where exponential amplification is no longer being achieved. This approach can result in different end product (amplicon) quantities being generated. In contrast, using quantitative, or real-time PCR, quantification of the amplicon is performed not at the end of the reaction, but rather during exponential amplification, where theoretically each cycle will result in a doubling of product being created. For real-time PCR, the cycle at which fluorescence is deemed to be detectable above the background during the exponential phase is termed the cycle threshold (Ct). The Ct values obtained are then used for quantitation, which will be discussed later

  12. Real time psychrometric data collection

    International Nuclear Information System (INIS)

    McDaniel, K.H.

    1996-01-01

    Eight Mine Weather Stations (MWS) installed at the Waste Isolation Pilot Plant (WIPP) to monitor the underground ventilation system are helping to simulate real-time ventilation scenarios. Seasonal weather extremes can result in variations of Natural Ventilation Pressure (NVP) which can significantly effect the ventilation system. The eight MWS(s) (which previously collected and stored temperature, barometric pressure and relative humidity data for subsequent NVP calculations) were upgraded to provide continuous real-time data to the site wide Central monitoring System. This data can now be utilized by the ventilation engineer to create realtime ventilation simulations and trends which assist in the prediction and mitigation of NVP and psychrometric related events

  13. Real-time holographic endoscopy

    Science.gov (United States)

    Smigielski, Paul; Albe, Felix; Dischli, Bernard

    1992-08-01

    Some new experiments concerning holographic endoscopy are presented. The quantitative measurements of deformations of objects are obtained by the double-exposure and double- reference beam method, using either a cw-laser or a pulsed laser. Qualitative experiments using an argon laser with time-average holographic endoscopy are also presented. A video film on real-time endoscopic holographic interferometry was recorded with the help of a frequency-doubled YAG-laser working at 25 Hz for the first time.

  14. [Real time 3D echocardiography

    Science.gov (United States)

    Bauer, F.; Shiota, T.; Thomas, J. D.

    2001-01-01

    Three-dimensional representation of the heart is an old concern. Usually, 3D reconstruction of the cardiac mass is made by successive acquisition of 2D sections, the spatial localisation and orientation of which require complex guiding systems. More recently, the concept of volumetric acquisition has been introduced. A matricial emitter-receiver probe complex with parallel data processing provides instantaneous of a pyramidal 64 degrees x 64 degrees volume. The image is restituted in real time and is composed of 3 planes (planes B and C) which can be displaced in all spatial directions at any time during acquisition. The flexibility of this system of acquisition allows volume and mass measurement with greater accuracy and reproducibility, limiting inter-observer variability. Free navigation of the planes of investigation allows reconstruction for qualitative and quantitative analysis of valvular heart disease and other pathologies. Although real time 3D echocardiography is ready for clinical usage, some improvements are still necessary to improve its conviviality. Then real time 3D echocardiography could be the essential tool for understanding, diagnosis and management of patients.

  15. A real-time in-memory discovery service leveraging hierarchical packaging information in a unique identifier network to retrieve track and trace information

    CERN Document Server

    Müller, Jürgen

    2014-01-01

    This book examines how to efficiently retrieve track and trace information for an item that took a certain path through a complex network of manufacturers, wholesalers, retailers and consumers. It includes valuable tips on in-memory data management.

  16. Study and realisation of a gateway between a MIL1553 network and an Ethernet network. Implementation of the OS9NET homogeneous network and of the TCP/IP heterogeneous network on the OS-9/68000 real time operating system

    International Nuclear Information System (INIS)

    Tricot-Censier, Pascal

    1989-01-01

    This research thesis addresses the design of a homogeneous network for machines acquiring data in real time, and the interconnection by a heterogeneous network of this group with three groups of mini-computers, workstations, and personal computers. Thus, this work involved hardware as well as software designs and developments. After a recall of main notions related to networks, and a presentation of the OS9 real time core, the author reports the design and development of the Ethernet controller card. He reports the design and realisation of a gateway between Ethernet and MIL1553 which is notably based on the previously mentioned controller card. An Ethernet driver is then designed for the OS9 operating system. As the connection with other machines which do not support OS9, requires the development of applications using TCP/IP protocols, the author describes how software designed for PCs have been adapted for a use in real time and for the OS9 operating system. He presents an additional software layer to TCP/IP for an inter-process communication through a heterogeneous network. This layer allows the development of applications distributed among systems which possess different processors and operating systems. Finally, the author presents a test protocol which ensures the fast transfer of memory blocks between OS9 machines [fr

  17. Design and implementation of pan-tilt FSO transceiver gimbals for real-time compensation of platform disturbances using a secondary control network

    Science.gov (United States)

    Rzasa, John; Milner, Stuart D.; Davis, Christopher C.

    2011-09-01

    Free-space optical (FSO) systems are known for providing data rates much higher than RF based systems, however their narrow beams require a method to keep the transceivers precisely aligned. To date, most systems have used a combination of coarse pointing platforms and fast steering mirrors tied to a feedback loop based on received optical power to accomplish this. This method can encounter problems if the alignment of one of the transceivers is disrupted or obstructed. In this paper, we present an approach to mitigating this problem using a low data-rate, omni-directional RF network that disseminates pointing commands to all platforms in the network, thereby if the main FSO channels are disrupted, the network can recover faster than a purely received signal strength (RSS) based approach. Utilizing custommade high precision direct drive servo pan-tilt platforms coupled with position and orientation sensors, we can calculate the appropriate pointing angles for all the transceiver platforms, which are then relayed over the control network. We present theoretical calculations regarding the required performance specifications of the control network and pan-tiltplatforms. Experimental results are then presented for a link where one transceiver is mounted on a coarse vibration platform to simulate disturbances in a real network.

  18. RadNet-Air Near Real Time Data

    Data.gov (United States)

    U.S. Environmental Protection Agency — RadNet-Air is a national network of air monitoring stations that regularly collect air samples for near real time analysis of radioactivity. The data is transmitted...

  19. Real-Time Multi-Directional Equipment Site

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) Program, Lehigh University has established the Real-Time Multi-Directional...

  20. Real-time video quality monitoring

    Science.gov (United States)

    Liu, Tao; Narvekar, Niranjan; Wang, Beibei; Ding, Ran; Zou, Dekun; Cash, Glenn; Bhagavathy, Sitaram; Bloom, Jeffrey

    2011-12-01

    The ITU-T Recommendation G.1070 is a standardized opinion model for video telephony applications that uses video bitrate, frame rate, and packet-loss rate to measure the video quality. However, this model was original designed as an offline quality planning tool. It cannot be directly used for quality monitoring since the above three input parameters are not readily available within a network or at the decoder. And there is a great room for the performance improvement of this quality metric. In this article, we present a real-time video quality monitoring solution based on this Recommendation. We first propose a scheme to efficiently estimate the three parameters from video bitstreams, so that it can be used as a real-time video quality monitoring tool. Furthermore, an enhanced algorithm based on the G.1070 model that provides more accurate quality prediction is proposed. Finally, to use this metric in real-world applications, we present an example emerging application of real-time quality measurement to the management of transmitted videos, especially those delivered to mobile devices.

  1. Polar coordinated fuzzy controller based real-time maximum-power point control of photovoltaic system

    Energy Technology Data Exchange (ETDEWEB)

    Syafaruddin; Hiyama, Takashi [Department of Computer Science and Electrical Engineering of Kumamoto University, 2-39-1 Kurokami, Kumamoto 860-8555 (Japan); Karatepe, Engin [Department of Electrical and Electronics Engineering of Ege University, 35100 Bornova-Izmir (Turkey)

    2009-12-15

    It is crucial to improve the photovoltaic (PV) system efficiency and to develop the reliability of PV generation control systems. There are two ways to increase the efficiency of PV power generation system. The first is to develop materials offering high conversion efficiency at low cost. The second is to operate PV systems optimally. However, the PV system can be optimally operated only at a specific output voltage and its output power fluctuates under intermittent weather conditions. Moreover, it is very difficult to test the performance of a maximum-power point tracking (MPPT) controller under the same weather condition during the development process and also the field testing is costly and time consuming. This paper presents a novel real-time simulation technique of PV generation system by using dSPACE real-time interface system. The proposed system includes Artificial Neural Network (ANN) and fuzzy logic controller scheme using polar information. This type of fuzzy logic rules is implemented for the first time to operate the PV module at optimum operating point. ANN is utilized to determine the optimum operating voltage for monocrystalline silicon, thin-film cadmium telluride and triple junction amorphous silicon solar cells. The verification of availability and stability of the proposed system through the real-time simulator shows that the proposed system can respond accurately for different scenarios and different solar cell technologies. (author)

  2. Opportunist combination of electronic technologies for real time calculations in the Tore Supra Tokamak

    International Nuclear Information System (INIS)

    Barbuti, A.; Gil, C.; Pastor, P.; Spuig, P.; Vincent, B.; Volpe, D.

    2013-06-01

    The Tore Supra tokamak real-time plasma control is based on measurements coming from various diagnostics. The complexity of all the events that occur during plasma is at the origin of measurements disturbances which have to be corrected in real time in order to ensure an optimal control. The signal correction does not just mean processing but requires complex algorithms. Electronics does not only need to process and adapt electrical signals, but it has to include corrections by mathematical calculation. The FPGA (field-programmable gate array) technology, with the help of basic adapted electronics, allows integrating the entire real time calculation and digital data transmission on the network. FMC (FPGA Mezzanine Card) coupled with in-house motherboard, which is used both as the interface with Tore Supra specific systems and as the support for other signals processing options, is the perfect answer to this request. The FMC includes a FPGA, memory, Ethernet port and multiple I/O for interfacing with the motherboard and Tore Supra signals. The algorithms are developed in VHDL (Very high speed integrated circuit Hardware Description Language), parallel process management that promotes faster calculation than a common μC (Micro-controller) in one clock pulse. The flexibility, the low cost and the implementation speed allow fitting a large number of various applications in fields where no 'off-theshelf' component can be found. And more specifically, in research and experimentation, algorithms can be continuously improved or modified for new requirements. (authors)

  3. Towards a Low-Cost Remote Memory Attestation for the Smart Grid.

    Science.gov (United States)

    Yang, Xinyu; He, Xiaofei; Yu, Wei; Lin, Jie; Li, Rui; Yang, Qingyu; Song, Houbing

    2015-08-21

    In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA), which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes.

  4. Towards a Low-Cost Remote Memory Attestation for the Smart Grid

    Directory of Open Access Journals (Sweden)

    Xinyu Yang

    2015-08-01

    Full Text Available In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA, which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes.

  5. Bridging FPGA and GPU technologies for AO real-time control

    Science.gov (United States)

    Perret, Denis; Lainé, Maxime; Bernard, Julien; Gratadour, Damien; Sevin, Arnaud

    2016-07-01

    Our team has developed a common environment for high performance simulations and real-time control of AO systems based on the use of Graphics Processors Units in the context of the COMPASS project. Such a solution, based on the ability of the real time core in the simulation to provide adequate computing performance, limits the cost of developing AO RTC systems and makes them more scalable. A code developed and validated in the context of the simulation may be injected directly into the system and tested on sky. Furthermore, the use of relatively low cost components also offers significant advantages for the system hardware platform. However, the use of GPUs in an AO loop comes with drawbacks: the traditional way of offloading computation from CPU to GPUs - involving multiple copies and unacceptable overhead in kernel launching - is not well suited in a real time context. This last application requires the implementation of a solution enabling direct memory access (DMA) to the GPU memory from a third party device, bypassing the operating system. This allows this device to communicate directly with the real-time core of the simulation feeding it with the WFS camera pixel stream. We show that DMA between a custom FPGA-based frame-grabber and a computation unit (GPU, FPGA, or Coprocessor such as Xeon-phi) across PCIe allows us to get latencies compatible with what will be needed on ELTs. As a fine-grained synchronization mechanism is not yet made available by GPU vendors, we propose the use of memory polling to avoid interrupts handling and involvement of a CPU. Network and Vision protocols are handled by the FPGA-based Network Interface Card (NIC). We present the results we obtained on a complete AO loop using camera and deformable mirror simulators.

  6. Real-time isotope monitoring network at the Biosphere 2 Landscape Evolution Observatory resolves meter-to-catchment scale flow dynamics

    Science.gov (United States)

    Volkmann, T. H. M.; Van Haren, J. L. M.; Kim, M.; Harman, C. J.; Pangle, L.; Meredith, L. K.; Troch, P. A.

    2017-12-01

    Stable isotope analysis is a powerful tool for tracking flow pathways, residence times, and the partitioning of water resources through catchments. However, the capacity of stable isotopes to characterize catchment hydrological dynamics has not been fully exploited as commonly used methodologies constrain the frequency and extent at which isotopic data is available across hydrologically-relevant compartments (e.g. soil, plants, atmosphere, streams). Here, building upon significant recent developments in laser spectroscopy and sampling techniques, we present a fully automated monitoring network for tracing water isotopes through the three model catchments of the Landscape Evolution Observatory (LEO) at the Biosphere 2, University of Arizona. The network implements state-of-the-art techniques for monitoring in great spatiotemporal detail the stable isotope composition of water in the subsurface soil, the discharge outflow, and the atmosphere above the bare soil surface of each of the 330-m2 catchments. The extensive valving and probing systems facilitate repeated isotope measurements from a total of more than five-hundred locations across the LEO domain, complementing an already dense array of hydrometric and other sensors installed on, within, and above each catchment. The isotope monitoring network is operational and was leveraged during several months of experimentation with deuterium-labelled rain pulse applications. Data obtained during the experiments demonstrate the capacity of the monitoring network to resolve sub-meter to whole-catchment scale flow and transport dynamics in continuous time. Over the years to come, the isotope monitoring network is expected to serve as an essential tool for collaborative interdisciplinary Earth science at LEO, allowing us to disentangle changes in hydrological behavior as the model catchments evolve in time through weathering and colonization by plant communities.

  7. The real time rolling shutter

    OpenAIRE

    Monaghan, David; O'Connor, Noel E.; Cleary, Anne; Connolly, Denis

    2015-01-01

    From an early age children are often told either, you are creative you should do art but stay away from science and maths. Or that you are mathematical you should do science but you're not that creative. Compounding this there also exist some traditional barriers of artistic rhetoric that say, "don't touch, don't think and don't be creative, we've already done that for you, you can just look...". The Real Time Rolling Shutter is part of a collaborative Art/Science partnership whose core tenet...

  8. Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula

    Science.gov (United States)

    Cazorla, Alberto; Andrés Casquero-Vera, Juan; Román, Roberto; Guerrero-Rascado, Juan Luis; Toledano, Carlos; Cachorro, Victoria E.; Orza, José Antonio G.; Cancillo, María Luisa; Serrano, Antonio; Titos, Gloria; Pandolfi, Marco; Alastuey, Andres; Hanrieder, Natalie; Alados-Arboledas, Lucas

    2017-10-01

    The interest in the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars; hence, they can be distributed in dense networks over large areas. However, due to the low signal-to-noise ratio it is not always possible to obtain particle backscatter coefficient profiles, and the vast number of data generated require an automated and unsupervised method that ensures the quality of the profiles inversions. In this work we describe a method that uses aerosol optical depth (AOD) measurements from the AERONET network that it is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with independent inversions obtained by co-located multiwavelength lidar measurements. A difference smaller than 15 % in backscatter is found between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET) and a case example during an unusually intense dust outbreak affecting the Iberian Peninsula between 20 and 24 February 2016 is shown. Results reveal that it is possible to obtain quantitative optical aerosol properties (particle backscatter coefficient) and discriminate the quality of these retrievals with ceilometers over large areas. This information has a great potential for alert systems and model assimilation and evaluation.

  9. Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula

    Directory of Open Access Journals (Sweden)

    A. Cazorla

    2017-10-01

    Full Text Available The interest in the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars; hence, they can be distributed in dense networks over large areas. However, due to the low signal-to-noise ratio it is not always possible to obtain particle backscatter coefficient profiles, and the vast number of data generated require an automated and unsupervised method that ensures the quality of the profiles inversions. In this work we describe a method that uses aerosol optical depth (AOD measurements from the AERONET network that it is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with independent inversions obtained by co-located multiwavelength lidar measurements. A difference smaller than 15 % in backscatter is found between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET and a case example during an unusually intense dust outbreak affecting the Iberian Peninsula between 20 and 24 February 2016 is shown. Results reveal that it is possible to obtain quantitative optical aerosol properties (particle backscatter coefficient and discriminate the quality of these retrievals with ceilometers over large areas. This information has a great potential for alert systems and model assimilation and evaluation.

  10. Real time analysis under EDS

    International Nuclear Information System (INIS)

    Schneberk, D.

    1985-07-01

    This paper describes the analysis component of the Enrichment Diagnostic System (EDS) developed for the Atomic Vapor Laser Isotope Separation Program (AVLIS) at Lawrence Livermore National Laboratory (LLNL). Four different types of analysis are performed on data acquired through EDS: (1) absorption spectroscopy on laser-generated spectral lines, (2) mass spectrometer analysis, (3) general purpose waveform analysis, and (4) separation performance calculations. The information produced from this data includes: measures of particle density and velocity, partial pressures of residual gases, and overall measures of isotope enrichment. The analysis component supports a variety of real-time modeling tasks, a means for broadcasting data to other nodes, and a great degree of flexibility for tailoring computations to the exact needs of the process. A particular data base structure and program flow is common to all types of analysis. Key elements of the analysis component are: (1) a fast access data base which can configure all types of analysis, (2) a selected set of analysis routines, (3) a general purpose data manipulation and graphics package for the results of real time analysis. Each of these components are described with an emphasis upon how each contributes to overall system capability. 3 figs

  11. Real-time immune-inspired optimum state-of-charge trajectory estimation using upcoming route information preview and neural networks for plug-in hybrid electric vehicles fuel economy

    Science.gov (United States)

    Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.

    2015-06-01

    The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.

  12. Development and deployment of a low-cost, mobile-ready, air quality sensor system: progress toward distributed networks and autonomous aerial sampling

    Science.gov (United States)

    Hersey, S. P.; DiVerdi, R.; Gadtaula, P.; Sheneman, T.; Flores, K.; Chen, Y. H.; Jayne, J. T.; Cross, E. S.

    2017-12-01

    Throughout the 2016-2017 academic year, a new partnership between Olin College of Engineering and Aerodyne Research, Inc. developed an affordable, self-contained air quality monitoring instrument called Modulair. The Modulair instrument is based on the same operating principles as Aerodyne's newly-developed ARISense integrated sensor system, employing electrochemical sensors for gas-phase measurements of CO, NO, NO2, and O3 and an off-the-shelf optical particle counter for particle concentration, number, and size distribution information (0.4 backend with a mobile, cloud-based data management system for real-time data posting and analysis. Open source tools and software were utilized in the development of the instrument. All initial work was completed by a team of undergraduate students as part of the Senior Capstone Program in Engineering (SCOPE) at Olin College. Deployment strategies for Modulair include distributed, mobile measurements and drone-based aerial sampling. Design goals for the drone integration include maximizing airborne sampling time and laying the foundation for software integration with the drone's autopilot system to allow for autonomous plume sampling across concentration gradients. Modulair and its flexible deployments enable real-time mapping of air quality data at exposure-relevant spatial scales, as well as regular, autonomous characterization of sources and dispersion of atmospheric pollutants. We will present an overview of the Modulair instrument and results from benchtop and field validation, including mobile and drone-based plume sampling in the Boston area.

  13. The FERMI-Elettra distributed real-time framework

    International Nuclear Information System (INIS)

    Pivetta, L.; Gaio, G.; Passuello, R.; Scalamera, G.

    2012-01-01

    FERMI-Elettra is a Free Electron Laser (FEL) based on a 1.5 GeV linac. The pulsed operation of the accelerator and the necessity to characterize and control each electron bunch requires synchronous acquisition of the beam diagnostics together with the ability to drive actuators in real-time at the linac repetition rate. The Adeos/Xenomai real-time extensions have been adopted in order to add real-time capabilities to the Linux based control system computers running the Tango software. A software communication protocol based on Gigabit Ethernet and known as Network Reflective Memory (NRM) has been developed to implement a shared memory across the whole control system, allowing computers to communicate in real-time. The NRM architecture, the real-time performance and the integration in the control system are described. (authors)

  14. Real-time solution of the forward kinematics for a parallel haptic device using a numerical approach based on neural networks

    International Nuclear Information System (INIS)

    Liu, Guan Yang; Zhang, Yuru; Wang, Yan; Xie, Zheng

    2015-01-01

    This paper proposes a neural network (NN)-based approach to solve the forward kinematics of a 3-RRR spherical parallel mechanism designed for a haptic device. The proposed algorithm aims to remarkably speed up computation to meet the requirement of high frequency rendering for haptic display. To achieve high accuracy, the workspace of the haptic device is divided into smaller subspaces. The proposed algorithm contains NNs of two different precision levels: a rough estimation NN to identify the index of the subspace and several precise estimation networks with expected accuracy to calculate the forward kinematics. For continuous motion, the algorithm structure is further simplified to save internal memory and increase computing speed, which are critical for a haptic device control system running on an embedded platform. Compared with the mostly used Newton-Raphson method, the proposed algorithm and its simplified version greatly increase the calculation speed by about four times and 10 times, respectively, while achieving the same accuracy level. The proposed approach is of great significance for solving the forward kinematics of parallel mechanism used as haptic devices when high update frequency is needed but hardware resources are limited.

  15. The rise of low-cost sensing for managing air pollution in cities.

    Science.gov (United States)

    Kumar, Prashant; Morawska, Lidia; Martani, Claudio; Biskos, George; Neophytou, Marina; Di Sabatino, Silvana; Bell, Margaret; Norford, Leslie; Britter, Rex

    2015-02-01

    Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, while addressing the major challenges for their effective implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. A Low-Cost Sensing System for Cooperative Air Quality Monitoring in Urban Areas

    Directory of Open Access Journals (Sweden)

    Simone Brienza

    2015-05-01

    Full Text Available Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring.

  17. Autonomous Real Time Requirements Tracing

    Science.gov (United States)

    Plattsmier, George; Stetson, Howard

    2014-01-01

    One of the more challenging aspects of software development is the ability to verify and validate the functional software requirements dictated by the Software Requirements Specification (SRS) and the Software Detail Design (SDD). Insuring the software has achieved the intended requirements is the responsibility of the Software Quality team and the Software Test team. The utilization of Timeliner-TLX(sup TM) Auto- Procedures for relocating ground operations positions to ISS automated on-board operations has begun the transition that would be required for manned deep space missions with minimal crew requirements. This transition also moves the auto-procedures from the procedure realm into the flight software arena and as such the operational requirements and testing will be more structured and rigorous. The autoprocedures would be required to meet NASA software standards as specified in the Software Safety Standard (NASASTD- 8719), the Software Engineering Requirements (NPR 7150), the Software Assurance Standard (NASA-STD-8739) and also the Human Rating Requirements (NPR-8705). The Autonomous Fluid Transfer System (AFTS) test-bed utilizes the Timeliner-TLX(sup TM) Language for development of autonomous command and control software. The Timeliner-TLX(sup TM) system has the unique feature of providing the current line of the statement in execution during real-time execution of the software. The feature of execution line number internal reporting unlocks the capability of monitoring the execution autonomously by use of a companion Timeliner-TLX(sup TM) sequence as the line number reporting is embedded inside the Timeliner-TLX(sup TM) execution engine. This negates I/O processing of this type data as the line number status of executing sequences is built-in as a function reference. This paper will outline the design and capabilities of the AFTS Autonomous Requirements Tracker, which traces and logs SRS requirements as they are being met during real-time execution of the

  18. Real Time Advanced Clustering System

    Directory of Open Access Journals (Sweden)

    Giuseppe Spampinato

    2017-05-01

    Full Text Available This paper describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since all the system is only based on optical flow, it is really simple and fast, to be easily integrated directly in low cost cameras. The experimental results show fast and robust performance of our method. The ANSI-C code has been tested on the ARM Cortex A15 CPU @2.32GHz, obtaining an impressive fps, about 3000 fps, excluding optical flow computation and I/O. Moreover, the system has been tested for different applications, cross traffic alert and video surveillance, in different conditions, indoor and outdoor, and with different lenses.

  19. Deployment Considerations for Low-cost Air Quality Sensor Networks; Examining Spatial Variability of Gas-Phase Pollutants Around a Building in Los Angeles

    Science.gov (United States)

    Collier-Oxandale, A. M.; Hannigan, M.; Casey, J. G.; Johnston, J.; Coffey, E.; Thorson, J.

    2017-12-01

    The field of low-cost air quality sensing technologies is growing rapidly through the continual development of new sensors, increased research into sensor performance, and more and more community groups utilizing sensors to investigate local issues. However, as this technology is still in an exploratory phase, there are few `best-practices' available to serve as guidelines for these projects and the standardization of some procedures could benefit the research community as a whole. For example, deployment considerations such as where and how to place a monitor at a given location are often determined by accessibility and safety, power-requirements, and what is an ideal for sampling the target pollutant. Using data from multiple gas-phase sensors, we will examine the importance of siting considerations for low-cost monitoring systems. During a sampling campaign in Los Angeles, a subset of monitors was deployed at one field site to explore the variability in air quality sensor data around a single building. The site is a three story, multi-family housing unit in a primarily residential neighborhood that is near two major roadways and other potential sources of pollution. Five low-cost monitors were co-located prior to and following the field deployment. During the approximately 2.5-month deployment, these monitors were placed at various heights above street level, on different sides of the building, and on the roof. In our analysis, we will examine how monitor placement affects a sensor's ability to detect local verses more regional trends and how this building-scale spatial variability changes over time. Additionally, examining data from VOC sensors (quantified for methane and total non-methane hydrocarbon signals) and O3 sensors will allow us to compare the variability of primary and secondary pollutants. An outcome of this analysis may include guidelines or `best practices' for siting sensors that could aid in ensuring the collection of high quality field data

  20. Real-time communication for distributed plasma control systems

    Energy Technology Data Exchange (ETDEWEB)

    Luchetta, A. [Consorzio RFX, Associazione Euratom-ENEA sulla Fusione, Corso Stati Uniti 4, Padova 35127 (Italy)], E-mail: adriano.luchetta@igi.cnr.it; Barbalace, A.; Manduchi, G.; Soppelsa, A.; Taliercio, C. [Consorzio RFX, Associazione Euratom-ENEA sulla Fusione, Corso Stati Uniti 4, Padova 35127 (Italy)

    2008-04-15

    Real-time control applications will benefit in the near future from the enhanced performance provided by multi-core processor architectures. Nevertheless real-time communication will continue to be critical in distributed plasma control systems where the plant under control typically is distributed over a wide area. At RFX-mod real-time communication is crucial for hard real-time plasma control, due to the distributed architecture of the system, which consists of several VMEbus stations. The system runs under VxWorks and uses Gigabit Ethernet for sub-millisecond real-time communication. To optimize communication in the system, a set of detailed measurements has been carried out on the target platforms (Motorola MVME5100 and MVME5500) using either the VxWorks User Datagram Protocol (UDP) stack or raw communication based on the data link layer. Measurements have been carried out also under Linux, using its UDP stack or, in alternative, RTnet, an open source hard real-time network protocol stack. RTnet runs under Xenomai or RTAI, two popular real-time extensions based on the Linux kernel. The paper reports on the measurements carried out and compares the results, showing that the performance obtained by using open source code is suitable for sub-millisecond real-time communication in plasma control.