WorldWideScience

Sample records for integrated wireless neural

  1. Wireless Neural Recording With Single Low-Power Integrated Circuit

    Science.gov (United States)

    Harrison, Reid R.; Kier, Ryan J.; Chestek, Cynthia A.; Gilja, Vikash; Nuyujukian, Paul; Ryu, Stephen; Greger, Bradley; Solzbacher, Florian; Shenoy, Krishna V.

    2010-01-01

    We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6-μm 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902–928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor. PMID:19497825

  2. Wireless neural recording with single low-power integrated circuit.

    Science.gov (United States)

    Harrison, Reid R; Kier, Ryan J; Chestek, Cynthia A; Gilja, Vikash; Nuyujukian, Paul; Ryu, Stephen; Greger, Bradley; Solzbacher, Florian; Shenoy, Krishna V

    2009-08-01

    We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902-928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor.

  3. Ultra low-power integrated circuit design for wireless neural interfaces

    CERN Document Server

    Holleman, Jeremy; Otis, Brian

    2014-01-01

    Presenting results from real prototype systems, this volume provides an overview of ultra low-power integrated circuits and systems for neural signal processing and wireless communication. Topics include analog, radio, and signal processing theory and design for ultra low-power circuits.

  4. A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

    2016-07-18

    Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

  5. A wireless integrated circuit for 100-channel charge-balanced neural stimulation.

    Science.gov (United States)

    Thurgood, B K; Warren, D J; Ledbetter, N M; Clark, G A; Harrison, R R

    2009-12-01

    The authors present the design of an integrated circuit for wireless neural stimulation, along with benchtop and in - vivo experimental results. The chip has the ability to drive 100 individual stimulation electrodes with constant-current pulses of varying amplitude, duration, interphasic delay, and repetition rate. The stimulation is performed by using a biphasic (cathodic and anodic) current source, injecting and retracting charge from the nervous system. Wireless communication and power are delivered over a 2.765-MHz inductive link. Only three off-chip components are needed to operate the stimulator: a 10-nF capacitor to aid in power-supply regulation, a small capacitor (power and command reception. The chip was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process. The chip was able to activate motor fibers to produce muscle twitches via a Utah Slanted Electrode Array implanted in cat sciatic nerve, and to activate sensory fibers to recruit evoked potentials in somatosensory cortex.

  6. Wireless Power Transfer Roadway Integration

    OpenAIRE

    Gardner, Trevor

    2017-01-01

    Electric vehicles represent a major accomplishment in the energy and transportation industry. Unfortunately, they are restricted to a small travel range because of limited battery life. Successful integration of wireless power transfer (WPT) systems into the infrastructure would remove the range restrictions of EVs. To successfully integrate this technology, several requirements must be met. First, the embedment process cannot interfere with the electrical performance of the inductive power t...

  7. Integration of RFID and Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    Miodrag; Bolic; Amiya; Nayak; Ivan; Stojmenovi.

    2007-01-01

    Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide limitless future potentials. However,RFID and sensor networks almost are under development in parallel way. Integration of RFID and wireless sensor networks attracts little attention from research community. This paper first presents a brief introduction on RFID,and then investigates recent research works,new products/patents and applications that integrate RFID with sensor networks. Four types of integration are discussed. They are integrating tags with sensors,integrating tags with wireless sensor nodes,integrating readers with wireless sensor nodes and wire-less devices,and mix of RFID and sensors. New challenges and future works are discussed in the end.

  8. Wireless synapses in bio-inspired neural networks

    Science.gov (United States)

    Jannson, Tomasz; Forrester, Thomas; Degrood, Kevin

    2009-05-01

    Wireless (virtual) synapses represent a novel approach to bio-inspired neural networks that follow the infrastructure of the biological brain, except that biological (physical) synapses are replaced by virtual ones based on cellular telephony modeling. Such synapses are of two types: intracluster synapses are based on IR wireless ones, while intercluster synapses are based on RF wireless ones. Such synapses have three unique features, atypical of conventional artificial ones: very high parallelism (close to that of the human brain), very high reconfigurability (easy to kill and to create), and very high plasticity (easy to modify or upgrade). In this paper we analyze the general concept of wireless synapses with special emphasis on RF wireless synapses. Also, biological mammalian (vertebrate) neural models are discussed for comparison, and a novel neural lensing effect is discussed in detail.

  9. IR wireless cluster synapses of HYDRA very large neural networks

    Science.gov (United States)

    Jannson, Tomasz; Forrester, Thomas

    2008-04-01

    RF/IR wireless (virtual) synapses are critical components of HYDRA (Hyper-Distributed Robotic Autonomy) neural networks, already discussed in two earlier papers. The HYDRA network has the potential to be very large, up to 10 11-neurons and 10 18-synapses, based on already established technologies (cellular RF telephony and IR-wireless LANs). It is organized into almost fully connected IR-wireless clusters. The HYDRA neurons and synapses are very flexible, simple, and low-cost. They can be modified into a broad variety of biologically-inspired brain-like computing capabilities. In this third paper, we focus on neural hardware in general, and on IR-wireless synapses in particular. Such synapses, based on LED/LD-connections, dominate the HYDRA neural cluster.

  10. Using Pulse Width Modulation for Wireless Transmission of Neural Signals in Multichannel Neural Recording Systems

    Science.gov (United States)

    Yin, Ming; Ghovanloo, Maysam

    2013-01-01

    We have used a well-known technique in wireless communication, pulse width modulation (PWM) of time division multiplexed (TDM) signals, within the architecture of a novel wireless integrated neural recording (WINeR) system. We have evaluated the performance of the PWM-based architecture and indicated its accuracy and potential sources of error through detailed theoretical analysis, simulations, and measurements on a setup consisting of a 15-channel WINeR prototype as the transmitter and two types of receivers; an Agilent 89600 vector signal analyzer and a custom wideband receiver, with 36 and 75 MHz of maximum bandwidth, respectively. Furthermore, we present simulation results from a realistic MATLAB-Simulink model of the entire WINeR system to observe the system behavior in response to changes in various parameters. We have concluded that the 15-ch WINeR prototype, which is fabricated in a 0.5-μm standard CMOS process and consumes 4.5 mW from ±1.5 V supplies, can acquire and wirelessly transmit up to 320 k-samples/s to a 75-MHz receiver with 8.4 bits of resolution, which is equivalent to a wireless data rate of ~ 2.26 Mb/s. PMID:19497823

  11. Smart Systems Integration for Autonomous Wireless Communications

    NARCIS (Netherlands)

    Danesh, M.

    2012-01-01

    Integration of sensors and wireless transceivers for system networking aims at emerging applications that are highly integrated, self-powered, and low cost, relying on efficient power management schemes to prolong lifetime, thus eliminating the need for batteries as a limited primary source of

  12. Artificial Neural Network for Location Estimation in Wireless Communication Systems

    Directory of Open Access Journals (Sweden)

    Chien-Sheng Chen

    2012-03-01

    Full Text Available In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS. To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA measurements and the angle of arrival (AOA information to locate MS when three base stations (BSs are available. Artificial neural networks (ANN are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line, based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  13. Artificial neural network for location estimation in wireless communication systems.

    Science.gov (United States)

    Chen, Chien-Sheng

    2012-01-01

    In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments.

  14. Integrated Passive And Wireless Sensor

    KAUST Repository

    Li, Bodong

    2015-04-30

    A passive and wireless sensor is provided for sensing at least one of magnetic field, temperature or humidity. The sensor can provide only one of the sensing functions, individually or any combination of them simultaneously. It can be used for various applications where magnetic field changes, temperature and/or humidity need to be measured. In one or more embodiments, a surface acoustic wave (SAW) sensor is provided that can measure one or more of a magnetic field (or current that generates the magnetic field), temperature and humidity. In one or more embodiments, a magnetoimpedence (MI) sensor (for example a thin film giant magnetoimpedance (GMI) sensor), a thermally sensitive (for example a Lithium Niobite (LiNbO.sub.3)) substrate, and a humidity sensitive film (for example a hydrogel film) can be used as sensing elements.

  15. Integrated Passive And Wireless Sensor

    KAUST Repository

    Li, Bodong; Kosel, Jü rgen

    2015-01-01

    A passive and wireless sensor is provided for sensing at least one of magnetic field, temperature or humidity. The sensor can provide only one of the sensing functions, individually or any combination of them simultaneously. It can be used for various applications where magnetic field changes, temperature and/or humidity need to be measured. In one or more embodiments, a surface acoustic wave (SAW) sensor is provided that can measure one or more of a magnetic field (or current that generates the magnetic field), temperature and humidity. In one or more embodiments, a magnetoimpedence (MI) sensor (for example a thin film giant magnetoimpedance (GMI) sensor), a thermally sensitive (for example a Lithium Niobite (LiNbO.sub.3)) substrate, and a humidity sensitive film (for example a hydrogel film) can be used as sensing elements.

  16. Load balancing in integrated optical wireless networks

    DEFF Research Database (Denmark)

    Yan, Ying; Dittmann, Lars; Wong, S-W.

    2010-01-01

    In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....

  17. A wirelessly powered microspectrometer for neural probe-pin device

    Science.gov (United States)

    Choi, Sang H.; Kim, Min H.; Song, Kyo D.; Yoon, Hargsoon; Lee, Uhn

    2015-12-01

    Treatment of neurological anomalies, whether done invasively or not, places stringent demands on device functionality and size. We have developed a micro-spectrometer for use as an implantable neural probe to monitor neuro-chemistry in synapses. The micro-spectrometer, based on a NASA-invented miniature Fresnel grating, is capable of differentiating the emission spectra from various brain tissues. The micro-spectrometer meets the size requirements, and is able to probe the neuro-chemistry and suppression voltage typically associated with a neural anomaly. This neural probe-pin device (PPD) is equipped with wireless power technology (WPT) to enable operation in a continuous manner without requiring an implanted battery. The implanted neural PPD, together with a neural electronics interface and WPT, enable real-time measurement and control/feedback for remediation of neural anomalies. The design and performance of the combined PPD/WPT device for monitoring dopamine in a rat brain will be presented to demonstrate the current level of development. Future work on this device will involve the addition of an embedded expert system capable of performing semi-autonomous management of neural functions through a routine of sensing, processing, and control.

  18. An implantable wireless neural interface for recording cortical circuit dynamics in moving primates

    Science.gov (United States)

    Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

    2013-04-01

    Objective. Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. Approach. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1 Hz to 7.8 kHz, 200× gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8 GHz to a receiver 1 m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7 h continuous operation between recharge via an inductive transcutaneous wireless power link at 2 MHz. Main results. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile

  19. A simple miniature device for wireless stimulation of neural circuits in small behaving animals.

    Science.gov (United States)

    Zhang, Yisi; Langford, Bruce; Kozhevnikov, Alexay

    2011-10-30

    The use of wireless neural stimulation devices offers significant advantages for neural stimulation experiments in behaving animals. We demonstrate a simple, low-cost and extremely lightweight wireless neural stimulation device which is made from off-the-shelf components. The device has low power consumption and does not require a high-power RF preamplifier. Neural stimulation can be carried out in either a voltage source mode or a current source mode. Using the device, we carry out wireless stimulation in the premotor brain area HVC of a songbird and demonstrate that such stimulation causes rapid perturbations of the acoustic structure of the song. Published by Elsevier B.V.

  20. Wireless Handheld Scanners Integrated with Waste Tracking

    International Nuclear Information System (INIS)

    Anderson, Robert Stephen

    2000-01-01

    The US Department of Energy (DOE) Idaho National Engineering and Environmental Laboratory (INEEL) has embraced mobile wireless technology to help the disposition of hazardous and mixed radiological waste. The following paper describes one application the INEEL developed to increase the data accuracy and near-real time reporting requirements for waste management. With the continuous operational demands at the ''site'', it was difficult to sustain an accurate, up-to-date database required for regulatory compliance audits and reporting. Incorporating wireless mobile technology, the INEEL was able to increase the accuracy while reducing the data delay times previously encountered. Installation issues prolonged the project along with obstacles encountered with operations personnel. However, the success of this project was found in persistence and management support as well as the technology itself. Future wireless, mobile computing will continue at the INEEL for years to come based on a successful project that was able to integrate new technology to an existing waste management system with proven, increased data accuracy

  1. Wireless power transfer and data communication for neural implants case study : epilepsy monitoring

    CERN Document Server

    Yilmaz, Gürkan

    2017-01-01

    This book presents new circuits and systems for implantable biomedical applications targeting neural recording. The authors describe a system design adapted to conform to the requirements of an epilepsy monitoring system. Throughout the book, these requirements are reflected in terms of implant size, power consumption, and data rate. In addition to theoretical background which explains the relevant technical challenges, the authors provide practical, step-by-step solutions to these problems. Readers will gain understanding of the numerical values in such a system, enabling projections for feasibility of new projects. Provides complete, system-level perspective for implantable batteryless biomedical system; Extends design example to implementation and long term in-vitro validation; Discusses system design concerns regarding wireless power transmission and wireless data communication, particularly for systems in which both are performed on the same channel/frequency; Presents fully-integrated, implantable syste...

  2. Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems

    Directory of Open Access Journals (Sweden)

    Sun-Il Chang

    2018-01-01

    Full Text Available This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM module. The core integrated circuit (IC consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm2 and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µVrms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.

  3. Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems.

    Science.gov (United States)

    Chang, Sun-Il; Park, Sung-Yun; Yoon, Euisik

    2018-01-17

    This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG) recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM) module. The core integrated circuit (IC) consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC) with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm² and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µV rms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.

  4. Trade-offs in the distribution of neural networks in a wireless sensor network

    NARCIS (Netherlands)

    Holenderski, M.J.; Lukkien, J.J.; Tham, C.K.

    2005-01-01

    This article investigates the tradeoff between communication and memory usage in different methods of distributing neural networks in a Wireless Sensor Network. A structural approach is presented, categorized in two dimensions: horizontal and vertical decomposition. Horizontal decomposition turns

  5. Wireless Integrated Microelectronic Vacuum Sensor System

    Science.gov (United States)

    Krug, Eric; Philpot, Brian; Trott, Aaron; Lawrence, Shaun

    2013-01-01

    NASA Stennis Space Center's (SSC's) large rocket engine test facility requires the use of liquid propellants, including the use of cryogenic fluids like liquid hydrogen as fuel, and liquid oxygen as an oxidizer (gases which have been liquefied at very low temperatures). These fluids require special handling, storage, and transfer technology. The biggest problem associated with transferring cryogenic liquids is product loss due to heat transfer. Vacuum jacketed piping is specifically designed to maintain high thermal efficiency so that cryogenic liquids can be transferred with minimal heat transfer. A vacuum jacketed pipe is essentially two pipes in one. There is an inner carrier pipe, in which the cryogenic liquid is actually transferred, and an outer jacket pipe that supports and seals the vacuum insulation, forming the "vacuum jacket." The integrity of the vacuum jacketed transmission lines that transfer the cryogenic fluid from delivery barges to the test stand must be maintained prior to and during engine testing. To monitor the vacuum in these vacuum jacketed transmission lines, vacuum gauge readings are used. At SSC, vacuum gauge measurements are done on a manual rotation basis with two technicians, each using a handheld instrument. Manual collection of vacuum data is labor intensive and uses valuable personnel time. Additionally, there are times when personnel cannot collect the data in a timely fashion (i.e., when a leak is detected, measurements must be taken more often). Additionally, distribution of this data to all interested parties can be cumbersome. To simplify the vacuum-gauge data collection process, automate the data collection, and decrease the labor costs associated with acquiring these measurements, an automated system that monitors the existing gauges was developed by Invocon, Inc. For this project, Invocon developed a Wireless Integrated Microelectronic Vacuum Sensor System (WIMVSS) that provides the ability to gather vacuum

  6. An Inductively-Powered Wireless Neural Recording System with a Charge Sampling Analog Front-End.

    Science.gov (United States)

    Lee, Seung Bae; Lee, Byunghun; Kiani, Mehdi; Mahmoudi, Babak; Gross, Robert; Ghovanloo, Maysam

    2016-01-15

    An inductively-powered wireless integrated neural recording system (WINeR-7) is presented for wireless and battery less neural recording from freely-behaving animal subjects inside a wirelessly-powered standard homecage. The WINeR-7 system employs a novel wide-swing dual slope charge sampling (DSCS) analog front-end (AFE) architecture, which performs amplification, filtering, sampling, and analog-to-time conversion (ATC) with minimal interference and small amount of power. The output of the DSCS-AFE produces a pseudo-digital pulse width modulated (PWM) signal. A circular shift register (CSR) time division multiplexes (TDM) the PWM pulses to create a TDM-PWM signal, which is fed into an on-chip 915 MHz transmitter (Tx). The AFE and Tx are supplied at 1.8 V and 4.2 V, respectively, by a power management block, which includes a high efficiency active rectifier and automatic resonance tuning (ART), operating at 13.56 MHz. The 8-ch system-on-a-chip (SoC) was fabricated in a 0.35-μm CMOS process, occupying 5.0 × 2.5 mm 2 and consumed 51.4 mW. For each channel, the sampling rate is 21.48 kHz and the power consumption is 19.3 μW. In vivo experiments were conducted on freely behaving rats in an energized homecage by continuously delivering 51.4 mW to the WINeR-7 system in a closed-loop fashion and recording local field potentials (LFP).

  7. Integrated resource management for Hybrid Optical Wireless (HOW) networks

    DEFF Research Database (Denmark)

    Yan, Ying; Yu, Hao; Wessing, Henrik

    2009-01-01

    Efficient utilization of available bandwidth over hybrid optical wireless networks is a critical issue, especially for multimedia applications with high data rates and stringent Quality of Service (QoS) requirements. In this paper, we propose an integrated resource management including an enhanced...... resource sharing scheme and an integrated admission control scheme for the hybrid optical wireless networks. It provides QoS guarantees for connections through both optical and wireless domain. Simulation results show that our proposed scheme improves QoS performances in terms of high throughput and low...

  8. Wireless Integrated Network Sensors Next Generation

    National Research Council Canada - National Science Library

    Merrill, William

    2004-01-01

    ..., autonomous networking, and distributed operations for wireless networked sensor systems. Multiple types of sensor systems were developed and provided including capabilities for acoustic, seismic, passive infrared detection, and visual imaging...

  9. Integrated Frequency Synthesis for Convergent Wireless Solutions

    CERN Document Server

    Atallah, Jad G

    2012-01-01

    This book describes the design and implementation of an electronic subsystem called the frequency synthesizer, which is a very important building block for any wireless transceiver. The discussion includes several new techniques for the design of such a subsystem which include the usage modes of the wireless device, including its support for several leading-edge wireless standards. This new perspective for designing such a demanding subsystem is based on the fact that optimizing the performance of a complete system is not always achieved by optimizing the performance of its building blocks separately.  This book provides “hands-on” examples of this sort of co-design of optimized subsystems, which can make the vision of an always-best-connected scenario a reality. Provides up-to-date design information regarding one of the most complex subsystems used in state-of-the-art wireless devices; Describes a wireless front-end solution designed to provide an always-best-connected solution, based on a wireless det...

  10. Wireless SAW Sensors Having Integrated Antennas

    Science.gov (United States)

    Gallagher, Mark (Inventor); Malocha, Donald C. (Inventor)

    2015-01-01

    A wireless surface acoustic wave sensor includes a piezoelectric substrate, a surface acoustic wave device formed on the substrate, and an antenna formed on the substrate. In some embodiments, the antenna is formed on the surface of the substrate using one or more of photolithography, thin film processing, thick film processing, plating, and printing.

  11. Integrated control platform for converged optical and wireless networks

    DEFF Research Database (Denmark)

    Yan, Ying

    The next generation of broadband access networks is expected to be heterogeneous. Multiple wired and wireless systems can be integrated, in order to simultaneously provide seamless access with an appropriate Quality of Service (QoS). Wireless networks support ubiquitous connectivity yet low data...... rates, whereas optical networks can offer much higher data rates but only provide fixed connection structures. Their complementary characteristics make the integration of the two networks a promising trend for next generation networks. With combined strengths, the converged network will provide both...... the complementary characteristics of the optical networks and the wireless networks, addresses motivations for their interworking, discusses the current progress in hybrid network architectures as well as the functionalities of a control system, and identifies the achieved research contributions in the integrated...

  12. Battery-Free Love-Wave-Based Neural Probe and Its Wireless Characterizations

    Science.gov (United States)

    Jung, In Ki; Fu, Chen; Lee, Keekeun

    2013-06-01

    A wireless Love-wave-based neural probe that utilizes a one-port reflective delay line was developed for both reading and stimulating neurons in the brain. Poly(methyl methacrylate) (PMMA) as a waveguide layer and gold (Au) electrodes were structured on the top of a 41° YX LiNbO3 piezoelectric substrate, following the parameters extracted from coupling-of-mode (COM) modeling. For a one-port reflective delay line, single-phase unidirectional transducers (SPUDTs) and three shorted grating reflectors were employed, which made possible the implementation of a wireless and battery-free neural probe. The fabricated Love-wave-based neural probes were wirelessly measured using two antennas with a 440 MHz central frequency and a network analyzer. Sharp reflection peaks with a high signal-to-noise ratio were observed from the reflection peaks. The probe was immersed in 0.9% saline solution while applying input DC voltages. Good linearity, high sensitivity, and reproducibility were observed depending on DC applied voltage, in the range from 0 to 500 mV. The sensitivity obtained from the DC firings (artificial neural firings) was ˜0.04 µs/VDC, indicating that this prototype probe is very promising for the wireless reading and stimulation of neural firings in in vivo animal testing.

  13. Energy scavenging system by acoustic wave and integrated wireless communication

    Science.gov (United States)

    Kim, Albert

    The purpose of the project was developing an energy-scavenging device for other bio implantable devices. Researchers and scientist have studied energy scavenging method because of the limitation of traditional power source, especially for bio-implantable devices. In this research, piezoelectric power generator that activates by acoustic wave, or music was developed. Follow by power generator, a wireless communication also integrated with the device for monitoring the power generation. The Lead Zirconate Titanate (PZT) bimorph cantilever with a proof mass at the free end tip was studied to convert acoustic wave to power. The music or acoustic wave played through a speaker to vibrate piezoelectric power generator. The LC circuit integrated with the piezoelectric material for purpose of wireless monitoring power generation. However, wireless monitoring can be used as wireless power transmission, which means the signal received via wireless communication also can be used for power for other devices. Size of 74 by 7 by 7cm device could generate and transmit 100mVp from 70 mm distance away with electrical resonant frequency at 420.2 kHz..

  14. A Wireless Fully Passive Neural Recording Device for Unobtrusive Neuropotential Monitoring.

    Science.gov (United States)

    Kiourti, Asimina; Lee, Cedric W L; Chae, Junseok; Volakis, John L

    2016-01-01

    We propose a novel wireless fully passive neural recording device for unobtrusive neuropotential monitoring. Previous work demonstrated the feasibility of monitoring emulated brain signals in a wireless fully passive manner. In this paper, we propose a novel realistic recorder that is significantly smaller and much more sensitive. The proposed recorder utilizes a highly efficient microwave backscattering method and operates without any formal power supply or regulating elements. Also, no intracranial wires or cables are required. In-vitro testing is performed inside a four-layer head phantom (skin, bone, gray matter, and white matter). Compared to our former implementation, the neural recorder proposed in this study has the following improved features: 1) 59% smaller footprint, 2) up to 20-dB improvement in neuropotential detection sensitivity, and 3) encapsulation in biocompatible polymer. For the first time, temporal emulated neuropotentials as low as 63 μVpp can be detected in a wireless fully passive manner. Remarkably, the high-sensitivity achieved in this study implies reading of most neural signals generated by the human brain. The proposed recorder brings forward transformational possibilities in wireless fully passive neural detection for a very wide range of applications (e.g., epilepsy, Alzheimer's, mental disorders, etc.).

  15. An externally head-mounted wireless neural recording device for laboratory animal research and possible human clinical use.

    Science.gov (United States)

    Yin, Ming; Li, Hao; Bull, Christopher; Borton, David A; Aceros, Juan; Larson, Lawrence; Nurmikko, Arto V

    2013-01-01

    In this paper we present a new type of head-mounted wireless neural recording device in a highly compact package, dedicated for untethered laboratory animal research and designed for future mobile human clinical use. The device, which takes its input from an array of intracortical microelectrode arrays (MEA) has ninety-seven broadband parallel neural recording channels and was integrated on to two custom designed printed circuit boards. These house several low power, custom integrated circuits, including a preamplifier ASIC, a controller ASIC, plus two SAR ADCs, a 3-axis accelerometer, a 48MHz clock source, and a Manchester encoder. Another ultralow power RF chip supports an OOK transmitter with the center frequency tunable from 3GHz to 4GHz, mounted on a separate low loss dielectric board together with a 3V LDO, with output fed to a UWB chip antenna. The IC boards were interconnected and packaged in a polyether ether ketone (PEEK) enclosure which is compatible with both animal and human use (e.g. sterilizable). The entire system consumes 17mA from a 1.2Ahr 3.6V Li-SOCl2 1/2AA battery, which operates the device for more than 2 days. The overall system includes a custom RF receiver electronics which are designed to directly interface with any number of commercial (or custom) neural signal processors for multi-channel broadband neural recording. Bench-top measurements and in vivo testing of the device in rhesus macaques are presented to demonstrate the performance of the wireless neural interface.

  16. Photonic integrated circuits for millimeter-wave wireless communications

    NARCIS (Netherlands)

    Carpintero, G.; Balakier, K.; Yang, Z.; Guzmán, R.C.; Corradi, A.; Jimenez, A.; Kervalla, G.; Fice, M.; Lamponi, M.; Chtioui, M.; Van Dijk, Frédéric; Renaud, C.C.; Wonfor, A.; Bente, E.A.J.M.; Penty, R.V.; White, I.H.; Seeds, A.J.

    2014-01-01

    This paper describes the advantages that the introduction of photonic integration technologies can bring to the development of photonic-enabled wireless communications systems operating in the millimeter wave frequency range. We present two approaches for the development of dual wavelength sources

  17. Seamless integrated network system for wireless communication systems

    NARCIS (Netherlands)

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

    2006-01-01

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

  18. Seamless integrated network system for wireless communication systems

    NARCIS (Netherlands)

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

    2002-01-01

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

  19. System-level Modeling of Wireless Integrated Sensor Networks

    DEFF Research Database (Denmark)

    Virk, Kashif M.; Hansen, Knud; Madsen, Jan

    2005-01-01

    Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

  20. An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode.

    Science.gov (United States)

    Shon, Ahnsei; Chu, Jun-Uk; Jung, Jiuk; Kim, Hyungmin; Youn, Inchan

    2017-12-21

    Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS) components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC)-compliant power transmission circuit, a medical implant communication service (MICS)-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

  1. An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode

    Directory of Open Access Journals (Sweden)

    Ahnsei Shon

    2017-12-01

    Full Text Available Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC-compliant power transmission circuit, a medical implant communication service (MICS-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

  2. A wireless transmission neural interface system for unconstrained non-human primates.

    Science.gov (United States)

    Fernandez-Leon, Jose A; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J; Hansen, Bryan J; Hu, Ming; Dragoi, Valentin

    2015-10-01

    Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.

  3. A wireless transmission neural interface system for unconstrained non-human primates

    Science.gov (United States)

    Fernandez-Leon, Jose A.; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J.; Hansen, Bryan J.; Hu, Ming; Dragoi, Valentin

    2015-10-01

    Objective. Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. Approach. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. Main results. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. Significance. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.

  4. Integrated cable vibration control system using wireless sensors

    Science.gov (United States)

    Jeong, Seunghoo; Cho, Soojin; Sim, Sung-Han

    2017-04-01

    As the number of long-span bridges is increasing worldwide, maintaining their structural integrity and safety become an important issue. Because the stay cable is a critical member in most long-span bridges and vulnerable to wind-induced vibrations, vibration mitigation has been of interest both in academia and practice. While active and semi-active control schemes are known to be quite effective in vibration reduction compared to the passive control, requirements for equipment including data acquisition, control devices, and power supply prevent a widespread adoption in real-world applications. This study develops an integrated system for vibration control of stay-cables using wireless sensors implementing a semi-active control. Arduino, a low-cost single board system, is employed with a MEMS digital accelerometer and a Zigbee wireless communication module to build the wireless sensor. The magneto-rheological (MR) damper is selected as a damping device, controlled by an optimal control algorithm implemented on the Arduino sensing system. The developed integrated system is tested in a laboratory environment using a cable to demonstrate the effectiveness of the proposed system on vibration reduction. The proposed system is shown to reduce the vibration of stay-cables with low operating power effectively.

  5. A wireless sensor tag platform for container security and integrity

    Science.gov (United States)

    Amaya, Ivan A.; Cree, Johnathan V.; Mauss, Fredrick J.

    2011-04-01

    Cargo containers onboard ships are widely used in the global supply chain. The need for container security is evidenced by the Container Security Initiative launched by the U.S. Bureau of Customs and Border Protection (CBP). One method of monitoring cargo containers is using low power wireless sensor tags. The wireless sensor tags are used to set up a network that is comprised of tags internal to the container and a central device. The sensor network reports alarms and other anomalies to a central device, which then relays the message to an outside network upon arrival at the destination port. This allows the port authorities to have knowledge of potential security or integrity issues before physically examining the container. Challenges of using wireless sensor tag networks for container security include battery life, size, environmental conditions, information security, and cost among others. PNNL developed an active wireless sensor tag platform capable of reporting data wirelessly to a central node as well as logging data to nonvolatile memory. The tags, operate at 2.4 GHz over an IEEE 802.15.4 protocol, and were designed to be distributed throughout the inside of a shipping container in the upper support frame. The tags are mounted in a housing that allows for simple and efficient installation or removal prior to, during, or after shipment. The distributed tags monitor the entire container volume. The sensor tag platform utilizes low power electronics and provides an extensible sensor interface for incorporating a wide range of sensors including chemical, biological, and environmental sensors.

  6. Integrating neural network technology and noise analysis

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Oak Ridge National Lab., TN

    1995-01-01

    The integrated use of neural network and noise analysis technologies offers advantages not available by the use of either technology alone. The application of neural network technology to noise analysis offers an opportunity to expand the scope of problems where noise analysis is useful and unique ways in which the integration of these technologies can be used productively. The two-sensor technique, in which the responses of two sensors to an unknown driving source are related, is used to demonstration such integration. The relationship between power spectral densities (PSDs) of accelerometer signals is derived theoretically using noise analysis to demonstrate its uniqueness. This relationship is modeled from experimental data using a neural network when the system is working properly, and the actual PSD of one sensor is compared with the PSD of that sensor predicted by the neural network using the PSD of the other sensor as an input. A significant deviation between the actual and predicted PSDs indicate that system is changing (i.e., failing). Experiments carried out on check values and bearings illustrate the usefulness of the methodology developed. (Author)

  7. 3D Integration for Wireless Multimedia

    Science.gov (United States)

    Kimmich, Georg

    The convergence of mobile phone, internet, mapping, gaming and office automation tools with high quality video and still imaging capture capability is becoming a strong market trend for portable devices. High-density video encode and decode, 3D graphics for gaming, increased application-software complexity and ultra-high-bandwidth 4G modem technologies are driving the CPU performance and memory bandwidth requirements close to the PC segment. These portable multimedia devices are battery operated, which requires the deployment of new low-power-optimized silicon process technologies and ultra-low-power design techniques at system, architecture and device level. Mobile devices also need to comply with stringent silicon-area and package-volume constraints. As for all consumer devices, low production cost and fast time-to-volume production is key for success. This chapter shows how 3D architectures can bring a possible breakthrough to meet the conflicting power, performance and area constraints. Multiple 3D die-stacking partitioning strategies are described and analyzed on their potential to improve the overall system power, performance and cost for specific application scenarios. Requirements and maturity of the basic process-technology bricks including through-silicon via (TSV) and die-to-die attachment techniques are reviewed. Finally, we highlight new challenges which will arise with 3D stacking and an outlook on how they may be addressed: Higher power density will require thermal design considerations, new EDA tools will need to be developed to cope with the integration of heterogeneous technologies and to guarantee signal and power integrity across the die stack. The silicon/wafer test strategies have to be adapted to handle high-density IO arrays, ultra-thin wafers and provide built-in self-test of attached memories. New standards and business models have to be developed to allow cost-efficient assembly and testing of devices from different silicon and technology

  8. Integrated Neural Flight and Propulsion Control System

    Science.gov (United States)

    Kaneshige, John; Gundy-Burlet, Karen; Norvig, Peter (Technical Monitor)

    2001-01-01

    This paper describes an integrated neural flight and propulsion control system. which uses a neural network based approach for applying alternate sources of control power in the presence of damage or failures. Under normal operating conditions, the system utilizes conventional flight control surfaces. Neural networks are used to provide consistent handling qualities across flight conditions and for different aircraft configurations. Under damage or failure conditions, the system may utilize unconventional flight control surface allocations, along with integrated propulsion control, when additional control power is necessary for achieving desired flight control performance. In this case, neural networks are used to adapt to changes in aircraft dynamics and control allocation schemes. Of significant importance here is the fact that this system can operate without emergency or backup flight control mode operations. An additional advantage is that this system can utilize, but does not require, fault detection and isolation information or explicit parameter identification. Piloted simulation studies were performed on a commercial transport aircraft simulator. Subjects included both NASA test pilots and commercial airline crews. Results demonstrate the potential for improving handing qualities and significantly increasing survivability rates under various simulated failure conditions.

  9. Toward a distributed free-floating wireless implantable neural recording system.

    Science.gov (United States)

    Pyungwoo Yeon; Xingyuan Tong; Byunghun Lee; Mirbozorgi, Abdollah; Ash, Bruce; Eckhardt, Helmut; Ghovanloo, Maysam

    2016-08-01

    To understand the complex correlations between neural networks across different regions in the brain and their functions at high spatiotemporal resolution, a tool is needed for obtaining long-term single unit activity (SUA) across the entire brain area. The concept and preliminary design of a distributed free-floating wireless implantable neural recording (FF-WINeR) system are presented, which can enabling SUA acquisition by dispersedly implanting tens to hundreds of untethered 1 mm3 neural recording probes, floating with the brain and operating wirelessly across the cortical surface. For powering FF-WINeR probes, a 3-coil link with an intermediate high-Q resonator provides a minimum S21 of -22.22 dB (in the body medium) and -21.23 dB (in air) at 2.8 cm coil separation, which translates to 0.76%/759 μW and 0.6%/604 μW of power transfer efficiency (PTE) / power delivered to a 9 kΩ load (PDL), in body and air, respectively. A mock-up FF-WINeR is implemented to explore microassembly method of the 1×1 mm2 micromachined silicon die with a bonding wire-wound coil and a tungsten micro-wire electrode. Circuit design methods to fit the active circuitry in only 0.96 mm2 of die area in a 130 nm standard CMOS process, and satisfy the strict power and performance requirements (in simulations) are discussed.

  10. Improved Selectivity From a Wavelength Addressable Device for Wireless Stimulation of Neural Tissue

    Directory of Open Access Journals (Sweden)

    Elif Ç. Seymour

    2014-02-01

    Full Text Available Electrical neural stimulation with micro electrodes is a promising technique for restoring lost functions in the central nervous system as a result of injury or disease. One of the problems related to current neural stimulators is the tissue response due to the connecting wires and the presence of a rigid electrode inside soft neural tissue. We have developed a novel, optically activated, microscale photovoltaic neurostimulator based on a custom layered compound semiconductor heterostructure that is both wireless and has a comparatively small volume. Optical activation provides a wireless means of energy transfer to the neurostimulator, eliminating wires and the associated complications. This neurostimulator was shown to evoke action potentials and a functional motor response in the rat spinal cord. In this work, we extend our design to include wavelength selectivity and thus allowing independent activation of devices. As a proof of concept, we fabricated two different microscale devices with different spectral responsivities in the near-infrared region. We assessed the improved addressability of individual devices via wavelength selectivity as compared to spatial selectivity alone through on-bench optical measurements of the devices in combination with an in vivo light intensity profile in the rat cortex obtained in a previous study. We show that wavelength selectivity improves the individual addressability of the floating stimulators, thus increasing the number of devices that can be implanted in close proximity to each other.

  11. Studies in RF power communication, SAR, and temperature elevation in wireless implantable neural interfaces.

    Directory of Open Access Journals (Sweden)

    Yujuan Zhao

    Full Text Available Implantable neural interfaces are designed to provide a high spatial and temporal precision control signal implementing high degree of freedom real-time prosthetic systems. The development of a Radio Frequency (RF wireless neural interface has the potential to expand the number of applications as well as extend the robustness and longevity compared to wired neural interfaces. However, it is well known that RF signal is absorbed by the body and can result in tissue heating. In this work, numerical studies with analytical validations are performed to provide an assessment of power, heating and specific absorption rate (SAR associated with the wireless RF transmitting within the human head. The receiving antenna on the neural interface is designed with different geometries and modeled at a range of implanted depths within the brain in order to estimate the maximum receiving power without violating SAR and tissue temperature elevation safety regulations. Based on the size of the designed antenna, sets of frequencies between 1 GHz to 4 GHz have been investigated. As expected the simulations demonstrate that longer receiving antennas (dipole and lower working frequencies result in greater power availability prior to violating SAR regulations. For a 15 mm dipole antenna operating at 1.24 GHz on the surface of the brain, 730 uW of power could be harvested at the Federal Communications Commission (FCC SAR violation limit. At approximately 5 cm inside the head, this same antenna would receive 190 uW of power prior to violating SAR regulations. Finally, the 3-D bio-heat simulation results show that for all evaluated antennas and frequency combinations we reach FCC SAR limits well before 1 °C. It is clear that powering neural interfaces via RF is possible, but ultra-low power circuit designs combined with advanced simulation will be required to develop a functional antenna that meets all system requirements.

  12. A low-cost multichannel wireless neural stimulation system for freely roaming animals

    Science.gov (United States)

    Alam, Monzurul; Chen, Xi; Fernandez, Eduardo

    2013-12-01

    Objectives. Electrical stimulation of nerve tissue and recording of neural activity are the basis of many therapies and neural prostheses. Conventional stimulation systems have a number of practical limitations, especially in experiments involving freely roaming subjects. Our main objective was to develop a modular, versatile and inexpensive multichannel wireless system able to overcome some of these constraints. Approach. We have designed and implemented a new multichannel wireless neural stimulator based on commercial components. The system is small (2 cm × 4 cm × 0.5 cm) and light in weight (9 g) which allows it to be easily carried in a small backpack. To test and validate the performance and reliability of the whole system we conducted several bench tests and in vivo experiments. Main results. The performance and accuracy of the stimulator were comparable to commercial threaded systems. Stimulation sequences can be constructed on-the-fly with 251 selectable current levels (from 0 to 250 µA) with 1 µA step resolution. The pulse widths and intervals can be as long as 65 ms in 2 µs time resolution. The system covers approximately 10 m of transmission range in a regular laboratory environment and 100 m in free space (line of sight). Furthermore it provides great flexibility for experiments since it allows full control of the stimulator and the stimulation parameters in real time. When there is no stimulation, the device automatically goes into low-power sleep mode to preserve battery power. Significance. We introduce the design of a powerful multichannel wireless stimulator assembled from commercial components. Key features of the system are their reliability, robustness and small size. The system has a flexible design that can be modified straightforwardly to tailor it to any specific experimental need. Furthermore it can be effortlessly adapted for use with any kind of multielectrode arrays.

  13. Fabrication and Microassembly of a mm-Sized Floating Probe for a Distributed Wireless Neural Interface

    Directory of Open Access Journals (Sweden)

    Pyungwoo Yeon

    2016-09-01

    Full Text Available A new class of wireless neural interfaces is under development in the form of tens to hundreds of mm-sized untethered implants, distributed across the target brain region(s. Unlike traditional interfaces that are tethered to a centralized control unit and suffer from micromotions that may damage the surrounding neural tissue, the new free-floating wireless implantable neural recording (FF-WINeR probes will be stand-alone, directly communicating with an external interrogator. Towards development of the FF-WINeR, in this paper we describe the micromachining, microassembly, and hermetic packaging of 1-mm3 passive probes, each of which consists of a thinned micromachined silicon die with a centered Ø(diameter 130 μm through-hole, an Ø81 μm sharpened tungsten electrode, a 7-turn gold wire-wound coil wrapped around the die, two 0201 surface mount capacitors on the die, and parylene-C/Polydimethylsiloxane (PDMS coating. The fabricated passive probe is tested under a 3-coil inductive link to evaluate power transfer efficiency (PTE and power delivered to a load (PDL for feasibility assessment. The minimum PTE/PDL at 137 MHz were 0.76%/240 μW and 0.6%/191 μW in the air and lamb head medium, respectively, with coil separation of 2.8 cm and 9 kΩ receiver (Rx loading. Six hermetically sealed probes went through wireless hermeticity testing, using a 2-coil inductive link under accelerated lifetime testing condition of 85 °C, 1 atm, and 100%RH. The mean-time-to-failure (MTTF of the probes at 37 °C is extrapolated to be 28.7 years, which is over their lifetime.

  14. Integrated 3d printed wireless sensing system for environmental monitoring

    KAUST Repository

    Farooqui, Muhammad Fahad; Shamim, Atif

    2017-01-01

    transmitters on a panel. The wireless sensor device may be configured to take environment measurements, such as temperature, gas, humidity, and wirelessly communicate the environment measurements to a remote computing device, in addition, the present disclosure

  15. Wireless Amperometric Neurochemical Monitoring Using an Integrated Telemetry Circuit

    Science.gov (United States)

    Roham, Masoud; Halpern, Jeffrey M.; Martin, Heidi B.; Chiel, Hillel J.

    2015-01-01

    An integrated circuit for wireless real-time monitoring of neurochemical activity in the nervous system is described. The chip is capable of conducting high-resolution amperometric measurements in four settings of the input current. The chip architecture includes a first-order ΔΣ modulator (ΔΣM) and a frequency-shift-keyed (FSK) voltage-controlled oscillator (VCO) operating near 433 MHz. It is fabricated using the AMI 0.5 μm double-poly triple-metal n-well CMOS process, and requires only one off-chip component for operation. Measured dc current resolutions of ~250 fA, ~1.5 pA, ~4.5 pA, and ~17 pA were achieved for input currents in the range of ±5, ±37, ±150, and ±600 nA, respectively. The chip has been interfaced with a diamond-coated, quartz-insulated, microneedle, tungsten electrode, and successfully recorded dopamine concentration levels as low as 0.5 μM wirelessly over a transmission distance of ~0.5 m in flow injection analysis experiments. PMID:18990633

  16. Wireless amperometric neurochemical monitoring using an integrated telemetry circuit.

    Science.gov (United States)

    Roham, Masoud; Halpern, Jeffrey M; Martin, Heidi B; Chiel, Hillel J; Mohseni, Pedram

    2008-11-01

    An integrated circuit for wireless real-time monitoring of neurochemical activity in the nervous system is described. The chip is capable of conducting high-resolution amperometric measurements in four settings of the input current. The chip architecture includes a first-order Delta Sigma modulator (Delta Sigma M) and a frequency-shift-keyed (FSK) voltage-controlled oscillator (VCO) operating near 433 MHz. It is fabricated using the AMI 0.5 microm double-poly triple-metal n-well CMOS process, and requires only one off-chip component for operation. Measured dc current resolutions of approximately 250 fA, approximately 1.5 pA, approximately 4.5 pA, and approximately 17 pA were achieved for input currents in the range of +/-5, +/-37, +/-150, and +/-600 nA, respectively. The chip has been interfaced with a diamond-coated, quartz-insulated, microneedle, tungsten electrode, and successfully recorded dopamine concentration levels as low as 0.5 microM wirelessly over a transmission distance of approximately 0.5 m in flow injection analysis experiments.

  17. LRN, ERN:, & BERN @ Wireless Integrating the Sciences (WITS) Theatre

    Science.gov (United States)

    Hilliard, L.; Campbell, B.; Foody, M.; Klitsner, D.

    2010-01-01

    In order to develop a call to action for a learning tool that would work to best teach Science Technology Engineering and Math (STEM), the NASA Goddard team will partner with the inventor of Bop It!, an interactive game of verbs and following instructions; and Global Imagination, the developers of Magic Planet. In this paper Decision-making Orbital Health! (DOH!) will be described as a game derived from the basic functions necessary for Bop lt!, a familiar game. that will ask the educational audience to respond to changing commands to Bop It!, Twist It!, and Squeeze It! The success of the new version of the game, will be that the Earth will be making these commands from Dynamic Planet, and the crowd assembled can play wirelessly. Wireless Integrating The Sciences (WITS) Theatre : A balanced approach will describe how the communities local to Goddard and perhaps San Francisco will develop curriculum that helps kids teach kids with an engaging game and a STEM message. The performing arts will be employed to make it entertaining and appropriate to the size of the gathering, and the students educational level.

  18. Low Power Consumption Wireless Sensor Communication System Integrated with an Energy Harvesting Power Source

    OpenAIRE

    Vlad MARSIC; Alessandro GIULIANO; Meiling ZHU

    2013-01-01

    This paper presents the testing results of a wireless sensor communication system with low power consumption integrated with an energy harvesting power source. The experiments focus on the system’s capability to perform continuous monitoring and to wirelessly transmit the data acquired from the sensors to a user base station, for realization of completely battery-free wireless sensor system. Energy harvesting technologies together with system design optimization for power consumption minimiza...

  19. Implantable neurotechnologies: a review of integrated circuit neural amplifiers.

    Science.gov (United States)

    Ng, Kian Ann; Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V

    2016-01-01

    Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

  20. Millimeter wave beam steered fiber wireless systems for 5G indoor coverage : Integrated circuits and systems

    NARCIS (Netherlands)

    Cao, Zizheng; Zhang, Xuebing; Zhao, Xinran; Shen, Longfei; Deng, Xiong; Yin, Xin; Koonen, Ton

    2017-01-01

    In this talk, we review our recent progress and on-going research on millimeter wave beam steered fiber wireless systems for 5G indoor coverage enabled by the advanced photonic integrated circuit and well-designed fiber-wireless networks.

  1. mm-Wave Wireless Communications based on Silicon Photonics Integrated Circuits

    DEFF Research Database (Denmark)

    Rommel, Simon; Heck, Martijn; Vegas Olmos, Juan José

    Hybrid photonic-wireless transmission schemes in the mm-wave frequency range are promising candidates to enable the multi-gigabit per second data communications required from wireless and mobile networks of the 5th and future generations. Photonic integration may pave the way to practical applica...

  2. Silicon Photonics Integrated Circuits for 5th Generation mm-Wave Wireless Communications

    DEFF Research Database (Denmark)

    Rommel, Simon; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso

    Hybrid photonic-wireless transmission schemes in the mm-wave frequency are promising candidates to enable the multi-gigabit per second data communications required from wireless and mobile networks of the 5th and future generations. Photonic integration may pave the way to practical applicability...

  3. Wireless, smartphone controlled potentiostat integrated with lab-on-disc platform

    DEFF Research Database (Denmark)

    Cheng, Chung-Hsiang; Zor, Kinga; Wang, Jen-Hung

    A smartphone controlled wireless data transmitting and inductive powering Power Lab-on-disc (PLoD) platform is developed based on 2.4 GHz Bluetooth and 205 kHz Qi techniques, respectively. A potentiostat is integrated on the PLoD platform, and amperometric measurements are performed. The wireless...

  4. Integrating wireless sensor network for monitoring subsidence phenomena

    Science.gov (United States)

    Marturià, Jordi; Lopez, Ferran; Gigli, Giovanni; Intrieri, Emanuele; Mucchi, Lorenzo; Fornaciai, Alessandro

    2016-04-01

    An innovative wireless sensor network (WSN) for the 3D superficial monitoring of deformations (such as landslides and subsidence) is being developed in the frame of the Wi-GIM project (Wireless sensor network for Ground Instability Monitoring - LIFE12 ENV/IT/001033). The surface movement is detected acquiring the position (x, y and z) by integrating large bandwidth technology able to detect the 3D coordinates of the sensor with a sub-meter error, with continuous wave radar, which allows decreasing the error down to sub-cm. The Estació neighborhood in Sallent is located over the old potassium mine Enrique. This zone has been affected by a subsidence process over more than twenty years. The implementation of a wide network for ground auscultation has allowed monitoring the process of subsidence since 1997. This network consists of: i) a high-precision topographic leveling network to control the subsidence in surface; ii) a rod extensometers network to monitor subsurface deformation; iii) an automatic Leica TCA Total Station to monitor building movements; iv) an inclinometers network to measure the horizontal displacements on subsurface and v) a piezometer to measure the water level. Those networks were implemented within an alert system for an organized an efficient response of the civil protection authorities in case of an emergency. On 23rd December 2008, an acceleration of subsoil movements (of approx. 12-18 cm/year) provoked the activation of the emergency plan by the Catalan Civil Protection. This implied the preventive and scheduled evacuation of the neighbours (January 2009) located in the area with a higher risk of collapse: around 120 residents of 43 homes. As a consequence, the administration implemented a compensation plan for the evacuation of the whole neighbourhood residents and the demolition of 405 properties. In this work, the adaptation and integration process of Wi-GIM system with those conventional monitoring network are presented for its testing

  5. Wireless Indoor Location Estimation Based on Neural Network RSS Signature Recognition (LENSR)

    Energy Technology Data Exchange (ETDEWEB)

    Kurt Derr; Milos Manic

    2008-06-01

    Location Based Services (LBS), context aware applications, and people and object tracking depend on the ability to locate mobile devices, also known as localization, in the wireless landscape. Localization enables a diverse set of applications that include, but are not limited to, vehicle guidance in an industrial environment, security monitoring, self-guided tours, personalized communications services, resource tracking, mobile commerce services, guiding emergency workers during fire emergencies, habitat monitoring, environmental surveillance, and receiving alerts. This paper presents a new neural network approach (LENSR) based on a competitive topological Counter Propagation Network (CPN) with k-nearest neighborhood vector mapping, for indoor location estimation based on received signal strength. The advantage of this approach is both speed and accuracy. The tested accuracy of the algorithm was 90.6% within 1 meter and 96.4% within 1.5 meters. Several approaches for location estimation using WLAN technology were reviewed for comparison of results.

  6. A wideband wireless neural stimulation platform for high-density microelectrode arrays.

    Science.gov (United States)

    Myers, Frank B; Simpson, Jim A; Ghovanloo, Maysam

    2006-01-01

    We describe a system that allows researchers to control an implantable neural microstimulator from a PC via a USB 2.0 interface and a novel dual-carrier wireless link, which provides separate data and power transmission. Our wireless stimulator, Interestim-2B (IS-2B), is a modular device capable of generating controlled-current stimulation pulse trains across 32 sites per module with support for a variety of stimulation schemes (biphasic/monophasic, bipolar/monopolar). We have developed software to generate multi-site stimulation commands for the IS-2B based on streaming data from artificial sensory devices such as cameras and microphones. For PC interfacing, we have developed a USB 2.0 microcontroller-based interface. Data is transmitted using frequency-shift keying (FSK) at 6/12 MHz to achieve a data rate of 3 Mb/s via a pair of rectangular coils. Power is generated using a class-E power amplifier operating at 1 MHz and transmitted via a separate pair of spiral planar coils which are oriented perpendicular to the data coils to minimize cross-coupling. We have successfully demonstrated the operation of the system by applying it as a visual prosthesis. Pulse-frequency modulated stimuli are generated in real-time based on a grayscale image from a webcam. These pulses are projected onto an 11x11 LED matrix that represents a 2D microelectrode array.

  7. 3D-Printed Disposable Wireless Sensors with Integrated Microelectronics for Large Area Environmental Monitoring

    KAUST Repository

    Farooqui, Muhammad Fahad; Karimi, Muhammad Akram; Salama, Khaled N.; Shamim, Atif

    2017-01-01

    disposable, compact, dispersible 3D-printed wireless sensor nodes with integrated microelectronics which can be dispersed in the environment and work in conjunction with few fixed nodes for large area monitoring applications. As a proof of concept

  8. Investigation of interference in multiple-input multiple-output wireless transmission at W band for an optical wireless integration system.

    Science.gov (United States)

    Li, Xinying; Yu, Jianjun; Dong, Ze; Zhang, Junwen; Chi, Nan; Yu, Jianguo

    2013-03-01

    We experimentally investigate the interference in multiple-input multiple-output (MIMO) wireless transmission by adjusting the relative locations of horn antennas (HAs) in a 100 GHz optical wireless integration system, which can deliver a 50 Gb/s polarization-division-multiplexing quadrature-phase-shift-keying signal over 80 km single-mode fiber-28 and a 2×2 MIMO wireless link. For the parallel 2×2 MIMO wireless link, each receiver HA can only get wireless power from the corresponding transmitter HA, while for the crossover ones, the receiver HA can get wireless power from two transmitter HAs. At the wireless receiver, polarization demultiplexing is realized by the constant modulus algorithm (CMA) in the digital-signal-processing part. Compared to the parallel case, wireless interference causes about 2 dB optical signal-to-noise ratio penalty at a bit-error ratio (BER) of 3.8×10(-3) for the crossover cases if similar CMA taps are employed. The increase in CMA tap length can reduce wireless interference and improve BER performance. Furthermore, more CMA taps should be adopted to overcome the severe wireless interference when two pairs of transmitter and receiver HAs have different wireless distances.

  9. Low Power Consumption Wireless Sensor Communication System Integrated with an Energy Harvesting Power Source

    Directory of Open Access Journals (Sweden)

    Vlad MARSIC

    2013-01-01

    Full Text Available This paper presents the testing results of a wireless sensor communication system with low power consumption integrated with an energy harvesting power source. The experiments focus on the system’s capability to perform continuous monitoring and to wirelessly transmit the data acquired from the sensors to a user base station, for realization of completely battery-free wireless sensor system. Energy harvesting technologies together with system design optimization for power consumption minimization ensure the system’s energy autonomous capability demonstrated in this paper by presenting the promising testing results achieved following its integration with structural health monitoring and body area network applications.

  10. Integrated 3d printed wireless sensing system for environmental monitoring

    KAUST Repository

    Farooqui, Muhammad Fahad

    2017-12-21

    Disclosed are various embodiments of a wireless sensor device for monitoring environment conditions. A wireless sensor device may comprise, for example, a computing device, printable circuitry, sensors, and antennas combined with one or more transmitters on a panel. The wireless sensor device may be configured to take environment measurements, such as temperature, gas, humidity, and wirelessly communicate the environment measurements to a remote computing device, in addition, the present disclosure relates to a method of assembling the wireless sensor device. The method may comprise printing sensors, circuitry, and antennas to a panel; folding the panel to form an enclosure comprising a plurality of side panels; and attaching the plurality of side panels to a circuit board panel.

  11. A Wireless Physiological Signal Monitoring System with Integrated Bluetooth and WiFi Technologies.

    Science.gov (United States)

    Yu, Sung-Nien; Cheng, Jen-Chieh

    2005-01-01

    This paper proposes a wireless patient monitoring system which integrates Bluetooth and WiFi wireless technologies. A wireless portable multi-parameter device was designated to acquire physiological signals and transmit them to a local server via Bluetooth wireless technology. Four kinds of monitor units were designed to communicate via the WiFi wireless technology, including a local monitor unit, a control center, mobile devices (personal digital assistant; PDA), and a web page. The use of various monitor units is intending to meet different medical requirements for different medical personnel. This system was demonstrated to promote the mobility and flexibility for both the patients and the medical personnel, which further improves the quality of health care.

  12. Wireless passive polymer-derived SiCN ceramic sensor with integrated resonator/antenna

    Science.gov (United States)

    Li, Yan; Yu, Yuxi; San, Haisheng; Wang, Yansong; An, Linan

    2013-10-01

    This paper presents a passive wireless polymer-derived silicon carbonitride (SiCN) ceramic sensor based on cavity radio frequency resonator together with integrated slot antenna. The effect of the cavity sensor dimensions on the Q-factor and resonant frequency is investigated by numerical simulation. A sensor with optimal dimensions is designed and fabricated. It is demonstrated that the sensor signal can be wirelessly detected at distances up to 20 mm. Given the high-temperature stability of the SiCN, the sensor is very promising for high-temperature wireless sensing applications.

  13. [The Development of Information Centralization and Management Integration System for Monitors Based on Wireless Sensor Network].

    Science.gov (United States)

    Xu, Xiu; Zhang, Honglei; Li, Yiming; Li, Bin

    2015-07-01

    Developed the information centralization and management integration system for monitors of different brands and models with wireless sensor network technologies such as wireless location and wireless communication, based on the existing wireless network. With adaptive implementation and low cost, the system which possesses the advantages of real-time, efficiency and elaboration is able to collect status and data of the monitors, locate the monitors, and provide services with web server, video server and locating server via local network. Using an intranet computer, the clinical and device management staffs can access the status and parameters of monitors. Applications of this system provide convenience and save human resource for clinical departments, as well as promote the efficiency, accuracy and elaboration for the device management. The successful achievement of this system provides solution for integrated and elaborated management of the mobile devices including ventilator and infusion pump.

  14. Differential neural network configuration during human path integration

    Science.gov (United States)

    Arnold, Aiden E. G. F; Burles, Ford; Bray, Signe; Levy, Richard M.; Iaria, Giuseppe

    2014-01-01

    Path integration is a fundamental skill for navigation in both humans and animals. Despite recent advances in unraveling the neural basis of path integration in animal models, relatively little is known about how path integration operates at a neural level in humans. Previous attempts to characterize the neural mechanisms used by humans to visually path integrate have suggested a central role of the hippocampus in allowing accurate performance, broadly resembling results from animal data. However, in recent years both the central role of the hippocampus and the perspective that animals and humans share similar neural mechanisms for path integration has come into question. The present study uses a data driven analysis to investigate the neural systems engaged during visual path integration in humans, allowing for an unbiased estimate of neural activity across the entire brain. Our results suggest that humans employ common task control, attention and spatial working memory systems across a frontoparietal network during path integration. However, individuals differed in how these systems are configured into functional networks. High performing individuals were found to more broadly express spatial working memory systems in prefrontal cortex, while low performing individuals engaged an allocentric memory system based primarily in the medial occipito-temporal region. These findings suggest that visual path integration in humans over short distances can operate through a spatial working memory system engaging primarily the prefrontal cortex and that the differential configuration of memory systems recruited by task control networks may help explain individual biases in spatial learning strategies. PMID:24808849

  15. FUZZY NEURAL NETWORK FOR OBJECT IDENTIFICATION ON INTEGRATED CIRCUIT LAYOUTS

    Directory of Open Access Journals (Sweden)

    A. A. Doudkin

    2015-01-01

    Full Text Available Fuzzy neural network model based on neocognitron is proposed to identify layout objects on images of topological layers of integrated circuits. Testing of the model on images of real chip layouts was showed a highеr degree of identification of the proposed neural network in comparison to base neocognitron.

  16. Commentary. Integrative Modeling and the Role of Neural Constraints

    Czech Academy of Sciences Publication Activity Database

    Bantegnie, Brice

    2017-01-01

    Roč. 8, SEP 5 (2017), s. 1-2, č. článku 1531. ISSN 1664-1078 Institutional support: RVO:67985955 Keywords : mechanistic explanation * functional analysis * mechanistic integration * reverse inference * neural plasticity * neural networks Subject RIV: AA - Philosophy ; Religion Impact factor: 2.323, year: 2016

  17. Transmission of wireless neural signals through a 0.18 µm CMOS low-power amplifier.

    Science.gov (United States)

    Gazziro, M; Braga, C F R; Moreira, D A; Carvalho, A C P L F; Rodrigues, J F; Navarro, J S; Ardila, J C M; Mioni, D P; Pessatti, M; Fabbro, P; Freewin, C; Saddow, S E

    2015-01-01

    In the field of Brain Machine Interfaces (BMI) researchers still are not able to produce clinically viable solutions that meet the requirements of long-term operation without the use of wires or batteries. Another problem is neural compatibility with the electrode probes. One of the possible ways of approaching these problems is the use of semiconductor biocompatible materials (silicon carbide) combined with an integrated circuit designed to operate with low power consumption. This paper describes a low-power neural signal amplifier chip, named Cortex, fabricated using 0.18 μm CMOS process technology with all electronics integrated in an area of 0.40 mm(2). The chip has 4 channels, total power consumption of only 144 μW, and is impedance matched to silicon carbide biocompatible electrodes.

  18. A Wireless and Batteryless Microsystem with Implantable Grid Electrode/3-Dimensional Probe Array for ECoG and Extracellular Neural Recording in Rats

    Directory of Open Access Journals (Sweden)

    Chih-Wei Chang

    2013-04-01

    Full Text Available This paper presents the design and implementation of an integrated wireless microsystem platform that provides the possibility to support versatile implantable neural sensing devices in free laboratory rats. Inductive coupled coils with low dropout regulator design allows true long-term recording without limitation of battery capacity. A 16-channel analog front end chip located on the headstage is designed for high channel account neural signal conditioning with low current consumption and noise. Two types of implantable electrodes including grid electrode and 3D probe array are also presented for brain surface recording and 3D biopotential acquisition in the implanted target volume of tissue. The overall system consumes less than 20 mA with small form factor, 3.9 × 3.9 cm2 mainboard and 1.8 × 3.4 cm2 headstage, is packaged into a backpack for rats. Practical in vivo recordings including auditory response, brain resection tissue and PZT-induced seizures recording demonstrate the correct function of the proposed microsystem. Presented achievements addressed the aforementioned properties by combining MEMS neural sensors, low-power circuit designs and commercial chips into system-level integration.

  19. Faulty node detection in wireless sensor networks using a recurrent neural network

    Science.gov (United States)

    Atiga, Jamila; Mbarki, Nour Elhouda; Ejbali, Ridha; Zaied, Mourad

    2018-04-01

    The wireless sensor networks (WSN) consist of a set of sensors that are more and more used in surveillance applications on a large scale in different areas: military, Environment, Health ... etc. Despite the minimization and the reduction of the manufacturing costs of the sensors, they can operate in places difficult to access without the possibility of reloading of battery, they generally have limited resources in terms of power of emission, of processing capacity, data storage and energy. These sensors can be used in a hostile environment, such as, for example, on a field of battle, in the presence of fires, floods, earthquakes. In these environments the sensors can fail, even in a normal operation. It is therefore necessary to develop algorithms tolerant and detection of defects of the nodes for the network of sensor without wires, therefore, the faults of the sensor can reduce the quality of the surveillance if they are not detected. The values that are measured by the sensors are used to estimate the state of the monitored area. We used the Non-linear Auto- Regressive with eXogeneous (NARX), the recursive architecture of the neural network, to predict the state of a node of a sensor from the previous values described by the functions of time series. The experimental results have verified that the prediction of the State is enhanced by our proposed model.

  20. A wireless recording system that utilizes Bluetooth technology to transmit neural activity in freely moving animals

    Science.gov (United States)

    Hampson, Robert E.; Collins, Vernell; Deadwyler, Sam A.

    2009-01-01

    A new wireless transceiver is described for recording individual neuron firing from behaving rats utilizing Bluetooth transmission technology and a processor onboard for discrimination of neuronal waveforms and associated time stamps. This universal brain activity transmitter (UBAT) is attached to rodents via a backpack and amplifier headstage and can transmit 16 channels of captured neuronal firing data via a Bluetooth transceiver chip over very large and unconstrained distances. The onboard microprocessor of the UBAT allows flexible online control over waveform isolation criteria via transceiver instruction and the two-way communication capacity allows for closed-loop applications between neural events and behavioral or physiological processes which can be modified by transceiver instructions. A detailed description of the multiplexer processing of channel data as well as examples of neuronal recordings in different behavioral testing contexts is provided to demonstrate the capacity for robust transmission within almost any laboratory environment. A major advantage of the UBAT is the long transmission range and lack of object-based line of sight interference afforded by Bluetooth technology, allowing flexible recording capabilities within multiple experimental paradigms without interruption. Continuous recordings over very large distance separations from the monitor station are demonstrated providing experimenters with recording advantages not previously available with other telemetry devices. PMID:19524612

  1. Convolutional neural network-based classification system design with compressed wireless sensor network images.

    Science.gov (United States)

    Ahn, Jungmo; Park, JaeYeon; Park, Donghwan; Paek, Jeongyeup; Ko, JeongGil

    2018-01-01

    With the introduction of various advanced deep learning algorithms, initiatives for image classification systems have transitioned over from traditional machine learning algorithms (e.g., SVM) to Convolutional Neural Networks (CNNs) using deep learning software tools. A prerequisite in applying CNN to real world applications is a system that collects meaningful and useful data. For such purposes, Wireless Image Sensor Networks (WISNs), that are capable of monitoring natural environment phenomena using tiny and low-power cameras on resource-limited embedded devices, can be considered as an effective means of data collection. However, with limited battery resources, sending high-resolution raw images to the backend server is a burdensome task that has direct impact on network lifetime. To address this problem, we propose an energy-efficient pre- and post- processing mechanism using image resizing and color quantization that can significantly reduce the amount of data transferred while maintaining the classification accuracy in the CNN at the backend server. We show that, if well designed, an image in its highly compressed form can be well-classified with a CNN model trained in advance using adequately compressed data. Our evaluation using a real image dataset shows that an embedded device can reduce the amount of transmitted data by ∼71% while maintaining a classification accuracy of ∼98%. Under the same conditions, this process naturally reduces energy consumption by ∼71% compared to a WISN that sends the original uncompressed images.

  2. A dual slope charge sampling analog front-end for a wireless neural recording system.

    Science.gov (United States)

    Lee, Seung Bae; Lee, Byunghun; Gosselin, Benoit; Ghovanloo, Maysam

    2014-01-01

    This paper presents a novel dual slope charge sampling (DSCS) analog front-end (AFE) architecture, which amplifies neural signals by taking advantage of the charge sampling concept for analog signal conditioning, such as amplification and filtering. The presented DSCS-AFE achieves amplification, filtering, and sampling in a simultaneous fashion, while consuming very small amount of power. The output of the DSCS-AFE produces a pulse width modulated (PWM) signal that is proportional to the input voltage amplitude. A circular shift register (CSR) utilizes time division multiplexing (TDM) of the PWM pulses to create a pseudo-digital TDM-PWM signal that can feed a wireless transmitter. The 8-channel system-on-a-chip was fabricated in a 0.35-μm CMOS process, occupying 2.4 × 2.1 mm(2) and consuming 255 μW from a 1.8V supply. Measured input-referred noise for the entire system, including the FPGA in order to recover PWM signal is 6.50 μV(rms) in the 288 Hz~10 kHz range. For each channel, sampling rate is 31.25 kHz, and power consumption is 31.8 μW.

  3. An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

    International Nuclear Information System (INIS)

    Dimas, George; Iakovidis, Dimitris K; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

    2017-01-01

    Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup. (paper)

  4. An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

    Science.gov (United States)

    Dimas, George; Iakovidis, Dimitris K.; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

    2017-09-01

    Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup.

  5. A wireless recording system that utilizes Bluetooth technology to transmit neural activity in freely moving animals.

    Science.gov (United States)

    Hampson, Robert E; Collins, Vernell; Deadwyler, Sam A

    2009-09-15

    A new wireless transceiver is described for recording individual neuron firing from behaving rats utilizing Bluetooth transmission technology and a processor onboard for discrimination of neuronal waveforms and associated time stamps. This universal brain activity transmitter (UBAT) is attached to rodents via a backpack and amplifier headstage and can transmit 16 channels of captured neuronal firing data via a Bluetooth transceiver chip over very large and unconstrained distances. The onboard microprocessor of the UBAT allows flexible online control over waveform isolation criteria via transceiver instruction and the two-way communication capacity allows for closed-loop applications between neural events and behavioral or physiological processes which can be modified by transceiver instructions. A detailed description of the multiplexer processing of channel data as well as examples of neuronal recordings in different behavioral testing contexts is provided to demonstrate the capacity for robust transmission within almost any laboratory environment. A major advantage of the UBAT is the long transmission range and lack of object-based line of sight interference afforded by Bluetooth technology, allowing flexible recording capabilities within multiple experimental paradigms without interruption. Continuous recordings over very large distance separations from the monitor station are demonstrated providing experimenters with recording advantages not previously available with other telemetry devices.

  6. Integrated wireless systems: The future has arrived (Keynote Address)

    Science.gov (United States)

    Rivoir, Roberto

    2005-06-01

    It is believed that we are just at the beginning with wireless, and that a new age is dawning for this breakthrough technology. Thanks to several years of industrial manufacturing in mass-market applications such as cellular phones, wireless technology has nowadays reached a level of maturity that, combined with other achievements arising from different fields, such as information technology, artificial intelligence, pervasive computing, science of new materials, and micro-electro-mechanical systems (MEMS), will enable the realization of a networked stream-flow of real-time information, that will accompany us in our daily life, in a total seamless, transparent fashion. As almost any application scenario will require the deployment of complex, miniaturized, almost "invisible" systems, operating with different wireless standards, hard technological challenges will have to be faced for designing and fabricating ultra-low-cost, reconfigurable, and multi-mode heterogeneous smart micro-devices. But ongoing, unending progresses on wireless technology keeps the promise of helping to solve important societal problems in the health-care, safety, security, industry, environment sectors, and in general opening the possibility for an improved quality of life at work, on travel, at home, practically "everywhere, anytime".

  7. An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

    Science.gov (United States)

    Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

    2015-01-01

    Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

  8. Three-dimensional integration and modeling a revolution in RF and wireless packaging

    CERN Document Server

    Lee, Jong-Hoon

    2007-01-01

    This book presents a step-by-step discussion of the 3D integration approach for the development of compact system-on-package (SOP) front-ends.Various examples of fully-integrated passive building blocks (cavity/microstip filters, duplexers, antennas), as well as a multilayer ceramic (LTCC) V-band transceiver front-end midule demonstrate the revolutionary effects of this approach in RF/Wireless packaging and multifunctional miniaturization.Designs covered are based on novel ideas and are presented for the first time for millimeterwave (60GHz) ultrabroadband wireless modules.Table of Contents: I

  9. Portable Integrated Wireless Device Threat Assessment to Aircraft Radio Systems

    Science.gov (United States)

    Salud, Maria Theresa P.; Williams, Reuben A. (Technical Monitor)

    2004-01-01

    An assessment was conducted on multiple wireless local area network (WLAN) devices using the three wireless standards for spurious radiated emissions to determine their threat to aircraft radio navigation systems. The measurement process, data and analysis are provided for devices tested using IEEE 802.11a, IEEE 802.11b, and Bluetooth as well as data from portable laptops/tablet PCs and PDAs (grouping known as PEDs). A comparison was made between wireless LAN devices and portable electronic devices. Spurious radiated emissions were investigated in the radio frequency bands for the following aircraft systems: Instrument Landing System Localizer and Glideslope, Very High Frequency (VHF) Communication, VHF Omnidirectional Range, Traffic Collision Avoidance System, Air Traffic Control Radar Beacon System, Microwave Landing System and Global Positioning System. Since several of the contiguous navigation systems were grouped under one encompassing measurement frequency band, there were five measurement frequency bands where spurious radiated emissions data were collected for the PEDs and WLAN devices. The report also provides a comparison between emissions data and regulatory emission limit.

  10. 3D-Printed Disposable Wireless Sensors with Integrated Microelectronics for Large Area Environmental Monitoring

    KAUST Repository

    Farooqui, Muhammad Fahad

    2017-05-19

    Large area environmental monitoring can play a crucial role in dealing with crisis situations. However, it is challenging as implementing a fixed sensor network infrastructure over large remote area is economically unfeasible. This work proposes disposable, compact, dispersible 3D-printed wireless sensor nodes with integrated microelectronics which can be dispersed in the environment and work in conjunction with few fixed nodes for large area monitoring applications. As a proof of concept, the wireless sensing of temperature, humidity, and H2S levels are shown which are important for two critical environmental conditions namely forest fires and industrial leaks. These inkjet-printed sensors and an antenna are realized on the walls of a 3D-printed cubic package which encloses the microelectronics developed on a 3D-printed circuit board. Hence, 3D printing and inkjet printing are uniquely combined in order to realize a low-cost, fully integrated wireless sensor node.

  11. Flexible neural interfaces with integrated stiffening shank

    Energy Technology Data Exchange (ETDEWEB)

    Tooker, Angela C.; Felix, Sarah H.; Pannu, Satinderpall S.; Shah, Kedar G.; Sheth, Heeral; Tolosa, Vanessa

    2017-10-17

    A neural interface includes a first dielectric material having at least one first opening for a first electrical conducting material, a first electrical conducting material in the first opening, and at least one first interconnection trace electrical conducting material connected to the first electrical conducting material. A stiffening shank material is located adjacent the first dielectric material, the first electrical conducting material, and the first interconnection trace electrical conducting material.

  12. Flexible neural interfaces with integrated stiffening shank

    Science.gov (United States)

    Tooker, Angela C.; Felix, Sarah H.; Pannu, Satinderpall S.; Shah, Kedar G.; Sheth, Heeral; Tolosa, Vanessa

    2016-07-26

    A neural interface includes a first dielectric material having at least one first opening for a first electrical conducting material, a first electrical conducting material in the first opening, and at least one first interconnection trace electrical conducting material connected to the first electrical conducting material. A stiffening shank material is located adjacent the first dielectric material, the first electrical conducting material, and the first interconnection trace electrical conducting material.

  13. Integrated Coherent Radio-over-Fiber Units for Millimeter-Wave Wireless Access

    DEFF Research Database (Denmark)

    Stöhr, A.; Babiel, S.; Chuenchom, M.

    2015-01-01

    For providing wireless access as a complementary access technology to direct optical access, supporting 1–10 Gb/s per client, we propose a novel scheme based upon the transparent integration of coherent Radio-over-Fiber (CRoF) units with next generation optical access (NGOA) networks using dense ...

  14. System-Level Design of an Integrated Receiver Front End for a Wireless Ultrasound Probe

    DEFF Research Database (Denmark)

    di Ianni, Tommaso; Hemmsen, Martin Christian; Llimos Muntal, Pere

    2016-01-01

    In this paper, a system-level design is presented for an integrated receive circuit for a wireless ultrasound probe, which includes analog front ends and beamformation modules. This paper focuses on the investigation of the effects of architectural design choices on the image quality. The point...

  15. Integrating wireless sensor networks with CE devices for health care activity tracking in the home environment

    NARCIS (Netherlands)

    Bosman, R.P.; Lukkien, J.J.; Verhoeven, R.

    2009-01-01

    Wireless sensing devices containing limited processing and communication capabilities are becoming available for all sorts of purposes. An important problem is to integrate networks of these sensors with the existing CE en IT infrastructure such that a) data coming out of the sensor network can be

  16. Broadband nanophotonic wireless links and networks using on-chip integrated plasmonic antennas.

    Science.gov (United States)

    Yang, Yuanqing; Li, Qiang; Qiu, Min

    2016-01-19

    Owing to their high capacity and flexibility, broadband wireless communications have been widely employed in radio and microwave regimes, playing indispensable roles in our daily life. Their optical analogs, however, have not been demonstrated at the nanoscale. In this paper, by exploiting plasmonic nanoantennas, we demonstrate the complete design of broadband wireless links and networks in the realm of nanophotonics. With a 100-fold enhancement in power transfer superior to previous designs as well as an ultrawide bandwidth that covers the entire telecommunication wavelength range, such broadband nanolinks and networks are expected to pave the way for future optical integrated nanocircuits.

  17. Development of Wireless System for Containment Integrated Leakage Rate Test

    International Nuclear Information System (INIS)

    Lee, Kwang-Dae; Oh, Eung-Se; Yang, Seung-Ok

    2006-01-01

    The containment system leakage rate should be estimated periodically with reliable test equipment. In light-water reactor nuclear power plants, ANSI/ANS- 56.8 is a basis for determining leakage rates. Two types of data acquisition system, centralized type and networked type, has been used. In centralized type, all sensors are connected directly from sensors in the containment to the measuring equipment outside the building. The other hand, the networked type has several branch chains which connect one group of the network-sensors together. To test leakage rate, more than 20 temperature sensors and 6 humidity sensors, which are different for each plant, should be installed on a specific level in the containment. A wireless technology gives the benefits such as reducing installation efforts, making pretest easy, so it is widely used more and more in the plant monitoring. As the containment system has many kinds of complex barriers to the radio frequency, the radio power and frequency band for better transmission rate as well as the interference by the radio frequency should be considered. The overview of the wireless sensor system for the containment leakage rate test is described here and the test results on Yonggwang unit 4 PWR plant is presented

  18. Use of Time-Frequency Analysis and Neural Networks for Mode Identification in a Wireless Software-Defined Radio Approach

    Directory of Open Access Journals (Sweden)

    Matteo Gandetto

    2004-09-01

    Full Text Available The use of time-frequency distributions is proposed as a nonlinear signal processing technique that is combined with a pattern recognition approach to identify superimposed transmission modes in a reconfigurable wireless terminal based on software-defined radio techniques. In particular, a software-defined radio receiver is described aiming at the identification of two coexistent communication modes: frequency hopping code division multiple access and direct sequence code division multiple access. As a case study, two standards, based on the previous modes and operating in the same band (industrial, scientific, and medical, are considered: IEEE WLAN 802.11b (direct sequence and Bluetooth (frequency hopping. Neural classifiers are used to obtain identification results. A comparison between two different neural classifiers is made in terms of relative error frequency.

  19. Molecular annotation of integrative feeding neural circuits.

    Science.gov (United States)

    Pérez, Cristian A; Stanley, Sarah A; Wysocki, Robert W; Havranova, Jana; Ahrens-Nicklas, Rebecca; Onyimba, Frances; Friedman, Jeffrey M

    2011-02-02

    The identity of higher-order neurons and circuits playing an associative role to control feeding is unknown. We injected pseudorabies virus, a retrograde tracer, into masseter muscle, salivary gland, and tongue of BAC-transgenic mice expressing GFP in specific neural populations and identified several CNS regions that project multisynaptically to the periphery. MCH and orexin neurons were identified in the lateral hypothalamus, and Nurr1 and Cnr1 in the amygdala and insular/rhinal cortices. Cholera toxin β tracing showed that insular Nurr1(+) and Cnr1(+) neurons project to the amygdala or lateral hypothalamus, respectively. Finally, we show that cortical Cnr1(+) neurons show increased Cnr1 mRNA and c-Fos expression after fasting, consistent with a possible role for Cnr1(+) neurons in feeding. Overall, these studies define a general approach for identifying specific molecular markers for neurons in complex neural circuits. These markers now provide a means for functional studies of specific neuronal populations in feeding or other complex behaviors. Copyright © 2011 Elsevier Inc. All rights reserved.

  20. Classical Conditioning with Pulsed Integrated Neural Networks: Circuits and System

    DEFF Research Database (Denmark)

    Lehmann, Torsten

    1998-01-01

    In this paper we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems and we find that abiologically inspired approach using simple circuit structures is most likely to bring success. We develop a ...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

  1. A multi-channel low-power system-on-chip for single-unit recording and narrowband wireless transmission of neural signal.

    Science.gov (United States)

    Bonfanti, A; Ceravolo, M; Zambra, G; Gusmeroli, R; Spinelli, A S; Lacaita, A L; Angotzi, G N; Baranauskas, G; Fadiga, L

    2010-01-01

    This paper reports a multi-channel neural recording system-on-chip (SoC) with digital data compression and wireless telemetry. The circuit consists of a 16 amplifiers, an analog time division multiplexer, an 8-bit SAR AD converter, a digital signal processor (DSP) and a wireless narrowband 400-MHz binary FSK transmitter. Even though only 16 amplifiers are present in our current die version, the whole system is designed to work with 64 channels demonstrating the feasibility of a digital processing and narrowband wireless transmission of 64 neural recording channels. A digital data compression, based on the detection of action potentials and storage of correspondent waveforms, allows the use of a 1.25-Mbit/s binary FSK wireless transmission. This moderate bit-rate and a low frequency deviation, Manchester-coded modulation are crucial for exploiting a narrowband wireless link and an efficient embeddable antenna. The chip is realized in a 0.35- εm CMOS process with a power consumption of 105 εW per channel (269 εW per channel with an extended transmission range of 4 m) and an area of 3.1 × 2.7 mm(2). The transmitted signal is captured by a digital TV tuner and demodulated by a wideband phase-locked loop (PLL), and then sent to a PC via an FPGA module. The system has been tested for electrical specifications and its functionality verified in in-vivo neural recording experiments.

  2. Thermal photovoltaic solar integrated system analysis using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering

    2007-07-01

    The energy demand in Jordan is primarily met by petroleum products. As such, the development of renewable energy systems is quite attractive. In particular, solar energy is a promising renewable energy source in Jordan and has been used for food canning, paper production, air-conditioning and sterilization. Artificial neural networks (ANNs) have received significant attention due to their capabilities in forecasting, modelling of complex nonlinear systems and control. ANNs have been used for forecasting solar energy. This paper presented a study that examined a thermal photovoltaic solar integrated system that was built in Jordan. Historical input-output system data that was collected experimentally was used to train an ANN that predicted the collector, PV module, pump and total efficiencies. The model predicted the efficiencies well and can therefore be utilized to find the operating conditions of the system that will produce the maximum system efficiencies. The paper provided a description of the photovoltaic solar system including equations for PV module efficiency; pump efficiency; and total efficiency. The paper also presented data relevant to the system performance and neural networks. The results of a neural net model were also presented based on the thermal PV solar integrated system data that was collected. It was concluded that the neural net model of the thermal photovoltaic solar integrated system set the background for achieving the best system performance. 10 refs., 6 figs.

  3. A model of interval timing by neural integration.

    Science.gov (United States)

    Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

    2011-06-22

    We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

  4. Neural activity based biofeedback therapy for Autism spectrum disorder through wearable wireless textile EEG monitoring system

    Science.gov (United States)

    Sahi, Ahna; Rai, Pratyush; Oh, Sechang; Ramasamy, Mouli; Harbaugh, Robert E.; Varadan, Vijay K.

    2014-04-01

    Mu waves, also known as mu rhythms, comb or wicket rhythms are synchronized patterns of electrical activity involving large numbers of neurons, in the part of the brain that controls voluntary functions. Controlling, manipulating, or gaining greater awareness of these functions can be done through the process of Biofeedback. Biofeedback is a process that enables an individual to learn how to change voluntary movements for purposes of improving health and performance through the means of instruments such as EEG which rapidly and accurately 'feedback' information to the user. Biofeedback is used for therapeutic purpose for Autism Spectrum Disorder (ASD) by focusing on Mu waves for detecting anomalies in brain wave patterns of mirror neurons. Conventional EEG measurement systems use gel based gold cup electrodes, attached to the scalp with adhesive. It is obtrusive and wires sticking out of the electrodes to signal acquisition system make them impractical for use in sensitive subjects like infants and children with ASD. To remedy this, sensors can be incorporated with skull cap and baseball cap that are commonly used for infants and children. Feasibility of Textile based Sensor system has been investigated here. Textile based multi-electrode EEG, EOG and EMG monitoring system with embedded electronics for data acquisition and wireless transmission has been seamlessly integrated into fabric of these items for continuous detection of Mu waves. Textile electrodes were placed on positions C3, CZ, C4 according to 10-20 international system and their capability to detect Mu waves was tested. The system is ergonomic and can potentially be used for early diagnosis in infants and planning therapy for ASD patients.

  5. Integrated evolutionary computation neural network quality controller for automated systems

    Energy Technology Data Exchange (ETDEWEB)

    Patro, S.; Kolarik, W.J. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Industrial Engineering

    1999-06-01

    With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time.

  6. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-01-01

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

  7. PERFORMANCE EVALUATION OF INTEGRATED MACRO AND MICRO MOBILITY PROTOCOLS FOR WIDE AREA WIRELESS NETWORKS

    Directory of Open Access Journals (Sweden)

    R.Gunasundari

    2010-03-01

    Full Text Available The success of next generation wireless networks will rely much on advanced mechanisms for seamless mobility support among emerging heterogeneous technologies. Currently, Mobile IP is the most promising solution for mobility management in the Internet. Several IP micro mobility approaches have been proposed to enhance the performance of Mobile IP which supports quality of service, minimum packet loss, limited handoff delay and scalability and power conservation but they are not scalable for macro mobility. A practical solution would therefore require integration of Mobile IP and Micro mobility protocols where Mobile IP handles macro mobility and micro mobility protocols handles micro mobility. In this paper an integrated mobility management protocol for IP based wireless networks is proposed and analyzed. Simulation results presented in this paper are based on ns 2.

  8. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-11-17

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

  9. Enabling IoT: Integration of wireless sensor network for healthcare application using Waspmote

    Science.gov (United States)

    Azmi, Noraini; Kamarudin, Latifah Munirah

    2017-03-01

    The number of patients that require medical assistance is increasing each day while staff-patient ratio is not balanced causing issues such as treatment delay and often leads to patient dissatisfaction. Besides that, healthcare devices are getting complex and challenging for it to be handled and interpreted personally by patient. Lack of staff and challenges in operating the medical devices not only affect patient in hospital but also caused problem to home care patients that require full attention and constant monitoring. This urges for a development of new method or technology. At present, Wireless Sensor Network (WSN) is gaining interest as one of the major components in enabling Internet of Things (IoT) since it offers low cost, low power monitoring besides reducing devices dependency on wires or cable. Although, WSN is initially developed for military application, nowadays, it is being integrated into various applications such as environmental monitoring, smart monitoring and agricultural monitoring. The idea of wireless monitoring with low power consumption motivates researchers to discover the possibility of deploying wireless sensor network for mission critical application such as in healthcare applications. This paper presents the details on the design and development of wireless sensor network using Waspmote from Libelium Inc. for mission critical applications such as healthcare applications.

  10. Integration of Antennas and Solar cells for Low Power Wireless Systems

    OpenAIRE

    O’Conchubhair, Oisin

    2015-01-01

    This thesis reports on design methods for enhanced integration of low-profile antennas for short-range wireless communications with solar voltaic systems. The need to transform to more sustainable energy sources arises from the excessive production of harmful carbon emissions from fossil fuels. The Internet of Things and the proliferation of battery powered devices makes energy harvesting from the environment more desirable in order to reduce dependency on the power grid and running costs. Wh...

  11. Risk Assessment along Supply Chain: A RFID and Wireless Sensor Network Integration Approach

    OpenAIRE

    Laurent GOMEZ; Maryline LAURENT; Ethmane EL MOUSTAINE

    2012-01-01

    Wireless Sensor Networks together with Radio Frequency Identification are promising technologies for supply chain management systems. They both provide supply chain players with goods tracking and monitoring functions along the chain. Whereas RFIDs are rather focusing on identification of goods (e.g., identification, classification), WSNs are meant to monitor and control the supply chain environment. Nevertheless, despite the interest for the supply chain management systems, their integration...

  12. Accelerated DNA Methylation Age: Associations with PTSD and Neural Integrity

    Science.gov (United States)

    Wolf, Erika J.; Logue, Mark W.; Hayes, Jasmeet P.; Sadeh, Naomi; Schichman, Steven A.; Stone, Annjanette; Salat, David H.; Milberg, William; McGlinchey, Regina; Miller, Mark W.

    2015-01-01

    Background Accumulating evidence suggests that post traumatic stress disorder (PTSD) may accelerate cellular aging and lead to premature morbidity and neurocognitive decline. Methods This study evaluated associations between PTSD and DNA methylation (DNAm) age using recently developed algorithms of cellular age by Horvath (2013) and Hannum et al. (2013). These estimates reflect accelerated aging when they exceed chronological age. We also examined if accelerated cellular age manifested in degraded neural integrity, indexed via diffusion tensor imaging. Results Among 281 male and female veterans of the conflicts in Iraq and Afghanistan, DNAm age was strongly related to chronological age (rs ~.88). Lifetime PTSD severity was associated with Hannum DNAm age estimates residualized for chronological age (β = .13, p= .032). Advanced DNAm age was associated with reduced integrity in the genu of the corpus callosum (β = −.17, p= .009) and indirectly linked to poorer working memory performance via this region (indirect β = − .05, p= .029). Horvath DNAm age estimates were not associated with PTSD or neural integrity. Conclusions Results provide novel support for PTSD-related accelerated aging in DNAm and extend the evidence base of known DNAm age correlates to the domains of neural integrity and cognition. PMID:26447678

  13. Integration and analysis of neighbor discovery and link quality estimation in wireless sensor networks.

    Science.gov (United States)

    Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

    2014-01-01

    Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  14. Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Marjan Radi

    2014-01-01

    Full Text Available Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  15. Vehicular Integration of Wireless Power Transfer Systems and Hardware Interoperability Case Studies

    Energy Technology Data Exchange (ETDEWEB)

    Onar, Omer C [ORNL; Campbell, Steven L [ORNL; Seiber, Larry Eugene [ORNL; White, Cliff P [ORNL; Chinthavali, Madhu Sudhan [ORNL

    2016-01-01

    Several wireless charging methods are under development or available as an aftermarket option in the light-duty automotive market. However, there are not a sufficient number of studies detailing the vehicle integration methods, particularly a complete vehicle integration with higher power levels. This paper presents the design, development, implementation, and vehicle integration of wireless power transfer (WPT)-based electric vehicle (EV) charging systems for various test vehicles. Before having the standards effective, it is expected that WPT technology first will be integrated as an aftermarket retrofitting approach. Inclusion of this technology on production vehicles is contingent upon the release of the international standards. The power stages of the system are introduced with the design specifications and control systems including the active front-end rectifier with power factor correction, high frequency power inverter, high frequency isolation transformer, coupling coils, vehicle side full-bridge rectifier and filter, and the vehicle battery. The operating principles of the control, and communications, systems are presented. Aftermarket conversion approaches including the WPT on-board charger (OBC) integration, WPT CHAdeMO integration, and WPT direct battery connection scenarios are described. The experiments are carried out using the integrated vehicles and the results obtained to demonstrate the system performance including the stage-by-stage efficiencies.

  16. An analog integrated front-end amplifier for neural applications

    OpenAIRE

    Zhou, Zhijun; Warr, Paul

    2017-01-01

    The front-end amplifier forms the critical element for signal detection and pre-processing within neural monitoring systems. It determines not only the fidelity of the biosignal, but also impacts power consumption and detector size. In this paper, a combined feedback loop-controlled approach is proposed to neutralize for the input leakage currents generated by low noise amplifiers when in integrated circuit form, alongside signal leakage into the input bias network. Significantly, this loop t...

  17. Least Squares Neural Network-Based Wireless E-Nose System Using an SnO₂ Sensor Array.

    Science.gov (United States)

    Shahid, Areej; Choi, Jong-Hyeok; Rana, Abu Ul Hassan Sarwar; Kim, Hyun-Seok

    2018-05-06

    Over the last few decades, the development of the electronic nose (E-nose) for detection and quantification of dangerous and odorless gases, such as methane (CH₄) and carbon monoxide (CO), using an array of SnO₂ gas sensors has attracted considerable attention. This paper addresses sensor cross sensitivity by developing a classifier and estimator using an artificial neural network (ANN) and least squares regression (LSR), respectively. Initially, the ANN was implemented using a feedforward pattern recognition algorithm to learn the collective behavior of an array as the signature of a particular gas. In the second phase, the classified gas was quantified by minimizing the mean square error using LSR. The combined approach produced 98.7% recognition probability, with 95.5 and 94.4% estimated gas concentration accuracies for CH₄ and CO, respectively. The classifier and estimator parameters were deployed in a remote microcontroller for the actualization of a wireless E-nose system.

  18. Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

    Science.gov (United States)

    Hoomod, Haider K.; Kareem Jebur, Tuka

    2018-05-01

    Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

  19. Securing Digital Images Integrity using Artificial Neural Networks

    Science.gov (United States)

    Hajji, Tarik; Itahriouan, Zakaria; Ouazzani Jamil, Mohammed

    2018-05-01

    Digital image signature is a technique used to protect the image integrity. The application of this technique can serve several areas of imaging applied to smart cities. The objective of this work is to propose two methods to protect digital image integrity. We present a description of two approaches using artificial neural networks (ANN) to digitally sign an image. The first one is “Direct Signature without learning” and the second is “Direct Signature with learning”. This paper presents the theory of proposed approaches and an experimental study to test their effectiveness.

  20. Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays.

    Science.gov (United States)

    Park, Jihun; Kim, Joohee; Kim, So-Yun; Cheong, Woon Hyung; Jang, Jiuk; Park, Young-Geun; Na, Kyungmin; Kim, Yun-Tae; Heo, Jun Hyuk; Lee, Chang Young; Lee, Jung Heon; Bien, Franklin; Park, Jang-Ung

    2018-01-01

    Recent advances in wearable electronics combined with wireless communications are essential to the realization of medical applications through health monitoring technologies. For example, a smart contact lens, which is capable of monitoring the physiological information of the eye and tear fluid, could provide real-time, noninvasive medical diagnostics. However, previous reports concerning the smart contact lens have indicated that opaque and brittle components have been used to enable the operation of the electronic device, and this could block the user's vision and potentially damage the eye. In addition, the use of expensive and bulky equipment to measure signals from the contact lens sensors could interfere with the user's external activities. Thus, we report an unconventional approach for the fabrication of a soft, smart contact lens in which glucose sensors, wireless power transfer circuits, and display pixels to visualize sensing signals in real time are fully integrated using transparent and stretchable nanostructures. The integration of this display into the smart lens eliminates the need for additional, bulky measurement equipment. This soft, smart contact lens can be transparent, providing a clear view by matching the refractive indices of its locally patterned areas. The resulting soft, smart contact lens provides real-time, wireless operation, and there are in vivo tests to monitor the glucose concentration in tears (suitable for determining the fasting glucose level in the tears of diabetic patients) and, simultaneously, to provide sensing results through the contact lens display.

  1. A contact lens with integrated telecommunication circuit and sensors for wireless and continuous tear glucose monitoring

    International Nuclear Information System (INIS)

    Yao, H; Liao, Y; Lingley, A R; Afanasiev, A; Lähdesmäki, I; Otis, B P; Parviz, B A

    2012-01-01

    We present an integrated functional contact lens, composed of a differential glucose sensor module, metal interconnects, sensor read-out circuit, antenna and telecommunication circuit, to monitor tear glucose levels wirelessly, continuously and non-invasively. The electrochemical differential sensor module is based on immobilization of activated and de-activated glucose oxidase. We characterized the sensor on a model polymer eye and determined that it showed good repeatability, molecular interference rejection and linearity in the range of 0–2 mM glucose, covering normal tear glucose concentrations (0.1–0.6 mM). We also report the temperature, ageing and protein-fouling sensitivity of the sensor. We report the design and implementation of a low-power (3 µW) sensor read-out and telecommunication circuit to deliver wireless power and transmit data for the sensor module. Using this small chip (0.36 mm 2 ), we produced an integrated contact lens with sensors and demonstrated wireless operation of the system and glucose read-out over the distance of several centimeters. (paper)

  2. Laser Direct Writing and Selective Metallization of Metallic Circuits for Integrated Wireless Devices.

    Science.gov (United States)

    Cai, Jinguang; Lv, Chao; Watanabe, Akira

    2018-01-10

    Portable and wearable devices have attracted wide research attention due to their intimate relations with human daily life. As basic structures in the devices, the preparation of high-conductive metallic circuits or micro-circuits on flexible substrates should be facile, cost-effective, and easily integrated with other electronic units. In this work, high-conductive carbon/Ni composite structures were prepared by using a facile laser direct writing method, followed by an electroless Ni plating process, which exhibit a 3-order lower sheet resistance of less than 0.1 ohm/sq compared to original structures before plating, showing the potential for practical use. The carbon/Ni composite structures exhibited a certain flexibility and excellent anti-scratch property due to the tight deposition of Ni layers on carbon surfaces. On the basis of this approach, a wireless charging and storage device on a polyimide film was demonstrated by integrating an outer rectangle carbon/Ni composite coil for harvesting electromagnetic waves and an inner carbon micro-supercapacitor for energy storage, which can be fast charged wirelessly by a commercial wireless charger. Furthermore, a near-field communication (NFC) tag was prepared by combining a carbon/Ni composite coil for harvesting signals and a commercial IC chip for data storage, which can be used as an NFC tag for practical application.

  3. Low-power analog integrated circuits for wireless ECG acquisition systems.

    Science.gov (United States)

    Tsai, Tsung-Heng; Hong, Jia-Hua; Wang, Liang-Hung; Lee, Shuenn-Yuh

    2012-09-01

    This paper presents low-power analog ICs for wireless ECG acquisition systems. Considering the power-efficient communication in the body sensor network, the required low-power analog ICs are developed for a healthcare system through miniaturization and system integration. To acquire the ECG signal, a low-power analog front-end system, including an ECG signal acquisition board, an on-chip low-pass filter, and an on-chip successive-approximation analog-to-digital converter for portable ECG detection devices is presented. A quadrature CMOS voltage-controlled oscillator and a 2.4 GHz direct-conversion transmitter with a power amplifier and upconversion mixer are also developed to transmit the ECG signal through wireless communication. In the receiver, a 2.4 GHz fully integrated CMOS RF front end with a low-noise amplifier, differential power splitter, and quadrature mixer based on current-reused folded architecture is proposed. The circuits have been implemented to meet the specifications of the IEEE 802.15.4 2.4 GHz standard. The low-power ICs of the wireless ECG acquisition systems have been fabricated using a 0.18 μm Taiwan Semiconductor Manufacturing Company (TSMC) CMOS standard process. The measured results on the human body reveal that ECG signals can be acquired effectively by the proposed low-power analog front-end ICs.

  4. Integrated Wireless Monitoring and Control System in Reverse Osmosis Membrane Desalination Plants

    Directory of Open Access Journals (Sweden)

    Al Haji Ahmad

    2015-01-01

    Full Text Available The operational processes of the Reverse Osmosis (RO membrane desalination plants require continuous monitoring through the constant attendance of operators to ensure proper productivity and minimize downtime and prevent membrane failure. Therefore, the plant must be equipped with a control system that monitors and controls the operational variables. Monitoring and controlling the affecting parameters are critical to the evaluation of the performance of the desalination plant, which will help the operator find and resolve problems immediately. Therefore, this paper was aimed at developing an RO unit by utilizing a wireless sensor network (WSN system. Hence, an RO pilot plant with a feed capacity of 1.2 m3/h was utilized, commissioned, and tested in Kuwait to assess and verify the performance of the integrated WSN in RO membrane desalination system. The investigated system allowed the operators to remotely monitor the operational process of the RO system. The operational data were smoothly recorded and monitored. Furthermore, the technical problems were immediately determined, which reduced the time and effort in rectifying the technical problems relevant to the RO performance. The manpower requirements of such treatment system were dramatically reduced by about 50%. Based on a comparison between manual and wireless monitoring operational processes, the availability of the integrated RO unit with a wireless monitoring was increased by 10%

  5. Bidirectional fiber-wireless and fiber-IVLLC integrated system based on polarization-orthogonal modulation scheme.

    Science.gov (United States)

    Lu, Hai-Han; Li, Chung-Yi; Chen, Hwan-Wei; Ho, Chun-Ming; Cheng, Ming-Te; Huang, Sheng-Jhe; Yang, Zih-Yi; Lin, Xin-Yao

    2016-07-25

    A bidirectional fiber-wireless and fiber-invisible laser light communication (IVLLC) integrated system that employs polarization-orthogonal modulation scheme for hybrid cable television (CATV)/microwave (MW)/millimeter-wave (MMW)/baseband (BB) signal transmission is proposed and demonstrated. To our knowledge, it is the first one that adopts a polarization-orthogonal modulation scheme in a bidirectional fiber-wireless and fiber-IVLLC integrated system with hybrid CATV/MW/MMW/BB signal. For downlink transmission, carrier-to-noise ratio (CNR), composite second-order (CSO), composite triple-beat (CTB), and bit error rate (BER) perform well over 40-km single-mode fiber (SMF) and 10-m RF/50-m optical wireless transport scenarios. For uplink transmission, good BER performance is obtained over 40-km SMF and 50-m optical wireless transport scenario. Such a bidirectional fiber-wireless and fiber-IVLLC integrated system for hybrid CATV/MW/MMW/BB signal transmission will be an attractive alternative for providing broadband integrated services, including CATV, Internet, and telecommunication services. It is shown to be a prominent one to present the advancements for the convergence of fiber backbone and RF/optical wireless feeder.

  6. Technology for 3D System Integration for Flexible Wireless Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Wen-Cheng Kuo

    2018-05-01

    Full Text Available This paper presents a new 3D bottom-up packing technology for integrating a chip, an induction coil, and interconnections for flexible wireless biomedical applications. Parylene was used as a flexible substrate for the bottom-up embedding of the chip, insulation layer, interconnection, and inductors to form a flexible wireless biomedical microsystem. The system can be implanted on or inside the human body. A 50-μm gold foil deposited through laser micromachining by using a picosecond laser was used as an inductor to yield a higher quality factor than that yielded by thickness-increasing methods such as the fold-and-bond method or thick-metal electroplating method at the operation frequency of 1 MHz. For system integration, parylene was used as a flexible substrate, and the contact pads and connections between the coil and chip were generated using gold deposition. The advantage of the proposed process can integrate the chip and coil vertically to generate a single biocompatible system in order to reduce required area. The proposed system entails the use of 3D integrated circuit packaging concepts to integrate the chip and coil. The results validated the feasibility of this technology.

  7. Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Vivek [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Yanliang [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-09-01

    This report focuses on integrating TEG and WSN simulators with DC-DC converter as an interface. Here DC stands for direct current. DC-DC converter is essential to balance a wide range of analog, digital, and radio loads acting on the energy source. Also, the voltage level generated by TEGs under varying temperature conditions could be low, irregular, and insufficient to operate WSN, therefore DC-DC is required to boost up the voltage to a desired level. Most of the main problems of DC-DC converters used in TEG system are related to impedance matching between the internal resistance of TEG and the input resistance of DC-DC converter. This report would address the issue associated with dynamic impedance matching under varying temperature conditions in the effort to integrate TEG and WSN. In this effort, dynamic impedance matching algorithms like perturb and observe (P&O) and extremum seeking control (ESC) algorithms will de implemented and compared to achieve maximum peak power tracking (MPPT). In addition, the report will summarize the experimental study performed at BSU on profiling behavior of WSN prototype.

  8. Smart integrated containment leakage rate test system using wireless communication

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Dong Hwan; Lee, Sang Yong; Kim, Jung Sun; Kim, Gun Soo; Kim, Jong Myeong; Ahn, Jong Han [Research and Development Center, Ulsan (Korea, Republic of)

    2012-10-15

    Integrated Leakage Rate Test (ILRT) is the important test the confidentiality and integrity of the containment building, which is the last barrier when Design basis accidents (DBA) of Nuclear Power plant occur. Since the result of this test is the basis to guarantee the safety of nuclear power plants, the test process, test procedure, and the test equipment are required to have high reliability. The test devices previously used have been products of VOLUMERTRICS and GRAFTEL of USA. These devices have been inconvenient to calibrate and use. Thus improved devices needed to be developed to remove the inconveniences, to verify the safety of Korean nuclear power plants with Korea's own technology, and to secure core technology. A new leak test system was developed by domestic technology for that purpose and needed to be verified. In this paper, technical details of the newly developed easy to use and highly reliable measuring test device, which is in operation at the nuclear power plant sites, will be introduced. State of art technology was applied to the device to address the shortcomings of previous US made devices and the difficulties to use on site.

  9. Integration of Thermoelectric Generator and Wireless Sensor Node Simulators

    International Nuclear Information System (INIS)

    Agarwal, Vivek; Zhang, Yanliang

    2016-01-01

    This report focuses on integrating TEG and WSN simulators with DC-DC converter as an interface. Here DC stands for direct current. DC-DC converter is essential to balance a wide range of analog, digital, and radio loads acting on the energy source. Also, the voltage level generated by TEGs under varying temperature conditions could be low, irregular, and insufficient to operate WSN, therefore DC-DC is required to boost up the voltage to a desired level. Most of the main problems of DC-DC converters used in TEG system are related to impedance matching between the internal resistance of TEG and the input resistance of DC-DC converter. This report would address the issue associated with dynamic impedance matching under varying temperature conditions in the effort to integrate TEG and WSN. In this effort, dynamic impedance matching algorithms like perturb and observe (P&O) and extremum seeking control (ESC) algorithms will de implemented and compared to achieve maximum peak power tracking (MPPT). In addition, the report will summarize the experimental study performed at BSU on profiling behavior of WSN prototype.

  10. A 10.6mm3 Fully-Integrated, Wireless Sensor Node with 8GHz UWB Transmitter.

    Science.gov (United States)

    Kim, Hyeongseok; Kim, Gyouho; Lee, Yoonmyung; Foo, Zhiyoong; Sylvester, Dennis; Blaauw, David; Wentzloff, David

    2015-06-01

    This paper presents a complete, autonomous, wireless temperature sensor, fully encapsulated in a 10.6mm 3 volume. The sensor includes solar energy harvesting with an integrated 2 μAh battery, optical receiver for programming, microcontroller and memory, 8GHz UWB transmitter, and miniaturized custom antennas with a wireless range of 7 meters. Full, stand-alone operation was demonstrated for the first time for a system of this size and functionality.

  11. Soft computing integrating evolutionary, neural, and fuzzy systems

    CERN Document Server

    Tettamanzi, Andrea

    2001-01-01

    Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

  12. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  13. Integrated wireless sensor network for monitoring pregnant women.

    Science.gov (United States)

    Niţulescu, Adina; Crişan-Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Bernad, Elena

    2015-01-01

    The paper presents an integrated monitoring system for pregnant women in the third trimester using a mobile cardiotocograph and body sensors. The medical staff has a useful tool to detect abnormalities and prevent unfortunate events in time. The mobile cardiotocograph sends data in real time to a Smartphone that communicates the information in a cloud. The physician accesses the data using the hospital ObgGyn application. The advantage of using this system is that the pregnant woman can follow her pregnancy status evolution from home, and the physician receives alarms from the system if the data is not in normal range and has available information about the health status at any time and location.

  14. Wireless Biological Electronic Sensors.

    Science.gov (United States)

    Cui, Yue

    2017-10-09

    The development of wireless biological electronic sensors could open up significant advances for both fundamental studies and practical applications in a variety of areas, including medical diagnosis, environmental monitoring, and defense applications. One of the major challenges in the development of wireless bioelectronic sensors is the successful integration of biosensing units and wireless signal transducers. In recent years, there are a few types of wireless communication systems that have been integrated with biosensing systems to construct wireless bioelectronic sensors. To successfully construct wireless biological electronic sensors, there are several interesting questions: What types of biosensing transducers can be used in wireless bioelectronic sensors? What types of wireless systems can be integrated with biosensing transducers to construct wireless bioelectronic sensors? How are the electrical sensing signals generated and transmitted? This review will highlight the early attempts to address these questions in the development of wireless biological electronic sensors.

  15. Toward a fully integrated wireless wearable EEG-NIRS bimodal acquisition system.

    Science.gov (United States)

    Safaie, J; Grebe, R; Abrishami Moghaddam, H; Wallois, F

    2013-10-01

    Interactions between neuronal electrical activity and regional changes in microcirculation are assumed to play a major role in physiological brain activity and the development of pathological disorders, but have been poorly elucidated to date. There is a need for advanced diagnostic tools to investigate the relationships between these two physiological processes. To meet these needs, a wireless wearable system has been developed, which combines a near infrared spectroscopy (NIRS) system using light emitting diodes (LEDs) as a light source and silicon photodiodes as a detector with an integrated electroencephalography (EEG) system. The main advantages over currently available devices are miniaturization and integration of a real-time electrical and hemodynamic activity monitor into one wearable device. For patient distributed monitoring and creating a body-area network, up to seven same devices can be connected to a single base station (PC) synchronously. Each node presents enhanced portability due to the wireless communication and highly integrated components resulting in a small, lightweight signal acquisition device. Further progress includes the individual control of LEDs output to automatically or interactively adjust emitted light to the actual local situation online, the use of silicon photodiodes with a safe low-voltage power supply, and an integrated three dimensional accelerometer for movement detection for the identification of motion artifacts. The device was tested and validated using our enhanced EEG-NIRS tissue mimicking fluid phantom for sensitivity mapping. Typical somatotopic electrical evoked potential experiments were performed to verify clinical applicability.

  16. Toward a fully integrated wireless wearable EEG-NIRS bimodal acquisition system

    Science.gov (United States)

    Safaie, J.; Grebe, R.; Abrishami Moghaddam, H.; Wallois, F.

    2013-10-01

    Objective. Interactions between neuronal electrical activity and regional changes in microcirculation are assumed to play a major role in physiological brain activity and the development of pathological disorders, but have been poorly elucidated to date. There is a need for advanced diagnostic tools to investigate the relationships between these two physiological processes.Approach. To meet these needs, a wireless wearable system has been developed, which combines a near infrared spectroscopy (NIRS) system using light emitting diodes (LEDs) as a light source and silicon photodiodes as a detector with an integrated electroencephalography (EEG) system. Main results. The main advantages over currently available devices are miniaturization and integration of a real-time electrical and hemodynamic activity monitor into one wearable device. For patient distributed monitoring and creating a body-area network, up to seven same devices can be connected to a single base station (PC) synchronously. Each node presents enhanced portability due to the wireless communication and highly integrated components resulting in a small, lightweight signal acquisition device. Further progress includes the individual control of LEDs output to automatically or interactively adjust emitted light to the actual local situation online, the use of silicon photodiodes with a safe low-voltage power supply, and an integrated three dimensional accelerometer for movement detection for the identification of motion artifacts. Significance. The device was tested and validated using our enhanced EEG-NIRS tissue mimicking fluid phantom for sensitivity mapping. Typical somatotopic electrical evoked potential experiments were performed to verify clinical applicability.

  17. An Integrated Signaling-Encryption Mechanism to Reduce Error Propagation in Wireless Communications: Performance Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Olama, Mohammed M [ORNL; Matalgah, Mustafa M [ORNL; Bobrek, Miljko [ORNL

    2015-01-01

    Traditional encryption techniques require packet overhead, produce processing time delay, and suffer from severe quality of service deterioration due to fades and interference in wireless channels. These issues reduce the effective transmission data rate (throughput) considerably in wireless communications, where data rate with limited bandwidth is the main constraint. In this paper, performance evaluation analyses are conducted for an integrated signaling-encryption mechanism that is secure and enables improved throughput and probability of bit-error in wireless channels. This mechanism eliminates the drawbacks stated herein by encrypting only a small portion of an entire transmitted frame, while the rest is not subject to traditional encryption but goes through a signaling process (designed transformation) with the plaintext of the portion selected for encryption. We also propose to incorporate error correction coding solely on the small encrypted portion of the data to drastically improve the overall bit-error rate performance while not noticeably increasing the required bit-rate. We focus on validating the signaling-encryption mechanism utilizing Hamming and convolutional error correction coding by conducting an end-to-end system-level simulation-based study. The average probability of bit-error and throughput of the encryption mechanism are evaluated over standard Gaussian and Rayleigh fading-type channels and compared to the ones of the conventional advanced encryption standard (AES).

  18. A Wireless Pressure Sensor Integrated with a Biodegradable Polymer Stent for Biomedical Applications.

    Science.gov (United States)

    Park, Jongsung; Kim, Ji-Kwan; Patil, Swati J; Park, Jun-Kyu; Park, SuA; Lee, Dong-Weon

    2016-06-02

    This paper describes the fabrication and characterization of a wireless pressure sensor for smart stent applications. The micromachined pressure sensor has an area of 3.13 × 3.16 mm² and is fabricated with a photosensitive SU-8 polymer. The wireless pressure sensor comprises a resonant circuit and can be used without the use of an internal power source. The capacitance variations caused by changes in the intravascular pressure shift the resonance frequency of the sensor. This change can be detected using an external antenna, thus enabling the measurement of the pressure changes inside a tube with a simple external circuit. The wireless pressure sensor is capable of measuring pressure from 0 mmHg to 230 mmHg, with a sensitivity of 0.043 MHz/mmHg. The biocompatibility of the pressure sensor was evaluated using cardiac cells isolated from neonatal rat ventricular myocytes. After inserting a metal stent integrated with the pressure sensor into a cardiovascular vessel of an animal, medical systems such as X-ray were employed to consistently monitor the condition of the blood vessel. No abnormality was found in the animal blood vessel for approximately one month. Furthermore, a biodegradable polymer (polycaprolactone) stent was fabricated with a 3D printer. The polymer stent exhibits better sensitivity degradation of the pressure sensor compared to the metal stent.

  19. A Wireless Pressure Sensor Integrated with a Biodegradable Polymer Stent for Biomedical Applications

    Directory of Open Access Journals (Sweden)

    Jongsung Park

    2016-06-01

    Full Text Available This paper describes the fabrication and characterization of a wireless pressure sensor for smart stent applications. The micromachined pressure sensor has an area of 3.13 × 3.16 mm2 and is fabricated with a photosensitive SU-8 polymer. The wireless pressure sensor comprises a resonant circuit and can be used without the use of an internal power source. The capacitance variations caused by changes in the intravascular pressure shift the resonance frequency of the sensor. This change can be detected using an external antenna, thus enabling the measurement of the pressure changes inside a tube with a simple external circuit. The wireless pressure sensor is capable of measuring pressure from 0 mmHg to 230 mmHg, with a sensitivity of 0.043 MHz/mmHg. The biocompatibility of the pressure sensor was evaluated using cardiac cells isolated from neonatal rat ventricular myocytes. After inserting a metal stent integrated with the pressure sensor into a cardiovascular vessel of an animal, medical systems such as X-ray were employed to consistently monitor the condition of the blood vessel. No abnormality was found in the animal blood vessel for approximately one month. Furthermore, a biodegradable polymer (polycaprolactone stent was fabricated with a 3D printer. The polymer stent exhibits better sensitivity degradation of the pressure sensor compared to the metal stent.

  20. Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegie gait with machine learning classification by multilayer perceptron neural network.

    Science.gov (United States)

    LeMoyne, Robert; Mastroianni, Timothy

    2016-08-01

    Natural gait consists of synchronous and rhythmic patterns for both the lower and upper limb. People with hemiplegia can experience reduced arm swing, which can negatively impact the quality of gait. Wearable and wireless sensors, such as through a smartphone, have demonstrated the ability to quantify various features of gait. With a software application the smartphone (iPhone) can function as a wireless gyroscope platform capable of conveying a gyroscope signal recording as an email attachment by wireless connectivity to the Internet. The gyroscope signal recordings of the affected hemiplegic arm with reduced arm swing arm and the unaffected arm are post-processed into a feature set for machine learning. Using a multilayer perceptron neural network a considerable degree of classification accuracy is attained to distinguish between the affected hemiplegic arm with reduced arm swing arm and the unaffected arm.

  1. 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.

  2. From behavior to neural dynamics: An integrated theory of attention

    Science.gov (United States)

    Buschman, Timothy J.; Kastner, Sabine

    2015-01-01

    The brain has a limited capacity and therefore needs mechanisms to selectively enhance the information most relevant to one’s current behavior. We refer to these mechanisms as ‘attention’. Attention acts by increasing the strength of selected neural representations and preferentially routing them through the brain’s large-scale network. This is a critical component of cognition and therefore has been a central topic in cognitive neuroscience. Here we review a diverse literature that has studied attention at the level of behavior, networks, circuits and neurons. We then integrate these disparate results into a unified theory of attention. PMID:26447577

  3. Integrated Vehicle Health Management Project-Modeling and Simulation for Wireless Sensor Applications

    Science.gov (United States)

    Wallett, Thomas M.; Mueller, Carl H.; Griner, James H., Jr.

    2009-01-01

    This paper describes the efforts in modeling and simulating electromagnetic transmission and reception as in a wireless sensor network through a realistic wing model for the Integrated Vehicle Health Management project at the Glenn Research Center. A computer model in a standard format for an S-3 Viking aircraft was obtained, converted to a Microwave Studio software format, and scaled to proper dimensions in Microwave Studio. The left wing portion of the model was used with two antenna models, one transmitting and one receiving, to simulate radio frequency transmission through the wing. Transmission and reception results were inconclusive.

  4. Integrated passive and wireless sensor for magnetic fields, temperature and humidity

    KAUST Repository

    Li, Bodong

    2013-11-01

    This paper presents a surface acoustic wave-based passive and wireless sensor that can measure magnetic field, temperature and humidity. A thin film giant magnetoimpedance sensor, a thermally sensitive LiNbO3 substrate and a humidity sensitive hydrogel are integrated together with a surface acoustic wave transducer to realize the multifunctional sensor. The device is characterized using a network analyzer under sequentially changing humidity, temperature and magnetic field conditions. The first hand results show the sensor response to all three sensing parameters with small temperature interference on the magnetic signals. © 2013 IEEE.

  5. Integrated passive and wireless sensor for magnetic fields, temperature and humidity

    KAUST Repository

    Li, Bodong; Yassine, Omar; Kosel, Jü rgen

    2013-01-01

    This paper presents a surface acoustic wave-based passive and wireless sensor that can measure magnetic field, temperature and humidity. A thin film giant magnetoimpedance sensor, a thermally sensitive LiNbO3 substrate and a humidity sensitive hydrogel are integrated together with a surface acoustic wave transducer to realize the multifunctional sensor. The device is characterized using a network analyzer under sequentially changing humidity, temperature and magnetic field conditions. The first hand results show the sensor response to all three sensing parameters with small temperature interference on the magnetic signals. © 2013 IEEE.

  6. Conformally integrated stent cell resonators for wireless monitoring of peripheral artery disease

    KAUST Repository

    Viswanath, Anupam

    2013-01-01

    This paper presents the design and in vitro evaluation of magnetoelastic sensors intended for wireless monitoring of tissue accumulation in peripheral artery stents. The sensors, shaped like stent cells, are fabricated from 28-μm thick foils of magnetoelastic Ni-Fe alloy and are conformally integrated with the stent. The typical sensitivity to viscosity is 427 ppm/cP over a 1.1-8.6 cP range. The sensitivity to mass loading is typically 63,000-65000 ppm/mg with resonant frequency showing an 8.1% reduction for an applied mass that is 15% of the unloaded mass of the sensor. © 2013 IEEE.

  7. An integrated artificial neural networks approach for predicting global radiation

    International Nuclear Information System (INIS)

    Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

    2009-01-01

    This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

  8. Ultracompact Implantable Design With Integrated Wireless Power Transfer and RF Transmission Capabilities.

    Science.gov (United States)

    Sun, Guilin; Muneer, Badar; Li, Ying; Zhu, Qi

    2018-04-01

    This paper presents an ultracompact design of biomedical implantable devices with integrated wireless power transfer (WPT) and RF transmission capabilities for implantable medical applications. By reusing the spiral coil in an implantable device, both RF transmission and WPT are realized without the performance degradation of both functions in ultracompact size. The complete theory of WPT based on magnetic resonant coupling is discussed and the design methodology of an integrated structure is presented in detail, which can guide the design effectively. A system with an external power transmitter and implantable structure is fabricated to validate the proposed approach. The experimental results show that the implantable structure can receive power wirelessly at 39.86 MHz with power transfer efficiency of 47.2% and can also simultaneously radiate at 2.45 GHz with an impedance bandwidth of 10.8% and a gain of -15.71 dBi in the desired direction. Furthermore, sensitivity analyses are carried out with the help of experiment and simulation. The results reveal that the system has strong tolerance to the nonideal conditions. Additionally, the specific absorption rate distribution is evaluated in the light of strict IEEE standards. The results reveal that the implantable structure can receive up to 115 mW power from an external transmitter and radiate 6.4 dB·m of power safely.

  9. Integration of Resonant Coil for Wireless Power Transfer and Implantable Antenna for Signal Transfer

    Directory of Open Access Journals (Sweden)

    Dong-Wook Seo

    2016-01-01

    Full Text Available We propose the integration of the resonant coil for wireless power transfer (WPT and the implantable antenna for physiological signal transfer. The integration allows for a compact biomedical implantable system such as electrocardiogram (ECG recorder and pacemaker. While the resonant coils resonate at the frequency of 13.56 MHz for the WPT, the implantable antenna works in the medical implant communications service (MICS band of 402–405 MHz for wireless communications. They share the narrow substrate area of a bar-type shape; the coil has the current path on the outer part of the substrate and the meandered planar inverted-F antenna (PIFA occupies the inside of the coil. To verify the potentials of the proposed structure, a prototype is fabricated and tested in vitro. The power transfer efficiency (PTE of about 20% is obtained at a distance of 15 mm and the antenna gain of roughly −40 dBi is achieved.

  10. Thermomechanical stability and integrability of an embedded ceramic antenna with an integrated sensor element for wireless reading in harsh environments

    Science.gov (United States)

    Sturesson, P.; Khaji, Z.; Knaust, S.; Sundqvist, J.; Klintberg, L.; Thornell, G.

    2013-12-01

    This paper reports on the design, manufacturing and evaluation of a small, wirelessly powered and read resonating antenna circuit with an integrated pressure sensor. The work aims at developing miniature devices suitable for harsh environments, where high temperature prevents the use of conventional, silicon-based microdevices. Here, the device is made of alumina with platinum as conducting material. Ceramic green tapes were structured using high-precision milling, metallized using screen printing, and subsequently laminated to form stacks before they were sintered. The device's frequency shift as a function of temperature was studied up to 900°C. The contributions to the shift both from the thermomechanical deformation of the device at large, and from the integrated and, so far, self-pressurized sensor were sorted out. A total frequency shift of 3200 ppm was observed for the pressure sensor for heating over the whole range. Negligible levels of thermally induced radius of curvature were observed. With three-point bending, a frequency shift of 180 ppm was possible to induce with a curvature of radius of 220 m at a 10 N load. The results indicate that a robust pressure sensor node, which can register pressure changes of a few bars at 900°C and wirelessly transmit the signal, is viable.

  11. Thermomechanical stability and integrability of an embedded ceramic antenna with an integrated sensor element for wireless reading in harsh environments

    International Nuclear Information System (INIS)

    Sturesson, P; Sundqvist, J; Thornell, G; Khaji, Z; Knaust, S; Klintberg, L

    2013-01-01

    This paper reports on the design, manufacturing and evaluation of a small, wirelessly powered and read resonating antenna circuit with an integrated pressure sensor. The work aims at developing miniature devices suitable for harsh environments, where high temperature prevents the use of conventional, silicon-based microdevices. Here, the device is made of alumina with platinum as conducting material. Ceramic green tapes were structured using high-precision milling, metallized using screen printing, and subsequently laminated to form stacks before they were sintered. The device's frequency shift as a function of temperature was studied up to 900°C. The contributions to the shift both from the thermomechanical deformation of the device at large, and from the integrated and, so far, self-pressurized sensor were sorted out. A total frequency shift of 3200 ppm was observed for the pressure sensor for heating over the whole range. Negligible levels of thermally induced radius of curvature were observed. With three-point bending, a frequency shift of 180 ppm was possible to induce with a curvature of radius of 220 m at a 10 N load. The results indicate that a robust pressure sensor node, which can register pressure changes of a few bars at 900°C and wirelessly transmit the signal, is viable

  12. A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Nadia Adnan Shiltagh

    2015-11-01

    Full Text Available Wireless Multimedia Sensor Networks (WMSNs are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC. The Modify Spike Neural Network controller (MSNC can calculate the appropriate traffic load parameter μ for each parent node and then use in the EWPBRC algorithm to estimate the transmission rate of parent nodes and then assign a suitable transmission rate for each child node. A comparative study between (MSNTLP with EWBPRC and fuzzy logic controller for traffic load parameter with Exponential Weight of Priority Based Rate Control algorithm (FTLP with EWBPRC algorithm shows that the (MSNTLP with EWBPRC is more efficient than (FTLP with EWBPRC algorithm in terms of packet loss, queue delay and throughput. Another comparative study between (MSNTLP with EWBPRC and EWBPRC with fixed traffic load parameter (µ shows that the MSNTLP with EWBPRC is more efficient than EWBPRC with fixed traffic load parameter (µ in terms of packet loss ratio and queue delay. A simulation process is developed and tested using the network simulator _2 (NS2 in a computer having the following properties: windows 7 (64-bit, core i7, RAM 8GB, hard 1TB.

  13. Adaptive quantization of local field potentials for wireless implants in freely moving animals: an open-source neural recording device

    Science.gov (United States)

    Martinez, Dominique; Clément, Maxime; Messaoudi, Belkacem; Gervasoni, Damien; Litaudon, Philippe; Buonviso, Nathalie

    2018-04-01

    Objective. Modern neuroscience research requires electrophysiological recording of local field potentials (LFPs) in moving animals. Wireless transmission has the advantage of removing the wires between the animal and the recording equipment but is hampered by the large number of data to be sent at a relatively high rate. Approach. To reduce transmission bandwidth, we propose an encoder/decoder scheme based on adaptive non-uniform quantization. Our algorithm uses the current transmitted codeword to adapt the quantization intervals to changing statistics in LFP signals. It is thus backward adaptive and does not require the sending of side information. The computational complexity is low and similar at the encoder and decoder sides. These features allow for real-time signal recovery and facilitate hardware implementation with low-cost commercial microcontrollers. Main results. As proof-of-concept, we developed an open-source neural recording device called NeRD. The NeRD prototype digitally transmits eight channels encoded at 10 kHz with 2 bits per sample. It occupies a volume of 2  ×  2  ×  2 cm3 and weighs 8 g with a small battery allowing for 2 h 40 min of autonomy. The power dissipation is 59.4 mW for a communication range of 8 m and transmission losses below 0.1%. The small weight and low power consumption offer the possibility of mounting the entire device on the head of a rodent without resorting to a separate head-stage and battery backpack. The NeRD prototype is validated in recording LFPs in freely moving rats at 2 bits per sample while maintaining an acceptable signal-to-noise ratio (>30 dB) over a range of noisy channels. Significance. Adaptive quantization in neural implants allows for lower transmission bandwidths while retaining high signal fidelity and preserving fundamental frequencies in LFPs.

  14. 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.

  15. A Review on Radio-Over-Fiber Technology-Based Integrated (Optical/Wireless) Networks

    Science.gov (United States)

    Rajpal, Shivika; Goyal, Rakesh

    2017-06-01

    In the present paper, radio-over-fiber (RoF) technology has been proposed, which is the integration of the optical and radio networks. With a high transmission capacity, comparatively low cost and low attenuation, optical fiber provides an ideal solution for accomplishing the interconnections. In addition, a radio system enables the significant mobility, flexibility and easy access. Therefore, the system integration can meet the increasing demands of subscribers for voice, data and multimedia services that require the access network to support high data rates at any time and any place inexpensively. RoF has the potentiality to the backbone of the wireless access network and it has gained significant momentum in the last decade as a potential last-mile access scheme. This paper gives the comprehensive review of RoF technology used in the communication system. Concept, applications, advantages and limitations of RoF technology are also discussed in this paper.

  16. Attention Modulates the Neural Processes Underlying Multisensory Integration of Emotion

    Directory of Open Access Journals (Sweden)

    Hao Tam Ho

    2011-10-01

    Full Text Available Integrating emotional information from multiple sensory modalities is generally assumed to be a pre-attentive process (de Gelder et al., 1999. This assumption, however, presupposes that the integrative process occurs independent of attention. Using event-potentials (ERP the present study investigated whether the neural processes underlying the integration of dynamic facial expression and emotional prosody is indeed unaffected by attentional manipulations. To this end, participants were presented with congruent and incongruent face-voice combinations (eg, an angry face combined with a neutral voice and performed different two-choice tasks in four consecutive blocks. Three of the tasks directed the participants' attention to emotion expressions in the face, the voice or both. The fourth task required participants to attend to the synchronicity between voice and lip movements. The results show divergent modulations of early ERP components by the different attentional manipulations. For example, when attention was directed to the face (or the voice, incongruent stimuli elicited a reduced N1 as compared to congruent stimuli. This effect was absent, when attention was diverted away from the emotionality in both face and voice suggesting that the detection of emotional incongruence already requires attention. Based on these findings, we question whether multisensory integration of emotion occurs indeed pre-attentively.

  17. Modeling and Characterization of Capacitive Elements With Tissue as Dielectric Material for Wireless Powering of Neural Implants.

    Science.gov (United States)

    Erfani, Reza; Marefat, Fatemeh; Sodagar, Amir M; Mohseni, Pedram

    2018-05-01

    This paper reports on the modeling and characterization of capacitive elements with tissue as the dielectric material, representing the core building block of a capacitive link for wireless power transfer to neural implants. Each capacitive element consists of two parallel plates that are aligned around the tissue layer and incorporate a grounded, guarded, capacitive pad to mitigate the adverse effect of stray capacitances and shield the plates from external interfering electric fields. The plates are also coated with a biocompatible, insulating, coating layer on the inner side of each plate in contact with the tissue. A comprehensive circuit model is presented that accounts for the effect of the coating layers and is validated by measurements of the equivalent capacitance as well as impedance magnitude/phase of the parallel plates over a wide frequency range of 1 kHz-10 MHz. Using insulating coating layers of Parylene-C at a thickness of and Parylene-N at a thickness of deposited on two sets of parallel plates with different sizes and shapes of the guarded pad, our modeling and characterization results accurately capture the effect of the thickness and electrical properties of the coating layers on the behavior of the capacitive elements over frequency and with different tissues.

  18. Integration of active devices on smart polymers for neural interfaces

    Science.gov (United States)

    Avendano-Bolivar, Adrian Emmanuel

    The increasing ability to ever more precisely identify and measure neural interactions and other phenomena in the central and peripheral nervous systems is revolutionizing our understanding of the human body and brain. To facilitate further understanding, more sophisticated neural devices, perhaps using microelectronics processing, must be fabricated. Materials often used in these neural interfaces, while compatible with these fabrication processes, are not optimized for long-term use in the body and are often orders of magnitude stiffer than the tissue with which they interact. Using the smart polymer substrates described in this work, suitability for processing as well as chronic implantation is demonstrated. We explore how to integrate reliable circuitry onto these flexible, biocompatible substrates that can withstand the aggressive environment of the body. To increase the capabilities of these devices beyond individual channel sensing and stimulation, active electronics must also be included onto our systems. In order to add this functionality to these substrates and explore the limits of these devices, we developed a process to fabricate single organic thin film transistors with mobilities up to 0.4 cm2/Vs and threshold voltages close to 0V. A process for fabricating organic light emitting diodes on flexible substrates is also addressed. We have set a foundation and demonstrated initial feasibility for integrating multiple transistors onto thin-film flexible devices to create new applications, such as matrix addressable functionalized electrodes and organic light emitting diodes. A brief description on how to integrate waveguides for their use in optogenetics is addressed. We have built understanding about device constraints on mechanical, electrical and in vivo reliability and how various conditions affect the electronics' lifetime. We use a bi-layer gate dielectric using an inorganic material such as HfO 2 combined with organic Parylene-c. A study of

  19. Neural Networks Integrated Circuit for Biomimetics MEMS Microrobot

    Directory of Open Access Journals (Sweden)

    Ken Saito

    2014-06-01

    Full Text Available In this paper, we will propose the neural networks integrated circuit (NNIC which is the driving waveform generator of the 4.0, 2.7, 2.5 mm, width, length, height in size biomimetics microelectromechanical systems (MEMS microrobot. The microrobot was made from silicon wafer fabricated by micro fabrication technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the ant-like switching behavior. The NNIC generates the driving waveform using synchronization phenomena such as biological neural networks. The driving waveform can operate the actuators of the MEMS microrobot directly. Therefore, the NNIC bare chip realizes the robot control without using any software programs or A/D converters. The microrobot performed forward and backward locomotion, and also changes direction by inputting an external single trigger pulse. The locomotion speed of the microrobot was 26.4 mm/min when the step width was 0.88 mm. The power consumption of the system was 250 mWh when the room temperature was 298 K.

  20. Two multichannel integrated circuits for neural recording and signal processing.

    Science.gov (United States)

    Obeid, Iyad; Morizio, James C; Moxon, Karen A; Nicolelis, Miguel A L; Wolf, Patrick D

    2003-02-01

    We have developed, manufactured, and tested two analog CMOS integrated circuit "neurochips" for recording from arrays of densely packed neural electrodes. Device A is a 16-channel buffer consisting of parallel noninverting amplifiers with a gain of 2 V/V. Device B is a 16-channel two-stage analog signal processor with differential amplification and high-pass filtering. It features selectable gains of 250 and 500 V/V as well as reference channel selection. The resulting amplifiers on Device A had a mean gain of 1.99 V/V with an equivalent input noise of 10 microV(rms). Those on Device B had mean gains of 53.4 and 47.4 dB with a high-pass filter pole at 211 Hz and an equivalent input noise of 4.4 microV(rms). Both devices were tested in vivo with electrode arrays implanted in the somatosensory cortex.

  1. Integrated digital printing of flexible circuits for wireless sensing (Conference Presentation)

    Science.gov (United States)

    Mei, Ping; Whiting, Gregory L.; Schwartz, David E.; Ng, Tse Nga; Krusor, Brent S.; Ready, Steve E.; Daniel, George; Veres, Janos; Street, Bob

    2016-09-01

    Wireless sensing has broad applications in a wide variety of fields such as infrastructure monitoring, chemistry, environmental engineering and cold supply chain management. Further development of sensing systems will focus on achieving light weight, flexibility, low power consumption and low cost. Fully printed electronics provide excellent flexibility and customizability, as well as the potential for low cost and large area applications, but lack solutions for high-density, high-performance circuitry. Conventional electronics mounted on flexible printed circuit boards provide high performance but are not digitally fabricated or readily customizable. Incorporation of small silicon dies or packaged chips into a printed platform enables high performance without compromising flexibility or cost. At PARC, we combine high functionality c-Si CMOS and digitally printed components and interconnects to create an integrated platform that can read and process multiple discrete sensors. Our approach facilitates customization to a wide variety of sensors and user interfaces suitable for a broad range of applications including remote monitoring of health, structures and environment. This talk will describe several examples of printed wireless sensing systems. The technologies required for these sensor systems are a mix of novel sensors, printing processes, conventional microchips, flexible substrates and energy harvesting power solutions.

  2. Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.

    Science.gov (United States)

    Shi, Shengchao; Li, Guangxia; An, Kang; Gao, Bin; Zheng, Gan

    2017-09-04

    This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach's method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint.

  3. Cost-Efficient DWDM-PON / Mm-Wave Wireless Integration using Coherent Radio-over-Fiber (CRoF)

    DEFF Research Database (Denmark)

    Thakur, Manoj P.; Mikroulis, S.; Renaud, C. C.

    2015-01-01

    This work aims to investigate the performance of millimetre wave (mm-wave) broadband wireless access for seamless integration with the (ultra-dense) WDM infrastructure. By using two uncorrelated lasers, this system concept allows simple implementation that can additionally be improved, if thermally...... for transmission. In this work, we analyze the performance of heterodyne based optical receivers, using OOK and multilevel modulation formats....

  4. Advanced Integration Techniques on Broadband Millimeter-Wave Beam Steering for 5G Wireless Networks and Beyond

    NARCIS (Netherlands)

    Cao, Zizheng; Ma, Qian; Smolders, Bart; Jiao, Yuqing; Wale, Mike; Oh, Joanne; wu, hequan; Koonen, Ton

    2015-01-01

    Recently, the desired very high throughput of 5G wireless networks drives millimeter-wave (mm-wave) communication into practical applications. A phased array technique is required to increase the effective antenna aperture at mm-wave frequency. Integrated solutions of beamforming/beam steering are

  5. Low cost Polymer Optical Fibre based transmission system for feeding integrated broadband wireless in-house LANs

    NARCIS (Netherlands)

    Ng'Oma, A.; Koonen, A.M.J.; Tafur Monroy, I.; Boom, van den H.P.A.; Smulders, P.F.M.; Khoe, G.D.; Visser, D. Taco; Lenstra, Daan; Schouten, F. Hugo

    2002-01-01

    A bi-directional transmission system using low cost Polymer Optical Fibre (POF) to feed the required large number of radio access points in next-generation integrated broadband wireless in-house LANs is proposed. Results from simulations and experiments show that, by tuning system parameters, a

  6. High-Frequency Wireless Communications System: 2.45-GHz Front-End Circuit and System Integration

    Science.gov (United States)

    Chen, M.-H.; Huang, M.-C.; Ting, Y.-C.; Chen, H.-H.; Li, T.-L.

    2010-01-01

    In this article, a course on high-frequency wireless communications systems is presented. With the 145-MHz baseband subsystem available from a prerequisite course, the present course emphasizes the design and implementation of the 2.45-GHz front-end subsystem as well as system integration issues. In this curriculum, the 2.45-GHz front-end…

  7. Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

    Science.gov (United States)

    Dâmaso, Antônio; Maciel, Paulo

    2017-01-01

    Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way. PMID:29113078

  8. Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Antônio Dâmaso

    2017-11-01

    Full Text Available Power consumption is a primary interest in Wireless Sensor Networks (WSNs, and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

  9. A proportional integral estimator-based clock synchronization protocol for wireless sensor networks.

    Science.gov (United States)

    Yang, Wenlun; Fu, Minyue

    2017-11-01

    Clock synchronization is an issue of vital importance in applications of WSNs. This paper proposes a proportional integral estimator-based protocol (EBP) to achieve clock synchronization for wireless sensor networks. As each local clock skew gradually drifts, synchronization accuracy will decline over time. Compared with existing consensus-based approaches, the proposed synchronization protocol improves synchronization accuracy under time-varying clock skews. Moreover, by restricting synchronization error of clock skew into a relative small quantity, it could reduce periodic re-synchronization frequencies. At last, a pseudo-synchronous implementation for skew compensation is introduced as synchronous protocol is unrealistic in practice. Numerical simulations are shown to illustrate the performance of the proposed protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks.

    Science.gov (United States)

    de Araújo, Paulo Régis C; Filho, Raimir Holanda; Rodrigues, Joel J P C; Oliveira, João P C M; Braga, Stephanie A

    2018-04-24

    At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

  11. Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Paulo Régis C. de Araújo

    2018-04-01

    Full Text Available At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs. In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

  12. Seamless integration of 57.2-Gb/s signal wireline transmission and 100-GHz wireless delivery.

    Science.gov (United States)

    Li, Xinying; Yu, Jianjun; Dong, Ze; Cao, Zizheng; Chi, Nan; Zhang, Junwen; Shao, Yufeng; Tao, Li

    2012-10-22

    We experimentally demonstrated the seamless integration of 57.2-Gb/s signal wireline transmission and 100-GHz wireless delivery adopting polarization-division-multiplexing quadrature-phase-shift-keying (PDM-QPSK) modulation with 400-km single-mode fiber-28 (SMF-28) transmission and 1-m wireless delivery. The X- and Y-polarization components of optical PDM-QPSK baseband signal are simultaneously up-converted to 100 GHz by optical polarization-diversity heterodyne beating, and then independently transmitted and received by two pairs of transmitter and receiver antennas, which make up a 2x2 multiple-input multiple-output (MIMO) wireless link based on microwave polarization multiplexing. At the wireless receiver, a two-stage down conversion is firstly done in analog domain based on balanced mixer and sinusoidal radio frequency (RF) signal, and then in digital domain based on digital signal processing (DSP). Polarization de-multiplexing is realized by constant modulus algorithm (CMA) based on DSP in heterodyne coherent detection. Our experimental results show that more taps are required for CMA when the X- and Y-polarization antennas have different wireless distance.

  13. Towards Internet of Things (IOTS):Integration of Wireless Sensor Network to Cloud Services for Data Collection and Sharing

    OpenAIRE

    Piyare, Rajeev; Lee, Seong Ro

    2013-01-01

    Cloud computing provides great benefits for applications hosted on the Web that also have special computational and storage requirements. This paper proposes an extensible and flexible architecture for integrating Wireless Sensor Networks with the Cloud. We have used REST based Web services as an interoperable application layer that can be directly integrated into other application domains for remote monitoring such as e-health care services, smart homes, or even vehicular area networks (VAN)...

  14. Activity in part of the neural correlates of consciousness reflects integration.

    Science.gov (United States)

    Eriksson, Johan

    2017-10-01

    Integration is commonly viewed as a key process for generating conscious experiences. Accordingly, there should be increased activity within the neural correlates of consciousness when demands on integration increase. We used fMRI and "informational masking" to isolate the neural correlates of consciousness and measured how the associated brain activity changed as a function of required integration. Integration was manipulated by comparing the experience of hearing simple reoccurring tones to hearing harmonic tone triplets. The neural correlates of auditory consciousness included superior temporal gyrus, lateral and medial frontal regions, cerebellum, and also parietal cortex. Critically, only activity in left parietal cortex increased significantly as a function of increasing demands on integration. We conclude that integration can explain part of the neural activity associated with the generation conscious experiences, but that much of associated brain activity apparently reflects other processes. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Electromagnetic design methods in systems-on-chip: integrated filters for wireless CMOS RFICs

    International Nuclear Information System (INIS)

    Contopanagos, Harry

    2005-01-01

    We present general methods for designing on-chip CMOS passives and utilizing these integrated elements to design on-chip CMOS filters for wireless communications. These methods rely on full-wave electromagnetic numerical calculations that capture all the physics of the underlying foundry technologies. This is especially crucial for deep sub-micron CMOS technologies as it is important to capture the physical effects of finite (and mediocre) Q-factors limited by material losses and constraints on expensive die area, low self-resonance frequencies and dual parasitics that are particularly prevalent in deep sub-micron CMOS processes (65 nm-0.18 μm. We use these integrated elements in an ideal synthesis of a Bluetooth/WLAN pass-band filter in single-ended or differential architectures, and show the significant deviations of the on-chip filter response from the ideal one. We identify which elements in the filter circuit need to maximize their Q-factors and which Q-factors do not affect the filter performance. This saves die area, and predicts the FET parameters (especially transconductances) and negative-resistance FET topologies that have to be integrated in the filter to restore its performance. (invited paper)

  16. Electromagnetic design methods in systems-on-chip: integrated filters for wireless CMOS RFICs

    Energy Technology Data Exchange (ETDEWEB)

    Contopanagos, Harry [Institute for Microelectronics, NCSR ' Demokritos' , PO Box 60228, GR-153 10 Aghia Paraskevi, Athens (Greece)

    2005-01-01

    We present general methods for designing on-chip CMOS passives and utilizing these integrated elements to design on-chip CMOS filters for wireless communications. These methods rely on full-wave electromagnetic numerical calculations that capture all the physics of the underlying foundry technologies. This is especially crucial for deep sub-micron CMOS technologies as it is important to capture the physical effects of finite (and mediocre) Q-factors limited by material losses and constraints on expensive die area, low self-resonance frequencies and dual parasitics that are particularly prevalent in deep sub-micron CMOS processes (65 nm-0.18 {mu}m. We use these integrated elements in an ideal synthesis of a Bluetooth/WLAN pass-band filter in single-ended or differential architectures, and show the significant deviations of the on-chip filter response from the ideal one. We identify which elements in the filter circuit need to maximize their Q-factors and which Q-factors do not affect the filter performance. This saves die area, and predicts the FET parameters (especially transconductances) and negative-resistance FET topologies that have to be integrated in the filter to restore its performance. (invited paper)

  17. A 60-GHz energy harvesting module with on-chip antenna and switch for co-integration with ULP radios in 65-nm CMOS with fully wireless mm-wave power transfer measurement

    NARCIS (Netherlands)

    Gao, H.; Matters - Kammerer, M.; Harpe, P.J.A.; Milosevic, D.; Roermund, van A.H.M.; Linnartz, J.P.M.G.; Baltus, P.G.M.

    2014-01-01

    In this paper the architecture and performance of a co-integrated 60 GHz on-chip wireless energy harvester and ultra-low power (ULP) radio in 65-nm CMOS are discussed. Integration of an on-chip antenna with wireless power receiver and wireless data transfer module is the crucial next step to achieve

  18. Sierra Nevada snowpack and runoff prediction integrating basin-wide wireless-sensor network data

    Science.gov (United States)

    Yoon, Y.; Conklin, M. H.; Bales, R. C.; Zhang, Z.; Zheng, Z.; Glaser, S. D.

    2016-12-01

    We focus on characterizing snowpack and estimating runoff from snowmelt in high elevation area (>2100 m) in Sierra Nevada for daily (for use in, e.g. flood and hydropower forecasting), seasonal (supply prediction), and decadal (long-term planning) time scale. Here, basin-wide wireless-sensor network data (ARHO, http://glaser.berkeley.edu/wsn/) is integrated into the USGS Precipitation-Runoff Modeling System (PRMS), and a case study of the American River basin is presented. In the American River basin, over 140 wireless sensors have been planted in 14 sites considering elevation gradient, slope, aspect, and vegetation density, which provides spatially distributed snow depth, temperature, solar radiation, and soil moisture from 2013. 800 m daily gridded dataset (PRISM) is used as the climate input for the PRMS. Model parameters are obtained from various sources (e.g., NLCD 2011, SSURGO, and NED) with a regionalization method and GIS analysis. We use a stepwise framework for a model calibration to improve model performance and localities of estimates. For this, entire basin is divided into 12 subbasins that include full natural flow measurements. The study period is between 1982 and 2014, which contains three major storm events and recent severe drought. Simulated snow depth and snow water equivalent (SWE) are initially compared with the water year 2014 ARHO observations. The overall results show reasonable agreements having the Nash-Sutcliffe efficiency coefficient (NS) of 0.7, ranged from 0.3 to 0.86. However, the results indicate a tendency to underestimate the SWE in a high elevation area compared with ARHO observations, which is caused by the underestimated PRISM precipitation data. Precipitation at gauge-sparse regions (e.g., high elevation area), in general, cannot be well represented in gridded datasets. Streamflow estimates of the basin outlet have NS of 0.93, percent bias of 7.8%, and normalized root mean square error of 3.6% for the monthly time scale.

  19. System-on-fluidics immunoassay device integrating wireless radio-frequency-identification sensor chips.

    Science.gov (United States)

    Yazawa, Yoshiaki; Oonishi, Tadashi; Watanabe, Kazuki; Shiratori, Akiko; Funaoka, Sohei; Fukushima, Masao

    2014-09-01

    A simple and sensitive point-of-care-test (POCT) device for chemiluminescence (CL) immunoassay was devised and tested. The device consists of a plastic flow-channel reactor and two wireless-communication sensor chips, namely, a photo-sensor chip and a temperature-sensor chip. In the flow-channel reactor, a target antigen is captured by an antibody immobilized on the inner wall of the flow-channel and detected with enzyme labeled antibody by using CL substrate. The CL signal corresponding to the amount of antigen is measured by a newly developed radio-frequency-identification (RFID) sensor, which enables batteryless operation and wireless data communication with an external reader. As for the POCT device, its usage environment, especially temperature, varies for each measurement. Hence, temperature compensation is a key issue in regard to eliminating dark-signal fluctuation, which is a major factor in deterioration of the precision of the POCT device. A two-stage temperature-compensation scheme was adopted. As for the first stage, the signals of two photodiodes, one with an open window and one with a sealed window, integrated on the photo-sensor chip are differentiated to delete the dark signal. As for the second stage, the differentiated signal fluctuation caused by a temperature variation is compensated by using the other sensor chip (equipped with a temperature sensor). The dark-level fluctuation caused by temperature was reduced from 0.24 to 0.02 pA/°C. The POCT device was evaluated as a CL immunoassay of thyroid-stimulating hormone (TSH). The flow rate of the CL reagent in the flow channel was optimized. As a result, the detection limit of the POCT device was 0.08 ng/ml (i.e., 0.4 μIU/ml). Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  20. Integration of a prototype wireless communication system with micro-electromechanical temperature and humidity sensor for concrete pavement health monitoring

    Directory of Open Access Journals (Sweden)

    Shuo Yang

    2015-12-01

    Full Text Available In recent years, structural health monitoring and management (SHMM has become a popular approach and is considered essential for achieving well-performing, long-lasting, sustainable transportation infrastructure systems. Key requirements in ideal SHMM of road infrastructure include long-term, continuous, and real-time monitoring of pavement response and performance under various pavement geometry-materials-loading configurations and environmental conditions. With advancements in wireless technologies, integration of wireless communications into sensing device is considered an alternate and superior solution to existing time- and labor-intensive wired sensing systems in meeting the requirements of an ideal SHMM. This study explored the development and integration of a wireless communications sub-system into a commercial off-the-shelf micro-electromechanical sensor-based concrete pavement monitoring system. A success-rate test was performed after the wireless transmission system was buried in the concrete slab, and the test results indicated that the system was able to provide reliable communications at a distance of more than 46 m (150 feet. This will be a useful feature for highway engineers performing routine pavement scans from the pavement shoulder without the need for traffic control or road closure.

  1. An implantable, batteryless, and wireless capsule with integrated impedance and pH sensors for gastroesophageal reflux monitoring.

    Science.gov (United States)

    Cao, Hung; Landge, Vaibhav; Tata, Uday; Seo, Young-Sik; Rao, Smitha; Tang, Shou-Jiang; Tibbals, H F; Spechler, Stuart; Chiao, J-C

    2012-11-01

    In this study, a device for gastroesophageal reflux disease (GERD) monitoring has been prototyped. The system consists of an implantable, batteryless and wireless transponder with integrated impedance and pH sensors; and a wearable, external reader that wirelessly powers up the transponder and interprets the transponded radio-frequency signals. The transponder implant with the total size of 0.4 cm × 0.8 cm × 3.8 cm harvests radio frequency energy to operate dual-sensor and load-modulation circuitry. The external reader can store the data in a memory card and/or send it to a base station wirelessly, which is optional in the case of multiple-patient monitoring in a hospital or conducting large-scale freely behaving animal experiments. Tests were carried out to verify the signal transduction reliability in different situations for antenna locations and orientation. In vitro, experiments were conducted in a mannequin model by positioning the sensor capsule inside the wall of a tube mimicking the esophagus. Different liquids with known pH values were flushed through the tube creating reflux episodes and wireless signals were recorded. Live pigs under anesthesia were used for the animal models with the transponder implant attached on the esophageal wall. The reflux episodes were created while the sensor data were recorded wirelessly. The data were compared with those recorded independently by a clinically used wireless pH sensor capsule placed next to our implant transponder. The results showed that our transponder detected every episode in both acid and nonacid nature, while the commercial pH sensor missed events that had similar, repeated pH values, and failed to detect pH values higher than 10. Our batteryless transponder does not require a battery thus allowing longer diagnosis and prognosis periods to monitor drug efficacy, as well as providing accurate assessment of GERD symptoms.

  2. Flexible Conductive Composite Integrated with Personal Earphone for Wireless, Real-Time Monitoring of Electrophysiological Signs.

    Science.gov (United States)

    Lee, Joong Hoon; Hwang, Ji-Young; Zhu, Jia; Hwang, Ha Ryeon; Lee, Seung Min; Cheng, Huanyu; Lee, Sang-Hoon; Hwang, Suk-Won

    2018-06-14

    We introduce optimized elastomeric conductive electrodes using a mixture of silver nanowires (AgNWs) with carbon nanotubes/polydimethylsiloxane (CNTs/PDMS), to build a portable earphone type of wearable system that is designed to enable recording electrophysiological activities as well as listening to music at the same time. A custom-built, plastic frame integrated with soft, deformable fabric-based memory foam of earmuffs facilitates essential electronic components, such as conductive elastomers, metal strips, signal transducers and a speaker. Such platform incorporates with accessory cables to attain wireless, real-time monitoring of electrical potentials whose information can be displayed on a cell phone during outdoor activities and music appreciation. Careful evaluations on experimental results reveal that the performance of fabricated dry electrodes are comparable to that of commercial wet electrodes, and position-dependent signal behaviors provide a route toward accomplishing maximized signal quality. This research offers a facile approach for a wearable healthcare monitor via integration of soft electronic constituents with personal belongings.

  3. Substrate Integrated Waveguide (SIW)-Based Wireless Temperature Sensor for Harsh Environments.

    Science.gov (United States)

    Tan, Qiulin; Guo, Yanjie; Zhang, Lei; Lu, Fei; Dong, Helei; Xiong, Jijun

    2018-05-03

    This paper presents a new wireless sensor structure based on a substrate integrated circular waveguide (SICW) for the temperature test in harsh environments. The sensor substrate material is 99% alumina ceramic, and the SICW structure is composed of upper and lower metal plates and a series of metal cylindrical sidewall vias. A rectangular aperture antenna integrated on the surface of the SICW resonator is used for electromagnetic wave transmission between the sensor and the external antenna. The resonant frequency of the temperature sensor decreases when the temperature increases, because the relative permittivity of the alumina ceramic increases with temperature. The temperature sensor presented in this paper was tested four times at a range of 30⁻1200 °C, and a broad band coplanar waveguide (CPW)-fed antenna was used as an interrogation antenna during the test process. The resonant frequency changed from 2.371 to 2.141 GHz as the temperature varied from 30 to 1200 °C, leading to a sensitivity of 0.197 MHz/°C. The quality factor of the sensor changed from 3444.6 to 35.028 when the temperature varied from 30 to 1000 °C.

  4. Fully Integrated Solar Energy Harvester and Sensor Interface Circuits for Energy-Efficient Wireless Sensing Applications

    Directory of Open Access Journals (Sweden)

    Maher Kayal

    2013-02-01

    Full Text Available This paper presents an energy-efficient solar energy harvesting and sensing microsystem that harvests solar energy from a micro-power photovoltaic module for autonomous operation of a gas sensor. A fully integrated solar energy harvester stores the harvested energy in a rechargeable NiMH microbattery. Hydrogen concentration and temperature are measured and converted to a digital value with 12-bit resolution using a fully integrated sensor interface circuit, and a wireless transceiver is used to transmit the measurement results to a base station. As the harvested solar energy varies considerably in different lighting conditions, in order to guarantee autonomous operation of the sensor, the proposed area- and energy-efficient circuit scales the power consumption and performance of the sensor. The power management circuit dynamically decreases the operating frequency of digital circuits and bias currents of analog circuits in the sensor interface circuit and increases the idle time of the transceiver under reduced light intensity. The proposed microsystem has been implemented in a 0.18 µm complementary metal-oxide-semiconductor (CMOS process and occupies a core area of only 0.25 mm2. This circuit features a low power consumption of 2.1 µW when operating at its highest performance. It operates with low power supply voltage in the 0.8V to 1.6 V range.

  5. Hybrid information privacy system: integration of chaotic neural network and RSA coding

    Science.gov (United States)

    Hsu, Ming-Kai; Willey, Jeff; Lee, Ting N.; Szu, Harold H.

    2005-03-01

    Electronic mails are adopted worldwide; most are easily hacked by hackers. In this paper, we purposed a free, fast and convenient hybrid privacy system to protect email communication. The privacy system is implemented by combining private security RSA algorithm with specific chaos neural network encryption process. The receiver can decrypt received email as long as it can reproduce the specified chaos neural network series, so called spatial-temporal keys. The chaotic typing and initial seed value of chaos neural network series, encrypted by the RSA algorithm, can reproduce spatial-temporal keys. The encrypted chaotic typing and initial seed value are hidden in watermark mixed nonlinearly with message media, wrapped with convolution error correction codes for wireless 3rd generation cellular phones. The message media can be an arbitrary image. The pattern noise has to be considered during transmission and it could affect/change the spatial-temporal keys. Since any change/modification on chaotic typing or initial seed value of chaos neural network series is not acceptable, the RSA codec system must be robust and fault-tolerant via wireless channel. The robust and fault-tolerant properties of chaos neural networks (CNN) were proved by a field theory of Associative Memory by Szu in 1997. The 1-D chaos generating nodes from the logistic map having arbitrarily negative slope a = p/q generating the N-shaped sigmoid was given first by Szu in 1992. In this paper, we simulated the robust and fault-tolerance properties of CNN under additive noise and pattern noise. We also implement a private version of RSA coding and chaos encryption process on messages.

  6. Integration of Low-Power ASIC and MEMS Sensors for Monitoring Gastrointestinal Tract Using a Wireless Capsule System.

    Science.gov (United States)

    Arefin, Md Shamsul; Redoute, Jean-Michel; Yuce, Mehmet Rasit

    2018-01-01

    This paper presents a wireless capsule microsystem to detect and monitor the pH, pressure, and temperature of the gastrointestinal tract in real time. This research contributes to the integration of sensors (microfabricated capacitive pH, capacitive pressure, and resistive temperature sensors), frequency modulation and pulse width modulation based interface IC circuits, microcontroller, and transceiver with meandered conformal antenna for the development of a capsule system. The challenges associated with the system miniaturization, higher sensitivity and resolution of sensors, and lower power consumption of interface circuits are addressed. The layout, PCB design, and packaging of a miniaturized wireless capsule, having diameter of 13 mm and length of 28 mm, have successfully been implemented. A data receiver and recorder system is also designed to receive physiological data from the wireless capsule and to send it to a computer for real-time display and recording. Experiments are performed in vitro using a stomach model and minced pork as tissue simulating material. The real-time measurements also validate the suitability of sensors, interface circuits, and meandered antenna for wireless capsule applications.

  7. An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring

    OpenAIRE

    Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

    2014-01-01

    Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between t...

  8. Hybrid CATV/MMW/BB lightwave transmission system based on fiber-wired/fiber-wireless/fiber-VLLC integrations.

    Science.gov (United States)

    Li, Chung-Yi; Lu, Hai-Han; Lu, Ting-Chieh; Chu, Chien-An; Chen, Bo-Rui; Lin, Chun-Yu; Peng, Peng-Chun

    2015-12-14

    A hybrid lightwave transmission system for cable television (CATV)/millimeter-wave (MMW)/baseband (BB) signal transmission based on fiber-wired/fiber-wireless/fiber-visible laser light communication (VLLC) integrations is proposed and demonstrated. For down-link transmission, the light is intensity-modulated with 50-550 MHz CATV signal and optically promoted from 25 GHz radio frequency (RF) signal to 10 Gbps/50 GHz and 20 Gbps/100 GHz MMW data signals based on fiber-wired and fiber-wireless integrations. Good performances of carrier-to-noise ratio (CNR), composite second-order (CSO), composite triple-beat (CTB), and bit error rate (BER) are obtained over a 40-km single-mode fiber (SMF) and a 10-m RF wireless transport. For up-link transmission, the light is successfully intensity-remodulated with 5-Gbps BB data stream based on fiber-VLLC integration. Good BER performance is achieved over a 40-km SMF and a 10-m free-space VLLC transport. Such a hybrid CATV/MMW/BB lightwave transmission system is an attractive alternative, it gives the benefits of a communication link for broader bandwidth and higher transmission rate.

  9. 3D silicon neural probe with integrated optical fibers for optogenetic modulation.

    Science.gov (United States)

    Kim, Eric G R; Tu, Hongen; Luo, Hao; Liu, Bin; Bao, Shaowen; Zhang, Jinsheng; Xu, Yong

    2015-07-21

    Optogenetics is a powerful modality for neural modulation that can be useful for a wide array of biomedical studies. Penetrating microelectrode arrays provide a means of recording neural signals with high spatial resolution. It is highly desirable to integrate optics with neural probes to allow for functional study of neural tissue by optogenetics. In this paper, we report the development of a novel 3D neural probe coupled simply and robustly to optical fibers using a hollow parylene tube structure. The device shanks are hollow tubes with rigid silicon tips, allowing the insertion and encasement of optical fibers within the shanks. The position of the fiber tip can be precisely controlled relative to the electrodes on the shank by inherent design features. Preliminary in vivo rat studies indicate that these devices are capable of optogenetic modulation simultaneously with 3D neural signal recording.

  10. Distributed Database Semantic Integration of Wireless Sensor Network to Access the Environmental Monitoring System

    Directory of Open Access Journals (Sweden)

    Ubaidillah Umar

    2018-06-01

    Full Text Available A wireless sensor network (WSN works continuously to gather information from sensors that generate large volumes of data to be handled and processed by applications. Current efforts in sensor networks focus more on networking and development services for a variety of applications and less on processing and integrating data from heterogeneous sensors. There is an increased need for information to become shareable across different sensors, database platforms, and applications that are not easily implemented in traditional database systems. To solve the issue of these large amounts of data from different servers and database platforms (including sensor data, a semantic sensor web service platform is needed to enable a machine to extract meaningful information from the sensor’s raw data. This additionally helps to minimize and simplify data processing and to deduce new information from existing data. This paper implements a semantic web data platform (SWDP to manage the distribution of data sensors based on the semantic database system. SWDP uses sensors for temperature, humidity, carbon monoxide, carbon dioxide, luminosity, and noise. The system uses the Sesame semantic web database for data processing and a WSN to distribute, minimize, and simplify information processing. The sensor nodes are distributed in different places to collect sensor data. The SWDP generates context information in the form of a resource description framework. The experiment results demonstrate that the SWDP is more efficient than the traditional database system in terms of memory usage and processing time.

  11. An Integrated Quantum Dot Barcode Smartphone Optical Device for Wireless Multiplexed Diagnosis of Infected Patients

    Science.gov (United States)

    Ming, Kevin

    Integrating mobile-cellular devices with multiplex molecular diagnostics can potentially provide the most powerful platform for tracking, managing and preventing the transmission of infectious diseases. With over 6.9 billion subscriptions globally, handheld mobile-cellular devices can be programmed to spatially map, temporally track, and transmit information on infections over wide geographical space and boundaries. Current cell phone diagnostic technologies have poor limit of detection, dynamic range, and cannot detect multiple pathogen targets simultaneously, limiting their utility to single infections with high load. Here we combined recent advances in quantum dot barcode technology for molecular detection with smartphones to engineer a simple and low-cost chip-based wireless multiplex diagnostic device. We validated our device using a variety of synthetic genomic targets for the respiratory virus and blood-borne pathogens, and demonstrated that it could detect clinical samples after simple amplification. More importantly, we confirmed that the device is capable of detecting patients infected with a single or multiple infectious pathogens (e.g., HIV and hepatitis B) in a single test. This device advances the capacity for global surveillance of infectious diseases and has the potential to accelerate knowledge exchange-transfer of emerging or exigent disease threats with healthcare and military organizations in real-time.

  12. An Integrated Hybrid Energy Harvester for Autonomous Wireless Sensor Network Nodes

    Directory of Open Access Journals (Sweden)

    Mukter Zaman

    2014-01-01

    Full Text Available Profiling environmental parameter using a large number of spatially distributed wireless sensor network (WSN NODEs is an extensive illustration of advanced modern technologies, but high power requirement for WSN NODEs limits the widespread deployment of these technologies. Currently, WSN NODEs are extensively powered up using batteries, but the battery has limitation of lifetime, power density, and environmental concerns. To overcome this issue, energy harvester (EH is developed and presented in this paper. Solar-based EH has been identified as the most viable source of energy to be harvested for autonomous WSN NODEs. Besides, a novel chemical-based EH is reported as the potential secondary source for harvesting energy because of its uninterrupted availability. By integrating both solar-based EH and chemical-based EH, a hybrid energy harvester (HEH is developed to power up WSN NODEs. Experimental results from the real-time deployment shows that, besides supporting the daily operation of WSN NODE and Router, the developed HEH is capable of producing a surplus of 971 mA·hr equivalent energy to be stored inside the storage for NODE and 528.24 mA·hr equivalent energy for Router, which is significantly enough for perpetual operation of autonomous WSN NODEs used in environmental parameter profiling.

  13. Structural reliability calculation method based on the dual neural network and direct integration method.

    Science.gov (United States)

    Li, Haibin; He, Yun; Nie, Xiaobo

    2018-01-01

    Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

  14. Data security issues arising from integration of wireless access into healthcare networks.

    Science.gov (United States)

    Frenzel, John C

    2003-04-01

    The versatility of having Ethernet speed connectivity without wires is rapidly driving adoption of wireless data networking by end users across all types of industry. Designed to be easy to configure and work among diverse platforms, wireless brings online data to mobile users. This functionality is particularly useful in modern clinical medicine. Wireless presents operators of networks containing or transmitting sensitive and confidential data with several new types of security vulnerabilities, and potentially opens previously protected core network resources to outside attack. Herein, we review the types of vulnerabilities, the tools necessary to exploit them, and strategies to thwart a successful attack.

  15. Integrated Markov-neural reliability computation method: A case for multiple automated guided vehicle system

    International Nuclear Information System (INIS)

    Fazlollahtabar, Hamed; Saidi-Mehrabad, Mohammad; Balakrishnan, Jaydeep

    2015-01-01

    This paper proposes an integrated Markovian and back propagation neural network approaches to compute reliability of a system. While states of failure occurrences are significant elements for accurate reliability computation, Markovian based reliability assessment method is designed. Due to drawbacks shown by Markovian model for steady state reliability computations and neural network for initial training pattern, integration being called Markov-neural is developed and evaluated. To show efficiency of the proposed approach comparative analyses are performed. Also, for managerial implication purpose an application case for multiple automated guided vehicles (AGVs) in manufacturing networks is conducted. - Highlights: • Integrated Markovian and back propagation neural network approach to compute reliability. • Markovian based reliability assessment method. • Managerial implication is shown in an application case for multiple automated guided vehicles (AGVs) in manufacturing networks

  16. The modulation of neural gain facilitates a transition between functional segregation and integration in the brain.

    Science.gov (United States)

    Shine, James M; Aburn, Matthew J; Breakspear, Michael; Poldrack, Russell A

    2018-01-29

    Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain directed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal 'rich club' regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain. © 2018, Shine et al.

  17. Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2009-01-01

    A new fault diagnosis method based on integrated neural networks for nuclear steam generator (SG) was proposed in view of the shortcoming of the conventional fault monitoring and diagnosis method. In the method, two neural networks (ANNs) were employed for the fault diagnosis of steam generator. A neural network, which was used for predicting the values of steam generator operation parameters, was taken as the dynamics model of steam generator. The principle of fault monitoring method using the neural network model is to detect the deviations between process signals measured from an operating steam generator and corresponding output signals from the neural network model of steam generator. When the deviation exceeds the limit set in advance, the abnormal event is thought to occur. The other neural network as a fault classifier conducts the fault classification of steam generator. So, the fault types of steam generator are given by the fault classifier. The clear information on steam generator faults was obtained by fusing the monitoring and diagnosis results of two neural networks. The simulation results indicate that employing integrated neural networks can improve the capacity of fault monitoring and diagnosis for the steam generator. (authors)

  18. Conformally integrated stent cell resonators for wireless monitoring of peripheral artery disease

    KAUST Repository

    Viswanath, Anupam; Green, Scott Ryan; Kosel, Jü rgen; Gianchandani, Yogesh B.

    2013-01-01

    This paper presents the design and in vitro evaluation of magnetoelastic sensors intended for wireless monitoring of tissue accumulation in peripheral artery stents. The sensors, shaped like stent cells, are fabricated from 28-μm thick foils

  19. Market-Based Resource Allocation in a Wirelessly Integrated Naval Engineering Plant

    Science.gov (United States)

    2009-12-01

    available wireless nodes will be developed. Using a multi-agent approach based on free market economics (termed market based control) will be explored...as battery power, data storage capacity, MPU time, wireless bandwidth, etc.) required to perform complex computational tasks are available only in a...network. One approach to this problem is to apply free-market economics to help allocate these resources. Free-market economies can be thought of as

  20. INTEGRATING ARTIFICIAL NEURAL NETWORKS FOR DEVELOPING TELEMEDICINE SOLUTION

    Directory of Open Access Journals (Sweden)

    Mihaela GHEORGHE

    2015-06-01

    Full Text Available Artificial intelligence is assuming an increasing important role in the telemedicine field, especially neural networks with their ability to achieve meaning from large sets of data characterized by lacking exactness and accuracy. These can be used for assisting physicians or other clinical staff in the process of taking decisions under uncertainty. Thus, machine learning methods which are specific to this technology are offering an approach for prediction based on pattern classification. This paper aims to present the importance of neural networks in detecting trends and extracting patterns which can be used within telemedicine domains, particularly for taking medical diagnosis decisions.

  1. Artificial Neural Network Based State Estimators Integrated into Kalmtool

    DEFF Research Database (Denmark)

    Bayramoglu, Enis; Ravn, Ole; Poulsen, Niels Kjølstad

    2012-01-01

    In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation as...

  2. Effects of sleep deprivation on neural functioning: an integrative review

    NARCIS (Netherlands)

    Boonstra, T.W.; Stins, J.F.; Daffertshofer, A.; Beek, P.J.

    2007-01-01

    Sleep deprivation has a broad variety of effects on human performance and neural functioning that manifest themselves at different levels of description. On a macroscopic level, sleep deprivation mainly affects executive functions, especially in novel tasks. Macroscopic and mesoscopic effects of

  3. An Integrated Chip High-Voltage Power Receiver for Wireless Biomedical Implants

    Directory of Open Access Journals (Sweden)

    Vijith Vijayakumaran Nair

    2015-06-01

    Full Text Available In near-field wireless-powered biomedical implants, the receiver voltage largely overrides the compliance of low-voltage power receiver systems. To limit the induced voltage, generally, low-voltage topologies utilize limiter circuits, voltage clippers or shunt regulators, which are power-inefficient methods. In order to overcome the voltage limitation and improve power efficiency, we propose an integrated chip high-voltage power receiver based on the step down approach. The topology accommodates voltages as high as 30 V and comprises a high-voltage semi-active rectifier, a voltage reference generator and a series regulator. Further, a battery management circuit that enables safe and reliable implant battery charging based on analog control is proposed and realized. The power receiver is fabricated in 0.35-μm high-voltage Bipolar-CMOS-DMOStechnology based on the LOCOS0.35-μm CMOS process. Measurement results indicate 83.5% power conversion efficiency for a rectifier at 2.1 mA load current. The low drop-out regulator based on the current buffer compensation and buffer impedance attenuation scheme operates with low quiescent current, reduces the power consumption and provides good stability. The topology also provides good power supply rejection, which is adequate for the design application. Measurement results indicate regulator output of 4 ± 0.03 V for input from 5 to 30 V and 10 ± 0.05 V output for input from 11 to 30 V with load current 0.01–100 mA. The charger circuit manages the charging of the Li-ion battery through all if the typical stages of the Li-ion battery charging profile.

  4. Simulation of sensory integration dysfunction in autism with dynamic neural fields model

    NARCIS (Netherlands)

    Chonnaparamutt, W.; Barakova, E.I.; Rutkowski, L.; Taseusiewicz, R.

    2008-01-01

    This paper applies dynamic neural fields model [1,23,7] to multimodal interaction of sensory cues obtained from a mobile robot, and shows the impact of different temporal aspects of the integration to the precision of movements. We speculate that temporally uncoordinated sensory integration might be

  5. Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Petr Maca

    2016-01-01

    Full Text Available The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI and the standardized precipitation evaporation index (SPEI and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

  6. A wireless sensor enabled by wireless power.

    Science.gov (United States)

    Lee, Da-Sheng; Liu, Yu-Hong; Lin, Chii-Ruey

    2012-11-22

    Through harvesting energy by wireless charging and delivering data by wireless communication, this study proposes the concept of a wireless sensor enabled by wireless power (WPWS) and reports the fabrication of a prototype for functional tests. One WPWS node consists of wireless power module and sensor module with different chip-type sensors. Its main feature is the dual antenna structure. Following RFID system architecture, a power harvesting antenna was designed to gather power from a standard reader working in the 915 MHz band. Referring to the Modbus protocol, the other wireless communication antenna was integrated on a node to send sensor data in parallel. The dual antenna structure integrates both the advantages of an RFID system and a wireless sensor. Using a standard UHF RFID reader, WPWS can be enabled in a distributed area with a diameter up to 4 m. Working status is similar to that of a passive tag, except that a tag can only be queried statically, while the WPWS can send dynamic data from the sensors. The function is the same as a wireless sensor node. Different WPWSs equipped with temperature and humidity, optical and airflow velocity sensors are tested in this study. All sensors can send back detection data within 8 s. The accuracy is within 8% deviation compared with laboratory equipment. A wireless sensor network enabled by wireless power should be a totally wireless sensor network using WPWS. However, distributed WPWSs only can form a star topology, the simplest topology for constructing a sensor network. Because of shielding effects, it is difficult to apply other complex topologies. Despite this limitation, WPWS still can be used to extend sensor network applications in hazardous environments. Further research is needed to improve WPWS to realize a totally wireless sensor network.

  7. Performance of the Wavelet Transform-Neural Network Based Receiver for DPIM in Diffuse Indoor Optical Wireless Links in Presence of Artificial Light Interference

    Directory of Open Access Journals (Sweden)

    Sujan Rajbhandari

    2009-06-01

    Full Text Available Artificial neural network (ANN has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT with both the time and the frequency resolution provides the exact representation of signal in both domains. Applying these signal processing tools for channel compensation and noise reduction can provide an enhanced performance compared to the traditional tools. In this paper, the slot error rate (SER performance of digital pulse interval modulation (DPIM in diffuse indoor optical wireless (OW links subjected to the artificial light interference (ALI is reported with new receiver structure based on the discrete WT (DWT and ANN. Simulation results show that the DWT-ANN based receiver is very effective in reducing the effect of multipath induced inter-symbol interference (ISI and ALI.

  8. A High-Power Wireless Charging System Development and Integration for a Toyota RAV4 Electric Vehicle

    Energy Technology Data Exchange (ETDEWEB)

    Onar, Omer C [ORNL; Seiber, Larry Eugene [ORNL; White, Cliff P [ORNL; Chinthavali, Madhu Sudhan [ORNL; Campbell, Steven L [ORNL

    2016-01-01

    Several wireless charging methods are underdevelopment or available as an aftermarket option in the light-duty automotive market. However, there are not many studies detailing the vehicle integrations, particularly a complete vehicle integration with higher power levels. This paper presents the development, implementation, and vehicle integration of a high-power (>10 kW) wireless power transfer (WPT)-based electric vehicle (EV) charging system for a Toyota RAV4 vehicle. The power stages of the system are introduced with the design specifications and control systems including the active front-end rectifier with power factor correction (PFC), high frequency power inverter, high frequency isolation transformer, coupling coils, vehicle side full-bridge rectifier and filter, and the vehicle battery. The operating principles of the control, communications, and protection systems are also presented in addition to the alignment and the driver interface system. The physical limitations of the system are also defined that would prevent the system operating at higher levels. The experiments are carried out using the integrated vehicle and the results obtained to demonstrate the system performance including the stage-by-stage efficiencies with matched and interoperable primary and secondary coils.

  9. Optimal multiple-information integration inherent in a ring neural network

    International Nuclear Information System (INIS)

    Takiyama, Ken

    2017-01-01

    Although several behavioral experiments have suggested that our neural system integrates multiple sources of information based on the certainty of each type of information in the manner of maximum-likelihood estimation, it is unclear how the maximum-likelihood estimation is implemented in our neural system. Here, I investigate the relationship between maximum-likelihood estimation and a widely used ring-type neural network model that is used as a model of visual, motor, or prefrontal cortices. Without any approximation or ansatz, I analytically demonstrate that the equilibrium of an order parameter in the neural network model exactly corresponds to the maximum-likelihood estimation when the strength of the symmetrical recurrent synaptic connectivity within a neural population is appropriately stronger than that of asymmetrical connectivity, that of local and external inputs, and that of symmetrical or asymmetrical connectivity between different neural populations. In this case, strengths of local and external inputs or those of symmetrical connectivity between different neural populations exactly correspond to the input certainty in maximum-likelihood estimation. Thus, my analysis suggests appropriately strong symmetrical recurrent connectivity as a possible candidate for implementing the maximum-likelihood estimation within our neural system. (paper)

  10. Integration of Neural Networks and Cellular Automata for Urban Planning

    Institute of Scientific and Technical Information of China (English)

    Anthony Gar-on Yeh; LI Xia

    2004-01-01

    This paper presents a new type of cellular automata (CA) model for the simulation of alternative land development using neural networks for urban planning. CA models can be regarded as a planning tool because they can generate alternative urban growth. Alternative development patterns can be formed by using different sets of parameter values in CA simulation. A critical issue is how to define parameter values for realistic and idealized simulation. This paper demonstrates that neural networks can simplify CA models but generate more plausible results. The simulation is based on a simple three-layer network with an output neuron to generate conversion probability. No transition rules are required for the simulation. Parameter values are automatically obtained from the training of network by using satellite remote sensing data. Original training data can be assessed and modified according to planning objectives. Alternative urban patterns can be easily formulated by using the modified training data sets rather than changing the model.

  11. Efficient Bandwidth Allocation for Integrated Services in Broadband Wireless ATM Networks

    DEFF Research Database (Denmark)

    Liu, Hong; Dittmann, Lars; Gliese, Ulrik Bo

    1999-01-01

    An efficient bandwidth allocation scheme is proposed for supporting intergrated services in wireless ATM networks. These include CBR, VBR amd ABR types of traffic. The proposed scheme is based om A-PRMA for carrying ATM traffic in a dynamic TDMA type access system. It allows mobile users to adjust...

  12. Wireless link using on-chip photonic integrated millimeter-wave sources

    NARCIS (Netherlands)

    Guzmán, R. C.; Gordón, C.; Carpintero, G.; Leijtens, X.; Lawniczak, Katarzyna

    2015-01-01

    Over the last few years wireless link data traffic has drastically increased due to a change in the way today's society creates, shares, and consumes information. Millimeter-waves (30-300 GHz) have a great advantage due to the wide bandwidths available for carrying information, enabling broadband

  13. Integration of wireless sensor networks into automatic irrigation scheduling of a center pivot

    Science.gov (United States)

    A six-span center pivot system was used as a platform for testing two wireless sensor networks (WSN) of infrared thermometers. The cropped field was a semi-circle, divided into six pie shaped sections of which three were irrigated manually and three were irrigated automatically based on the time tem...

  14. 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.

  15. Detection of vapor-phase organophosphate threats using wearable conformable integrated epidermal and textile wireless biosensor systems.

    Science.gov (United States)

    Mishra, Rupesh K; Martín, Aida; Nakagawa, Tatsuo; Barfidokht, Abbas; Lu, Xialong; Sempionatto, Juliane R; Lyu, Kay Mengjia; Karajic, Aleksandar; Musameh, Mustafa M; Kyratzis, Ilias L; Wang, Joseph

    2018-03-15

    Flexible epidermal tattoo and textile-based electrochemical biosensors have been developed for vapor-phase detection of organophosphorus (OP) nerve agents. These new wearable sensors, based on stretchable organophosphorus hydrolase (OPH) enzyme electrodes, are coupled with a fully integrated conformal flexible electronic interface that offers rapid and selective square-wave voltammetric detection of OP vapor threats and wireless data transmission to a mobile device. The epidermal tattoo and textile sensors display a good reproducibility (with RSD of 2.5% and 4.2%, respectively), along with good discrimination against potential interferences and linearity over the 90-300mg/L range, with a sensitivity of 10.7µA∙cm 3 ∙mg -1 (R 2 = 0.983) and detection limit of 12mg/L in terms of OP air density. Stress-enduring inks, used for printing the electrode transducers, ensure resilience against mechanical deformations associated with textile and skin-based on-body sensing operations. Theoretical simulations are used to estimate the OP air density over the sensor surface. These fully integrated wearable wireless tattoo and textile-based nerve-agent vapor biosensor systems offer considerable promise for rapid warning regarding personal exposure to OP nerve-agent vapors in variety of decentralized security applications. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Highly Sensitive Reentrant Cavity-Microstrip Patch Antenna Integrated Wireless Passive Pressure Sensor for High Temperature Applications

    Directory of Open Access Journals (Sweden)

    Fei Lu

    2017-01-01

    Full Text Available A novel reentrant cavity-microstrip patch antenna integrated wireless passive pressure sensor was proposed in this paper for high temperature applications. The reentrant cavity was analyzed from aspects of distributed model and equivalent lumped circuit model, on the basis of which an optimal sensor structure integrated with a rectangular microstrip patch antenna was proposed to better transmit/receive wireless signals. In this paper, the proposed sensor was fabricated with high temperature resistant alumina ceramic and silver metalization with weld sealing, and it was measured in a hermetic metal tank with nitrogen pressure loading. It was verified that the sensor was highly sensitive, keeping stable performance up to 300 kPa with an average sensitivity of 981.8 kHz/kPa at temperature 25°C, while, for high temperature measurement, the sensor can operate properly under pressure of 60–120 kPa in the temperature range of 25–300°C with maximum pressure sensitivity of 179.2 kHz/kPa. In practical application, the proposed sensor is used in a method called table lookup with a maximum error of 5.78%.

  17. Collaborative Catchment-Scale Water Quality Management using Integrated Wireless Sensor Networks

    Science.gov (United States)

    Zia, Huma; Harris, Nick; Merrett, Geoff

    2013-04-01

    Electronics and Computer Science, University of Southampton, United Kingdom Summary The challenge of improving water quality (WQ) is a growing global concern [1]. Poor WQ is mainly attributed to poor water management and outdated agricultural activities. We propose that collaborative sensor networks spread across an entire catchment can allow cooperation among individual activities for integrated WQ monitoring and management. We show that sharing information on critical parameters among networks of water bodies and farms can enable identification and quantification of the contaminant sources, enabling better decision making for agricultural practices and thereby reducing contaminants fluxes. Motivation and results Nutrient losses from land to water have accelerated due to agricultural and urban pursuits [2]. In many cases, the application of fertiliser can be reduced by 30-50% without any loss of yield [3]. Thus information about nutrient levels and trends around the farm can improve agricultural practices and thereby reduce water contamination. The use of sensor networks for monitoring WQ in a catchment is in its infancy, but more applications are being tested [4]. However, these are focussed on local requirements and are mostly limited to water bodies. They have yet to explore the use of this technology for catchment-scale monitoring and management decisions, in an autonomous and dynamic manner. For effective and integrated WQ management, we propose a system that utilises local monitoring networks across a catchment, with provision for collaborative information sharing. This system of networks shares information about critical events, such as rain or flooding. Higher-level applications make use of this information to inform decisions about nutrient management, improving the quality of monitoring through the provision of richer datasets of catchment information to local networks. In the full paper, we present example scenarios and analyse how the benefits of

  18. Neural Correlates of Impaired Reward-Effort Integration in Remitted Bulimia Nervosa.

    Science.gov (United States)

    Mueller, Stefanie Verena; Morishima, Yosuke; Schwab, Simon; Wiest, Roland; Federspiel, Andrea; Hasler, Gregor

    2018-03-01

    The integration of reward magnitudes and effort costs is required for an effective behavioral guidance. This reward-effort integration was reported to be dependent on dopaminergic neurotransmission. As bulimia nervosa has been associated with a dysregulated dopamine system and catecholamine depletion led to reward-processing deficits in remitted bulimia nervosa, the purpose of this study was to identify the role of catecholamine dysfunction and its relation to behavioral and neural reward-effort integration in bulimia nervosa. To investigate the interaction between catecholamine functioning and behavioral, and neural responses directly, 17 remitted bulimic (rBN) and 21 healthy individuals (HC) received alpha-methyl-paratyrosine (AMPT) over 24 h to achieve catecholamine depletion in a randomized, crossover study design. We used functional magnetic resonance imaging (fMRI) and the monetary incentive delay (MID) task to assess reward-effort integration in relation to catecholaminergic neurotransmission at the behavioral and neural level. AMPT reduced the ability to integrate rewards and efforts effectively in HC participants. In contrast, in rBN participants, the reduced reward-effort integration was associated with illness duration in the sham condition and unrelated to catecholamine depletion. Regarding neural activation, AMPT decreased the reward anticipation-related neural activation in the anteroventral striatum. This decrease was associated with the AMPT-induced reduction of monetary earning in HC in contrast to rBN participants. Our findings contributed to the theory of a desensitized dopaminergic system in bulimia nervosa. A disrupted processing of reward magnitudes and effort costs might increase the probability of maintenance of bulimic symptoms.

  19. Integrated Eye Tracking and Neural Monitoring for Enhanced Assessment of Mild TBI

    Science.gov (United States)

    2017-06-01

    working memory load effects after mild traumatic brain injury. Neuroimage, 2001. 14(5): p. 1004-12. 2. Chen, J.K., et al., Functional abnormalities in...report. 10 Supporting Data None. Integrated Eye Tracking and Neural Monitoring for Enhanced Assessment of Mild TBI Psychological Health

  20. Neural basis of limb ownership in individuals with body integrity identity disorder

    NARCIS (Netherlands)

    van Dijk, Milenna T.; van Wingen, Guido A.; van Lammeren, Anouk; Blom, Rianne M.; de Kwaasteniet, Bart P.; Scholte, H. Steven; Denys, Damiaan

    2013-01-01

    Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID) lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis

  1. Wireless implantable chip with integrated nitinol-based pump for radio-controlled local drug delivery.

    Science.gov (United States)

    Fong, Jeffrey; Xiao, Zhiming; Takahata, Kenichi

    2015-02-21

    We demonstrate an active, implantable drug delivery device embedded with a microfluidic pump that is driven by a radio-controlled actuator for temporal drug delivery. The polyimide-packaged 10 × 10 × 2 mm(3) chip contains a micromachined pump chamber and check valves of Parylene C to force the release of the drug from a 76 μL reservoir by wirelessly activating the actuator using external radio-frequency (RF) electromagnetic fields. The rectangular-shaped spiral-coil actuator based on nitinol, a biocompatible shape-memory alloy, is developed to perform cantilever-like actuation for pumping operation. The nitinol-coil actuator itself forms a passive 185 MHz resonant circuit that serves as a self-heat source activated via RF power transfer to enable frequency-selective actuation and pumping. Experimental wireless operation of fabricated prototypes shows successful release of test agents from the devices placed in liquid and excited by radiating tuned RF fields with an output power of 1.1 W. These tests reveal a single release volume of 219 nL, suggesting a device's capacity of ~350 individual ejections of drug from its reservoir. The thermal behavior of the activated device is also reported in detail. This proof-of-concept prototype validates the effectiveness of wireless RF pumping for fully controlled, long-lasting drug delivery, a key step towards enabling patient-tailored, targeted local drug delivery through highly miniaturized implants.

  2. Challenges in Wireless System Integration as Enablers for Indoor Context Aware Environments

    Directory of Open Access Journals (Sweden)

    Peio López-Iturri

    2017-07-01

    Full Text Available The advent of fully interactive environments within Smart Cities and Smart Regions requires the use of multiple wireless systems. In the case of user-device interaction, which finds multiple applications such as Ambient Assisted Living, Intelligent Transportation Systems or Smart Grids, among others, large amount of transceivers are employed in order to achieve anytime, anyplace and any device connectivity. The resulting combination of heterogeneous wireless network exhibits fundamental limitations derived from Coverage/Capacity relations, as a function of required Quality of Service parameters, required bit rate, energy restrictions and adaptive modulation and coding schemes. In this context, inherent transceiver density poses challenges in overall system operation, given by multiple node operation which increases overall interference levels. In this work, a deterministic based analysis applied to variable density wireless sensor network operation within complex indoor scenarios is presented, as a function of topological node distribution. The extensive analysis derives interference characterizations, both for conventional transceivers as well as wearables, which provide relevant information in terms of individual node configuration as well as complete network layout.

  3. Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

    Science.gov (United States)

    Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

    2018-04-19

    Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

  4. Neural Network Control for the Probe Landing Based on Proportional Integral Observer

    Directory of Open Access Journals (Sweden)

    Yuanchun Li

    2015-01-01

    Full Text Available For the probe descending and landing safely, a neural network control method based on proportional integral observer (PIO is proposed. First, the dynamics equation of the probe under the landing site coordinate system is deduced and the nominal trajectory meeting the constraints in advance on three axes is preplanned. Then the PIO designed by using LMI technique is employed in the control law to compensate the effect of the disturbance. At last, the neural network control algorithm is used to guarantee the double zero control of the probe and ensure the probe can land safely. An illustrative design example is employed to demonstrate the effectiveness of the proposed control approach.

  5. Dynamic stability analysis of fractional order leaky integrator echo state neural networks

    Science.gov (United States)

    Pahnehkolaei, Seyed Mehdi Abedi; Alfi, Alireza; Tenreiro Machado, J. A.

    2017-06-01

    The Leaky integrator echo state neural network (Leaky-ESN) is an improved model of the recurrent neural network (RNN) and adopts an interconnected recurrent grid of processing neurons. This paper presents a new proof for the convergence of a Lyapunov candidate function to zero when time tends to infinity by means of the Caputo fractional derivative with order lying in the range (0, 1). The stability of Fractional-Order Leaky-ESN (FO Leaky-ESN) is then analyzed, and the existence, uniqueness and stability of the equilibrium point are provided. A numerical example demonstrates the feasibility of the proposed method.

  6. The PennBMBI: Design of a General Purpose Wireless Brain-Machine-Brain Interface System.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Subei, Basheer; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

    2015-04-01

    In this paper, a general purpose wireless Brain-Machine-Brain Interface (BMBI) system is presented. The system integrates four battery-powered wireless devices for the implementation of a closed-loop sensorimotor neural interface, including a neural signal analyzer, a neural stimulator, a body-area sensor node and a graphic user interface implemented on the PC end. The neural signal analyzer features a four channel analog front-end with configurable bandpass filter, gain stage, digitization resolution, and sampling rate. The target frequency band is configurable from EEG to single unit activity. A noise floor of 4.69 μVrms is achieved over a bandwidth from 0.05 Hz to 6 kHz. Digital filtering, neural feature extraction, spike detection, sensing-stimulating modulation, and compressed sensing measurement are realized in a central processing unit integrated in the analyzer. A flash memory card is also integrated in the analyzer. A 2-channel neural stimulator with a compliance voltage up to ± 12 V is included. The stimulator is capable of delivering unipolar or bipolar, charge-balanced current pulses with programmable pulse shape, amplitude, width, pulse train frequency and latency. A multi-functional sensor node, including an accelerometer, a temperature sensor, a flexiforce sensor and a general sensor extension port has been designed. A computer interface is designed to monitor, control and configure all aforementioned devices via a wireless link, according to a custom designed communication protocol. Wireless closed-loop operation between the sensory devices, neural stimulator, and neural signal analyzer can be configured. The proposed system was designed to link two sites in the brain, bridging the brain and external hardware, as well as creating new sensory and motor pathways for clinical practice. Bench test and in vivo experiments are performed to verify the functions and performances of the system.

  7. An integrative neural model of social perception, action observation, and theory of mind

    Science.gov (United States)

    Yang, Daniel Y.-J.; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A.

    2016-01-01

    In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. PMID:25660957

  8. Functional Stem Cell Integration into Neural Networks Assessed by Organotypic Slice Cultures.

    Science.gov (United States)

    Forsberg, David; Thonabulsombat, Charoensri; Jäderstad, Johan; Jäderstad, Linda Maria; Olivius, Petri; Herlenius, Eric

    2017-08-14

    Re-formation or preservation of functional, electrically active neural networks has been proffered as one of the goals of stem cell-mediated neural therapeutics. A primary issue for a cell therapy approach is the formation of functional contacts between the implanted cells and the host tissue. Therefore, it is of fundamental interest to establish protocols that allow us to delineate a detailed time course of grafted stem cell survival, migration, differentiation, integration, and functional interaction with the host. One option for in vitro studies is to examine the integration of exogenous stem cells into an existing active neural network in ex vivo organotypic cultures. Organotypic cultures leave the structural integrity essentially intact while still allowing the microenvironment to be carefully controlled. This allows detailed studies over time of cellular responses and cell-cell interactions, which are not readily performed in vivo. This unit describes procedures for using organotypic slice cultures as ex vivo model systems for studying neural stem cell and embryonic stem cell engraftment and communication with CNS host tissue. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

  9. An integrative neural model of social perception, action observation, and theory of mind.

    Science.gov (United States)

    Yang, Daniel Y-J; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A

    2015-04-01

    In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. F-band millimeter-wave signal generation for wireless link data transmission using on-chip photonic integrated dual-wavelength sources

    NARCIS (Netherlands)

    Guzman, Robinson; Carpintero, G.; Gordon Gallegos, Carlos; Lawniczuk, Katarzyna; Leijtens, Xaveer

    2015-01-01

    Millimeter-waves (30-300 GHz) have interest due to the wide bandwidths available for carrying information, enabling broadband wireless communications. Photonics is a key technology for millimeter wave signal generation, recently demonstrating the use of photonic integration to reduce size and cost.

  11. Monitoring and classifying animal behavior using ZigBee-based mobile ad hoc wireless sensor networks and artificial neural networks

    DEFF Research Database (Denmark)

    S. Nadimi, Esmaeil; Nyholm Jørgensen, Rasmus; Blanes-Vidal, Victoria

    2012-01-01

    Animal welfare is an issue of great importance in modern food production systems. Because animal behavior provides reliable information about animal health and welfare, recent research has aimed at designing monitoring systems capable of measuring behavioral parameters and transforming them...... into their corresponding behavioral modes. However, network unreliability and high-energy consumption have limited the applicability of those systems. In this study, a 2.4-GHz ZigBee-based mobile ad hoc wireless sensor network (MANET) that is able to overcome those problems is presented. The designed MANET showed high...... communication reliability, low energy consumption and low packet loss rate (14.8%) due to the deployment of modern communication protocols (e.g. multi-hop communication and handshaking protocol). The measured behavioral parameters were transformed into the corresponding behavioral modes using a multilayer...

  12. An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination.

    Science.gov (United States)

    Kuo, R J; Wu, P; Wang, C P

    2002-09-01

    Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.

  13. A fully integrated wireless system for intracranial direct cortical stimulation, real-time electrocorticography data transmission, and smart cage for wireless battery recharge.

    Science.gov (United States)

    Piangerelli, Marco; Ciavarro, Marco; Paris, Antonino; Marchetti, Stefano; Cristiani, Paolo; Puttilli, Cosimo; Torres, Napoleon; Benabid, Alim Louis; Romanelli, Pantaleo

    2014-01-01

    Wireless transmission of cortical signals is an essential step to improve the safety of epilepsy procedures requiring seizure focus localization and to provide chronic recording of brain activity for Brain Computer Interface (BCI) applications. Our group developed a fully implantable and externally rechargeable device, able to provide wireless electrocorticographic (ECoG) recording and cortical stimulation (CS). The first prototype of a wireless multi-channel very low power ECoG system was custom-designed to be implanted on non-human primates. The device, named ECOGIW-16E, is housed in a compact hermetically sealed Polyether ether ketone (PEEK) enclosure, allowing seamless battery recharge. ECOGIW-16E is recharged in a wireless fashion using a special cage designed to facilitate the recharge process in monkeys and developed in accordance with guidelines for accommodation of animals by Council of Europe (ETS123). The inductively recharging cage is made up of nylon and provides a thoroughly novel experimental setting on freely moving animals. The combination of wireless cable-free ECoG and external seamless battery recharge solves the problems and shortcomings caused by the presence of cables leaving the skull, providing a safer and easier way to monitor patients and to perform ECoG recording on primates. Data transmission exploits the newly available Medical Implant Communication Service band (MICS): 402-405 MHz. ECOGIW-16E was implanted over the left sensorimotor cortex of a macaca fascicularis to assess the feasibility of wireless ECoG monitoring and brain mapping through CS. With this device, we were able to record the everyday life ECoG signal from a monkey and to deliver focal brain stimulation with movement elicitation.

  14. A Fully-Integrated Wireless System for Intracranial Direct Cortical Stimulation, Real-Time Electrocorticography Data Trasmission and Smart Cage for Wireless Battery Recharge

    Directory of Open Access Journals (Sweden)

    Marco ePiangerelli

    2014-08-01

    Full Text Available Wireless transmission of cortical signals is an essential step to improve the safety of epilepsy procedures requiring seizure focus localization and to provide chronic recording of brain activity for Brain Computer Interface(BCI applications .Our group developed a fully implantable and externally rechargeable device, able to provide wireless electrocorticographic (ECoG recording and cortical stimulation (CS. The first prototype of a wireless multi-channel very low power ECoG system was custom-designed to be implanted on non-human primates. The device,named ECOGIW-16E, is housed in a compact hermetically sealed Polyether ether ketone (PEEK enclosure, allowing seamless battery recharge. ECOGIW-16E is recharged in a wireless fashion using a special cage designed to facilitate the recharge process in monkeys and , developed in accordance with guidelines for accommodation of animals by Council of Europe (ETS123. The inductively recharging cage is made of nylon and provides a thoroughly novel experimental setting on freely moving animals. The combination of wireless cable-free ECoG and external seamless battery recharge solve the problems and shortcomings caused by the presence of cables leaving the skull,providing a safer and easier way to monitor patients and to perform ECoG recording on primates. Data transmission exploits the newly available Medical Implant Communication Service band (MICS: 402-405 MHz. ECOGW-16E was implanted over the left sensorimotor cortex of a macaca fascicularis to assess the feasibility of wireless ECoG monitoring and brain mapping through CS. With this device we were able to record the everyday life ECoG signal from a monkey and to deliver focal brain stimulation with movement elicitation.

  15. Experimental Results on a Wireless Wattmeter Device for the Integration in Home Energy Management Systems

    Directory of Open Access Journals (Sweden)

    Eduardo M. G. Rodrigues

    2017-03-01

    Full Text Available This paper presents a home area network (HAN-based domestic load energy consumption monitoring prototype device as part of an advanced metering system (AMS. This device can be placed on individual loads or configured to measure several loads as a whole. The wireless communication infrastructure is supported on IEEE 805.12.04 radios that run a ZigBee stack. Data acquisition concerning load energy transit is processed in real time and the main electrical parameters are then transmitted through a RF link to a wireless terminal unit, which works as a data logger and as a human-machine interface. Voltage and current sensing are implemented using Hall effect principle-based transducers, while C code is developed on two 16/32-bit microcontroller units (MCUs. The main features and design options are then thoroughly discussed. The main contribution of this paper is that the proposed metering system measures the reactive energy component through the Hilbert transform for low cost measuring device systems.

  16. Crossmodal integration enhances neural representation of task-relevant features in audiovisual face perception.

    Science.gov (United States)

    Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Liu, Yongjian; Liang, Changhong; Sun, Pei

    2015-02-01

    Previous studies have shown that audiovisual integration improves identification performance and enhances neural activity in heteromodal brain areas, for example, the posterior superior temporal sulcus/middle temporal gyrus (pSTS/MTG). Furthermore, it has also been demonstrated that attention plays an important role in crossmodal integration. In this study, we considered crossmodal integration in audiovisual facial perception and explored its effect on the neural representation of features. The audiovisual stimuli in the experiment consisted of facial movie clips that could be classified into 2 gender categories (male vs. female) or 2 emotion categories (crying vs. laughing). The visual/auditory-only stimuli were created from these movie clips by removing the auditory/visual contents. The subjects needed to make a judgment about the gender/emotion category for each movie clip in the audiovisual, visual-only, or auditory-only stimulus condition as functional magnetic resonance imaging (fMRI) signals were recorded. The neural representation of the gender/emotion feature was assessed using the decoding accuracy and the brain pattern-related reproducibility indices, obtained by a multivariate pattern analysis method from the fMRI data. In comparison to the visual-only and auditory-only stimulus conditions, we found that audiovisual integration enhanced the neural representation of task-relevant features and that feature-selective attention might play a role of modulation in the audiovisual integration. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  17. Neural Circuit to Integrate Opposing Motions in the Visual Field.

    Science.gov (United States)

    Mauss, Alex S; Pankova, Katarina; Arenz, Alexander; Nern, Aljoscha; Rubin, Gerald M; Borst, Alexander

    2015-07-16

    When navigating in their environment, animals use visual motion cues as feedback signals that are elicited by their own motion. Such signals are provided by wide-field neurons sampling motion directions at multiple image points as the animal maneuvers. Each one of these neurons responds selectively to a specific optic flow-field representing the spatial distribution of motion vectors on the retina. Here, we describe the discovery of a group of local, inhibitory interneurons in the fruit fly Drosophila key for filtering these cues. Using anatomy, molecular characterization, activity manipulation, and physiological recordings, we demonstrate that these interneurons convey direction-selective inhibition to wide-field neurons with opposite preferred direction and provide evidence for how their connectivity enables the computation required for integrating opposing motions. Our results indicate that, rather than sharpening directional selectivity per se, these circuit elements reduce noise by eliminating non-specific responses to complex visual information. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Integrated wireless fast-scan cyclic voltammetry recording and electrical stimulation for reward-predictive learning in awake, freely moving rats

    Science.gov (United States)

    Li, Yu-Ting; Wickens, Jeffery R.; Huang, Yi-Ling; Pan, Wynn H. T.; Chen, Fu-Yu Beverly; Chen, Jia-Jin Jason

    2013-08-01

    Objective. Fast-scan cyclic voltammetry (FSCV) is commonly used to monitor phasic dopamine release, which is usually performed using tethered recording and for limited types of animal behavior. It is necessary to design a wireless dopamine sensing system for animal behavior experiments. Approach. This study integrates a wireless FSCV system for monitoring the dopamine signal in the ventral striatum with an electrical stimulator that induces biphasic current to excite dopaminergic neurons in awake freely moving rats. The measured dopamine signals are unidirectionally transmitted from the wireless FSCV module to the host unit. To reduce electrical artifacts, an optocoupler and a separate power are applied to isolate the FSCV system and electrical stimulator, which can be activated by an infrared controller. Main results. In the validation test, the wireless backpack system has similar performance in comparison with a conventional wired system and it does not significantly affect the locomotor activity of the rat. In the cocaine administration test, the maximum electrically elicited dopamine signals increased to around 230% of the initial value 20 min after the injection of 10 mg kg-1 cocaine. In a classical conditioning test, the dopamine signal in response to a cue increased to around 60 nM over 50 successive trials while the electrically evoked dopamine concentration decreased from about 90 to 50 nM in the maintenance phase. In contrast, the cue-evoked dopamine concentration progressively decreased and the electrically evoked dopamine was eliminated during the extinction phase. In the histological evaluation, there was little damage to brain tissue after five months chronic implantation of the stimulating electrode. Significance. We have developed an integrated wireless voltammetry system for measuring dopamine concentration and providing electrical stimulation. The developed wireless FSCV system is proven to be a useful experimental tool for the continuous

  19. Neural Basis of Limb Ownership in Individuals with Body Integrity Identity Disorder

    OpenAIRE

    van Dijk, Milenna T.; van Wingen, Guido A.; van Lammeren, Anouk; Blom, Rianne M.; de Kwaasteniet, Bart P.; Scholte, H. Steven; Denys, Damiaan

    2013-01-01

    Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID) lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis underlying the feeling of limb ownership, since these individuals have a feeling of disownership for a limb in the absence of apparent brain damage. Here we directly compared brain activation between limbs ...

  20. An integrated environment monitoring system for underground coal mines--Wireless Sensor Network subsystem with multi-parameter monitoring.

    Science.gov (United States)

    Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

    2014-07-21

    Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected.

  1. Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases.

    Science.gov (United States)

    Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

    2015-02-11

    Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

  2. Development and Integration of a Solar Powered Unmanned Aerial Vehicle and a Wireless Sensor Network to Monitor Greenhouse Gases

    Science.gov (United States)

    Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

    2015-01-01

    Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology. PMID:25679312

  3. Development and Integration of a Solar Powered Unmanned Aerial Vehicle and a Wireless Sensor Network to Monitor Greenhouse Gases

    Directory of Open Access Journals (Sweden)

    Alexander Malaver

    2015-02-01

    Full Text Available Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs and Unmanned Aerial Vehicles (UAVs currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

  4. An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring

    Science.gov (United States)

    Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

    2014-01-01

    Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected. PMID:25051037

  5. An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring

    Directory of Open Access Journals (Sweden)

    Yu Zhang

    2014-07-01

    Full Text Available Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs. We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected.

  6. EIRP Characterization of Electrically Large Wireless Equipment with Integrated Signal Generator in a Compact Environment

    Directory of Open Access Journals (Sweden)

    Soon-Soo Oh

    2015-01-01

    Full Text Available We describe a measurement technique to characterize the equivalent isotropically radiated power (EIRP of electrically large wireless equipment in a compact environment. A modified phase-measurement method was proposed and, thus, the separation of the signal generator and radiating element was not required during the measurement. A Fresnel-to-far-field transformation was used for the fast measurement time in a compact anechoic chamber. An experimental verification of the method was carried out in a compact anechoic chamber, where the source-detector separation was approximately 1/5 of the far-field distance. The measured magnitude and phase pattern exhibited only a small error. The EIRP obtained using a Fresnel-to-far-field transformation was compared with a reference value, and the error was within 0.5 dB.

  7. A model for integrating elementary neural functions into delayed-response behavior.

    Directory of Open Access Journals (Sweden)

    Thomas Gisiger

    2006-04-01

    Full Text Available It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning, and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task, or recalling from this image another one that has been associated with it during training (delayed-pair association task. The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

  8. A model for integrating elementary neural functions into delayed-response behavior.

    Science.gov (United States)

    Gisiger, Thomas; Kerszberg, Michel

    2006-04-01

    It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning), and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task), or recalling from this image another one that has been associated with it during training (delayed-pair association task). The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

  9. Stress affects the neural ensemble for integrating new information and prior knowledge.

    Science.gov (United States)

    Vogel, Susanne; Kluen, Lisa Marieke; Fernández, Guillén; Schwabe, Lars

    2018-06-01

    Prior knowledge, represented as a schema, facilitates memory encoding. This schema-related learning is assumed to rely on the medial prefrontal cortex (mPFC) that rapidly integrates new information into the schema, whereas schema-incongruent or novel information is encoded by the hippocampus. Stress is a powerful modulator of prefrontal and hippocampal functioning and first studies suggest a stress-induced deficit of schema-related learning. However, the underlying neural mechanism is currently unknown. To investigate the neural basis of a stress-induced schema-related learning impairment, participants first acquired a schema. One day later, they underwent a stress induction or a control procedure before learning schema-related and novel information in the MRI scanner. In line with previous studies, learning schema-related compared to novel information activated the mPFC, angular gyrus, and precuneus. Stress, however, affected the neural ensemble activated during learning. Whereas the control group distinguished between sets of brain regions for related and novel information, stressed individuals engaged the hippocampus even when a relevant schema was present. Additionally, stressed participants displayed aberrant functional connectivity between brain regions involved in schema processing when encoding novel information. The failure to segregate functional connectivity patterns depending on the presence of prior knowledge was linked to impaired performance after stress. Our results show that stress affects the neural ensemble underlying the efficient use of schemas during learning. These findings may have relevant implications for clinical and educational settings. Copyright © 2018 Elsevier Inc. All rights reserved.

  10. Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

    Science.gov (United States)

    Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

    2003-01-01

    An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

  11. A biologically inspired neural model for visual and proprioceptive integration including sensory training.

    Science.gov (United States)

    Saidi, Maryam; Towhidkhah, Farzad; Gharibzadeh, Shahriar; Lari, Abdolaziz Azizi

    2013-12-01

    Humans perceive the surrounding world by integration of information through different sensory modalities. Earlier models of multisensory integration rely mainly on traditional Bayesian and causal Bayesian inferences for single causal (source) and two causal (for two senses such as visual and auditory systems), respectively. In this paper a new recurrent neural model is presented for integration of visual and proprioceptive information. This model is based on population coding which is able to mimic multisensory integration of neural centers in the human brain. The simulation results agree with those achieved by casual Bayesian inference. The model can also simulate the sensory training process of visual and proprioceptive information in human. Training process in multisensory integration is a point with less attention in the literature before. The effect of proprioceptive training on multisensory perception was investigated through a set of experiments in our previous study. The current study, evaluates the effect of both modalities, i.e., visual and proprioceptive training and compares them with each other through a set of new experiments. In these experiments, the subject was asked to move his/her hand in a circle and estimate its position. The experiments were performed on eight subjects with proprioception training and eight subjects with visual training. Results of the experiments show three important points: (1) visual learning rate is significantly more than that of proprioception; (2) means of visual and proprioceptive errors are decreased by training but statistical analysis shows that this decrement is significant for proprioceptive error and non-significant for visual error, and (3) visual errors in training phase even in the beginning of it, is much less than errors of the main test stage because in the main test, the subject has to focus on two senses. The results of the experiments in this paper is in agreement with the results of the neural model

  12. INTEGRATION OF FRACTAL AND NEURAL NETWORK TECHNOLOGIES IN PEDAGOGICAL MONITORING AND ASSESSMENT OF KNOWLEDGE OF TRAINEES

    Directory of Open Access Journals (Sweden)

    Svetlana N Dvoryatkina

    2017-12-01

    Full Text Available The possibility of statement and solution of the problem of searching of theoretical justification and development of efficient didactic mechanisms of the organization of process of pedagogical monitoring and assessment of level of knowledge of trainees can be based on convergence of the leading psychological and pedagogical, mathematical, and informational technologies with accounting of the modern achievements in science. In the article, the pedagogical expediency of realization of opportunities of means of informational technologies in monitoring and assessment of the composite mathematical knowledge, in the management of cognitive activity of students is proved. The ability to integrate fractal methods and neural network technologies in perfecting of a system of pedagogical monitoring of mathematical knowledge of trainees as a part of the automated training systems (ATS is investigated and realized in practice. It is proved that fractal methods increase the accuracy and depth of estimation of the level of proficiency of students and also complexes of intellectual operations of the integrative qualities allowing to master and apply cross-disciplinary knowledge and abilities in professional activity. Neural network technologies solve a problem of realization of the personal focused tutoring from positions of optimum individualization of mathematical education and self-realization of the person. The technology of projection of integrative system of pedagogical monitoring of knowledge of students includes the following stages: establishment of the required tutoring parameters; definition and preparation of input data for realization of integration of fractal and neural network technologies; development of the diagnostic module as a part of the block of an artificial intelligence of ATS, filling of the databases structured by system; start of system for obtaining the forecast. In development of the integrative automated system of pedagogical

  13. Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios

    Science.gov (United States)

    Dong, Feihong; Li, Hongjun; Gong, Xiangwu; Liu, Quan; Wang, Jingchao

    2015-01-01

    A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation. PMID:26404292

  14. Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios

    Directory of Open Access Journals (Sweden)

    Feihong Dong

    2015-09-01

    Full Text Available A typical application scenario of remote wireless sensor networks (WSNs is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.

  15. Energy-Efficient Transmissions for Remote Wireless Sensor Networks: An Integrated HAP/Satellite Architecture for Emergency Scenarios.

    Science.gov (United States)

    Dong, Feihong; Li, Hongjun; Gong, Xiangwu; Liu, Quan; Wang, Jingchao

    2015-09-03

    A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.

  16. DO DYNAMIC NEURAL NETWORKS STAND A BETTER CHANCE IN FRACTIONALLY INTEGRATED PROCESS FORECASTING?

    Directory of Open Access Journals (Sweden)

    Majid Delavari

    2013-04-01

    Full Text Available The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model and a regressive (Auto Regressive Fractionally Integrated Moving Average model which is based on Fractional Integration Approach in forecasting daily data related to the return index of Tehran Stock Exchange (TSE. In order to compare these models under similar conditions, Mean Square Error (MSE and also Root Mean Square Error (RMSE were selected as criteria for the models’ simulated out-of-sample forecasting performance. Besides, fractal markets hypothesis was examined and according to the findings, fractal structure was confirmed to exist in the time series under investigation. Another finding of the study was that dynamic artificial neural network model had the best performance in out-of-sample forecasting based on the criteria introduced for calculating forecasting error in comparison with the ARFIMA model.

  17. Integration of neural networks with fuzzy reasoning for measuring operational parameters in a nuclear reactor

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.

    1993-01-01

    A novel approach is described for measuring variables with operational significance in a complex system such as a nuclear reactor. The methodology is based on the integration of artificial neural networks with fuzzy reasoning. Neural networks are used to map dynamic time series to a set of user-defined linguistic labels called fuzzy values. The process takes place in a manner analogous to that of measurement. Hence, the entire procedure is referred to as virtual measurement and its software implementation as a virtual measuring device. An optimization algorithm based on information criteria and fuzzy algebra augments the process and assists in the identification of different states of the monitored parameter. The proposed technique is applied for monitoring parameters such as performance, valve position, transient type, and reactivity. The results obtained from the application of the neural network-fuzzy reasoning integration in a high power research reactor clearly demonstrate the excellent tolerance of the virtual measuring device to faulty signals as well as its ability to accommodate noisy inputs

  18. Co-Design Method and Wafer-Level Packaging Technique of Thin-Film Flexible Antenna and Silicon CMOS Rectifier Chips for Wireless-Powered Neural Interface Systems

    Directory of Open Access Journals (Sweden)

    Kenji Okabe

    2015-12-01

    Full Text Available In this paper, a co-design method and a wafer-level packaging technique of a flexible antenna and a CMOS rectifier chip for use in a small-sized implantable system on the brain surface are proposed. The proposed co-design method optimizes the system architecture, and can help avoid the use of external matching components, resulting in the realization of a small-size system. In addition, the technique employed to assemble a silicon large-scale integration (LSI chip on the very thin parylene film (5 μm enables the integration of the rectifier circuits and the flexible antenna (rectenna. In the demonstration of wireless power transmission (WPT, the fabricated flexible rectenna achieved a maximum efficiency of 0.497% with a distance of 3 cm between antennas. In addition, WPT with radio waves allows a misalignment of 185% against antenna size, implying that the misalignment has a less effect on the WPT characteristics compared with electromagnetic induction.

  19. Co-Design Method and Wafer-Level Packaging Technique of Thin-Film Flexible Antenna and Silicon CMOS Rectifier Chips for Wireless-Powered Neural Interface Systems.

    Science.gov (United States)

    Okabe, Kenji; Jeewan, Horagodage Prabhath; Yamagiwa, Shota; Kawano, Takeshi; Ishida, Makoto; Akita, Ippei

    2015-12-16

    In this paper, a co-design method and a wafer-level packaging technique of a flexible antenna and a CMOS rectifier chip for use in a small-sized implantable system on the brain surface are proposed. The proposed co-design method optimizes the system architecture, and can help avoid the use of external matching components, resulting in the realization of a small-size system. In addition, the technique employed to assemble a silicon large-scale integration (LSI) chip on the very thin parylene film (5 μm) enables the integration of the rectifier circuits and the flexible antenna (rectenna). In the demonstration of wireless power transmission (WPT), the fabricated flexible rectenna achieved a maximum efficiency of 0.497% with a distance of 3 cm between antennas. In addition, WPT with radio waves allows a misalignment of 185% against antenna size, implying that the misalignment has a less effect on the WPT characteristics compared with electromagnetic induction.

  20. Integration of wireless sensor networks into cyberinfrastructure for monitoring Hawaiian "mountain-to-sea" environments.

    Science.gov (United States)

    Kido, Michael H; Mundt, Carsten W; Montgomery, Kevin N; Asquith, Adam; Goodale, David W; Kaneshiro, Kenneth Y

    2008-10-01

    Monitoring the complex environmental relationships and feedbacks of ecosystems on catchment (or mountain)-to-sea scales is essential for social systems to effectively deal with the escalating impacts of expanding human populations globally on watersheds. However, synthesis of emerging technologies into a robust observing platform for the monitoring of coupled human-natural environments on extended spatial scales has been slow to develop. For this purpose, the authors produced a new cyberinfrastructure for environmental monitoring which successfully merged the use of wireless sensor technologies, grid computing with three-dimensional (3D) geospatial data visualization/exploration, and a secured internet portal user interface, into a working prototype for monitoring mountain-to-sea environments in the high Hawaiian Islands. A use-case example is described in which native Hawaiian residents of Waipa Valley (Kauai) utilized the technology to monitor the effects of regional weather variation on surface water quality/quantity response, to better understand their local hydrologic cycle, monitor agricultural water use, and mitigate the effects of lowland flooding.

  1. Slot Antenna Integrated Re-Entrant Resonator Based Wireless Pressure Sensor for High-Temperature Applications.

    Science.gov (United States)

    Su, Shujing; Lu, Fei; Wu, Guozhu; Wu, Dezhi; Tan, Qiulin; Dong, Helei; Xiong, Jijun

    2017-08-25

    The highly sensitive pressure sensor presented in this paper aims at wireless passive sensing in a high temperature environment by using microwave backscattering technology. The structure of the re-entrant resonator was analyzed and optimized using theoretical calculation, software simulation, and its equivalent lump circuit model was first modified by us. Micro-machining and high-temperature co-fired ceramic (HTCC) process technologies were applied to fabricate the sensor, solving the common problem of cavity sealing during the air pressure loading test. In addition, to prevent the response signal from being immersed in the strong background clutter of the hermetic metal chamber, which makes its detection difficult, we proposed two key techniques to improve the signal to noise ratio: the suppression of strong background clutter and the detection of the weak backscattered signal of the sensor. The pressure sensor demonstrated in this paper works well for gas pressure loading between 40 and 120 kPa in a temperature range of 24 °C to 800 °C. The experimental results show that the sensor resonant frequency lies at 2.1065 GHz, with a maximum pressure sensitivity of 73.125 kHz/kPa.

  2. Simulation electromagnetic scattering on bodies through integral equation and neural networks methods

    Science.gov (United States)

    Lvovich, I. Ya; Preobrazhenskiy, A. P.; Choporov, O. N.

    2018-05-01

    The paper deals with the issue of electromagnetic scattering on a perfectly conducting diffractive body of a complex shape. Performance calculation of the body scattering is carried out through the integral equation method. Fredholm equation of the second time was used for calculating electric current density. While solving the integral equation through the moments method, the authors have properly described the core singularity. The authors determined piecewise constant functions as basic functions. The chosen equation was solved through the moments method. Within the Kirchhoff integral approach it is possible to define the scattered electromagnetic field, in some way related to obtained electrical currents. The observation angles sector belongs to the area of the front hemisphere of the diffractive body. To improve characteristics of the diffractive body, the authors used a neural network. All the neurons contained a logsigmoid activation function and weighted sums as discriminant functions. The paper presents the matrix of weighting factors of the connectionist model, as well as the results of the optimized dimensions of the diffractive body. The paper also presents some basic steps in calculation technique of the diffractive bodies, based on the combination of integral equation and neural networks methods.

  3. CMOS On-Chip Optoelectronic Neural Interface Device with Integrated Light Source for Optogenetics

    International Nuclear Information System (INIS)

    Sawadsaringkarn, Y; Kimura, H; Maezawa, Y; Nakajima, A; Kobayashi, T; Sasagawa, K; Noda, T; Tokuda, T; Ohta, J

    2012-01-01

    A novel optoelectronic neural interface device is proposed for target applications in optogenetics for neural science. The device consists of a light emitting diode (LED) array implemented on a CMOS image sensor for on-chip local light stimulation. In this study, we designed a suitable CMOS image sensor equipped with on-chip electrodes to drive the LEDs, and developed a device structure and packaging process for LED integration. The prototype device produced an illumination intensity of approximately 1 mW with a driving current of 2.0 mA, which is expected to be sufficient to activate channelrhodopsin (ChR2). We also demonstrated the functions of light stimulation and on-chip imaging using a brain slice from a mouse as a target sample.

  4. Crossmodal deficit in dyslexic children: practice affects the neural timing of letter-speech sound integration

    Directory of Open Access Journals (Sweden)

    Gojko eŽarić

    2015-06-01

    Full Text Available A failure to build solid letter-speech sound associations may contribute to reading impairments in developmental dyslexia. Whether this reduced neural integration of letters and speech sounds changes over time within individual children and how this relates to behavioral gains in reading skills remains unknown. In this research, we examined changes in event-related potential (ERP measures of letter-speech sound integration over a 6-month period during which 9-year-old dyslexic readers (n=17 followed a training in letter-speech sound coupling next to their regular reading curriculum. We presented the Dutch spoken vowels /a/ and /o/ as standard and deviant stimuli in one auditory and two audiovisual oddball conditions. In one audiovisual condition (AV0, the letter ‘a’ was presented simultaneously with the vowels, while in the other (AV200 it was preceding vowel onset for 200 ms. Prior to the training (T1, dyslexic readers showed the expected pattern of typical auditory mismatch responses, together with the absence of letter-speech sound effects in a late negativity (LN window. After the training (T2, our results showed earlier (and enhanced crossmodal effects in the LN window. Most interestingly, earlier LN latency at T2 was significantly related to higher behavioral accuracy in letter-speech sound coupling. On a more general level, the timing of the earlier mismatch negativity (MMN in the simultaneous condition (AV0 measured at T1, significantly related to reading fluency at both T1 and T2 as well as with reading gains. Our findings suggest that the reduced neural integration of letters and speech sounds in dyslexic children may show moderate improvement with reading instruction and training and that behavioral improvements relate especially to individual differences in the timing of this neural integration.

  5. A 30 Gb/s full-duplex bi-directional transmission optical wireless-over fiber integration system at W-band.

    Science.gov (United States)

    Tang, Chanjuan; Yu, Jianjun; Li, Xinying; Chi, Nan; Xiao, Jiangnan; Tian, Yumin; Zhang, Junwen

    2014-01-13

    We propose and experimentally demonstrate a full-duplex bi-directional transmission optical wireless-over fiber integration system at W-band (75-100 GHz) with the speed up to 15 Gb/s for both 95.4 GHz link and 88.6 GHz link for the first time. The generation of millimeter-wave (mm-wave) wireless signal is based on the photonic technique by heterodyne mixing of an optical quadrature-phase-shift-keying (QPSK) signal with a free-running light at different wavelength. After 20 km fiber transmission, up to 30 Gb/s mm-wave signal is delivered over 2 m wireless link, and then converted to the optical signal for another 20 km fiber transmission. At the wireless receiver, coherent detection and advanced digital signal processing (DSP) are introduced to improve receiver sensitivity and system performance. With the OSNR of 15 dB, the bit error ratios (BERs) for 10 Gb/s signal transmission at 95.4 GHz and 88.6 GHz are below the forward-error-correction (FEC) threshold of 3.8 × 10(-3) whether post filter is used or not, while the BER for 15 Gb/s QPSK signal employing post filter in the link of 95.4 GHz is 2.9 × 10(-3).

  6. A scalable neural chip with synaptic electronics using CMOS integrated memristors

    International Nuclear Information System (INIS)

    Cruz-Albrecht, Jose M; Derosier, Timothy; Srinivasa, Narayan

    2013-01-01

    The design and simulation of a scalable neural chip with synaptic electronics using nanoscale memristors fully integrated with complementary metal–oxide–semiconductor (CMOS) is presented. The circuit consists of integrate-and-fire neurons and synapses with spike-timing dependent plasticity (STDP). The synaptic conductance values can be stored in memristors with eight levels, and the topology of connections between neurons is reconfigurable. The circuit has been designed using a 90 nm CMOS process with via connections to on-chip post-processed memristor arrays. The design has about 16 million CMOS transistors and 73 728 integrated memristors. We provide circuit level simulations of the entire chip performing neuronal and synaptic computations that result in biologically realistic functional behavior. (paper)

  7. A framework of call admission control procedures for integrated services mobile wireless networks

    International Nuclear Information System (INIS)

    Mahmoud, Ashraf S. Hasan; Al-Qahtani, Salman A.

    2007-01-01

    This paper presents a general framework for a wide range of call admission control (CAC) algorithms. For several CAC schemes, which are a subset of this general framework, an analytical performance evaluation is presented for a multi-traffic mobile wireless network. These CAC algorithms consider a variety of mechanisms to prioritize traffic in an attempt to support different levels of quality of service (QoS) for different types of calls. These mechanisms include dividing the handoff traffic into more than one class and using guard channels or allowing channel splitting to admit more handoff calls. Other mechanisms aimed at adding priority for handoff calls consider employing queuing of handoff calls or dynamically reducing the number lower priority calls. Furthermore our analysis relaxes the typically used assumptions of equal channel holding time and equal resource usage for voice and data calls. The main contribution of this paper is the development of an analytical model for each of the three CAC algorithms specified in this study. In addition to the call blocking and termination probabilities which are usually cited as the performance metrics, in this work we derive and evaluate other metrics that not have be considered by the previous work such as the average queue length, the average queue residency, and the time-out probability for handoff calls. We also develop a simulation tool to test and verify our results. Finally, we present numerical examples to demonstrate the performance of the proposed CAG algorithms and we show that analytical and simulation results are in total agreement. (author)

  8. Wireless Access

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Wireless Access. Wireless connect to the Base station. Easy and Convenient access. Costlier as compared to the wired technology. Reliability challenges. We see it as a complementary technology to the DSL.

  9. Human neural progenitors derived from integration-free iPSCs for SCI therapy

    Directory of Open Access Journals (Sweden)

    Ying Liu

    2017-03-01

    Full Text Available As a potentially unlimited autologous cell source, patient induced pluripotent stem cells (iPSCs provide great capability for tissue regeneration, particularly in spinal cord injury (SCI. However, despite significant progress made in translation of iPSC-derived neural progenitor cells (NPCs to clinical settings, a few hurdles remain. Among them, non-invasive approach to obtain source cells in a timely manner, safer integration-free delivery of reprogramming factors, and purification of NPCs before transplantation are top priorities to overcome. In this study, we developed a safe and cost-effective pipeline to generate clinically relevant NPCs. We first isolated cells from patients' urine and reprogrammed them into iPSCs by non-integrating Sendai viral vectors, and carried out experiments on neural differentiation. NPCs were purified by A2B5, an antibody specifically recognizing a glycoganglioside on the cell surface of neural lineage cells, via fluorescence activated cell sorting. Upon further in vitro induction, NPCs were able to give rise to neurons, oligodendrocytes and astrocytes. To test the functionality of the A2B5+ NPCs, we grafted them into the contused mouse thoracic spinal cord. Eight weeks after transplantation, the grafted cells survived, integrated into the injured spinal cord, and differentiated into neurons and glia. Our specific focus on cell source, reprogramming, differentiation and purification method purposely addresses timing and safety issues of transplantation to SCI models. It is our belief that this work takes one step closer on using human iPSC derivatives to SCI clinical settings.

  10. The 128-channel fully differential digital integrated neural recording and stimulation interface.

    Science.gov (United States)

    Shahrokhi, Farzaneh; Abdelhalim, Karim; Serletis, Demitre; Carlen, Peter L; Genov, Roman

    2010-06-01

    We present a fully differential 128-channel integrated neural interface. It consists of an array of 8 X 16 low-power low-noise signal-recording and generation circuits for electrical neural activity monitoring and stimulation, respectively. The recording channel has two stages of signal amplification and conditioning with and a fully differential 8-b column-parallel successive approximation (SAR) analog-to-digital converter (ADC). The total measured power consumption of each recording channel, including the SAR ADC, is 15.5 ¿W. The measured input-referred noise is 6.08 ¿ Vrms over a 5-kHz bandwidth, resulting in a noise efficiency factor of 5.6. The stimulation channel performs monophasic or biphasic voltage-mode stimulation, with a maximum stimulation current of 5 mA and a quiescent power dissipation of 51.5 ¿W. The design is implemented in 0.35-¿m complementary metal-oxide semiconductor technology with the channel pitch of 200 ¿m for a total die size of 3.4 mm × 2.5 mm and a total power consumption of 9.33 mW. The neural interface was validated in in vitro recording of a low-Mg(2+)/high-K(+) epileptic seizure model in an intact hippocampus of a mouse.

  11. Neural initialization of audiovisual integration in prereaders at varying risk for developmental dyslexia.

    Science.gov (United States)

    I Karipidis, Iliana; Pleisch, Georgette; Röthlisberger, Martina; Hofstetter, Christoph; Dornbierer, Dario; Stämpfli, Philipp; Brem, Silvia

    2017-02-01

    Learning letter-speech sound correspondences is a major step in reading acquisition and is severely impaired in children with dyslexia. Up to now, it remains largely unknown how quickly neural networks adopt specific functions during audiovisual integration of linguistic information when prereading children learn letter-speech sound correspondences. Here, we simulated the process of learning letter-speech sound correspondences in 20 prereading children (6.13-7.17 years) at varying risk for dyslexia by training artificial letter-speech sound correspondences within a single experimental session. Subsequently, we acquired simultaneously event-related potentials (ERP) and functional magnetic resonance imaging (fMRI) scans during implicit audiovisual presentation of trained and untrained pairs. Audiovisual integration of trained pairs correlated with individual learning rates in right superior temporal, left inferior temporal, and bilateral parietal areas and with phonological awareness in left temporal areas. In correspondence, a differential left-lateralized parietooccipitotemporal ERP at 400 ms for trained pairs correlated with learning achievement and familial risk. Finally, a late (650 ms) posterior negativity indicating audiovisual congruency of trained pairs was associated with increased fMRI activation in the left occipital cortex. Taken together, a short (audiovisual integration in neural systems that are responsible for processing linguistic information in proficient readers. To conclude, the ability to learn grapheme-phoneme correspondences, the familial history of reading disability, and phonological awareness of prereading children account for the degree of audiovisual integration in a distributed brain network. Such findings on emerging linguistic audiovisual integration could allow for distinguishing between children with typical and atypical reading development. Hum Brain Mapp 38:1038-1055, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals

  12. Neural Integration of Information Specifying Human Structure from Form, Motion, and Depth

    Science.gov (United States)

    Jackson, Stuart; Blake, Randolph

    2010-01-01

    Recent computational models of biological motion perception operate on ambiguous two-dimensional representations of the body (e.g., snapshots, posture templates) and contain no explicit means for disambiguating the three-dimensional orientation of a perceived human figure. Are there neural mechanisms in the visual system that represent a moving human figure’s orientation in three dimensions? To isolate and characterize the neural mechanisms mediating perception of biological motion, we used an adaptation paradigm together with bistable point-light (PL) animations whose perceived direction of heading fluctuates over time. After exposure to a PL walker with a particular stereoscopically defined heading direction, observers experienced a consistent aftereffect: a bistable PL walker, which could be perceived in the adapted orientation or reversed in depth, was perceived predominantly reversed in depth. A phase-scrambled adaptor produced no aftereffect, yet when adapting and test walkers differed in size or appeared on opposite sides of fixation aftereffects did occur. Thus, this heading direction aftereffect cannot be explained by local, disparity-specific motion adaptation, and the properties of scale and position invariance imply higher-level origins of neural adaptation. Nor is disparity essential for producing adaptation: when suspended on top of a stereoscopically defined, rotating globe, a context-disambiguated “globetrotter” was sufficient to bias the bistable walker’s direction, as were full-body adaptors. In sum, these results imply that the neural signals supporting biomotion perception integrate information on the form, motion, and three-dimensional depth orientation of the moving human figure. Models of biomotion perception should incorporate mechanisms to disambiguate depth ambiguities in two-dimensional body representations. PMID:20089892

  13. Single-Chip Fully Integrated Direct-Modulation CMOS RF Transmitters for Short-Range Wireless Applications

    Directory of Open Access Journals (Sweden)

    M. Jamal Deen

    2013-08-01

    Full Text Available Ultra-low power radio frequency (RF transceivers used in short-range application such as wireless sensor networks (WSNs require efficient, reliable and fully integrated transmitter architectures with minimal building blocks. This paper presents the design, implementation and performance evaluation of single-chip, fully integrated 2.4 GHz and 433 MHz RF transmitters using direct-modulation power voltage-controlled oscillators (PVCOs in addition to a 2.0 GHz phase-locked loop (PLL based transmitter. All three RF transmitters have been fabricated in a standard mixed-signal CMOS 0.18 µm technology. Measurement results of the 2.4 GHz transmitter show an improvement in drain efficiency from 27% to 36%. The 2.4 GHz and 433 MHz transmitters deliver an output power of 8 dBm with a phase noise of −122 dBc/Hz at 1 MHz offset, while drawing 15.4 mA of current and an output power of 6.5 dBm with a phase noise of −120 dBc/Hz at 1 MHz offset, while drawing 20.8 mA of current from 1.5 V power supplies, respectively. The PLL transmitter delivers an output power of 9 mW with a locking range of 128 MHz and consumes 26 mA from 1.8 V power supply. The experimental results demonstrate that the RF transmitters can be efficiently used in low power WSN applications.

  14. Integration of Wireless Technologies in Smart University Campus Environment: Framework Architecture

    Science.gov (United States)

    Khamayseh, Yaser; Mardini, Wail; Aljawarneh, Shadi; Yassein, Muneer Bani

    2015-01-01

    In this paper, the authors are particularly interested in enhancing the education process by integrating new tools to the teaching environments. This enhancement is part of an emerging concept, called smart campus. Smart University Campus will come up with a new ubiquitous computing and communication field and change people's lives radically by…

  15. Green heterogeneous wireless networks

    CERN Document Server

    Ismail, Muhammad; Nee, Hans-Peter; Qaraqe, Khalid A; Serpedin, Erchin

    2016-01-01

    This book focuses on the emerging research topic "green (energy efficient) wireless networks" which has drawn huge attention recently from both academia and industry. This topic is highly motivated due to important environmental, financial, and quality-of-experience (QoE) considerations. Specifically, the high energy consumption of the wireless networks manifests in approximately 2% of all CO2 emissions worldwide. This book presents the authors’ visions and solutions for deployment of energy efficient (green) heterogeneous wireless communication networks. The book consists of three major parts. The first part provides an introduction to the "green networks" concept, the second part targets the green multi-homing resource allocation problem, and the third chapter presents a novel deployment of device-to-device (D2D) communications and its successful integration in Heterogeneous Networks (HetNets). The book is novel in that it specifically targets green networking in a heterogeneous wireless medium, which re...

  16. A recurrent neural model for proto-object based contour integration and figure-ground segregation.

    Science.gov (United States)

    Hu, Brian; Niebur, Ernst

    2017-12-01

    Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594-6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492-1499 2007; Chen et al. Neuron, 82(3), 682-694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.

  17. Neural precursor cells in the ischemic brain - integration, cellular crosstalk and consequences for stroke recovery

    Directory of Open Access Journals (Sweden)

    Dirk M. Hermann

    2014-09-01

    Full Text Available After an ischemic stroke, neural precursor cells (NPCs proliferate within major germinal niches of the brain. Endogenous NPCs subsequently migrate towards the ischemic lesion where they promote tissue remodelling and neural repair. Unfortunately, this restorative process is generally insufficient and thus unable to support a full recovery of lost neurological functions. Supported by solid experimental and preclinical data, the transplantation of exogenous NPCs has emerged as a potential tool for stroke treatment. Transplanted NPCs are thought to act mainly via trophic and immune modulatory effects, thereby complementing the restorative responses initially executed by the endogenous NPC population. Recent studies have attempted to elucidate how the therapeutic properties of transplanted NPCs vary depending on the route of transplantation. Systemic NPC delivery leads to potent immune modulatory actions, which prevent secondary neuronal degeneration, reduces glial scar formation, diminishes oxidative stress and stabilizes blood-brain barrier integrity. On the contrary, local stem cell delivery, allows for the accumulation of large numbers of transplanted NPCs in the brain, thus achieving high levels of locally available tissue trophic factors, which may better induce a strong endogenous NPC proliferative response.Herein we describe the diverse capabilities of exogenous (systemically vs locally transplanted NPCs in enhancing the endogenous neurogenic response after stroke, and how the route of transplantation may affect migration, survival, bystander effects and integration of the cellular graft. It is the authors’ claim that understanding these aspects will be of pivotal importance in discerning how transplanted NPCs exert their therapeutic effects in stroke.

  18. Neural network integration during the perception of in-group and out-group members.

    Science.gov (United States)

    Greven, Inez M; Ramsey, Richard

    2017-11-01

    Group biases guide social interactions by promoting in-group favouritism, but the neural mechanisms underpinning group biases remain unclear. While neuroscience research has shown that distributed brain circuits are associated with seeing in-group and out-group members as "us" and "them", it is less clear how these networks exchange signals. This fMRI study uses functional connectivity analyses to investigate the contribution of functional integration to group bias modulation of person perception. Participants were assigned to an arbitrary group and during scanning they observed bodies of in-group or out-group members that cued the recall of positive or negative social knowledge. The results showed that functional coupling between perceptual and cognitive neural networks is tuned to particular combinations of group membership and social knowledge valence. Specifically, coupling between body perception and theory-of-mind networks is biased towards seeing a person that had previously been paired with information consistent with group bias (positive for in-group and negative for out-group). This demonstrates how brain regions associated with visual analysis of others and belief reasoning exchange and integrate signals when evaluating in-group and out-group members. The results update models of person perception by showing how and when interplay occurs between perceptual and extended systems when developing a representation of another person. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Fully integrated low-loss band-pass filters for wireless applications

    International Nuclear Information System (INIS)

    Rais-Zadeh, M; Kapoor, A; Lavasani, H M; Ayazi, F

    2009-01-01

    Fully integrated low insertion loss micromachined band-pass filters are designed and fabricated on the silicon substrate (ρ = 10–20 Ω cm, ε r = 11.9) for UHF applications. Filters are made of silver, which has the highest conductivity of all metals, to minimize the ohmic loss. A detailed analysis for realizing low insertion loss and high out-of-band rejection filters using elliptic magnitude characteristics is presented, and a comprehensive model to take into account inductive parasitics of the interconnects is developed. Temperature characteristics of the filters are measured and show stable performance. The presented filters are different from the previously reported lumped element filters in that all filters are fully integrated on silicon substrate and occupy a remarkably smaller die area. Two filters are fabricated using the silver micromachining technique with center frequencies at 1.05 and 1.35 GHz. The filters have a constant 3 dB bandwidth of 300 MHz (28.6% and 22.2%) and an insertion loss of 1.4–1.7 dB. The low insertion loss and CMOS compatibility make the presented filters suitable candidates for radio frequency integrated circuits

  20. Detecting PHG frames in wireless capsule endoscopy video by integrating rough global dominate-color with fine local texture features

    Science.gov (United States)

    Liu, Xiaoqi; Wang, Chengliang; Bai, Jianying; Liao, Guobin

    2018-02-01

    Portal hypertensive gastropathy (PHG) is common in gastrointestinal (GI) diseases, and a severe stage of PHG (S-PHG) is a source of gastrointestinal active bleeding. Generally, the diagnosis of PHG is made visually during endoscopic examination; compared with traditional endoscopy, (wireless capsule endoscopy) WCE with noninvasive and painless is chosen as a prevalent tool for visual observation of PHG. However, accurate measurement of WCE images with PHG is a difficult task due to faint contrast and confusing variations in background gastric mucosal tissue for physicians. Therefore, this paper proposes a comprehensive methodology to automatically detect S-PHG images in WCE video to help physicians accurately diagnose S-PHG. Firstly, a rough dominatecolor-tone extraction approach is proposed for better describing global color distribution information of gastric mucosa. Secondly, a hybrid two-layer texture acquisition model is designed by integrating co-occurrence matrix into local binary pattern to depict complex and unique gastric mucosal microstructure local variation. Finally, features of mucosal color and microstructure texture are merged into linear support vector machine to accomplish this automatic classification task. Experiments were implemented on an annotated data set including 1,050 SPHG and 1,370 normal images collected from 36 real patients of different nationalities, ages and genders. By comparison with three traditional texture extraction methods, our method, combined with experimental results, performs best in detection of S-PHG images in WCE video: the maximum of accuracy, sensitivity and specificity reach 0.90, 0.92 and 0.92 respectively.

  1. The QoS Indicators Analysis of Integrated EUHT Wireless Communication System Based on Urban Rail Transit in High-Speed Scenario

    Directory of Open Access Journals (Sweden)

    Xiaoxuan Wang

    2018-01-01

    Full Text Available Nowadays, in urban rail transit systems, train wayside communication system uses Wireless Local Area Network (WLAN as wireless technologies to achieve safety-related information exchange between trains and wayside equipment. However, according to the high speed mobility of trains and the limitations of frequency band, WLAN is unable to meet the demands of future intracity and intercity rail transit. And although the Time Division-Long Term Evolution (TD-LTE technology has high performance compared with WLAN, only 20 MHz bandwidth can be used at most. Moreover, in high-speed scenario over 300 km/h, TD-LTE can hardly meet the future requirement as well. The equipment based on Enhanced Ultra High Throughput (EUHT technology can achieve a better performance in high-speed scenario compared with WLAN and TD-LTE. Furthermore, it allows using the frequency resource flexibly based on 5.8 GHz, such as 20 MHz, 40 MHz, and 80 MHz. In this paper, we set up an EUHT wireless communication system for urban rail transit in high-speed scenario integrated all the traffics of it. An outdoor testing environment in Beijing-Tianjin High-speed Railway is set up to measure the performance of integrated EUHT wireless communication system based on urban rail transit. The communication delay, handoff latency, and throughput of this system are analyzed. Extensive testing results show that the Quality of Service (QoS of the designed integrated EUHT wireless communication system satisfies the requirements of urban rail transit system in high-speed scenario. Moreover, compared with testing results of TD-LTE which we got before, the maximum handoff latency of safety-critical traffics can be decreased from 225 ms to 150 ms. The performance of throughput-critical traffics can achieve 2-way 2 Mbps CCTV and 1-way 8 Mbps PIS which are much better than 2-way 1 Mbps CCTV and 1-way 2 Mbps PIS in TD-LTE.

  2. Integrated control of the cooling system and surface openings using the artificial neural networks

    International Nuclear Information System (INIS)

    Moon, Jin Woo

    2015-01-01

    This study aimed at suggesting an indoor temperature control method that can provide a comfortable thermal environment through the integrated control of the cooling system and the surface openings. Four control logic were developed, employing different application levels of rules and artificial neural network models. Rule-based control methods represented the conventional approach while ANN-based methods were applied for the predictive and adaptive controls. Comparative performance tests for the conventional- and ANN-based methods were numerically conducted for the double-skin-facade building, using the MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation) software, after proving the validity by comparing the simulation and field measurement results. Analysis revealed that the ANN-based controls of the cooling system and surface openings improved the indoor temperature conditions with increased comfortable temperature periods and decreased standard deviation of the indoor temperature from the center of the comfortable range. In addition, the proposed ANN-based logic effectively reduced the number of operating condition changes of the cooling system and surface openings, which can prevent system failure. The ANN-based logic, however, did not show superiority in energy efficiency over the conventional logic. Instead, they have increased the amount of heat removal by the cooling system. From the analysis, it can be concluded that the ANN-based temperature control logic was able to keep the indoor temperature more comfortably and stably within the comfortable range due to its predictive and adaptive features. - Highlights: • Integrated rule-based and artificial neural network based logics were developed. • A cooling device and surface openings were controlled in an integrated manner. • Computer simulation method was employed for comparative performance tests. • ANN-based logics showed the advanced features of thermal environment. • Rule

  3. Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

    Science.gov (United States)

    Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

    2013-11-30

    Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning.

    Science.gov (United States)

    Daniel, Reka; Pollmann, Stefan

    2010-01-06

    The dopaminergic system is known to play a central role in reward-based learning (Schultz, 2006), yet it was also observed to be involved when only cognitive feedback is given (Aron et al., 2004). Within the domain of information-integration category learning, in which information from several stimulus dimensions has to be integrated predecisionally (Ashby and Maddox, 2005), the importance of contingent feedback is well established (Maddox et al., 2003). We examined the common neural correlates of reward anticipation and prediction error in this task. Sixteen subjects performed two parallel information-integration tasks within a single event-related functional magnetic resonance imaging session but received a monetary reward only for one of them. Similar functional areas including basal ganglia structures were activated in both task versions. In contrast, a single structure, the nucleus accumbens, showed higher activation during monetary reward anticipation compared with the anticipation of cognitive feedback in information-integration learning. Additionally, this activation was predicted by measures of intrinsic motivation in the cognitive feedback task and by measures of extrinsic motivation in the rewarded task. Our results indicate that, although all other structures implicated in category learning are not significantly affected by altering the type of reward, the nucleus accumbens responds to the positive incentive properties of an expected reward depending on the specific type of the reward.

  5. Wireless Power Transfer Strategies for Implantable Bioelectronics.

    Science.gov (United States)

    Agarwal, Kush; Jegadeesan, Rangarajan; Guo, Yong-Xin; Thakor, Nitish V

    2017-01-01

    Neural implants have emerged over the last decade as highly effective solutions for the treatment of dysfunctions and disorders of the nervous system. These implants establish a direct, often bidirectional, interface to the nervous system, both sensing neural signals and providing therapeutic treatments. As a result of the technological progress and successful clinical demonstrations, completely implantable solutions have become a reality and are now commercially available for the treatment of various functional disorders. Central to this development is the wireless power transfer (WPT) that has enabled implantable medical devices (IMDs) to function for extended durations in mobile subjects. In this review, we present the theory, link design, and challenges, along with their probable solutions for the traditional near-field resonant inductively coupled WPT, capacitively coupled short-ranged WPT, and more recently developed ultrasonic, mid-field, and far-field coupled WPT technologies for implantable applications. A comparison of various power transfer methods based on their power budgets and WPT range follows. Power requirements of specific implants like cochlear, retinal, cortical, and peripheral are also considered and currently available IMD solutions are discussed. Patient's safety concerns with respect to electrical, biological, physical, electromagnetic interference, and cyber security from an implanted neurotech device are also explored in this review. Finally, we discuss and anticipate future developments that will enhance the capabilities of current-day wirelessly powered implants and make them more efficient and integrable with other electronic components in IMDs.

  6. Wireless Data Transmission at Terahertz Carrier Waves Generated from a Hybrid InP-Polymer Dual Tunable DBR Laser Photonic Integrated Circuit.

    Science.gov (United States)

    Carpintero, Guillermo; Hisatake, Shintaro; de Felipe, David; Guzman, Robinson; Nagatsuma, Tadao; Keil, Norbert

    2018-02-14

    We report for the first time the successful wavelength stabilization of two hybrid integrated InP/Polymer DBR lasers through optical injection. The two InP/Polymer DBR lasers are integrated into a photonic integrated circuit, providing an ideal source for millimeter and Terahertz wave generation by optical heterodyne technique. These lasers offer the widest tuning range of the carrier wave demonstrated to date up into the Terahertz range, about 20 nm (2.5 THz) on a single photonic integrated circuit. We demonstrate the application of this source to generate a carrier wave at 330 GHz to establish a wireless data transmission link at a data rate up to 18 Gbit/s. Using a coherent detection scheme we increase the sensitivity by more than 10 dB over direct detection.

  7. Neural substrates of reliability-weighted visual-tactile multisensory integration

    Directory of Open Access Journals (Sweden)

    Michael S Beauchamp

    2010-06-01

    Full Text Available As sensory systems deteriorate in aging or disease, the brain must relearn the appropriate weights to assign each modality during multisensory integration. Using blood-oxygen level dependent functional magnetic resonance imaging (BOLD fMRI of human subjects, we tested a model for the neural mechanisms of sensory weighting, termed “weighted connections”. This model holds that the connection weights between early and late areas vary depending on the reliability of the modality, independent of the level of early sensory cortex activity. When subjects detected viewed and felt touches to the hand, a network of brain areas was active, including visual areas in lateral occipital cortex, somatosensory areas in inferior parietal lobe, and multisensory areas in the intraparietal sulcus (IPS. In agreement with the weighted connection model, the connection weight measured with structural equation modeling between somatosensory cortex and IPS increased for somatosensory-reliable stimuli, and the connection weight between visual cortex and IPS increased for visual-reliable stimuli. This double dissociation of connection strengths was similar to the pattern of behavioral responses during incongruent multisensory stimulation, suggesting that weighted connections may be a neural mechanism for behavioral reliability weighting.for behavioral reliability weighting.

  8. Wideband LTE power amplifier with integrated novel analog pre-distorter linearizer for mobile wireless communications.

    Directory of Open Access Journals (Sweden)

    Eswaran Uthirajoo

    Full Text Available For the first time, a new circuit to extend the linear operation bandwidth of a LTE (Long Term Evolution power amplifier, while delivering a high efficiency is implemented in less than 1 mm2 chip area. The 950 µm × 900 µm monolithic microwave integrated circuit (MMIC power amplifier (PA is fabricated in a 2 µm InGaP/GaAs process. An on-chip analog pre-distorter (APD is designed to improve the linearity of the PA, up to 20 MHz channel bandwidth. Intended for 1.95 GHz Band 1 LTE application, the PA satisfies adjacent channel leakage ratio (ACLR and error vector magnitude (EVM specifications for a wide LTE channel bandwidth of 20 MHz at a linear output power of 28 dBm with corresponding power added efficiency (PAE of 52.3%. With a respective input and output return loss of 30 dB and 14 dB, the PA's power gain is measured to be 32.5 dB while exhibiting an unconditional stability characteristic from DC up to 5 GHz. The proposed APD technique serves to be a good solution to improve linearity of a PA without sacrificing other critical performance metrics.

  9. Wideband LTE power amplifier with integrated novel analog pre-distorter linearizer for mobile wireless communications.

    Science.gov (United States)

    Uthirajoo, Eswaran; Ramiah, Harikrishnan; Kanesan, Jeevan; Reza, Ahmed Wasif

    2014-01-01

    For the first time, a new circuit to extend the linear operation bandwidth of a LTE (Long Term Evolution) power amplifier, while delivering a high efficiency is implemented in less than 1 mm2 chip area. The 950 µm × 900 µm monolithic microwave integrated circuit (MMIC) power amplifier (PA) is fabricated in a 2 µm InGaP/GaAs process. An on-chip analog pre-distorter (APD) is designed to improve the linearity of the PA, up to 20 MHz channel bandwidth. Intended for 1.95 GHz Band 1 LTE application, the PA satisfies adjacent channel leakage ratio (ACLR) and error vector magnitude (EVM) specifications for a wide LTE channel bandwidth of 20 MHz at a linear output power of 28 dBm with corresponding power added efficiency (PAE) of 52.3%. With a respective input and output return loss of 30 dB and 14 dB, the PA's power gain is measured to be 32.5 dB while exhibiting an unconditional stability characteristic from DC up to 5 GHz. The proposed APD technique serves to be a good solution to improve linearity of a PA without sacrificing other critical performance metrics.

  10. Wideband LTE Power Amplifier with Integrated Novel Analog Pre-Distorter Linearizer for Mobile Wireless Communications

    Science.gov (United States)

    Uthirajoo, Eswaran; Ramiah, Harikrishnan; Kanesan, Jeevan; Reza, Ahmed Wasif

    2014-01-01

    For the first time, a new circuit to extend the linear operation bandwidth of a LTE (Long Term Evolution) power amplifier, while delivering a high efficiency is implemented in less than 1 mm2 chip area. The 950 µm × 900 µm monolithic microwave integrated circuit (MMIC) power amplifier (PA) is fabricated in a 2 µm InGaP/GaAs process. An on-chip analog pre-distorter (APD) is designed to improve the linearity of the PA, up to 20 MHz channel bandwidth. Intended for 1.95 GHz Band 1 LTE application, the PA satisfies adjacent channel leakage ratio (ACLR) and error vector magnitude (EVM) specifications for a wide LTE channel bandwidth of 20 MHz at a linear output power of 28 dBm with corresponding power added efficiency (PAE) of 52.3%. With a respective input and output return loss of 30 dB and 14 dB, the PA’s power gain is measured to be 32.5 dB while exhibiting an unconditional stability characteristic from DC up to 5 GHz. The proposed APD technique serves to be a good solution to improve linearity of a PA without sacrificing other critical performance metrics. PMID:25033049

  11. Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

    Science.gov (United States)

    Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

    2015-10-01

    This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Wireless virtualization

    CERN Document Server

    Wen, Heming; Le-Ngoc, Tho

    2013-01-01

    This SpringerBriefs is an overview of the emerging field of wireless access and mobile network virtualization. It provides a clear and relevant picture of the current virtualization trends in wireless technologies by summarizing and comparing different architectures, techniques and technologies applicable to a future virtualized wireless network infrastructure. The readers are exposed to a short walkthrough of the future Internet initiative and network virtualization technologies in order to understand the potential role of wireless virtualization in the broader context of next-generation ubiq

  13. Optimization and modeling of a photovoltaic solar integrated system by neural networks

    International Nuclear Information System (INIS)

    Ashhab, Moh'd Sami S.

    2008-01-01

    A photovoltaic solar integrated system is modeled with artificial neural networks (ANN's). Data relevant to the system performance was collected on April, 4th 1993 and every 15 min during the day. This input-output data is used to train the ANN. The ANN approximates the data well and therefore can be relied on in predicting the system performance, namely, system efficiencies. The solar system consists of a solar trainer which contains a photovoltaic panel, a DC centrifugal pump, flat plate collectors, storage tank, a flowmeter for measuring the water mass flow rate, pipes, pyranometer for measuring the solar intensity, thermocouples for measuring various system temperatures and wind speed meter. The complex method constrained optimization is applied to the solar system ANN model to find the operating conditions of the system that will produce the maximum system efficiencies. This information will be very hard to obtain by just looking at the available historical input-output data

  14. Optimization and modeling of a photovoltaic solar integrated system by neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ashhab, Moh' d Sami S. [Department of Mechanical Engineering, The Hashemite University, Zarqa 13115 (Jordan)

    2008-11-15

    A photovoltaic solar integrated system is modeled with artificial neural networks (ANN's). Data relevant to the system performance was collected on April, 4th 1993 and every 15 min during the day. This input-output data is used to train the ANN. The ANN approximates the data well and therefore can be relied on in predicting the system performance, namely, system efficiencies. The solar system consists of a solar trainer which contains a photovoltaic panel, a DC centrifugal pump, flat plate collectors, storage tank, a flowmeter for measuring the water mass flow rate, pipes, pyranometer for measuring the solar intensity, thermocouples for measuring various system temperatures and wind speed meter. The complex method constrained optimization is applied to the solar system ANN model to find the operating conditions of the system that will produce the maximum system efficiencies. This information will be very hard to obtain by just looking at the available historical input-output data. (author)

  15. FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

    Directory of Open Access Journals (Sweden)

    T. Pasupathi

    2014-05-01

    Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

  16. Neural basis of the time window for subjective motor-auditory integration

    Directory of Open Access Journals (Sweden)

    Koichi eToida

    2016-01-01

    Full Text Available Temporal contiguity between an action and corresponding auditory feedback is crucial to the perception of self-generated sound. However, the neural mechanisms underlying motor–auditory temporal integration are unclear. Here, we conducted four experiments with an oddball paradigm to examine the specific event-related potentials (ERPs elicited by delayed auditory feedback for a self-generated action. The first experiment confirmed that a pitch-deviant auditory stimulus elicits mismatch negativity (MMN and P300, both when it is generated passively and by the participant’s action. In our second and third experiments, we investigated the ERP components elicited by delayed auditory feedback of for a self-generated action. We found that delayed auditory feedback elicited an enhancement of P2 (enhanced-P2 and a N300 component, which were apparently different from the MMN and P300 components observed in the first experiment. We further investigated the sensitivity of the enhanced-P2 and N300 to delay length in our fourth experiment. Strikingly, the amplitude of the N300 increased as a function of the delay length. Additionally, the N300 amplitude was significantly correlated with the conscious detection of the delay (the 50% detection point was around 200 ms, and hence reduction in the feeling of authorship of the sound (the sense of agency. In contrast, the enhanced-P2 was most prominent in short-delay (≤ 200 ms conditions and diminished in long-delay conditions. Our results suggest that different neural mechanisms are employed for the processing of temporally-deviant and pitch-deviant auditory feedback. Additionally, the temporal window for subjective motor–auditory integration is likely about 200 ms, as indicated by these auditory ERP components.

  17. Advantages of comparative studies in songbirds to understand the neural basis of sensorimotor integration.

    Science.gov (United States)

    Murphy, Karagh; James, Logan S; Sakata, Jon T; Prather, Jonathan F

    2017-08-01

    Sensorimotor integration is the process through which the nervous system creates a link between motor commands and associated sensory feedback. This process allows for the acquisition and refinement of many behaviors, including learned communication behaviors such as speech and birdsong. Consequently, it is important to understand fundamental mechanisms of sensorimotor integration, and comparative analyses of this process can provide vital insight. Songbirds offer a powerful comparative model system to study how the nervous system links motor and sensory information for learning and control. This is because the acquisition, maintenance, and control of birdsong critically depend on sensory feedback. Furthermore, there is an incredible diversity of song organizations across songbird species, ranging from songs with simple, stereotyped sequences to songs with complex sequencing of vocal gestures, as well as a wide diversity of song repertoire sizes. Despite this diversity, the neural circuitry for song learning, control, and maintenance remains highly similar across species. Here, we highlight the utility of songbirds for the analysis of sensorimotor integration and the insights about mechanisms of sensorimotor integration gained by comparing different songbird species. Key conclusions from this comparative analysis are that variation in song sequence complexity seems to covary with the strength of feedback signals in sensorimotor circuits and that sensorimotor circuits contain distinct representations of elements in the vocal repertoire, possibly enabling evolutionary variation in repertoire sizes. We conclude our review by highlighting important areas of research that could benefit from increased comparative focus, with particular emphasis on the integration of new technologies. Copyright © 2017 the American Physiological Society.

  18. Integrated low noise low power interface for neural bio-potentials recording and conditioning

    Science.gov (United States)

    Bottino, Emanuele; Martinoia, Sergio; Valle, Maurizio

    2005-06-01

    The recent progress in both neurobiology and microelectronics suggests the creation of new, powerful tools to investigate the basic mechanisms of brain functionality. In particular, a lot of efforts are spent by scientific community to define new frameworks devoted to the analysis of in-vitro cultured neurons. One possible approach is recording their spiking activity to monitor the coordinated cellular behaviour and get insights about neural plasticity. Due to the nature of neurons action-potentials, when considering the design of an integrated microelectronic-based recording system, a number of problems arise. First, one would desire to have a high number of recording sites (i.e. several hundreds): this poses constraints on silicon area and power consumption. In this regard, our aim is to integrate-through on-chip post-processing techniques-hundreds of bio-compatible microsensors together with CMOS standard-process low-power (i.e. some tenths of uW per channel) conditioning electronics. Each recording channel is provided with sampling electronics to insure synchronous recording so that, for example, cross-correlation between signals coming from different sites can be performed. Extra-cellular potentials are in the range of [50-150] uV, so a comparison in terms of noise-efficiency was carried out among different architectures and very low-noise pre-amplification electronics (i.e. less than 5 uVrms) was designed. As spikes measurements are made with respect to the voltage of a reference electrode, we opted for an AC-coupled differential-input preamplifier provided with band-pass filtering capability. To achieve this, we implemented large time-constant (up to seconds) integrated components in the preamp feedback path. Thus, we got rid also of random slow-drifting DC-offsets and common mode signals. The paper will present our achievements in the design and implementation of a fully integrated bio-abio interface to record neural spiking activity. In particular

  19. A Neural Systems-Based Neurobiology and Neuropsychiatry Course: Integrating Biology, Psychodynamics, and Psychology in the Psychiatric Curriculum

    Science.gov (United States)

    Lacy, Timothy; Hughes, John D.

    2006-01-01

    Objective: Psychotherapy and biological psychiatry remain divided in psychiatry residency curricula. Behavioral neurobiology and neuropsychiatry provide a systems-level framework that allows teachers to integrate biology, psychodynamics, and psychology. Method: The authors detail the underlying assumptions and outline of a neural systems-based…

  20. Future of wireless communication

    Energy Technology Data Exchange (ETDEWEB)

    Barker, M

    1996-12-31

    This document reproduces slides from a conference presentation giving an overview of current and upcoming wireless communication methods of interest to Canadian electric utilities. Both voice and data communication methods are considered, including cellular telephone, satellite communications, personal communication services, regulated licensed arrowband data systems, and integrated services.

  1. Wireless Internet

    NARCIS (Netherlands)

    el Zarki, M.; Heijenk, Geert; Lee, Kenneth S.; Bidgoli, H.

    This chapter addresses the topic of wireless Internet, the extension of the wireline Internet architecture to the wireless domain. As such the chapter introduces the reader to the dominant characteristics of the Internet, from its structure to the protocols that control the forwarding of data and

  2. Integrating Artificial Immune, Neural and Endrocine Systems in Autonomous Sailing Robots

    Science.gov (United States)

    2010-09-24

    system - Development of an adaptive hormone system capable of changing operation and control of the neural network depending on changing enviromental ...and control of the neural network depending on changing enviromental conditions • First basic design of the MOOP and a simple neural-endocrine based

  3. The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

    Science.gov (United States)

    Goñi, Joaquín; Aznárez-Sanado, Maite; Arrondo, Gonzalo; Fernández-Seara, María; Loayza, Francis R; Heukamp, Franz H; Pastor, María A

    2011-03-09

    Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD) signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC) and left and right pre-supplementary motor areas (pre-SMA) and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively) of the uncertainty associated to an economic decision making paradigm.

  4. Neural basis of limb ownership in individuals with body integrity identity disorder.

    Directory of Open Access Journals (Sweden)

    Milenna T van Dijk

    Full Text Available Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis underlying the feeling of limb ownership, since these individuals have a feeling of disownership for a limb in the absence of apparent brain damage. Here we directly compared brain activation between limbs that do and do not feel as part of the body using functional MRI during separate tactile stimulation and motor execution experiments. In comparison to matched controls, individuals with BIID showed heightened responsivity of a large somatosensory network including the parietal cortex and right insula during tactile stimulation, regardless of whether the stimulated leg felt owned or alienated. Importantly, activity in the ventral premotor cortex depended on the feeling of ownership and was reduced during stimulation of the alienated compared to the owned leg. In contrast, no significant differences between groups were observed during the performance of motor actions. These results suggest that altered somatosensory processing in the premotor cortex is associated with the feeling of disownership in BIID, which may be related to altered integration of somatosensory and proprioceptive information.

  5. Neural basis of limb ownership in individuals with body integrity identity disorder.

    Science.gov (United States)

    van Dijk, Milenna T; van Wingen, Guido A; van Lammeren, Anouk; Blom, Rianne M; de Kwaasteniet, Bart P; Scholte, H Steven; Denys, Damiaan

    2013-01-01

    Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID) lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis underlying the feeling of limb ownership, since these individuals have a feeling of disownership for a limb in the absence of apparent brain damage. Here we directly compared brain activation between limbs that do and do not feel as part of the body using functional MRI during separate tactile stimulation and motor execution experiments. In comparison to matched controls, individuals with BIID showed heightened responsivity of a large somatosensory network including the parietal cortex and right insula during tactile stimulation, regardless of whether the stimulated leg felt owned or alienated. Importantly, activity in the ventral premotor cortex depended on the feeling of ownership and was reduced during stimulation of the alienated compared to the owned leg. In contrast, no significant differences between groups were observed during the performance of motor actions. These results suggest that altered somatosensory processing in the premotor cortex is associated with the feeling of disownership in BIID, which may be related to altered integration of somatosensory and proprioceptive information.

  6. The neural circuits of innate fear: detection, integration, action, and memorization

    Science.gov (United States)

    Silva, Bianca A.; Gross, Cornelius T.

    2016-01-01

    How fear is represented in the brain has generated a lot of research attention, not only because fear increases the chances for survival when appropriately expressed but also because it can lead to anxiety and stress-related disorders when inadequately processed. In this review, we summarize recent progress in the understanding of the neural circuits processing innate fear in rodents. We propose that these circuits are contained within three main functional units in the brain: a detection unit, responsible for gathering sensory information signaling the presence of a threat; an integration unit, responsible for incorporating the various sensory information and recruiting downstream effectors; and an output unit, in charge of initiating appropriate bodily and behavioral responses to the threatful stimulus. In parallel, the experience of innate fear also instructs a learning process leading to the memorization of the fearful event. Interestingly, while the detection, integration, and output units processing acute fear responses to different threats tend to be harbored in distinct brain circuits, memory encoding of these threats seems to rely on a shared learning system. PMID:27634145

  7. The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

    Directory of Open Access Journals (Sweden)

    Joaquín Goñi

    Full Text Available Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC and left and right pre-supplementary motor areas (pre-SMA and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively of the uncertainty associated to an economic decision making paradigm.

  8. An Integrated Circuit for Simultaneous Extracellular Electrophysiology Recording and Optogenetic Neural Manipulation.

    Science.gov (United States)

    Chen, Chang Hao; McCullagh, Elizabeth A; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I; Mak, Pui In; Klug, Achim; Lei, Tim C

    2017-03-01

    The ability to record and to control action potential firing in neuronal circuits is critical to understand how the brain functions. The objective of this study is to develop a monolithic integrated circuit (IC) to record action potentials and simultaneously control action potential firing using optogenetics. A low-noise and high input impedance (or low input capacitance) neural recording amplifier is combined with a high current laser/light-emitting diode (LED) driver in a single IC. The low input capacitance of the amplifier (9.7 pF) was achieved by adding a dedicated unity gain stage optimized for high impedance metal electrodes. The input referred noise of the amplifier is [Formula: see text], which is lower than the estimated thermal noise of the metal electrode. Thus, the action potentials originating from a single neuron can be recorded with a signal-to-noise ratio of at least 6.6. The LED/laser current driver delivers a maximum current of 330 mA, which is adequate for optogenetic control. The functionality of the IC was tested with an anesthetized Mongolian gerbil and auditory stimulated action potentials were recorded from the inferior colliculus. Spontaneous firings of fifth (trigeminal) nerve fibers were also inhibited using the optogenetic protein Halorhodopsin. Moreover, a noise model of the system was derived to guide the design. A single IC to measure and control action potentials using optogenetic proteins is realized so that more complicated behavioral neuroscience research and the translational neural disorder treatments become possible in the future.

  9. From early wireless to Everest.

    Science.gov (United States)

    Allen, A

    1998-01-01

    Medical information has been transmitted using wireless technologies for almost 80 years. A "wired wireless" electronic stethoscope was developed by the U.S. Army Signal Corps in the early 1920's, for potential use in ship-to-shore transmission of cardiac sounds. [Winters SR. Diagnosis by wireless. Scientific American June 11, 1921, p. 465] Today, wireless is used in a wide range of medical applications and at sites from transoceanic air flights to offshore oil platforms to Mt. Everest. 'Wireless LANs' are often used in medical environments. Typically, nurses and physicians in a hospital or clinic use hand-held "wireless thin client" pen computers that exchange patient information and images with the hospital server. Numerous companies, such as Fujitsu (article below) and Cruise Technologies (www.cruisetech.com) manufacture handheld pen-entry computers. One company, LXE, integrates radio-frequency (RF) enhanced hand-held computers specifically designed for production use within a wireless LAN (www.lxe.com). Other companies (Proxim, Symbol, and others) supply the wireless RF LAN infrastructure for the enterprise. Unfortunately, there have been problems with widespread deployment of wireless LANs. Perhaps the biggest impediment has been the lack of standards. Although an international standard (IEEE 802.11) was adopted in 1997, most wireless LAN products still are not compatible with the equipment of competing companies. A problem with the current standard for LAN adapters is that throughput is limited to 3 Mbps--compared to at least 10 Mbps, and often 100 Mbps, in a hard-wired Ethernet LAN. An II Mbps standard is due out in the next year or so, but it will be at least 2 years before standards-compliant products are available. This story profiles some of the ways that wireless is being used to overcome gaps in terrestrial and within-enterprise communication.

  10. Miniature wireless recording and stimulation system for rodent behavioural testing

    Science.gov (United States)

    Pinnell, R. C.; Dempster, J.; Pratt, J.

    2015-12-01

    Objective. Elucidation of neural activity underpinning rodent behaviour has traditionally been hampered by the use of tethered systems and human involvement. Furthermore the combination of deep-brain stimulation (DBS) and various neural recording modalities can lead to complex and time-consuming laboratory setups. For studies of this type, novel tools are required to drive forward this research. Approach. A miniature wireless system weighing 8.5 g (including battery) was developed for rodent use that combined multichannel DBS and local-field potential (LFP) recordings. Its performance was verified in a working memory task that involved 4-channel fronto-hippocampal LFP recording and bilateral constant-current fimbria-fornix DBS. The system was synchronised with video-tracking for extraction of LFP at discrete task phases, and DBS was activated intermittently at discrete phases of the task. Main results. In addition to having a fast set-up time, the system could reliably transmit continuous LFP at over 8 hours across 3-5 m distances. During the working memory task, LFP pertaining to discrete task phases was extracted and compared with well-known neural correlates of active exploratory behaviour in rodents. DBS could be wirelessly activated/deactivated at any part of the experiment during EEG recording and transmission, allowing for a seamless integration of this modality. Significance. The wireless system combines a small size with a level of robustness and versatility that can greatly simplify rodent behavioural experiments involving EEG recording and DBS. Designed for versatility and simplicity, the small size and low-cost of the system and its receiver allow for enhanced portability, fast experimental setup times, and pave the way for integration with more complex behaviour.

  11. A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm

    Directory of Open Access Journals (Sweden)

    Yu-xin Zhao

    2014-01-01

    Full Text Available This paper presents a novel wavelet kernel neural network (WKNN with wavelet kernel function. It is applicable in online learning with adaptive parameters and is applied on parameters tuning of fractional-order PID (FOPID controller, which could handle time delay problem of the complex control system. Combining the wavelet function and the kernel function, the wavelet kernel function is adopted and validated the availability for neural network. Compared to the conservative wavelet neural network, the most innovative character of the WKNN is its rapid convergence and high precision in parameters updating process. Furthermore, the integrated pressurized water reactor (IPWR system is established by RELAP5, and a novel control strategy combining WKNN and fuzzy logic rule is proposed for shortening controlling time and utilizing the experiential knowledge sufficiently. Finally, experiment results verify that the control strategy and controller proposed have the practicability and reliability in actual complicated system.

  12. Fiber-wireless integrated mobile backhaul network based on a hybrid millimeter-wave and free-space-optics architecture with an adaptive diversity combining technique.

    Science.gov (United States)

    Zhang, Junwen; Wang, Jing; Xu, Yuming; Xu, Mu; Lu, Feng; Cheng, Lin; Yu, Jianjun; Chang, Gee-Kung

    2016-05-01

    We propose and experimentally demonstrate a novel fiber-wireless integrated mobile backhaul network based on a hybrid millimeter-wave (MMW) and free-space-optics (FSO) architecture using an adaptive combining technique. Both 60 GHz MMW and FSO links are demonstrated and fully integrated with optical fibers in a scalable and cost-effective backhaul system setup. Joint signal processing with an adaptive diversity combining technique (ADCT) is utilized at the receiver side based on a maximum ratio combining algorithm. Mobile backhaul transportation of 4-Gb/s 16 quadrature amplitude modulation frequency-division multiplexing (QAM-OFDM) data is experimentally demonstrated and tested under various weather conditions synthesized in the lab. Performance improvement in terms of reduced error vector magnitude (EVM) and enhanced link reliability are validated under fog, rain, and turbulence conditions.

  13. 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 ...

  14. 3D inkjet printed disposable environmental monitoring wireless sensor node

    KAUST Repository

    Farooqui, Muhammad Fahad; Shamim, Atif

    2017-01-01

    We propose a disposable, miniaturized, moveable, fully integrated 3D inkjet-printed wireless sensor node for large area environmental monitoring applications. As a proof of concept, we show the wireless sensing of temperature, humidity and H2S

  15. Enhanced biocompatibility of neural probes by integrating microstructures and delivering anti-inflammatory agents via microfluidic channels

    Science.gov (United States)

    Liu, Bin; Kim, Eric; Meggo, Anika; Gandhi, Sachin; Luo, Hao; Kallakuri, Srinivas; Xu, Yong; Zhang, Jinsheng

    2017-04-01

    Objective. Biocompatibility is a major issue for chronic neural implants, involving inflammatory and wound healing responses of neurons and glial cells. To enhance biocompatibility, we developed silicon-parylene hybrid neural probes with open architecture electrodes, microfluidic channels and a reservoir for drug delivery to suppress tissue responses. Approach. We chronically implanted our neural probes in the rat auditory cortex and investigated (1) whether open architecture electrode reduces inflammatory reaction by measuring glial responses; and (2) whether delivery of antibiotic minocycline reduces inflammatory and tissue reaction. Four weeks after implantation, immunostaining for glial fibrillary acid protein (astrocyte marker) and ionizing calcium-binding adaptor molecule 1 (macrophages/microglia cell marker) were conducted to identify immunoreactive astrocyte and microglial cells, and to determine the extent of astrocytes and microglial cell reaction/activation. A comparison was made between using traditional solid-surface electrodes and newly-designed electrodes with open architecture, as well as between deliveries of minocycline and artificial cerebral-spinal fluid diffused through microfluidic channels. Main results. The new probes with integrated micro-structures induced minimal tissue reaction compared to traditional electrodes at 4 weeks after implantation. Microcycline delivered through integrated microfluidic channels reduced tissue response as indicated by decreased microglial reaction around the neural probes implanted. Significance. The new design will help enhance the long-term stability of the implantable devices.

  16. The wireless Web and patient care.

    Science.gov (United States)

    Bergeron, B P

    2001-01-01

    Wireless computing, when integrated with the Web, is poised to revolutionize the practice and teaching of medicine. As vendors introduce wireless Web technologies in the medical community that have been used successfully in the business and consumer markets, clinicians can expect profound increases in the amount of patient data, as well as the ease with which those data are acquired, analyzed, and disseminated. The enabling technologies involved in this transformation to the wireless Web range from the new generation of wireless PDAs, eBooks, and wireless data acquisition peripherals to new wireless network protocols. The rate-limiting step in the application of this technology in medicine is not technology per se but rather how quickly clinicians and their patients come to accept and appreciate the benefits and limitations of the application of wireless Web technology.

  17. Integrating Artificial Neural Networks into the VIC Model for Rainfall-Runoff Modeling

    Directory of Open Access Journals (Sweden)

    Changqing Meng

    2016-09-01

    Full Text Available A hybrid rainfall-runoff model was developed in this study by integrating the variable infiltration capacity (VIC model with artificial neural networks (ANNs. In the proposed model, the prediction interval of the ANN replaces separate, individual simulation (i.e., single simulation. The spatial heterogeneity of horizontal resolution, subgrid-scale features and their influence on the streamflow can be assessed according to the VIC model. In the routing module, instead of a simple linear superposition of the streamflow generated from each subbasin, ANNs facilitate nonlinear mappings of the streamflow produced from each subbasin into the total streamflow at the basin outlet. A total of three subbasins were delineated and calibrated independently via the VIC model; daily runoff errors were simulated for each subbasin, then corrected by an ANN bias-correction model. The initial streamflow and corrected runoff from the simulation for individual subbasins serve as inputs to the ANN routing model. The feasibility of this proposed method was confirmed according to the performance of its application to a case study on rainfall-runoff prediction in the Jinshajiang River Basin, the headwater area of the Yangtze River.

  18. Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques

    Science.gov (United States)

    Jain, Ashu; Srinivasulu, Sanaga

    2006-02-01

    This paper presents the findings of a study aimed at decomposing a flow hydrograph into different segments based on physical concepts in a catchment, and modelling different segments using different technique viz. conceptual and artificial neural networks (ANNs). An integrated modelling framework is proposed capable of modelling infiltration, base flow, evapotranspiration, soil moisture accounting, and certain segments of the decomposed flow hydrograph using conceptual techniques and the complex, non-linear, and dynamic rainfall-runoff process using ANN technique. Specifically, five different multi-layer perceptron (MLP) and two self-organizing map (SOM) models have been developed. The rainfall and streamflow data derived from the Kentucky River catchment were employed to test the proposed methodology and develop all the models. The performance of all the models was evaluated using seven different standard statistical measures. The results obtained in this study indicate that (a) the rainfall-runoff relationship in a large catchment consists of at least three or four different mappings corresponding to different dynamics of the underlying physical processes, (b) an integrated approach that models the different segments of the decomposed flow hydrograph using different techniques is better than a single ANN in modelling the complex, dynamic, non-linear, and fragmented rainfall runoff process, (c) a simple model based on the concept of flow recession is better than an ANN to model the falling limb of a flow hydrograph, and (d) decomposing a flow hydrograph into the different segments corresponding to the different dynamics based on the physical concepts is better than using the soft decomposition employed using SOM.

  19. Wireless Cybersecurity

    Science.gov (United States)

    2013-04-01

    completely change the entire landscape. For example, under the quantum computing regime, factoring prime numbers requires only polynomial time (i.e., Shor’s...AFRL-OSR-VA-TR-2013-0206 Wireless Cybersecurity Biao Chen Syracuse University April 2013 Final Report DISTRIBUTION A...19a. NAME OF RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) 21-02-2013 FINAL REPORT 01-04-2009 TO 30-11-2012 Wireless Cybersecurity

  20. Wireless home networking for dummies

    CERN Document Server

    Briere, Danny; Ferris, Edward

    2010-01-01

    The perennial bestseller shows you how share your files and Internet connection across a wireless network. Fully updated for Windows 7 and Mac OS X Snow Leopard, this new edition of this bestseller returns with all the latest in wireless standards and security. This fun and friendly guide shows you how to integrate your iPhone, iPod touch, smartphone, or gaming system into your home network. Veteran authors escort you through the various financial and logisitical considerations that you need to take into account before building a wireless network at home.: Covers the basics of planning, instal

  1. Wireless microsensor network solutions for neurological implantable devices

    Science.gov (United States)

    Abraham, Jose K.; Whitchurch, Ashwin; Varadan, Vijay K.

    2005-05-01

    The design and development of wireless mocrosensor network systems for the treatment of many degenerative as well as traumatic neurological disorders is presented in this paper. Due to the advances in micro and nano sensors and wireless systems, the biomedical sensors have the potential to revolutionize many areas in healthcare systems. The integration of nanodevices with neurons that are in communication with smart microsensor systems has great potential in the treatment of many neurodegenerative brain disorders. It is well established that patients suffering from either Parkinson"s disease (PD) or Epilepsy have benefited from the advantages of implantable devices in the neural pathways of the brain to alter the undesired signals thus restoring proper function. In addition, implantable devices have successfully blocked pain signals and controlled various pelvic muscles in patients with urinary and fecal incontinence. Even though the existing technology has made a tremendous impact on controlling the deleterious effects of disease, it is still in its infancy. This paper presents solutions of many problems of today's implantable and neural-electronic interface devices by combining nanowires and microelectronics with BioMEMS and applying them at cellular level for the development of a total wireless feedback control system. The only device that will actually be implanted in this research is the electrodes. All necessary controllers will be housed in accessories that are outside the body that communicate with the implanted electrodes through tiny inductively-coupled antennas. A Parkinson disease patient can just wear a hat-system close to the implantable neural probe so that the patient is free to move around, while the sensors continually monitor, record, transmit all vital information to health care specialist. In the event of a problem, the system provides an early warning to the patient while they are still mobile thus providing them the opportunity to react and

  2. Bio-WiTel: A Low-Power Integrated Wireless Telemetry System for Healthcare Applications in 401-406 MHz Band of MedRadio Spectrum.

    Science.gov (United States)

    Srivastava, Abhishek; Sankar K, Nithin; Chatterjee, Baibhab; Das, Devarshi; Ahmad, Meraj; Kukkundoor, Rakesh Keshava; Saraf, Vivek; Ananthapadmanabhan, Jayachandran; Sharma, Dinesh Kumar; Baghini, Maryam Shojaei

    2018-03-01

    This paper presents a low-power integrated wireless telemetry system (Bio-WiTel) for healthcare applications in 401-406 MHz frequency band of medical device radiocommunication (MedRadio) spectrum. In this paper, necessary design considerations for telemetry system for short-range (upto 3 m) communication of biosignals are presented. These considerations help greatly in making important design decisions, which eventually lead to a simple, low power, robust, and reliable wireless system implementation. Transmitter (TX) and receiver (RX) of Bio-WiTel system have been fabricated in 180 nm mixed mode CMOS technology. While radiating -18 dBm output power to a 50 antenna, the packaged TX IC consumes 250 μW power in 100% on state from 1 V supply, whereas the RX IC consumes 990 μW power from 1.8 V supply with a sensitivity of -75 dBm. Measurement results show that TX fulfils the spectral mask requirement at a maximum data rate of 72 kb/s. The measured bit error rate (BER) of RX is less than for a data rate of 200 kb/s. The proposed Bio-WiTel system is tested successfully in home and hospital environments for the communication of electrocardiogram and photoplethysmogram signals at a data rate of 57.6 kb/s with a measured BER of <10 for a maximum distance of 3 m.

  3. Fully Integrated On-Chip Coil in 0.13 μm CMOS for Wireless Power Transfer Through Biological Media.

    Science.gov (United States)

    Zargham, Meysam; Gulak, P Glenn

    2015-04-01

    Delivering milliwatts of wireless power at centimeter distances is advantageous to many existing and emerging biomedical applications. It is highly desirable to fully integrate the receiver on a single chip in standard CMOS with no additional post-processing steps or external components. This paper presents a 2 × 2.18 mm(2) on-chip wireless power transfer (WPT) receiver (Rx) coil fabricated in 0.13 μm CMOS. The WPT system utilizes a 14.5 × 14.5 mm(2) transmitter (Tx) coil that is fabricated on a standard FR4 substrate. The on-chip power harvester demonstrates a peak WPT efficiency of -18.47 dB , -20.96 dB and -20.15 dB at 10 mm of separation through air, bovine muscle and 0.2 molar NaCl, respectively. The achieved efficiency enables the delivery of milliwatts of power to application circuits while staying below safe power density and electromagnetic (EM) exposure limits.

  4. Functional integration of grafted neural stem cell-derived dopaminergic neurons monitored by optogenetics in an in vitro Parkinson model

    DEFF Research Database (Denmark)

    Tønnesen, Jan; Parish, Clare L; Sørensen, Andreas T

    2011-01-01

    Intrastriatal grafts of stem cell-derived dopamine (DA) neurons induce behavioral recovery in animal models of Parkinson's disease (PD), but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral...... of post-synaptic currents, and functional expression of DA D₂ autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation...... using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying...

  5. The first neural probe integrated with light source (blue laser diode) for optical stimulation and electrical recording.

    Science.gov (United States)

    Park, HyungDal; Shin, Hyun-Joon; Cho, Il-Joo; Yoon, Eui-sung; Suh, Jun-Kyo Francis; Im, Maesoon; Yoon, Euisik; Kim, Yong-Jun; Kim, Jinseok

    2011-01-01

    In this paper, we report a neural probe which can selectively stimulate target neurons optically through Si wet etched mirror surface and record extracellular neural signals in iridium oxide tetrodes. Consequently, the proposed approach provides to improve directional problem and achieve at least 150/m gap distance between stimulation and recording sites by wet etched mirror surface in V-groove. Also, we developed light source, blue laser diode (OSRAM Blue Laser Diode_PL 450), integration through simple jig for one-touch butt-coupling. Furthermore, optical power and impedance of iridium oxide tetrodes were measured as 200 μW on 5 mW from LD and 206.5 k Ω at 1 kHz and we demonstrated insertion test of probe in 0.5% agarose-gel successfully. We have successfully transmitted a light of 450 nm to optical fiber through the integrated LD using by butt-coupling method.

  6. MosquitoNet: investigating the use of UAV and artificial neural networks for integrated mosquito management

    Science.gov (United States)

    Case, E.; Ren, Y.; Shragai, T.; Erickson, D.

    2017-12-01

    Integrated mosquito control is expensive and resource intensive, and changing climatic factors are predicted to expand the habitable range of disease-carrying mosquitoes into new regions in the United States. Of particular concern in the northeastern United States are aedes albopictus, an aggressive, invasive species of mosquito that can transmit both native and exotic disease. Ae. albopictus prefer to live near human populations and breed in artificial containers with as little as two millimeters of standing water, exponentially increasing the difficulty of source control in suburban and urban areas. However, low-cost unmanned aerial vehicles (UAVs) can be used to photograph large regions at centimeter-resolution, and can image containers of interest in suburban neighborhoods. While proofs-of-concepts have been shown using UAVs to identify naturally occurring bodies of water, they have not been used to identify mosquito habitat in more populated areas. One of the primary challenges is that post-processing high-resolution aerial imagery is still time intensive, often labelled by hand or with programs built for satellite imagery. Artificial neural networks have been highly successful at image recognition tasks; in the past five years, convolutional neural networks (CNN) have surpassed or aided trained humans in identification of skin cancer, agricultural crops, and poverty levels from satellite imagery. MosquitoNet, a dual classifier built from the Single Shot Multibox Detector and VGG16 architectures, was trained on UAV­­­­­ aerial imagery taken during a larval study in Westchester County in southern New York State in July and August 2017. MosquitoNet was designed to assess the habitat risk of suburban properties by automating the identification and counting of containers like tires, toys, garbage bins, flower pots, etc. The SSD-based architecture marked small containers and other habitat indicators while the VGG16-based architecture classified the type of

  7. Glassy carbon MEMS for novel origami-styled 3D integrated intracortical and epicortical neural probes

    Science.gov (United States)

    Goshi, Noah; Castagnola, Elisa; Vomero, Maria; Gueli, Calogero; Cea, Claudia; Zucchini, Elena; Bjanes, David; Maggiolini, Emma; Moritz, Chet; Kassegne, Sam; Ricci, Davide; Fadiga, Luciano

    2018-06-01

    We report on a novel technology for microfabricating 3D origami-styled micro electro-mechanical systems (MEMS) structures with glassy carbon (GC) features and a supporting polymer substrate. GC MEMS devices that open to form 3D microstructures are microfabricated from GC patterns that are made through pyrolysis of polymer precursors on high-temperature resisting substrates like silicon or quartz and then transferring the patterned devices to a flexible substrate like polyimide followed by deposition of an insulation layer. The devices on flexible substrate are then folded into 3D form in an origami-fashion. These 3D MEMS devices have tunable mechanical properties that are achieved by selectively varying the thickness of the polymeric substrate and insulation layers at any desired location. This technology opens new possibilities by enabling microfabrication of a variety of 3D GC MEMS structures suited to applications ranging from biochemical sensing to implantable microelectrode arrays. As a demonstration of the technology, a neural signal recording microelectrode array platform that integrates both surface (cortical) and depth (intracortical) GC microelectrodes onto a single flexible thin-film device is introduced. When the device is unfurled, a pre-shaped shank of polyimide automatically comes off the substrate and forms the penetrating part of the device in a 3D fashion. With the advantage of being highly reproducible and batch-fabricated, the device introduced here allows for simultaneous recording of electrophysiological signals from both the brain surface (electrocorticography—ECoG) and depth (single neuron). Our device, therefore, has the potential to elucidate the roles of underlying neurons on the different components of µECoG signals. For in vivo validation of the design capabilities, the recording sites are coated with a poly(3,4-ethylenedioxythiophene)—polystyrene sulfonate—carbon nanotube composite, to improve the electrical conductivity of the

  8. Recurrent Neural Network Approach Based on the Integral Representation of the Drazin Inverse.

    Science.gov (United States)

    Stanimirović, Predrag S; Živković, Ivan S; Wei, Yimin

    2015-10-01

    In this letter, we present the dynamical equation and corresponding artificial recurrent neural network for computing the Drazin inverse for arbitrary square real matrix, without any restriction on its eigenvalues. Conditions that ensure the stability of the defined recurrent neural network as well as its convergence toward the Drazin inverse are considered. Several illustrative examples present the results of computer simulations.

  9. Integration and long distance axonal regeneration in the central nervous system from transplanted primitive neural stem cells.

    Science.gov (United States)

    Zhao, Jiagang; Sun, Woong; Cho, Hyo Min; Ouyang, Hong; Li, Wenlin; Lin, Ying; Do, Jiun; Zhang, Liangfang; Ding, Sheng; Liu, Yizhi; Lu, Paul; Zhang, Kang

    2013-01-04

    Spinal cord injury (SCI) results in devastating motor and sensory deficits secondary to disrupted neuronal circuits and poor regenerative potential. Efforts to promote regeneration through cell extrinsic and intrinsic manipulations have met with limited success. Stem cells represent an as yet unrealized therapy in SCI. Recently, we identified novel culture methods to induce and maintain primitive neural stem cells (pNSCs) from human embryonic stem cells. We tested whether transplanted human pNSCs can integrate into the CNS of the developing chick neural tube and injured adult rat spinal cord. Following injection of pNSCs into the developing chick CNS, pNSCs integrated into the dorsal aspects of the neural tube, forming cell clusters that spontaneously differentiated into neurons. Furthermore, following transplantation of pNSCs into the lesioned rat spinal cord, grafted pNSCs survived, differentiated into neurons, and extended long distance axons through the scar tissue at the graft-host interface and into the host spinal cord to form terminal-like structures near host spinal neurons. Together, these findings suggest that pNSCs derived from human embryonic stem cells differentiate into neuronal cell types with the potential to extend axons that associate with circuits of the CNS and, more importantly, provide new insights into CNS integration and axonal regeneration, offering hope for repair in SCI.

  10. Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

    Science.gov (United States)

    Greenwald, Elliot; Masters, Matthew R; Thakor, Nitish V

    2016-01-01

    A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.

  11. Optimal Plant Growth in Smart Farm Hydroponics System using the Integration of Wireless Sensor Networks into Internet of Things

    Directory of Open Access Journals (Sweden)

    Nathaphon Boonnam

    2017-07-01

    Full Text Available Greenhouse cultivation is easy to keep up and control important factors such as light, temperature, and humidity. Using of sensors and actuators in the greenhouse to capture different values allows for the control of the equipment, it can also be optimized for growth at optimal temperature and humidity of various crops planted. We use wireless sensor networks’ system by sending results to the cloud service, monitoring values, and devices’s controlling via smart phone. The results of this study are useful for growing crops not only in technical parts, but also in physical part; it was evaluated by questionnaire using technology acceptance model.

  12. Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

    Science.gov (United States)

    Lo, Ching F.

    1999-01-01

    The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

  13. Security-Oriented and Load-Balancing Wireless Data Routing Game in the Integration of Advanced Metering Infrastructure Network in Smart Grid

    Energy Technology Data Exchange (ETDEWEB)

    He, Fulin; Cao, Yang; Zhang, Jun Jason; Wei, Jiaolong; Zhang, Yingchen; Muljadi, Eduard; Gao, Wenzhong

    2016-11-21

    Ensuring flexible and reliable data routing is indispensable for the integration of Advanced Metering Infrastructure (AMI) networks, we propose a secure-oriented and load-balancing wireless data routing scheme. A novel utility function is designed based on security routing scheme. Then, we model the interactive security-oriented routing strategy among meter data concentrators or smart grid meters as a mixed-strategy network formation game. Finally, such problem results in a stable probabilistic routing scheme with proposed distributed learning algorithm. One contributions is that we studied that different types of applications affect the routing selection strategy and the strategy tendency. Another contributions is that the chosen strategy of our mixed routing can adaptively to converge to a new mixed strategy Nash equilibrium (MSNE) during the learning process in the smart grid.

  14. Self-Organizing Neural Integration of Pose-Motion Features for Human Action Recognition

    Directory of Open Access Journals (Sweden)

    German Ignacio Parisi

    2015-06-01

    Full Text Available The visual recognition of complex, articulated human movements is fundamental for a wide range of artificial systems oriented towards human-robot communication, action classification, and action-driven perception. These challenging tasks may generally involve the processing of a huge amount of visual information and learning-based mechanisms for generalizing a set of training actions and classifying new samples. To operate in natural environments, a crucial property is the efficient and robust recognition of actions, also under noisy conditions caused by, for instance, systematic sensor errors and temporarily occluded persons. Studies of the mammalian visual system and its outperforming ability to process biological motion information suggest separate neural pathways for the distinct processing of pose and motion features at multiple levels and the subsequent integration of these visual cues for action perception. We present a neurobiologically-motivated approach to achieve noise-tolerant action recognition in real time. Our model consists of self-organizing Growing When Required (GWR networks that obtain progressively generalized representations of sensory inputs and learn inherent spatiotemporal dependencies. During the training, the GWR networks dynamically change their topological structure to better match the input space. We first extract pose and motion features from video sequences and then cluster actions in terms of prototypical pose-motion trajectories. Multi-cue trajectories from matching action frames are subsequently combined to provide action dynamics in the joint feature space. Reported experiments show that our approach outperforms previous results on a dataset of full-body actions captured with a depth sensor, and ranks among the best 21 results for a public benchmark of domestic daily actions.

  15. Neural associative memories for the integration of language, vision and action in an autonomous agent.

    Science.gov (United States)

    Markert, H; Kaufmann, U; Kara Kayikci, Z; Palm, G

    2009-03-01

    Language understanding is a long-standing problem in computer science. However, the human brain is capable of processing complex languages with seemingly no difficulties. This paper shows a model for language understanding using biologically plausible neural networks composed of associative memories. The model is able to deal with ambiguities on the single word and grammatical level. The language system is embedded into a robot in order to demonstrate the correct semantical understanding of the input sentences by letting the robot perform corresponding actions. For that purpose, a simple neural action planning system has been combined with neural networks for visual object recognition and visual attention control mechanisms.

  16. In Vivo Transplantation of Enteric Neural Crest Cells into Mouse Gut; Engraftment, Functional Integration and Long-Term Safety.

    Directory of Open Access Journals (Sweden)

    Julie E Cooper

    Full Text Available Enteric neuropathies are severe gastrointestinal disorders with unsatisfactory outcomes. We aimed to investigate the potential of enteric neural stem cell therapy approaches for such disorders by transplanting mouse enteric neural crest cells (ENCCs into ganglionic and aganglionic mouse gut in vivo and analysing functional integration and long-term safety.Neurospheres generated from yellow fluorescent protein (YFP expressing ENCCs selected from postnatal Wnt1-cre;R26R-YFP/YFP murine gut were transplanted into ganglionic hindgut of wild-type littermates or aganglionic hindgut of Ednrbtm1Ywa mice (lacking functional endothelin receptor type-B. Intestines were then assessed for ENCC integration and differentiation using immunohistochemistry, cell function using calcium imaging, and long-term safety using PCR to detect off-target YFP expression.YFP+ ENCCs engrafted, proliferated and differentiated into enteric neurons and glia within recipient ganglionic gut. Transplanted cells and their projections spread along the endogenous myenteric plexus to form branching networks. Electrical point stimulation of endogenous nerve fibres resulted in calcium transients (F/F0 = 1.16 ± 0.01;43 cells, n = 6 in YFP+ transplanted ENCCs (abolished with TTX. Long-term follow-up (24 months showed transplanted ENCCs did not give rise to tumours or spread to other organs (PCR negative in extraintestinal sites. In aganglionic gut ENCCs similarly spread and differentiated to form neuronal and glial networks with projections closely associated with endogenous neural networks of the transition zone.Transplanted ENCCs successfully engrafted into recipient ganglionic and aganglionic gut showing appropriate spread, localisation and, importantly, functional integration without any long-term safety issues. This study provides key support for the development and use of enteric neural stem cell therapies.

  17. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

    KAUST Repository

    Zhang, Xuesong; Liang, Faming; Yu, Beibei; Zong, Ziliang

    2011-01-01

    Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow

  18. Compact wideband CMOS receiver frontends for wireless communication

    NARCIS (Netherlands)

    Blaakmeer, S.C.

    2010-01-01

    Abstract Wireless communication is an integral part of our daily life, the mobile phone is an example of a very popular wireless communication device. A communication link consists of a transmitter, a receiver and the transmission medium, which air or vacuum for a wireless link. Part of the receiver

  19. Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID

    Science.gov (United States)

    Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

    2018-01-01

    Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm–neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS. PMID:29671822

  20. Wireless Tots

    Science.gov (United States)

    Scott, Lee-Allison

    2003-01-01

    The first wireless technology program for preschoolers was implemented in January at the Primrose School at Bentwater in Atlanta, Georgia, a new corporate school operated by Primrose School Franchising Co. The new school serves as a testing and training facility for groundbreaking educational approaches, including emerging innovations in…

  1. Wireless Technician

    Science.gov (United States)

    Tech Directions, 2011

    2011-01-01

    One of the hottest areas in technology is invisible. Wireless communications allow people to transmit voice messages, data, and other signals through the air without physically connecting senders to receivers with cables or wires. And the technology is spreading at lightning speed. Cellular phones, personal digital assistants, and wireless…

  2. Distant supervision for neural relation extraction integrated with word attention and property features.

    Science.gov (United States)

    Qu, Jianfeng; Ouyang, Dantong; Hua, Wen; Ye, Yuxin; Li, Ximing

    2018-04-01

    Distant supervision for neural relation extraction is an efficient approach to extracting massive relations with reference to plain texts. However, the existing neural methods fail to capture the critical words in sentence encoding and meanwhile lack useful sentence information for some positive training instances. To address the above issues, we propose a novel neural relation extraction model. First, we develop a word-level attention mechanism to distinguish the importance of each individual word in a sentence, increasing the attention weights for those critical words. Second, we investigate the semantic information from word embeddings of target entities, which can be developed as a supplementary feature for the extractor. Experimental results show that our model outperforms previous state-of-the-art baselines. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review.

    Science.gov (United States)

    McClelland, James L

    2013-01-01

    This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.

  4. Photonics in wireless transceivers

    International Nuclear Information System (INIS)

    Bogani, A.; Ghelfi, P.

    2013-01-01

    During the last few years, the cross-fertilization between photonics and radio systems has been helping to overcome some major limitations of the classical radio technologies, setting new paradigms, and promising improved performance and new applications with strong benefits for public communications and safety. In particular, photonics-based wireless systems, albeit still at research level, are moving toward a new generation of multifunctional systems able to manage the wireless communication with several different frequencies and protocols, even simultaneously while also realizing surveillance operations. Photonics matches the new requirements of flexibility for software-defined architectures, thanks to its ultra-wide bandwidths and ease of tunability, and guarantees low footprint and weight, thanks to integrated photonic technologies. Moreover, photonics also allows increased resolution and sensitivity by means of the inherent low phase noise of lasers. (author)

  5. Induced Neural Stem Cells Achieve Long-Term Survival and Functional Integration in the Adult Mouse Brain

    Directory of Open Access Journals (Sweden)

    Kathrin Hemmer

    2014-09-01

    Full Text Available Differentiated cells can be converted directly into multipotent neural stem cells (i.e., induced neural stem cells [iNSCs]. iNSCs offer an attractive alternative to induced pluripotent stem cell (iPSC technology with regard to regenerative therapies. Here, we show an in vivo long-term analysis of transplanted iNSCs in the adult mouse brain. iNSCs showed sound in vivo long-term survival rates without graft overgrowths. The cells displayed a neural multilineage potential with a clear bias toward astrocytes and a permanent downregulation of progenitor and cell-cycle markers, indicating that iNSCs are not predisposed to tumor formation. Furthermore, the formation of synaptic connections as well as neuronal and glial electrophysiological properties demonstrated that differentiated iNSCs migrated, functionally integrated, and interacted with the existing neuronal circuitry. We conclude that iNSC long-term transplantation is a safe procedure; moreover, it might represent an interesting tool for future personalized regenerative applications.

  6. Induced neural stem cells achieve long-term survival and functional integration in the adult mouse brain.

    Science.gov (United States)

    Hemmer, Kathrin; Zhang, Mingyue; van Wüllen, Thea; Sakalem, Marna; Tapia, Natalia; Baumuratov, Aidos; Kaltschmidt, Christian; Kaltschmidt, Barbara; Schöler, Hans R; Zhang, Weiqi; Schwamborn, Jens C

    2014-09-09

    Differentiated cells can be converted directly into multipotent neural stem cells (i.e., induced neural stem cells [iNSCs]). iNSCs offer an attractive alternative to induced pluripotent stem cell (iPSC) technology with regard to regenerative therapies. Here, we show an in vivo long-term analysis of transplanted iNSCs in the adult mouse brain. iNSCs showed sound in vivo long-term survival rates without graft overgrowths. The cells displayed a neural multilineage potential with a clear bias toward astrocytes and a permanent downregulation of progenitor and cell-cycle markers, indicating that iNSCs are not predisposed to tumor formation. Furthermore, the formation of synaptic connections as well as neuronal and glial electrophysiological properties demonstrated that differentiated iNSCs migrated, functionally integrated, and interacted with the existing neuronal circuitry. We conclude that iNSC long-term transplantation is a safe procedure; moreover, it might represent an interesting tool for future personalized regenerative applications. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Identification and integration of sensory modalities: Neural basis and relation to consciousness

    NARCIS (Netherlands)

    Pennartz, C.M.A.

    2009-01-01

    A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be

  8. Integration of hydro-climatic data and land use in neural networks for ...

    African Journals Online (AJOL)

    BEEMG

    Technology. Full Length Research ... Operating Company and Airport Development and Meteorology ... These variants of models are ... neurons. During this process the parameters of neural models are ... and the system searches through successive iterations to obtain .... quality. They also thank the various teachers who.

  9. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

    KAUST Repository

    Zhang, Xuesong

    2011-11-01

    Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework (BNN-PIS) to incorporate the uncertainties associated with parameters, inputs, and structures into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform BNNs that only consider uncertainties associated with parameters and model structures. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters shows that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of and interactions among different uncertainty sources is expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting. © 2011 Elsevier B.V.

  10. Wireless Low-Power Integrated Basal-Body-Temperature Detection Systems Using Teeth Antennas in the MedRadio Band.

    Science.gov (United States)

    Yang, Chin-Lung; Zheng, Gou-Tsun

    2015-11-20

    This study proposes using wireless low power thermal sensors for basal-body-temperature detection using frequency modulated telemetry devices. A long-term monitoring sensor requires low-power circuits including a sampling circuit and oscillator. Moreover, temperature compensated technologies are necessary because the modulated frequency might have additional frequency deviations caused by the varying temperature. The temperature compensated oscillator is composed of a ring oscillator and a controlled-steering current source with temperature compensation, so the output frequency of the oscillator does not drift with temperature variations. The chip is fabricated in a standard Taiwan Semiconductor Manufacturing Company (TSMC) 0.18-μm complementary metal oxide semiconductor (CMOS) process, and the chip area is 0.9 mm². The power consumption of the sampling amplifier is 128 µW. The power consumption of the voltage controlled oscillator (VCO) core is less than 40 µW, and the output is -3.04 dBm with a buffer stage. The output voltage of the bandgap reference circuit is 1 V. For temperature measurements, the maximum error is 0.18 °C with a standard deviation of ±0.061 °C, which is superior to the required specification of 0.1 °C.

  11. Wireless Low-Power Integrated Basal-Body-Temperature Detection Systems Using Teeth Antennas in the MedRadio Band

    Directory of Open Access Journals (Sweden)

    Chin-Lung Yang

    2015-11-01

    Full Text Available This study proposes using wireless low power thermal sensors for basal-body-temperature detection using frequency modulated telemetry devices. A long-term monitoring sensor requires low-power circuits including a sampling circuit and oscillator. Moreover, temperature compensated technologies are necessary because the modulated frequency might have additional frequency deviations caused by the varying temperature. The temperature compensated oscillator is composed of a ring oscillator and a controlled-steering current source with temperature compensation, so the output frequency of the oscillator does not drift with temperature variations. The chip is fabricated in a standard Taiwan Semiconductor Manufacturing Company (TSMC 0.18-μm complementary metal oxide semiconductor (CMOS process, and the chip area is 0.9 mm2. The power consumption of the sampling amplifier is 128 µW. The power consumption of the voltage controlled oscillator (VCO core is less than 40 µW, and the output is −3.04 dBm with a buffer stage. The output voltage of the bandgap reference circuit is 1 V. For temperature measurements, the maximum error is 0.18 °C with a standard deviation of ±0.061 °C, which is superior to the required specification of 0.1 °C.

  12. Operating Protocol and Networking Issues of a Telemedicine Platform Integrating from Wireless Home Sensors to the Hospital Information System

    Directory of Open Access Journals (Sweden)

    Massimiliano Donati

    2013-01-01

    Full Text Available Chronic heart failure (CHF is among the major causes of hospitalization for elderly citizens. Its considerable impact on patient quality of life, the resources congestion, and the related costs can be efficiently mitigated using remote wireless biosensors networks placed at patient home, able to communicate in secure way over the public Internet with the cardiology departmental Hospital Information System (HIS. In this way, physicians can monitor the situation of several patients at distance and quickly realize and act alterations in vital parameters. In this scenario, the Health@Home (H@H platform is conceived. The pool of Bluetooth sensors enables patients to daily collect vital signs at home in noninvasive fashion. A home gateway receives and processes all signals before sending them to a server node in charge of interfacing with the usual HIS. The novel concept of operating protocol (OP represents a list of actions, remotely configurable, that the domestic network has to follow (required measurements, transmissions, comparisons with personalized thresholds, etc.. The first medical tests on 30 patients (1 month allowed to verify the model, both from the patient and the medical perspective. The main evaluation metrics were usability, flexibility, and reliability of the communication from sensors to HIS.

  13. An integral term adaptive neural control of fed-batch fermentation biotechnological process; Control neuronal adaptable con termino integral para un proceso biotecnologico de fermentacion por lote alimentado

    Energy Technology Data Exchange (ETDEWEB)

    Baruch, Ieroham; Hernandez, Luis Alberto; Barrera Cortes, Josefina [Centro de Investigacion y de Estudios Avanzados, Instituto Politecnico Nacional, Mexico D.F. (Mexico)

    2005-07-15

    A nonlinear mathematical model of aerobic biotechnological process of a fed-batch fermentation system is derived using ordinary differential equations. A neurocontrol is applied using Recurrent Trainable Neural Network (RTNN) plus integral term; the first network performs an approximation of the plant's output; the second network generates the control signal so that the biomass concentration could be regulated by the nutrient influent flow rate into the bioreactor. [Spanish] Un modelo matematico no lineal de un proceso biotecnologico aerobio de un sistema de fermentacion por lote alimentado es presentado mediante ecuaciones diferenciales ordinarias. Es propuesto un control utilizando dos redes neuronales recurrentes entrenables (RNRE) con la adicion de un termino integral; la primera red representa un aproximador de la salida de la planta y la segunda genera la senal de control tal que la concentracion de la biomasa pueda ser regulada mediante la alimentacion de un flujo con nutrientes al biorreactor.

  14. Wireless body sensor networks for health-monitoring applications

    International Nuclear Information System (INIS)

    Hao, Yang; Foster, Robert

    2008-01-01

    Current wireless technologies, such as wireless body area networks and wireless personal area networks, provide promising applications in medical monitoring systems to measure specified physiological data and also provide location-based information, if required. With the increasing sophistication of wearable and implantable medical devices and their integration with wireless sensors, an ever-expanding range of therapeutic and diagnostic applications is being pursued by research and commercial organizations. This paper aims to provide a comprehensive review of recent developments in wireless sensor technology for monitoring behaviour related to human physiological responses. It presents background information on the use of wireless technology and sensors to develop a wireless physiological measurement system. A generic miniature platform and other available technologies for wireless sensors have been studied in terms of hardware and software structural requirements for a low-cost, low-power, non-invasive and unobtrusive system. (topical review)

  15. Functional integration of grafted neural stem cell-derived dopaminergic neurons monitored by optogenetics in an in vitro Parkinson model.

    Directory of Open Access Journals (Sweden)

    Jan Tønnesen

    Full Text Available Intrastriatal grafts of stem cell-derived dopamine (DA neurons induce behavioral recovery in animal models of Parkinson's disease (PD, but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral mesencephalon of tyrosine hydroxylase-GFP transgenic mice were expanded as neurospheres and transplanted into organotypic cultures of wild type mouse striatum. Differentiated GFP-labeled DA neurons in the grafts exhibited mature neuronal properties, including spontaneous firing of action potentials, presence of post-synaptic currents, and functional expression of DA D₂ autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation or inhibition of grafted cells and host neurons using channelrhodopsin-2 (ChR2 and halorhodopsin (NpHR, respectively, revealed complex, bi-directional synaptic interactions between grafted cells and host neurons and extensive synaptic connectivity within the graft. Our data demonstrate for the first time using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying behavioral recovery as well as adverse effects following stem cell-based DA cell replacement strategies in PD.

  16. Path integration of head direction: updating a packet of neural activity at the correct speed using neuronal time constants.

    Science.gov (United States)

    Walters, D M; Stringer, S M

    2010-07-01

    A key question in understanding the neural basis of path integration is how individual, spatially responsive, neurons may self-organize into networks that can, through learning, integrate velocity signals to update a continuous representation of location within an environment. It is of vital importance that this internal representation of position is updated at the correct speed, and in real time, to accurately reflect the motion of the animal. In this article, we present a biologically plausible model of velocity path integration of head direction that can solve this problem using neuronal time constants to effect natural time delays, over which associations can be learned through associative Hebbian learning rules. The model comprises a linked continuous attractor network and competitive network. In simulation, we show that the same model is able to learn two different speeds of rotation when implemented with two different values for the time constant, and without the need to alter any other model parameters. The proposed model could be extended to path integration of place in the environment, and path integration of spatial view.

  17. Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

    Directory of Open Access Journals (Sweden)

    Nguyen Kim Quoc

    2015-08-01

    Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.

  18. Autoregressive Integrated Adaptive Neural Networks Classifier for EEG-P300 Classification

    Directory of Open Access Journals (Sweden)

    Demi Soetraprawata

    2013-06-01

    Full Text Available Brain Computer Interface has a potency to be applied in mechatronics apparatus and vehicles in the future. Compared to the other techniques, EEG is the most preferred for BCI designs. In this paper, a new adaptive neural network classifier of different mental activities from EEG-based P300 signals is proposed. To overcome the over-training that is caused by noisy and non-stationary data, the EEG signals are filtered and extracted using autoregressive models before passed to the adaptive neural networks classifier. To test the improvement in the EEG classification performance with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis. The experiment results show that the all subjects achieve a classification accuracy of 100%.

  19. An Integrative Model for the Neural Mechanism of Eye Movement Desensitization and Reprocessing (EMDR)

    OpenAIRE

    Coubard, Olivier A.

    2016-01-01

    Since the seminal report by Shapiro that bilateral stimulation induces cognitive and emotional changes, twenty-six years of basic and clinical research have examined the effects of Eye Movement Desensitization and Reprocessing (EMDR) in anxiety disorders, particularly in Post-Traumatic Stress Disorder (PTSD). The present article aims at better understanding EMDR neural mechanism. I first review procedural aspects of EMDR protocol and theoretical hypothesis about EMDR effects, and develop the ...

  20. Programmable neural processing on a smartdust for brain-computer interfaces.

    Science.gov (United States)

    Yuwen Sun; Shimeng Huang; Oresko, Joseph J; Cheng, Allen C

    2010-10-01

    Brain-computer interfaces (BCIs) offer tremendous promise for improving the quality of life for disabled individuals. BCIs use spike sorting to identify the source of each neural firing. To date, spike sorting has been performed by either using off-chip analysis, which requires a wired connection penetrating the skull to a bulky external power/processing unit, or via custom application-specific integrated circuits that lack the programmability to perform different algorithms and upgrades. In this research, we propose and test the feasibility of performing on-chip, real-time spike sorting on a programmable smartdust, including feature extraction, classification, compression, and wireless transmission. A detailed power/performance tradeoff analysis using DVFS is presented. Our experimental results show that the execution time and power density meet the requirements to perform real-time spike sorting and wireless transmission on a single neural channel.

  1. How to integrate geology, biology, and modern wireless technologies to assess biotic-abiotic interactions on coastal dune systems: a new multidisciplinary approach

    Science.gov (United States)

    Sarti, Giovanni; Bertoni, Duccio; Bini, Monica; Ciccarelli, Daniela; Ribolini, Adriano; Ruocco, Matteo; Pozzebon, Alessandro; Alquini, Fernanda; Giaccari, Riccardo; Tordella, Stefano

    2014-05-01

    Coastal dune systems are arguably one of the most dynamic environments because their evolution is controlled by many factors, both natural and human-related. Hence, they are often exposed to processes leading to erosion, which in turn determine serious naturalistic and economic losses. Most recent studies carried out on different dune fields worldwide emphasized the notion that a better definition of this environment needs an approach that systematically involves several disciplines, striving to merge every data collected from any individual analyses. Therefore, a new multidisciplinary method to study coastal dune systems has been conceived in order to integrate geology, biology, and modern wireless technologies. The aim of the work is threefold: i) to check the reliability of this new approach; ii) to provide a dataset as complete as ever about the factors affecting the evolution of coastal dunes; and iii) to evaluate the influence of any biotic and abiotic factors on plant communities. The experimentation site is located along the Pisa coast within the Migliarino - S. Rossore - Massaciuccoli Regional Park, a protected area where human influence is low (Tuscany, Italy). A rectangle of 100 x 200 m containing 50 grids of 20 x 20 m was established along the coastal dune systems from the coastline to the pinewood at the landward end of the backdune area. Sampling from each grid determined grain-size analysis carried out on surface sediment samples such as geologic aspects; topographic surveys performed by means of DGPS-RTK instruments; geophysical surveys conducted with a GPR equipment, which will be matched with core drilling activities; digital image analysis of high definition pictures taken by means of a remote controlled aircraft drone flying over the study area; biological data obtained by percent cover of each vascular plant species recorded in the sampling unit. Along with geologic and biologic methodologies, this research implemented the use of informatics

  2. The Dynamics and Neural Correlates of Audio-Visual Integration Capacity as Determined by Temporal Unpredictability, Proactive Interference, and SOA.

    Directory of Open Access Journals (Sweden)

    Jonathan M P Wilbiks

    Full Text Available Over 5 experiments, we challenge the idea that the capacity of audio-visual integration need be fixed at 1 item. We observe that the conditions under which audio-visual integration is most likely to exceed 1 occur when stimulus change operates at a slow rather than fast rate of presentation and when the task is of intermediate difficulty such as when low levels of proactive interference (3 rather than 8 interfering visual presentations are combined with the temporal unpredictability of the critical frame (Experiment 2, or, high levels of proactive interference are combined with the temporal predictability of the critical frame (Experiment 4. Neural data suggest that capacity might also be determined by the quality of perceptual information entering working memory. Experiment 5 supported the proposition that audio-visual integration was at play during the previous experiments. The data are consistent with the dynamic nature usually associated with cross-modal binding, and while audio-visual integration capacity likely cannot exceed uni-modal capacity estimates, performance may be better than being able to associate only one visual stimulus with one auditory stimulus.

  3. The Dynamics and Neural Correlates of Audio-Visual Integration Capacity as Determined by Temporal Unpredictability, Proactive Interference, and SOA.

    Science.gov (United States)

    Wilbiks, Jonathan M P; Dyson, Benjamin J

    2016-01-01

    Over 5 experiments, we challenge the idea that the capacity of audio-visual integration need be fixed at 1 item. We observe that the conditions under which audio-visual integration is most likely to exceed 1 occur when stimulus change operates at a slow rather than fast rate of presentation and when the task is of intermediate difficulty such as when low levels of proactive interference (3 rather than 8 interfering visual presentations) are combined with the temporal unpredictability of the critical frame (Experiment 2), or, high levels of proactive interference are combined with the temporal predictability of the critical frame (Experiment 4). Neural data suggest that capacity might also be determined by the quality of perceptual information entering working memory. Experiment 5 supported the proposition that audio-visual integration was at play during the previous experiments. The data are consistent with the dynamic nature usually associated with cross-modal binding, and while audio-visual integration capacity likely cannot exceed uni-modal capacity estimates, performance may be better than being able to associate only one visual stimulus with one auditory stimulus.

  4. System-Level Design of a 64-Channel Low Power Neural Spike Recording Sensor.

    Science.gov (United States)

    Delgado-Restituto, Manuel; Rodriguez-Perez, Alberto; Darie, Angela; Soto-Sanchez, Cristina; Fernandez-Jover, Eduardo; Rodriguez-Vazquez, Angel

    2017-04-01

    This paper reports an integrated 64-channel neural spike recording sensor, together with all the circuitry to process and configure the channels, process the neural data, transmit via a wireless link the information and receive the required instructions. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements an auto-calibration algorithm which individually configures the transfer characteristics of the recording site. The system has two transmission modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are released. Data streams coming from the channels are serialized by the embedded digital processor. Experimental results, including in vivo measurements, show that the power consumption of the complete system is lower than 330 μW.

  5. Optimum operating conditions for a water purification process integrated to a heat transformer with energy recycling using neural network inverse

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez, J.A.; Siqueiros, J.; Juarez-Romero, D. [Centro de Investigacion en Ingenieria y Ciencias Aplicadas, Universidad Autonoma del Estado de Morelos (UAEM), Av. Universidad No. 1001, Col. Chamilpa, Cuernavaca, Morelos C.P. 62209 (Mexico); Bassam, A. [Posgrado en Ingenieria y Ciencias Aplicadas, Universidad Autonoma del Estado de Morelos (UAEM), Av. Universidad No. 1001, Col. Chamilpa, Cuernavaca, Morelos C.P. 62209 (Mexico)

    2009-04-15

    Artificial neural network inverse (ANNi) is applied to calculate the optimal operating conditions on the coefficient of performance (COP) for a water purification process integrated to an absorption heat transformer with energy recycling. An artificial neural network (ANN) model is developed to predict the COP which was increased with energy recycling. This ANN model takes into account the input and output temperatures for each one of the four components (absorber, generator, evaporator, and condenser), as well as two pressures and LiBr + H{sub 2}O concentrations. For the network, a feedforward with one hidden layer, a Levenberg-Marquardt learning algorithm, a hyperbolic tangent sigmoid transfer function and a linear transfer function were used. The best fitting training data set was obtained with three neurons in the hidden layer. On the validation data set, simulations and experimental data test were in good agreement (R > 0.99). This ANN model can be used to predict the COP when the input variables (operating conditions) are well known. However, to control the COP in the system, we developed a strategy to estimate the optimal input variables when a COP is required from ANNi. An optimization method (the Nelder-Mead simplex method) is used to fit the unknown input variable resulted from the ANNi. This methodology can be applied to control on-line the performance of the system. (author)

  6. Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

    Directory of Open Access Journals (Sweden)

    Jan Hahne

    2017-05-01

    Full Text Available Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

  7. Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

    Science.gov (United States)

    Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

    2017-01-01

    Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

  8. An Integrative Model for the Neural Mechanism of Eye Movement Desensitization and Reprocessing (EMDR).

    Science.gov (United States)

    Coubard, Olivier A

    2016-01-01

    Since the seminal report by Shapiro that bilateral stimulation induces cognitive and emotional changes, 26 years of basic and clinical research have examined the effects of Eye Movement Desensitization and Reprocessing (EMDR) in anxiety disorders, particularly in post-traumatic stress disorder (PTSD). The present article aims at better understanding EMDR neural mechanism. I first review procedural aspects of EMDR protocol and theoretical hypothesis about EMDR effects, and develop the reasons why the scientific community is still divided about EMDR. I then slide from psychology to physiology describing eye movements/emotion interaction from the physiological viewpoint, and introduce theoretical and technical tools used in movement research to re-examine EMDR neural mechanism. Using a recent physiological model for the neuropsychological architecture of motor and cognitive control, the Threshold Interval Modulation with Early Release-Rate of rIse Deviation with Early Release (TIMER-RIDER)-model, I explore how attentional control and bilateral stimulation may participate to EMDR effects. These effects may be obtained by two processes acting in parallel: (i) activity level enhancement of attentional control component; and (ii) bilateral stimulation in any sensorimotor modality, both resulting in lower inhibition enabling dysfunctional information to be processed and anxiety to be reduced. The TIMER-RIDER model offers quantitative predictions about EMDR effects for future research about its underlying physiological mechanisms.

  9. An integrative model for the neural mechanism of Eye Movement Desensitization and Reprocessing (EMDR

    Directory of Open Access Journals (Sweden)

    Olivier A. Coubard

    2016-04-01

    Full Text Available Since the seminal report by Shapiro that bilateral stimulation induces cognitive and emotional changes, twenty-six years of basic and clinical research have examined the effects of Eye Movement Desensitization and Reprocessing (EMDR in anxiety disorders, particularly in Post-Traumatic Stress Disorder (PTSD. The present article aims at better understanding EMDR neural mechanism. I first review procedural aspects of EMDR protocol and theoretical hypothesis about EMDR effects, and develop the reasons why the scientific community is still divided about EMDR. I then slide from psychology to physiology describing eye movements/emotion interaction from the physiological viewpoint, and introduce theoretical and technical tools used in movement research to re-examine EMDR neural mechanism. Using a recent physiological model for the neuropsychological architecture of motor and cognitive control, the Threshold Interval Modulation with Early Release-Rate of rIse Deviation with Early Release – TIMER-RIDER – model, I explore how attentional control and bilateral stimulation may participate to EMDR effects. These effects may be obtained by two processes acting in parallel: (i activity level enhancement of attentional control component; and (ii bilateral stimulation in any sensorimotor modality, both resulting in lower inhibition enabling dysfunctional information to be processed and anxiety to be reduced. The TIMER-RIDER model offers quantitative predictions about EMDR effects for future research about its underlying physiological mechanisms.

  10. Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses

    International Nuclear Information System (INIS)

    Cofré, Rodrigo; Cessac, Bruno

    2013-01-01

    We investigate the effect of electric synapses (gap junctions) on collective neuronal dynamics and spike statistics in a conductance-based integrate-and-fire neural network, driven by Brownian noise, where conductances depend upon spike history. We compute explicitly the time evolution operator and show that, given the spike-history of the network and the membrane potentials at a given time, the further dynamical evolution can be written in a closed form. We show that spike train statistics is described by a Gibbs distribution whose potential can be approximated with an explicit formula, when the noise is weak. This potential form encompasses existing models for spike trains statistics analysis such as maximum entropy models or generalized linear models (GLM). We also discuss the different types of correlations: those induced by a shared stimulus and those induced by neurons interactions

  11. Toward an Interdisciplinary Understanding of Sensory Dysfunction in Autism Spectrum Disorder: An Integration of the Neural and Symptom Literatures.

    Science.gov (United States)

    Schauder, Kimberly B; Bennetto, Loisa

    2016-01-01

    Sensory processing differences have long been associated with autism spectrum disorder (ASD), and they have recently been added to the diagnostic criteria for the disorder. The focus on sensory processing in ASD research has increased substantially in the last decade. This research has been approached from two different perspectives: the first focuses on characterizing the symptoms that manifest in response to real world sensory stimulation, and the second focuses on the neural pathways and mechanisms underlying sensory processing. The purpose of this paper is to integrate the empirical literature on sensory processing in ASD from the last decade, including both studies characterizing sensory symptoms and those that investigate neural response to sensory stimuli. We begin with a discussion of definitions to clarify some of the inconsistencies in terminology that currently exist in the field. Next, the sensory symptoms literature is reviewed with a particular focus on developmental considerations and the relationship of sensory symptoms to other core features of the disorder. Then, the neuroscience literature is reviewed with a focus on methodological approaches and specific sensory modalities. Currently, these sensory symptoms and neuroscience perspectives are largely developing independently from each other leading to multiple, but separate, theories and methods, thus creating a multidisciplinary approach to sensory processing in ASD. In order to progress our understanding of sensory processing in ASD, it is now critical to integrate these two research perspectives and move toward an interdisciplinary approach. This will inevitably aid in a better understanding of the underlying biological basis of these symptoms and help realize the translational value through its application to early identification and treatment. The review ends with specific recommendations for future research to help bridge these two research perspectives in order to advance our understanding

  12. Neural networks supporting audiovisual integration for speech: A large-scale lesion study.

    Science.gov (United States)

    Hickok, Gregory; Rogalsky, Corianne; Matchin, William; Basilakos, Alexandra; Cai, Julia; Pillay, Sara; Ferrill, Michelle; Mickelsen, Soren; Anderson, Steven W; Love, Tracy; Binder, Jeffrey; Fridriksson, Julius

    2018-06-01

    Auditory and visual speech information are often strongly integrated resulting in perceptual enhancements for audiovisual (AV) speech over audio alone and sometimes yielding compelling illusory fusion percepts when AV cues are mismatched, the McGurk-MacDonald effect. Previous research has identified three candidate regions thought to be critical for AV speech integration: the posterior superior temporal sulcus (STS), early auditory cortex, and the posterior inferior frontal gyrus. We assess the causal involvement of these regions (and others) in the first large-scale (N = 100) lesion-based study of AV speech integration. Two primary findings emerged. First, behavioral performance and lesion maps for AV enhancement and illusory fusion measures indicate that classic metrics of AV speech integration are not necessarily measuring the same process. Second, lesions involving superior temporal auditory, lateral occipital visual, and multisensory zones in the STS are the most disruptive to AV speech integration. Further, when AV speech integration fails, the nature of the failure-auditory vs visual capture-can be predicted from the location of the lesions. These findings show that AV speech processing is supported by unimodal auditory and visual cortices as well as multimodal regions such as the STS at their boundary. Motor related frontal regions do not appear to play a role in AV speech integration. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Defining the neural fulcrum for chronic vagus nerve stimulation: implications for integrated cardiac control.

    Science.gov (United States)

    Ardell, Jeffrey L; Nier, Heath; Hammer, Matthew; Southerland, E Marie; Ardell, Christopher L; Beaumont, Eric; KenKnight, Bruce H; Armour, J Andrew

    2017-11-15

    The evoked cardiac response to bipolar cervical vagus nerve stimulation (VNS) reflects a dynamic interaction between afferent mediated decreases in central parasympathetic drive and suppressive effects evoked by direct stimulation of parasympathetic efferent axons to the heart. The neural fulcrum is defined as the operating point, based on frequency-amplitude-pulse width, where a null heart rate response is reproducibly evoked during the on-phase of VNS. Cardiac control, based on the principal of the neural fulcrum, can be elicited from either vagus. Beta-receptor blockade does not alter the tachycardia phase to low intensity VNS, but can increase the bradycardia to higher intensity VNS. While muscarinic cholinergic blockade prevented the VNS-induced bradycardia, clinically relevant doses of ACE inhibitors, beta-blockade and the funny channel blocker ivabradine did not alter the VNS chronotropic response. While there are qualitative differences in VNS heart control between awake and anaesthetized states, the physiological expression of the neural fulcrum is maintained. Vagus nerve stimulation (VNS) is an emerging therapy for treatment of chronic heart failure and remains a standard of therapy in patients with treatment-resistant epilepsy. The objective of this work was to characterize heart rate (HR) responses (HRRs) during the active phase of chronic VNS over a wide range of stimulation parameters in order to define optimal protocols for bidirectional bioelectronic control of the heart. In normal canines, bipolar electrodes were chronically implanted on the cervical vagosympathetic trunk bilaterally with anode cephalad to cathode (n = 8, 'cardiac' configuration) or with electrode positions reversed (n = 8, 'epilepsy' configuration). In awake state, HRRs were determined for each combination of pulse frequency (2-20 Hz), intensity (0-3.5 mA) and pulse widths (130-750 μs) over 14 months. At low intensities and higher frequency VNS, HR increased during the

  14. Conscious wireless electroretinogram and visual evoked potentials in rats.

    Directory of Open Access Journals (Sweden)

    Jason Charng

    Full Text Available The electroretinogram (ERG, retina and visual evoked potential (VEP, brain are widely used in vivo tools assaying the integrity of the visual pathway. Current recordings in preclinical models are conducted under anesthesia, which alters neural physiology and contaminates responses. We describe a conscious wireless ERG and VEP recording platform in rats. Using a novel surgical technique to chronically implant electrodes subconjunctivally on the eye and epidurally over the visual cortex, we are able to record stable and repeatable conscious ERG and VEP signals over at least 1 month. We show that the use of anaesthetics, necessary for conventional ERG and VEP measurements, alters electrophysiology recordings. Conscious visual electrophysiology improves the viability of longitudinal studies by eliminating complications associated with repeated anaesthesia. It will also enable uncontaminated assessment of drug effects, allowing the eye to be used as an effective biomarker of the central nervous system.

  15. Integrating a Storage Factor into R-NARX Neural Networks for Flood Forecasts

    Science.gov (United States)

    Chou, Po-Kai; Chang, Li-Chiu; Chang, Fi-John; Shih, Ban-Jwu

    2017-04-01

    Because mountainous terrains and steep landforms rapidly accelerate the speed of flood flow in Taiwan island, accurate multi-step-ahead inflow forecasts during typhoon events for providing reliable information benefiting the decision-makings of reservoir pre-storm release and flood-control operation are considered crucial and challenging. Various types of artificial neural networks (ANNs) have been successfully applied in hydrological fields. This study proposes a recurrent configuration of the nonlinear autoregressive with exogenous inputs (NARX) network, called R-NARX, with various effective inputs to forecast the inflows of the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, during typhoon periods. The proposed R-NARX is constructed based on the recurrent neural network (RNN), which is commonly used for modelling nonlinear dynamical systems. A large number of hourly rainfall and inflow data sets collected from 95 historical typhoon events in the last thirty years are used to train, validate and test the models. The potential input variables, including rainfall in previous time steps (one to six hours), cumulative rainfall, the storage factor and the storage function, are assessed, and various models are constructed with their reliability and accuracy being tested. We find that the previous (t-2) rainfall and cumulative rainfall are crucial inputs and the storage factor and the storage function would also improve the forecast accuracy of the models. We demonstrate that the R-NARX model not only can accurately forecast the inflows but also effectively catch the peak flow without adopting observed inflow data during the entire typhoon period. Besides, the model with the storage factor is superior to the model with the storage function, where its improvement can reach 24%. This approach can well model the rainfall-runoff process for the entire flood forecasting period without the use of observed inflow data and can provide

  16. A Neural Signature of Divisive Normalization at the Level of Multisensory Integration in Primate Cortex.

    Science.gov (United States)

    Ohshiro, Tomokazu; Angelaki, Dora E; DeAngelis, Gregory C

    2017-07-19

    Studies of multisensory integration by single neurons have traditionally emphasized empirical principles that describe nonlinear interactions between inputs from two sensory modalities. We previously proposed that many of these empirical principles could be explained by a divisive normalization mechanism operating in brain regions where multisensory integration occurs. This normalization model makes a critical diagnostic prediction: a non-preferred sensory input from one modality, which activates the neuron on its own, should suppress the response to a preferred input from another modality. We tested this prediction by recording from neurons in macaque area MSTd that integrate visual and vestibular cues regarding self-motion. We show that many MSTd neurons exhibit the diagnostic form of cross-modal suppression, whereas unisensory neurons in area MT do not. The normalization model also fits population responses better than a model based on subtractive inhibition. These findings provide strong support for a divisive normalization mechanism in multisensory integration. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Neural dynamics of audiovisual speech integration under variable listening conditions: an individual participant analysis.

    Science.gov (United States)

    Altieri, Nicholas; Wenger, Michael J

    2013-01-01

    Speech perception engages both auditory and visual modalities. Limitations of traditional accuracy-only approaches in the investigation of audiovisual speech perception have motivated the use of new methodologies. In an audiovisual speech identification task, we utilized capacity (Townsend and Nozawa, 1995), a dynamic measure of efficiency, to quantify audiovisual integration. Capacity was used to compare RT distributions from audiovisual trials to RT distributions from auditory-only and visual-only trials across three listening conditions: clear auditory signal, S/N ratio of -12 dB, and S/N ratio of -18 dB. The purpose was to obtain EEG recordings in conjunction with capacity to investigate how a late ERP co-varies with integration efficiency. Results showed efficient audiovisual integration for low auditory S/N ratios, but inefficient audiovisual integration when the auditory signal was clear. The ERP analyses showed evidence for greater audiovisual amplitude compared to the unisensory signals for lower auditory S/N ratios (higher capacity/efficiency) compared to the high S/N ratio (low capacity/inefficient integration). The data are consistent with an interactive framework of integration, where auditory recognition is influenced by speech-reading as a function of signal clarity.

  18. Analysis of a Statistical Relationship Between Dose and Error Tallies in Semiconductor Digital Integrated Circuits for Application to Radiation Monitoring Over a Wireless Sensor Network

    Science.gov (United States)

    Colins, Karen; Li, Liqian; Liu, Yu

    2017-05-01

    Mass production of widely used semiconductor digital integrated circuits (ICs) has lowered unit costs to the level of ordinary daily consumables of a few dollars. It is therefore reasonable to contemplate the idea of an engineered system that consumes unshielded low-cost ICs for the purpose of measuring gamma radiation dose. Underlying the idea is the premise of a measurable correlation between an observable property of ICs and radiation dose. Accumulation of radiation-damage-induced state changes or error events is such a property. If correct, the premise could make possible low-cost wide-area radiation dose measurement systems, instantiated as wireless sensor networks (WSNs) with unshielded consumable ICs as nodes, communicating error events to a remote base station. The premise has been investigated quantitatively for the first time in laboratory experiments and related analyses performed at the Canadian Nuclear Laboratories. State changes or error events were recorded in real time during irradiation of samples of ICs of different types in a 60Co gamma cell. From the error-event sequences, empirical distribution functions of dose were generated. The distribution functions were inverted and probabilities scaled by total error events, to yield plots of the relationship between dose and error tallies. Positive correlation was observed, and discrete functional dependence of dose quantiles on error tallies was measured, demonstrating the correctness of the premise. The idea of an engineered system that consumes unshielded low-cost ICs in a WSN, for the purpose of measuring gamma radiation dose over wide areas, is therefore tenable.

  19. In vivo transplantation of enteric neural crest cells into mouse gut; Engraftment, functional integration and long-term safety

    NARCIS (Netherlands)

    J.E. Cooper (Julie E.); C. Mccann; D. Natarajan (Dipa); S. Choudhury; W. Boesmans (Werend); J.-M. Delalande (Jean-Marie); P.V. Berghe (Pieter Vanden); A.J. Burns (Alan); N. Thapar (Nikhil)

    2016-01-01

    textabstractObjectives: Enteric neuropathies are severe gastrointestinal disorders with unsatisfactory outcomes. We aimed to investigate the potential of enteric neural stem cell therapy approaches for such disorders by transplanting mouse enteric neural crest cells (ENCCs) into ganglionic and

  20. A Neural Path Integration Mechanism for Adaptive Vector Navigation in Autonomous Agents

    DEFF Research Database (Denmark)

    Goldschmidt, Dennis; Dasgupta, Sakyasingha; Wörgötter, Florentin

    2015-01-01

    Animals show remarkable capabilities in navigating their habitat in a fully autonomous and energy-efficient way. In many species, these capabilities rely on a process called path integration, which enables them to estimate their current location and to find their way back home after long-distance...... of autonomous agent navigation, but it also reproduces various aspects of animal navigation. Finally, we discuss how the proposed path integration mechanism may be used as a scaffold for spatial learning in terms of vector navigation.......Animals show remarkable capabilities in navigating their habitat in a fully autonomous and energy-efficient way. In many species, these capabilities rely on a process called path integration, which enables them to estimate their current location and to find their way back home after long...

  1. 1 mm3-sized optical neural stimulator based on CMOS integrated photovoltaic power receiver

    Science.gov (United States)

    Tokuda, Takashi; Ishizu, Takaaki; Nattakarn, Wuthibenjaphonchai; Haruta, Makito; Noda, Toshihiko; Sasagawa, Kiyotaka; Sawan, Mohamad; Ohta, Jun

    2018-04-01

    In this work, we present a simple complementary metal-oxide semiconductor (CMOS)-controlled photovoltaic power-transfer platform that is suitable for very small (less than or equal to 1-2 mm) electronic devices such as implantable health-care devices or distributed nodes for the Internet of Things. We designed a 1.25 mm × 1.25 mm CMOS power receiver chip that contains integrated photovoltaic cells. We characterized the CMOS-integrated power receiver and successfully demonstrated blue light-emitting diode (LED) operation powered by infrared light. Then, we integrated the CMOS chip and a few off-chip components into a 1-mm3 implantable optogenetic stimulator, and demonstrated the operation of the device.

  2. Development of an artificial neural network model integrated with constitutive and FEM models

    International Nuclear Information System (INIS)

    Kong, L.X.; Hodgson, P.D.

    2000-01-01

    Although the standard error of IPANN model developed by Kong and Hodgson is lower than the constitutive model, it is found that the prediction of reaction force and torque during rolling with FEM is less accurate for IPANN model in some deformation regions. It is the summation of the product of the strain and stress in the deformation range, which contributes most to the precise prediction. An ANN model is therefore, developed in this work by integrating both the IPANN and FEM models. It is found that the integrated IPANN and FEM model is the most accurate model. (author)

  3. Neural Network Training by Integration of Adjoint Systems of Equations Forward in Time

    Science.gov (United States)

    Toomarian, Nikzad (Inventor); Barhen, Jacob (Inventor)

    1999-01-01

    A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically. it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved. but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. Tbc trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

  4. Integrated analysis of miRNA and mRNA expression in childhood medulloblastoma compared with neural stem cells.

    Directory of Open Access Journals (Sweden)

    Laura A Genovesi

    Full Text Available Medulloblastoma (MB is the most common malignant brain tumor in children and a leading cause of cancer-related mortality and morbidity. Several molecular sub-types of MB have been identified, suggesting they may arise from distinct cells of origin. Data from animal models indicate that some MB sub-types arise from multipotent cerebellar neural stem cells (NSCs. Hence, microRNA (miRNA expression profiles of primary MB samples were compared to CD133+ NSCs, aiming to identify deregulated miRNAs involved in MB pathogenesis. Expression profiling of 662 miRNAs in primary MB specimens, MB cell lines, and human CD133+ NSCs and CD133- neural progenitor cells was performed by qRT-PCR. Clustering analysis identified two distinct sub-types of MB primary specimens, reminiscent of sub-types obtained from their mRNA profiles. 21 significantly up-regulated and 12 significantly down-regulated miRNAs were identified in MB primary specimens relative to CD133+ NSCs (p<0.01. The majority of up-regulated miRNAs mapped to chromosomal regions 14q32 and 17q. Integration of the predicted targets of deregulated miRNAs with mRNA expression data from the same specimens revealed enrichment of pathways regulating neuronal migration, nervous system development and cell proliferation. Transient over-expression of a down-regulated miRNA, miR-935, resulted in significant down-regulation of three of the seven predicted miR-935 target genes at the mRNA level in a MB cell line, confirming the validity of this approach. This study represents the first integrated analysis of MB miRNA and mRNA expression profiles and is the first to compare MB miRNA expression profiles to those of CD133+ NSCs. We identified several differentially expressed miRNAs that potentially target networks of genes and signaling pathways that may be involved in the transformation of normal NSCs to brain tumor stem cells. Based on this integrative approach, our data provide an important platform for future

  5. Sustained NMDA receptor hypofunction induces compromised neural systems integration and schizophrenia-like alterations in functional brain networks.

    Science.gov (United States)

    Dawson, Neil; Xiao, Xiaolin; McDonald, Martin; Higham, Desmond J; Morris, Brian J; Pratt, Judith A

    2014-02-01

    Compromised functional integration between cerebral subsystems and dysfunctional brain network organization may underlie the neurocognitive deficits seen in psychiatric disorders. Applying topological measures from network science to brain imaging data allows the quantification of complex brain network connectivity. While this approach has recently been used to further elucidate the nature of brain dysfunction in schizophrenia, the value of applying this approach in preclinical models of psychiatric disease has not been recognized. For the first time, we apply both established and recently derived algorithms from network science (graph theory) to functional brain imaging data from rats treated subchronically with the N-methyl-D-aspartic acid (NMDA) receptor antagonist phencyclidine (PCP). We show that subchronic PCP treatment induces alterations in the global properties of functional brain networks akin to those reported in schizophrenia. Furthermore, we show that subchronic PCP treatment induces compromised functional integration between distributed neural systems, including between the prefrontal cortex and hippocampus, that have established roles in cognition through, in part, the promotion of thalamic dysconnectivity. We also show that subchronic PCP treatment promotes the functional disintegration of discrete cerebral subsystems and also alters the connectivity of neurotransmitter systems strongly implicated in schizophrenia. Therefore, we propose that sustained NMDA receptor hypofunction contributes to the pathophysiology of dysfunctional brain network organization in schizophrenia.

  6. An integrated multichannel neural recording analog front-end ASIC with area-efficient driven right leg circuit.

    Science.gov (United States)

    Tao Tang; Wang Ling Goh; Lei Yao; Jia Hao Cheong; Yuan Gao

    2017-07-01

    This paper describes an integrated multichannel neural recording analog front end (AFE) with a novel area-efficient driven right leg (DRL) circuit to improve the system common mode rejection ratio (CMRR). The proposed AFE consists of an AC-coupled low-noise programmable-gain amplifier, an area-efficient DRL block and a 10-bit SAR ADC. Compared to conventional DRL circuit, the proposed capacitor-less DRL design achieves 90% chip area reduction with enhanced CMRR performance, making it ideal for multichannel biomedical recording applications. The AFE circuit has been designed in a standard 0.18-μm CMOS process. Post-layout simulation results show that the AFE provides two gain settings of 54dB/60dB while consuming 1 μA per channel under a supply voltage of 1 V. The input-referred noise of the AFE integrated from 1 Hz to 10k Hz is only 4 μVrms and the CMRR is 110 dB.

  7. Mining Behavioral Groups in Large Wireless LANs

    OpenAIRE

    Hsu, Wei-jen; Dutta, Debojyoti; Helmy, Ahmed

    2006-01-01

    One vision of future wireless networks is that they will be deeply integrated and embedded in our lives and will involve the use of personalized mobile devices. User behavior in such networks is bound to affect the network performance. It is imperative to study and characterize the fundamental structure of wireless user behavior in order to model, manage, leverage and design efficient mobile networks. It is also important to make such study as realistic as possible, based on extensive measure...

  8. Sensor Fusion of Position- and Micro-Sensors (MEMS) integrated in a Wireless Sensor Network for movement detection in landslide areas

    Science.gov (United States)

    Arnhardt, Christian; Fernández-Steeger, Tomas; Azzam, Rafig

    2010-05-01

    Monitoring systems in landslide areas are important elements of effective Early Warning structures. Data acquisition and retrieval allows the detection of movement processes and thus is essential to generate warnings in time. Apart from the precise measurement, the reliability of data is fundamental, because outliers can trigger false alarms and leads to the loss of acceptance of such systems. For the monitoring of mass movements and their risk it is important to know, if there is movement, how fast it is and how trustworthy is the information. The joint project "Sensorbased landslide early warning system" (SLEWS) deals with these questions, and tries to improve data quality and to reduce false alarm rates, due to the combination of sensor date (sensor fusion). The project concentrates on the development of a prototypic Alarm- and Early Warning system (EWS) for different types of landslides by using various low-cost sensors, integrated in a wireless sensor network (WSN). The network consists of numerous connection points (nodes) that transfer data directly or over other nodes (Multi-Hop) in real-time to a data collection point (gateway). From there all the data packages are transmitted to a spatial data infrastructure (SDI) for further processing, analyzing and visualizing with respect to end-user specifications. The ad-hoc characteristic of the network allows the autonomous crosslinking of the nodes according to existing connections and communication strength. Due to the independent finding of new or more stable connections (self healing) a breakdown of the whole system is avoided. The bidirectional data stream enables the receiving of data from the network but also allows the transfer of commands and pointed requests into the WSN. For the detection of surface deformations in landslide areas small low-cost Micro-Electro-Mechanical-Systems (MEMS) and positionsensors from the automobile industries, different industrial applications and from other measurement

  9. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human--Robot Interaction

    Directory of Open Access Journals (Sweden)

    Tatsuro Yamada

    2016-07-01

    Full Text Available To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language--behavior relationships and the temporal patterns of interaction. Here, ``internal dynamics'' refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language--behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language--behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  10. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

    Science.gov (United States)

    Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

    2016-01-01

    To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  11. Nonassociative learning as gated neural integrator and differentiator in stimulus-response pathways

    Directory of Open Access Journals (Sweden)

    Young Daniel L

    2006-08-01

    Full Text Available Abstract Nonassociative learning is a basic neuroadaptive behavior exhibited across animal phyla and sensory modalities but its role in brain intelligence is unclear. Current literature on habituation and sensitization, the classic "dual process" of nonassociative learning, gives highly incongruous accounts between varying experimental paradigms. Here we propose a general theory of nonassociative learning featuring four base modes: habituation/primary sensitization in primary stimulus-response pathways, and desensitization/secondary sensitization in secondary stimulus-response pathways. Primary and secondary modes of nonassociative learning are distinguished by corresponding activity-dependent recall, or nonassociative gating, of neurotransmission memory. From the perspective of brain computation, nonassociative learning is a form of integral-differential calculus whereas nonassociative gating is a form of Boolean logic operator – both dynamically transforming the stimulus-response relationship. From the perspective of sensory integration, nonassociative gating provides temporal filtering whereas nonassociative learning affords low-pass, high-pass or band-pass/band-stop frequency filtering – effectively creating an intelligent sensory firewall that screens all stimuli for attention and resultant internal model adaptation and reaction. This unified framework ties together many salient characteristics of nonassociative learning and nonassociative gating and suggests a common kernel that correlates with a wide variety of sensorimotor integration behaviors such as central resetting and self-organization of sensory inputs, fail-safe sensorimotor compensation, integral-differential and gated modulation of sensorimotor feedbacks, alarm reaction, novelty detection and selective attention, as well as a variety of mental and neurological disorders such as sensorimotor instability, attention deficit hyperactivity, sensory defensiveness, autism

  12. Influence of neural monitoring during thyroid surgery on nerve integrity and postoperative vocal function.

    Science.gov (United States)

    Engelsman, A F; Warhurst, S; Fraser, S; Novakovic, D; Sidhu, S B

    2018-06-01

    Integrity of the recurrent laryngeal nerve (RLN) and the external branch of the superior laryngeal nerve (EBSLN) can be checked by intraoperative nerve monitoring (IONM) after visualization. The aim of this study was to determine the prevalence and nature of voice dysfunction following thyroid surgery with routine IONM. Thyroidectomies were performed with routine division of strap muscles and nerve monitoring to confirm integrity of the RLN and EBSLN following dissection. Patients were assessed for vocal function before surgery and at 1 and 3 months after operation. Assessment included use of the Voice Handicap Index (VHI) 10, maximum phonation time, fundamental frequency, pitch range, harmonic to noise ratio, cepstral peak prominence and smoothed cepstral peak prominence. A total of 172 nerves at risk were analysed in 102 consecutive patients undergoing elective thyroid surgery. In 23·3 per cent of EBSLNs and 0·6 per cent of RLNs nerve identification required the assistance of IONM in addition to visualization. Nerve integrity was confirmed during surgery for 98·8 per cent of EBSLNs and 98·3 per cent of RLNs. There were no differences between preoperative and postoperative VHI-10 scores. Acoustic voice assessment showed small changes in maximum phonation time at 1 and 3 months after surgery. Where there is routine division of strap muscles, thyroidectomy using nerve monitoring confirmation of RLN and EBSLN function following dissection results in no clinically significant voice change.

  13. Multi-Channel Wireless Sensor Networks: Protocols, Design and Evaluation

    OpenAIRE

    Durmaz, O.

    2009-01-01

    Pervasive systems, which are described as networked embedded systems integrated with everyday environments, are considered to have the potential to change our daily lives by creating smart surroundings and by their ubiquity, just as the Internet. In the last decade, “Wireless Sensor Networks��? have appeared as one of the real-world examples of pervasive systems by combining automated sensing, embedded computing and wireless networking into tiny embedded devices. A wireless sensor network typ...

  14. Wireless ATM : handover issues

    OpenAIRE

    Jiang, Fan; Käkölä, Timo

    1998-01-01

    Basic aspects of cellular systems and the ATM transmission technology are introduced. Wireless ATM is presented as a combination of radio ATM and mobile ATM. Radio ATM is a wireless extension of an ATM connection while mobile ATM contains the necessary extensions to ATM to support mobility. Because the current ATM technology does not support mobility, handover becomes one of the most important research issues for wireless ATM. Wireless ATM handover requirements are thus analysed. A handover s...

  15. Wireless communication technology NFC

    OpenAIRE

    MÁROVÁ, Kateřina

    2014-01-01

    Aim of this bachelor thesis is to handle the issue of new wireless communication technology NFC (Near Field Communication) including a comparison of advantages and disadvantages of NFC with other wireless technologies (Bluetooth, Wi-Fi, etc.). NFC is a technology for wireless communications between different electronic devices, one of which is typically a mobile phone. Near Field Communication allows wireless communication at very short distance by approaching or enclosing two devices and can...

  16. Wireless steganography

    Science.gov (United States)

    Agaian, Sos S.; Akopian, David; D'Souza, Sunil

    2006-02-01

    Modern mobile devices are some of the most technologically advanced devices that people use on a daily basis and the current trends in mobile phone technology indicate that tasks achievable by mobile devices will soon exceed our imagination. This paper undertakes a case study of the development and implementation of one of the first known steganography (data hiding) applications on a mobile device. Steganography is traditionally accomplished using the high processing speeds of desktop or notebook computers. With the introduction of mobile platform operating systems, there arises an opportunity for the users to develop and embed their own applications. We take advantage of this opportunity with the introduction of wireless steganographic algorithms. Thus we demonstrates that custom applications, popular with security establishments, can be developed also on mobile systems independent of both the mobile device manufacturer and mobile service provider. For example, this might be a very important feature if the communication is to be controlled exclusively by authorized personnel. The paper begins by reviewing the technological capabilities of modern mobile devices. Then we address a suitable development platform which is based on Symbian TM/Series60 TM architecture. Finally, two data hiding applications developed for Symbian TM/Series60 TM mobile phones are presented.

  17. Wireless Communication Technologies

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Wireless Communication Technologies. Since 1999, the wireless LAN has experienced a tremendous growth. Reasons: Adoption of industry standards. Interoperability testing. The progress of wireless equipments to higher data rates. Rapid decrease in product ...

  18. Neural bases of event knowledge and syntax integration in comprehension of complex sentences.

    Science.gov (United States)

    Malaia, Evie; Newman, Sharlene

    2015-01-01

    Comprehension of complex sentences is necessarily supported by both syntactic and semantic knowledge, but what linguistic factors trigger a readers' reliance on a specific system? This functional neuroimaging study orthogonally manipulated argument plausibility and verb event type to investigate cortical bases of the semantic effect on argument comprehension during reading. The data suggest that telic verbs facilitate online processing by means of consolidating the event schemas in episodic memory and by easing the computation of syntactico-thematic hierarchies in the left inferior frontal gyrus. The results demonstrate that syntax-semantics integration relies on trade-offs among a distributed network of regions for maximum comprehension efficiency.

  19. Efficient universal computing architectures for decoding neural activity.

    Directory of Open Access Journals (Sweden)

    Benjamin I Rapoport

    Full Text Available The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs. Such systems require input from tens to hundreds of brain-implanted recording electrodes in order to deliver robust and accurate performance; in serving that primary function they should also minimize power dissipation in order to avoid damaging neural tissue; and they should transmit data wirelessly in order to minimize the risk of infection associated with chronic, transcutaneous implants. Electronic architectures for brain- machine interfaces must therefore minimize size and power consumption, while maximizing the ability to compress data to be transmitted over limited-bandwidth wireless channels. Here we present a system of extremely low computational complexity, designed for real-time decoding of neural signals, and suited for highly scalable implantable systems. Our programmable architecture is an explicit implementation of a universal computing machine emulating the dynamics of a network of integrate-and-fire neurons; it requires no arithmetic operations except for counting, and decodes neural signals using only computationally inexpensive logic operations. The simplicity of this architecture does not compromise its ability to compress raw neural data by factors greater than [Formula: see text]. We describe a set of decoding algorithms based on this computational architecture, one designed to operate within an implanted system, minimizing its power consumption and data transmission bandwidth; and a complementary set of algorithms for learning, programming the decoder, and postprocessing the decoded output, designed to operate in an external, nonimplanted unit. The implementation of the implantable portion is estimated to require fewer than 5000 operations per second. A proof-of-concept, 32-channel field-programmable gate array (FPGA implementation of this portion

  20. Open-WiSe: a solar powered wireless sensor network platform.

    Science.gov (United States)

    González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

    2012-01-01

    Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

  1. Collaborative communication protocols for wireless sensor networks

    NARCIS (Netherlands)

    Dulman, S.O.; van Hoesel, L.F.W.; Nieberg, T.; Havinga, Paul J.M.

    In this document, the design of communication within a wireless sensor network is discussed. The resource limitations of such a network, especially in terms of energy, require an integrated approach for all (traditional) layers of communication. We present such an integrated, collaborative approach

  2. Integration of Adaptive Neuro-Fuzzy Inference System, Neural Networks and Geostatistical Methods for Fracture Density Modeling

    Directory of Open Access Journals (Sweden)

    Ja’fari A.

    2014-01-01

    Full Text Available Image logs provide useful information for fracture study in naturally fractured reservoir. Fracture dip, azimuth, aperture and fracture density can be obtained from image logs and have great importance in naturally fractured reservoir characterization. Imaging all fractured parts of hydrocarbon reservoirs and interpreting the results is expensive and time consuming. In this study, an improved method to make a quantitative correlation between fracture densities obtained from image logs and conventional well log data by integration of different artificial intelligence systems was proposed. The proposed method combines the results of Adaptive Neuro-Fuzzy Inference System (ANFIS and Neural Networks (NN algorithms for overall estimation of fracture density from conventional well log data. A simple averaging method was used to obtain a better result by combining results of ANFIS and NN. The algorithm applied on other wells of the field to obtain fracture density. In order to model the fracture density in the reservoir, we used variography and sequential simulation algorithms like Sequential Indicator Simulation (SIS and Truncated Gaussian Simulation (TGS. The overall algorithm applied to Asmari reservoir one of the SW Iranian oil fields. Histogram analysis applied to control the quality of the obtained models. Results of this study show that for higher number of fracture facies the TGS algorithm works better than SIS but in small number of fracture facies both algorithms provide approximately same results.

  3. A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Bangzhu Zhu

    2012-02-01

    Full Text Available Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD, genetic algorithm (GA and artificial neural network (ANN is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components are predicted using an ANN trained by GA, i.e., a GAANN model, and the final forecasting results can be obtained by the sum of these three forecasting results. For verification and testing, two main carbon future prices with different maturity in the European Climate Exchange (ECX are used to test the effectiveness of the proposed multiscale ensemble forecasting model. Empirical results obtained demonstrate that the proposed multiscale ensemble forecasting model can outperform the single random walk (RW, ARIMA, ANN and GAANN models without EMD preprocessing and the ensemble ARIMA model with EMD preprocessing.

  4. Beyond Neural Cubism: Promoting a Multidimensional View of Brain Disorders by Enhancing the Integration of Neurology and Psychiatry in Education

    Science.gov (United States)

    Taylor, Joseph J.; Williams, Nolan R.; George, Mark S.

    2014-01-01

    Cubism was an influential early 20th century art movement characterized by angular, disjointed imagery. The two-dimensional appearance of Cubist figures and objects is created through juxtaposition of angles. The authors posit that the constrained perspectives found in Cubism may also be found in the clinical classification of brain disorders. Neurological disorders are often separated from psychiatric disorders as if they stem from different organ systems. Maintaining two isolated clinical disciplines fractionalizes the brain in the same way that Pablo Picasso fractionalized figures and objects in his Cubist art. This Neural Cubism perpetuates a clinical divide that does not reflect the scope and depth of neuroscience. All brain disorders are complex and multidimensional, with aberrant circuitry and resultant psychopharmacology manifesting as altered behavior, affect, mood or cognition. Trainees should receive a multidimensional education based on modern neuroscience, not a partial education based on clinical precedent. The authors briefly outline the rationale for increasing the integration of neurology and psychiatry and discuss a nested model with which clinical neuroscientists (neurologists and psychiatrists) can approach and treat brain disorders. PMID:25340364

  5. CCNA Wireless Study Guide

    CERN Document Server

    Lammle, Todd

    2010-01-01

    A complete guide to the CCNA Wireless exam by leading networking authority Todd Lammle. The CCNA Wireless certification is the most respected entry-level certification in this rapidly growing field. Todd Lammle is the undisputed authority on networking, and this book focuses exclusively on the skills covered in this Cisco certification exam. The CCNA Wireless Study Guide joins the popular Sybex study guide family and helps network administrators advance their careers with a highly desirable certification.: The CCNA Wireless certification is the most respected entry-level wireless certification

  6. Wireless Sensing Opportunities for Aerospace Applications

    Directory of Open Access Journals (Sweden)

    William Wilson

    2008-07-01

    Full Text Available Wireless sensors and sensor networks is an emerging technology area with many applications within the aerospace industry. Integrated vehicle health monitoring (IVHM of aerospace vehicles is needed to ensure the safety of the crew and the vehicle, yet often high costs, weight, size and other constraints prevent the incorporation of instrumentation onto spacecraft. This paper presents a few of the areas such as IVHM, where new wireless sensing technology is needed on both existing vehicles as well as future spacecraft. From ground tests to inflatable structures to the International Space Station, many applications could receive benefits from small, low power, wireless sensors. This paper also highlights some of the challenges that need to overcome when implementing wireless sensor networks for aerospace vehicles.

  7. The Wireless ATM Architecture

    Directory of Open Access Journals (Sweden)

    R. Palitefka

    1998-06-01

    Full Text Available An overview of the proposed wireless ATM structure is provided. Wireless communication have been developed to a level where offered services can now be extended beyond voice and data. There are already wireless LANs, cordless systems offering data services and mobile data. Wireless LAN systems are basically planned for local, on-promises and in-house networking providing short distance radio or infrared links between computer system. The main challenge of wireless ATM is to harmonise the development of broadband wireless system with service B -ISDN/ATM and ATM LANs, and offer multimedia multiservice features for the support of time-sensitive voice communication, video, desktop multimedia applications, and LAN data traffic for the wireless user.

  8. Utah Wireless Integrated Network (UWIN)

    National Research Council Canada - National Science Library

    Anthony, S. C

    2006-01-01

    .... Ironically, the ground work for establishing and interoperable communication system nationwide is dependent upon effective human communication and coordination among policy makers, homeland security...

  9. A Survey on Cross-Layer Intrusion Detection System for Wireless ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... forwarding, and open wireless medium are the factors that make ... Wireless Sensor Network (WSN) is a kind of network that ... These tiny sensors are mainly small sized and have low ..... they were integrated to WSN for intrusion detection in ..... Anomaly Detection Techniques for Smart City Wireless Sensor.

  10. The Role of Wireless Computing Technology in the Design of Schools.

    Science.gov (United States)

    Nair, Prakash

    This document discusses integrating computers logically and affordably into a school building's infrastructure through the use of wireless technology. It begins by discussing why wireless networks using mobile computers are preferable to desktop machines in each classoom. It then explains the features of a wireless local area network (WLAN) and…

  11. Centralized optical-frequency-comb-based RF carrier generator for DWDM fiber-wireless access systems

    DEFF Research Database (Denmark)

    Pang, Xiaodan; Beltran, Marta; Sanchez, Jose

    2014-01-01

    In this paper, we report on a gigabit capacity fiber-wireless system that enables smooth integration between high-speed wireless networks and dense wavelength-division-multiplexing (DWDM) access networks. By employing a centralized optical frequency comb, both the wireline and the wireless services...

  12. Integrating the behavioral and neural dynamics of response selection in a dual-task paradigm: a dynamic neural field model of Dux et al. (2009).

    Science.gov (United States)

    Buss, Aaron T; Wifall, Tim; Hazeltine, Eliot; Spencer, John P

    2014-02-01

    People are typically slower when executing two tasks than when only performing a single task. These dual-task costs are initially robust but are reduced with practice. Dux et al. (2009) explored the neural basis of dual-task costs and learning using fMRI. Inferior frontal junction (IFJ) showed a larger hemodynamic response on dual-task trials compared with single-task trial early in learning. As dual-task costs were eliminated, dual-task hemodynamics in IFJ reduced to single-task levels. Dux and colleagues concluded that the reduction of dual-task costs is accomplished through increased efficiency of information processing in IFJ. We present a dynamic field theory of response selection that addresses two questions regarding these results. First, what mechanism leads to the reduction of dual-task costs and associated changes in hemodynamics? We show that a simple Hebbian learning mechanism is able to capture the quantitative details of learning at both the behavioral and neural levels. Second, is efficiency isolated to cognitive control areas such as IFJ, or is it also evident in sensory motor areas? To investigate this, we restrict Hebbian learning to different parts of the neural model. None of the restricted learning models showed the same reductions in dual-task costs as the unrestricted learning model, suggesting that efficiency is distributed across cognitive control and sensory motor processing systems.

  13. Chimeras in leaky integrate-and-fire neural networks: effects of reflecting connectivities

    Science.gov (United States)

    Tsigkri-DeSmedt, Nefeli Dimitra; Hizanidis, Johanne; Schöll, Eckehard; Hövel, Philipp; Provata, Astero

    2017-07-01

    The effects of attracting-nonlocal and reflecting connectivity are investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which model the exchange of electrical signals between neurons. Earlier investigations have demonstrated that repulsive-nonlocal and hierarchical network connectivity can induce complex synchronization patterns and chimera states in systems of coupled oscillators. In the LIF system we show that if the elements are nonlocally linked with positive diffusive coupling on a ring network, the system splits into a number of alternating domains. Half of these domains contain elements whose potential stays near the threshold and they are interrupted by active domains where the elements perform regular LIF oscillations. The active domains travel along the ring with constant velocity, depending on the system parameters. When we introduce reflecting coupling in LIF networks unexpected complex spatio-temporal structures arise. For relatively extensive ranges of parameter values, the system splits into two coexisting domains: one where all elements stay near the threshold and one where incoherent states develop, characterized by multi-leveled mean phase velocity profiles.

  14. Integration of Nanobots Into Neural Circuits As a Future Therapy for Treating Neurodegenerative Disorders.

    Science.gov (United States)

    Saniotis, Arthur; Henneberg, Maciej; Sawalma, Abdul-Rahman

    2018-01-01

    Recent neuroscientific research demonstrates that the human brain is becoming altered by technological devices. Improvements in biotechnologies and computer based technologies are now increasing the likelihood for the development of brain augmentation devices in the next 20 years. We have developed the idea of an "Endomyccorhizae like interface" (ELI) nanocognitive device as a new kind of future neuroprosthetic which aims to facilitate neuronal network properties in individuals with neurodegenerative disorders. The design of our ELI may overcome the problems of invasive neuroprosthetics, post-operative inflammation, and infection and neuroprosthetic degradation. The method in which our ELI is connected and integrated to neuronal networks is based on a mechanism similar to endomyccorhizae which is the oldest and most widespread form of plant symbiosis. We propose that the principle of Endomyccorhizae could be relevant for developing a crossing point between the ELI and neuronal networks. Similar to endomyccorhizae the ELI will be designed to form webs, each of which connects multiple neurons together. The ELI will function to sense action potentials and deliver it to the neurons it connects to. This is expected to compensate for neuronal loss in some neurodegenerative disorders, such as Alzheimer's disease and Parkinson's disease.

  15. Integration of Nanobots Into Neural Circuits As a Future Therapy for Treating Neurodegenerative Disorders

    Directory of Open Access Journals (Sweden)

    Arthur Saniotis

    2018-03-01

    Full Text Available Recent neuroscientific research demonstrates that the human brain is becoming altered by technological devices. Improvements in biotechnologies and computer based technologies are now increasing the likelihood for the development of brain augmentation devices in the next 20 years. We have developed the idea of an “Endomyccorhizae like interface” (ELI nanocognitive device as a new kind of future neuroprosthetic which aims to facilitate neuronal network properties in individuals with neurodegenerative disorders. The design of our ELI may overcome the problems of invasive neuroprosthetics, post-operative inflammation, and infection and neuroprosthetic degradation. The method in which our ELI is connected and integrated to neuronal networks is based on a mechanism similar to endomyccorhizae which is the oldest and most widespread form of plant symbiosis. We propose that the principle of Endomyccorhizae could be relevant for developing a crossing point between the ELI and neuronal networks. Similar to endomyccorhizae the ELI will be designed to form webs, each of which connects multiple neurons together. The ELI will function to sense action potentials and deliver it to the neurons it connects to. This is expected to compensate for neuronal loss in some neurodegenerative disorders, such as Alzheimer's disease and Parkinson's disease.

  16. Applying Fuzzy Artificial Neural Network OSPF to develop Smart ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Fuzzy Artificial Neural Network to create Smart Routing. Protocol Algorithm. ... manufactured mental aptitude strategy. The capacity to study .... Based Energy Efficiency in Wireless Sensor Networks: A Survey",. International ...

  17. Programming signal processing applications on heterogeneous wireless sensor platforms

    NARCIS (Netherlands)

    Buondonno, L.; Fortino, G.; Galzarano, S.; Giannantonio, R.; Giordano, A.; Gravina, R.; Guerrieri, A.

    2009-01-01

    This paper proposes the SPINE frameworks (SPINE1.x and SPINE2) for the programming of signal processing applications on heterogeneous wireless sensor platforms. In particular, two integrable approaches based on the proposed frameworks are described that allow to develop applications for wireless

  18. Collaborative Algortihms for Communication in Wireless Sensor Networks

    NARCIS (Netherlands)

    Nieberg, T.; Dulman, S.O.; Havinga, Paul J.M.; van Hoesel, L.F.W.; Wu Jian, W.J.

    In this paper, we present the design of the communication in a wireless sensor network. The resource limitations of a wireless sensor network, especially in terms of energy, require an integrated, and collaborative approach for the different layers of communication. In particular, energy-efficient

  19. Collaborative Algorithms for Communication in Wireless Sensor Networks

    NARCIS (Netherlands)

    Nieberg, T.; Dulman, S.O.; Havinga, Paul J.M.; van Hoesel, L.F.W.; Wu Jian, W.J.; Basten, Twan; Geilen, Marc; de Groot, Harmke

    2003-01-01

    In this paper, we present the design of the communication in a wireless sensor network. The resource limitations of a wireless sensor network, especially in terms of energy, require an integrated, and collaborative approach for the different layers of communication. In particular, energy-efficient

  20. Wireless sensor communications and internet connectivity for sensor networks

    Energy Technology Data Exchange (ETDEWEB)

    Dunbar, M. [Crossbow Technology, Inc., San Jose, CA (United States)

    2001-07-01

    A wireless sensor network architecture is an integrated hardware/software solution that has the potential to change the way sensors are used in a virtually unlimited range of industries and applications. By leveraging Bluetooth wireless technology for low-cost, short-range radio links, wireless sensor networks such as CrossNet{sup TM} enable users to create wireless sensor networks. These wireless networks can link dozens or hundreds of sensors of disparate types and brands with data acquisition/analysis systems, such as handheld devices, internet-enabled laptop or desktop PCs. The overwhelming majority of sensor applications are hard-wired at present, and since wiring is often the most time-consuming, tedious, trouble-prone and expensive aspect of sensor applications, users in many fields will find compelling reasons to adopt the wireless sensor network solution. (orig.)

  1. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    Directory of Open Access Journals (Sweden)

    Yongcheng Li

    Full Text Available Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  2. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    Science.gov (United States)

    Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  3. Energy optimization and prediction of complex petrochemical industries using an improved artificial neural network approach integrating data envelopment analysis

    International Nuclear Information System (INIS)

    Han, Yong-Ming; Geng, Zhi-Qiang; Zhu, Qun-Xiong

    2016-01-01

    Graphical abstract: This paper proposed an energy optimization and prediction of complex petrochemical industries based on a DEA-integrated ANN approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA-ANN prediction model is effectively verified by executing a linear comparison between all DMUs and the effective DMUs through the standard data source from the UCI (University of California at Irvine) repository. Finally, the proposed model is validated through an application in a complex ethylene production system of China petrochemical industry. Meanwhile, the optimization result and the prediction value are obtained to reduce energy consumption of the ethylene production system, guide ethylene production and improve energy efficiency. - Highlights: • The DEA-integrated ANN approach is proposed. • The DEA-ANN prediction model is effectively verified through the standard data source from the UCI repository. • The energy optimization and prediction framework of complex petrochemical industries based on the proposed method is obtained. • The proposed method is valid and efficient in improvement of energy efficiency in complex petrochemical plants. - Abstract: Since the complex petrochemical data have characteristics of multi-dimension, uncertainty and noise, it is difficult to accurately optimize and predict the energy usage of complex petrochemical systems. Therefore, this paper proposes a data envelopment analysis (DEA) integrated artificial neural network (ANN) approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA

  4. Finnish perspectives of wireless in healthcare.

    Science.gov (United States)

    Alasaarela, Esko

    2009-01-01

    Wireless solutions are a good choice for healthcare development in Finland. A survey of 135 experts in Finland show that (1) the competences needed for developing wireless solutions exist (2) the Finnish healthcare system is integrated enough and (3) the technology industry in this area is too weak for global marketing. The following recommendations can be concluded: (1) Cooperate internationally (2) Develop integrated solutions and health managing concepts for the important health problems (such as diabetes), (3) Harness the healthcare system to act as a test bed for new solutions and (4) Help companies to grow and take global roles.

  5. Wireless mesh networks.

    Science.gov (United States)

    Wang, Xinheng

    2008-01-01

    Wireless telemedicine using GSM and GPRS technologies can only provide low bandwidth connections, which makes it difficult to transmit images and video. Satellite or 3G wireless transmission provides greater bandwidth, but the running costs are high. Wireless networks (WLANs) appear promising, since they can supply high bandwidth at low cost. However, the WLAN technology has limitations, such as coverage. A new wireless networking technology named the wireless mesh network (WMN) overcomes some of the limitations of the WLAN. A WMN combines the characteristics of both a WLAN and ad hoc networks, thus forming an intelligent, large scale and broadband wireless network. These features are attractive for telemedicine and telecare because of the ability to provide data, voice and video communications over a large area. One successful wireless telemedicine project which uses wireless mesh technology is the Emergency Room Link (ER-LINK) in Tucson, Arizona, USA. There are three key characteristics of a WMN: self-organization, including self-management and self-healing; dynamic changes in network topology; and scalability. What we may now see is a shift from mobile communication and satellite systems for wireless telemedicine to the use of wireless networks based on mesh technology, since the latter are very attractive in terms of cost, reliability and speed.

  6. A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment.

    Directory of Open Access Journals (Sweden)

    Yongcheng Li

    Full Text Available We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning. Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.

  7. A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment.

    Science.gov (United States)

    Li, Yongcheng; Sun, Rong; Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

    2016-01-01

    We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.

  8. Optical wireless communications for micromachines

    Science.gov (United States)

    O'Brien, Dominic C.; Yuan, Wei Wen; Liu, Jing Jing; Faulkner, Grahame E.; Elston, Steve J.; Collins, Steve; Parry-Jones, Lesley A.

    2006-08-01

    A key challenge for wireless sensor networks is minimizing the energy required for network nodes to communicate with each other, and this becomes acute for self-powered devices such as 'smart dust'. Optical communications is a potentially attractive solution for such devices. The University of Oxford is currently involved in a project to build optical wireless links to smart dust. Retro-reflectors combined with liquid crystal modulators can be integrated with the micro-machine to create a low power transceiver. When illuminated from a base station a modulated beam is returned, transmitting data. Data from the base station can be transmitted using modulation of the illuminating beam and a receiver at the micro-machine. In this paper we outline the energy consumption and link budget considerations in the design of such micro-machines, and report preliminary experimental results.

  9. Ultrasonic wireless health monitoring

    Science.gov (United States)

    Petit, Lionel; Lefeuvre, Elie; Guyomar, Daniel; Richard, Claude; Guy, Philippe; Yuse, Kaori; Monnier, Thomas

    2006-03-01

    The integration of autonomous wireless elements in health monitoring network increases the reliability by suppressing power supplies and data transmission wiring. Micro-power piezoelectric generators are an attractive alternative to primary batteries which are limited by a finite amount of energy, a limited capacity retention and a short shelf life (few years). Our goal is to implement such an energy harvesting system for powering a single AWT (Autonomous Wireless Transmitter) using our SSH (Synchronized Switch Harvesting) method. Based on a non linear process of the piezoelement voltage, this SSH method optimizes the energy extraction from the mechanical vibrations. This AWT has two main functions : The generation of an identifier code by RF transmission to the central receiver and the Lamb wave generation for the health monitoring of the host structure. A damage index is derived from the variation between the transmitted wave spectrum and a reference spectrum. The same piezoelements are used for the energy harvesting function and the Lamb wave generation, thus reducing mass and cost. A micro-controller drives the energy balance and synchronizes the functions. Such an autonomous transmitter has been evaluated on a 300x50x2 mm 3 composite cantilever beam. Four 33x11x0.3 mm 3 piezoelements are used for the energy harvesting and for the wave lamb generation. A piezoelectric sensor is placed at the free end of the beam to track the transmitted Lamb wave. In this configuration, the needed energy for the RF emission is 0.1 mJ for a 1 byte-information and the Lamb wave emission requires less than 0.1mJ. The AWT can harvested an energy quantity of approximately 20 mJ (for a 1.5 Mpa lateral stress) with a 470 μF storage capacitor. This corresponds to a power density near to 6mW/cm 3. The experimental AWT energy abilities are presented and the damage detection process is discussed. Finally, some envisaged solutions are introduced for the implementation of the required data

  10. Intelligent Wireless Sensor Network

    OpenAIRE

    Saeed, Bakhtiar I.; Mehrdadi, Bruce

    2010-01-01

    In recent years, there has been significant increase in utilisation of embedded-microcontrollers in broad range of applications extending from commercial products to industrial process system monitoring. Furthermore, improvements in speed, size and power consumption of microcontrollers with added wireless capabilities has provided new generation of applications. These include versatile and\\ud low cost solutions in wireless sensor networking applications such as wireless system monitoring and ...

  11. Wireless security in mobile health.

    Science.gov (United States)

    Osunmuyiwa, Olufolabi; Ulusoy, Ali Hakan

    2012-12-01

    Mobile health (m-health) is an extremely broad term that embraces mobile communication in the health sector and data packaging. The four broad categories of wireless networks are wireless personal area network, wireless metropolitan area network, wireless wide area network, and wireless local area network. Wireless local area network is the most notable of the wireless networking tools obtainable in the health sector. Transfer of delicate and critical information on radio frequencies should be secure, and the right to use must be meticulous. This article covers the business opportunities in m-health, threats faced by wireless networks in hospitals, and methods of mitigating these threats.

  12. Toward multi-area distributed network of implanted neural interrogators

    Science.gov (United States)

    Powell, Marc P.; Hou, Xiaoxiao; Galligan, Craig; Ashe, Jeffrey; Borton, David A.

    2017-08-01

    As we aim to improve our understanding of the brain, it is critical that researchers have simultaneous multi-area, large-scale access to the brain. Information processing in the brain occurs through close and distant coupling of functional sub-domains, as opposed to within isolated single neurons. However, commercially available neural interfaces capable of sensing electrophysiology of single neurons, currently allow access to only a small, mm3 volume of cortical cells, are not scalable to recording from orders of magnitude more neurons, and leverage bulky, skull mounted hardware and cabling sensitive to relative movements of the skull and brain. In this work, we propose a system capable of recording from many individual distributed neural interrogator nodes, untethered from any external electronics. Using an array of epidural inductive coils to wirelessly power the implanted electronics, the system is intended to be agnostic to the surgical placement of any individual node. Here, we demonstrate the ability to transmit nearly 15mW of power with greater than 50% power transfer efficiency, benchtop testing of individual subcircuit system components showing successful digitization of neural signals, and wireless transmission currently supporting a data rate of 3.84Mbps. We leverage a software defined radio based RF receiver to demodulate the data which can be stored in memory for later retrieval. Finally, we introduce a packaging technology capable of isolating active electronics from the surrounding tissue while providing capability for electrical feed-through assemblies for external neural interfacing. We expect, based on the presented preliminary findings, that the system can be integrated into a platform technology for the study of the intricate interactions between cortical domains.

  13. Wireless Emulation Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Wireless Emulation Laboratory (WEL) is a researchtest bed used to investigate fundamental issues in networkscience. It is a research infrastructure that emulates...

  14. The research of nuclear experiment radiation environment wireless alarm device

    International Nuclear Information System (INIS)

    Wang Xiaoqiong; Wang Pan; Fang Fang

    2009-01-01

    This article introduces based on monolithic integrated circuit's nuclear experiment radiation environment wireless alarm device's software and hardware design. The system by G-M tube, high-pressured module, signal conditioning circuit, power source module, monolithic integrated circuit and wireless transmission module is composed. The device has low power consumption, high performance, high accuracy detection, easy maintenance, small size, simple operation, and other features, and has a broad application prospects. (authors)

  15. Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

    Science.gov (United States)

    Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

  16. Hybrid RRM Architecture for Future Wireless Networks

    DEFF Research Database (Denmark)

    Tragos, Elias; Mihovska, Albena D.; Mino, Emilio

    2007-01-01

    The concept of ubiquitous and scalable system is applied in the IST WINNER II [1] project to deliver optimum performance for different deployment scenarios from local area to wide area wireless networks. The integration of cellular and local area networks in a unique radio system will provide a g...

  17. A Remote WIRELESS Facility

    Directory of Open Access Journals (Sweden)

    Kees Uiterwijk

    2007-10-01

    Full Text Available Continuing need for available distance learning facilities has led to the development of a remote lab facility focusing on wireless technology. In the field of engineering there is a student need of gaining experience in set-up, monitoring and maintenance of 802.11A/B/G based wireless LAN environments.

  18. Warming Up to Wireless

    Science.gov (United States)

    Milner, Jacob

    2005-01-01

    In districts big and small across the U.S., students, teachers, and administrators alike have come to appreciate the benefits of wireless technology. Because the technology delivers Internet signals on airborne radio frequencies, wireless networking allows users of all portable devices to move freely on a school's campus and stay connected to the…

  19. Wireless mobile Internet security

    CERN Document Server

    Rhee, Man Young

    2013-01-01

      The mobile industry for wireless cellular services has grown at a rapid pace over the past decade. Similarly, Internet service technology has also made dramatic growth through the World Wide Web with a wire line infrastructure. Realization for complete wired/wireless mobile Internet technologies will become the future objectives for convergence of these technologies thr

  20. Wireless adiabatic power transfer

    International Nuclear Information System (INIS)

    Rangelov, A.A.; Suchowski, H.; Silberberg, Y.; Vitanov, N.V.

    2011-01-01

    Research highlights: → Efficient and robust mid-range wireless energy transfer between two coils. → The adiabatic energy transfer is analogous to adiabatic passage in quantum optics. → Wireless energy transfer is insensitive to any resonant constraints. → Wireless energy transfer is insensitive to noise in the neighborhood of the coils. - Abstract: We propose a technique for efficient mid-range wireless power transfer between two coils, by adapting the process of adiabatic passage for a coherently driven two-state quantum system to the realm of wireless energy transfer. The proposed technique is shown to be robust to noise, resonant constraints, and other interferences that exist in the neighborhood of the coils.

  1. A Streaming PCA VLSI Chip for Neural Data Compression.

    Science.gov (United States)

    Wu, Tong; Zhao, Wenfeng; Guo, Hongsun; Lim, Hubert H; Yang, Zhi

    2017-12-01

    Neural recording system miniaturization and integration with low-power wireless technologies require compressing neural data before transmission. Feature extraction is a procedure to represent data in a low-dimensional space; its integration into a recording chip can be an efficient approach to compress neural data. In this paper, we propose a streaming principal component analysis algorithm and its microchip implementation to compress multichannel local field potential (LFP) and spike data. The circuits have been designed in a 65-nm CMOS technology and occupy a silicon area of 0.06 mm. Throughout the experiments, the chip compresses LFPs by 10 at the expense of as low as 1% reconstruction errors and 144-nW/channel power consumption; for spikes, the achieved compression ratio is 25 with 8% reconstruction errors and 3.05-W/channel power consumption. In addition, the algorithm and its hardware architecture can swiftly adapt to nonstationary spiking activities, which enables efficient hardware sharing among multiple channels to support a high-channel count recorder.

  2. Enhanced robust fractional order proportional-plus-integral controller based on neural network for velocity control of permanent magnet synchronous motor.

    Science.gov (United States)

    Zhang, Bitao; Pi, YouGuo

    2013-07-01

    The traditional integer order proportional-integral-differential (IO-PID) controller is sensitive to the parameter variation or/and external load disturbance of permanent magnet synchronous motor (PMSM). And the fractional order proportional-integral-differential (FO-PID) control scheme based on robustness tuning method is proposed to enhance the robustness. But the robustness focuses on the open-loop gain variation of controlled plant. In this paper, an enhanced robust fractional order proportional-plus-integral (ERFOPI) controller based on neural network is proposed. The control law of the ERFOPI controller is acted on a fractional order implement function (FOIF) of tracking error but not tracking error directly, which, according to theory analysis, can enhance the robust performance of system. Tuning rules and approaches, based on phase margin, crossover frequency specification and robustness rejecting gain variation, are introduced to obtain the parameters of ERFOPI controller. And the neural network algorithm is used to adjust the parameter of FOIF. Simulation and experimental results show that the method proposed in this paper not only achieve favorable tracking performance, but also is robust with regard to external load disturbance and parameter variation. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  3. Identifying the Integrated Neural Networks Involved in Capsaicin-Induced Pain Using fMRI in Awake TRPV1 Knockout and Wild-Type Rats

    Directory of Open Access Journals (Sweden)

    Jason Richard Yee

    2015-02-01

    Full Text Available In the present study, we used functional MRI in awake rats to investigate the pain response that accompanies intradermal injection of capsaicin into the hindpaw. To this end, we used BOLD imaging together with a 3D segmented, annotated rat atlas and computational analysis to identify the integrated neural circuits involved in capsaicin-induced pain. The specificity of the pain response to capsaicin was tested in a transgenic model that contains a biallelic deletion of the gene encoding for the transient receptor potential cation channel subfamily V member 1 (TRPV1. Capsaicin is an exogenous ligand for the TRPV1 receptor, and in wild-type rats, activated the putative pain neural circuit. In addition, capsaicin-treated wild-type rats exhibited activation in brain regions comprising the Papez circuit and habenular system, systems that play important roles in the integration of emotional information, and learning and memory of aversive information, respectively. As expected, capsaicin administration to TRPV1-KO rats failed to elicit the robust BOLD activation pattern observed in wild-type controls. However, the intradermal injection of formalin elicited a significant activation of the putative pain pathway as represented by such areas as the anterior cingulate, somatosensory cortex, parabrachial nucleus, and periaqueductal gray. Notably, comparison of neural responses to capsaicin in wild-type versus knock-out rats uncovered evidence that capsaicin may function in an antinociceptive capacity independent of TRPV1 signaling. Our data suggest that neuroimaging of pain in awake, conscious animals has the potential to inform the neurobiological basis of full and integrated perceptions of pain.

  4. RF microwave circuit design for wireless applications

    CERN Document Server

    Rohde, Ulrich L

    2012-01-01

    Provides researchers and engineers with a complete set of modeling, design, and implementation tools for tackling the newest IC technologies Revised and completely updated, RF/Microwave Circuit Design for Wireless Applications, Second Edition is a unique, state-of-the-art guide to wireless integrated circuit design that provides researchers and engineers with a complete set of modeling, design, and implementation tools for tackling even the newest IC technologies. It emphasizes practical design solutions for high-performance devices and circuitry, incorporating ample exa

  5. Short-range wireless communication fundamentals of RF system design and application

    CERN Document Server

    Bensky, Alan

    2004-01-01

    The Complete "Tool Kit” for the Hottest Area in RF/Wireless Design!Short-range wireless-communications over distances of less than 100 meters-is the most rapidly growing segment of RF/wireless engineering. Alan Bensky is an internationally recognized expert in short-range wireless, and this new edition of his bestselling book is completely revised to cover the latest developments in this fast moving field.You'll find coverage of such cutting-edge topics as: architectural trends in RF/wireless integrated circuits compatibility and conflict issues between differen

  6. Technical Topic 3.2.2.d Bayesian and Non-Parametric Statistics: Integration of Neural Networks with Bayesian Networks for Data Fusion and Predictive Modeling

    Science.gov (United States)

    2016-05-31

    Distribution Unlimited UU UU UU UU 31-05-2016 15-Apr-2014 14-Jan-2015 Final Report: Technical Topic 3.2.2.d Bayesian and Non- parametric Statistics...of Papers published in non peer-reviewed journals: Final Report: Technical Topic 3.2.2.d Bayesian and Non- parametric Statistics: Integration of Neural...Transfer N/A Number of graduating undergraduates who achieved a 3.5 GPA to 4.0 (4.0 max scale ): Number of graduating undergraduates funded by a DoD funded

  7. Neural nets for the plausibility check of measured values in the integrated measurement and information system for the surveillance of environmental radioactivity (IMIS)

    International Nuclear Information System (INIS)

    Haase, G.

    2003-01-01

    Neural nets to the plausibility check of measured values in the ''integrated measurement and information system for the surveillance of environmental radioactivity, IMIS'' is a research project supported by the Federal Minister for the Environment, Nature Conservation and Nuclear Safety. A goal of this project was the automatic recognition of implausible measured values in the data base ORACLE, which measured values from surveillance of environmental radioactivity of most diverse environmental media contained. The conversion of this project [ 1 ] was realized by institut of logic, complexity and deduction systems of the university Karlsruhe under the direction of Professor Dr. Menzel, Dr. Martin Riedmueller and Martin Lauer. (orig.)

  8. Experiment of Wireless Sensor Network to Monitor Field Data

    Directory of Open Access Journals (Sweden)

    Kwang Sik Kim

    2009-08-01

    Full Text Available Recently the mobile wireless network has been drastically enhanced and one of the most efficient ways to realize the ubiquitous network will be to develop the converged network by integrating the mobile wireless network with other IP fixed network like NGN (Next Generation Network. So in this paper the term of the wireless ubiquitous network is used to describe this approach. In this paper, first, the wireless ubiquitous network architecture is described based on IMS which has been standardized by 3GPP (3rd Generation Partnership Program. Next, the field data collection system to match the satellite data using location information is proposed based on the concept of the wireless ubiquitous network architecture. The purpose of the proposed system is to provide more accurate analyzing method with the researchers in the remote sensing area.

  9. Wireless Sensor Networks Database: Data Management and Implementation

    Directory of Open Access Journals (Sweden)

    Ping Liu

    2014-04-01

    Full Text Available As the core application of wireless sensor network technology, Data management and processing have become the research hotspot in the new database. This article studied mainly data management in wireless sensor networks, in connection with the characteristics of the data in wireless sensor networks, discussed wireless sensor network data query, integrating technology in-depth, proposed a mobile database structure based on wireless sensor network and carried out overall design and implementation for the data management system. In order to achieve the communication rules of above routing trees, network manager uses a simple maintenance algorithm of routing trees. Design ordinary node end, server end in mobile database at gathering nodes and mobile client end that can implement the system, focus on designing query manager, storage modules and synchronous module at server end in mobile database at gathering nodes.

  10. Wireless Sensor Networks for Ambient Assisted Living

    Directory of Open Access Journals (Sweden)

    Raúl Aquino-Santos

    2013-11-01

    Full Text Available This paper introduces wireless sensor networks for Ambient Assisted Living as a proof of concept. Our workgroup has developed an arrhythmia detection algorithm that we evaluate in a closed space using a wireless sensor network to relay the information collected to where the information can be registered, monitored and analyzed to support medical decisions by healthcare providers. The prototype we developed is then evaluated using the TelosB platform. The proposed architecture considers very specific restrictions regarding the use of wireless sensor networks in clinical situations. The seamless integration of the system architecture enables both mobile node and network configuration, thus providing the versatile and robust characteristics necessary for real-time applications in medical situations. Likewise, this system architecture efficiently permits the different components of our proposed platform to interact efficiently within the parameters of this study.

  11. Security for multihop wireless networks

    CERN Document Server

    Khan, Shafiullah

    2014-01-01

    Security for Multihop Wireless Networks provides broad coverage of the security issues facing multihop wireless networks. Presenting the work of a different group of expert contributors in each chapter, it explores security in mobile ad hoc networks, wireless sensor networks, wireless mesh networks, and personal area networks.Detailing technologies and processes that can help you secure your wireless networks, the book covers cryptographic coprocessors, encryption, authentication, key management, attacks and countermeasures, secure routing, secure medium access control, intrusion detection, ep

  12. Integration of donor mesenchymal stem cell-derived neuron-like cells into host neural network after rat spinal cord transection.

    Science.gov (United States)

    Zeng, Xiang; Qiu, Xue-Cheng; Ma, Yuan-Huan; Duan, Jing-Jing; Chen, Yuan-Feng; Gu, Huai-Yu; Wang, Jun-Mei; Ling, Eng-Ang; Wu, Jin-Lang; Wu, Wutian; Zeng, Yuan-Shan

    2015-06-01

    Functional deficits following spinal cord injury (SCI) primarily attribute to loss of neural connectivity. We therefore tested if novel tissue engineering approaches could enable neural network repair that facilitates functional recovery after spinal cord transection (SCT). Rat bone marrow-derived mesenchymal stem cells (MSCs), genetically engineered to overexpress TrkC, receptor of neurotrophin-3 (NT-3), were pre-differentiated into cells carrying neuronal features via co-culture with NT-3 overproducing Schwann cells in 3-dimensional gelatin sponge (GS) scaffold for 14 days in vitro. Intra-GS formation of MSC assemblies emulating neural network (MSC-GS) were verified morphologically via electron microscopy (EM) and functionally by whole-cell patch clamp recording of spontaneous post-synaptic currents. The differentiated MSCs still partially maintained prototypic property with the expression of some mesodermal cytokines. MSC-GS or GS was then grafted acutely into a 2 mm-wide transection gap in the T9-T10 spinal cord segments of adult rats. Eight weeks later, hindlimb function of the MSC-GS-treated SCT rats was significantly improved relative to controls receiving the GS or lesion only as indicated by BBB score. The MSC-GS transplantation also significantly recovered cortical motor evoked potential (CMEP). Histologically, MSC-derived neuron-like cells maintained their synapse-like structures in vivo; they additionally formed similar connections with host neurites (i.e., mostly serotonergic fibers plus a few corticospinal axons; validated by double-labeled immuno-EM). Moreover, motor cortex electrical stimulation triggered c-fos expression in the grafted and lumbar spinal cord cells of the treated rats only. Our data suggest that MSC-derived neuron-like cells resulting from NT-3-TrkC-induced differentiation can partially integrate into transected spinal cord and this strategy should be further investigated for reconstructing disrupted neural circuits. Copyright

  13. The wireless internet explained

    CERN Document Server

    Rhoton, John

    2001-01-01

    The Wireless Internet Explained covers the full spectrum of wireless technologies from a wide range of vendors, including initiatives by Microsoft and Compaq. The Wireless Internet Explained takes a practical look at wireless technology. Rhoton explains the concepts behind the physics, and provides an overview that clarifies the convoluted set of standards heaped together under the umbrella of wireless. It then expands on these technical foundations to give a panorama of the increasingly crowded landscape of wireless product offerings. When it comes to actual implementation the book gives abundant down-to-earth advice on topics ranging from the selection and deployment of mobile devices to the extremely sensitive subject of security.Written by an expert on Internet messaging, the author of Digital Press''s successful Programmer''s Guide to Internet Mail and X.400 and SMTP: Battle of the E-mail Protocols, The Wireless Internet Explained describes and evaluates the current state of the fast-growing and crucial...

  14. Wireless rechargeable sensor networks

    CERN Document Server

    Yang, Yuanyuan

    2015-01-01

    This SpringerBrief provides a concise guide to applying wireless energy transfer techniques in traditional battery-powered sensor networks. It examines the benefits and challenges of wireless power including efficiency and reliability. The authors build a wireless rechargeable sensor networks from scratch and aim to provide perpetual network operation. Chapters cover a wide range of topics from the collection of energy information and recharge scheduling to joint design with typical sensing applications such as data gathering. Problems are approached using a natural combination of probability

  15. Wireless network pricing

    CERN Document Server

    Huang, Jianwei

    2013-01-01

    Today's wireless communications and networking practices are tightly coupled with economic considerations, to the extent that it is almost impossible to make a sound technology choice without understanding the corresponding economic implications. This book aims at providing a foundational introduction on how microeconomics, and pricing theory in particular, can help us to understand and build better wireless networks. The book can be used as lecture notes for a course in the field of network economics, or a reference book for wireless engineers and applied economists to understand how pricing

  16. An Experimentation Platform for On-Chip Integration of Analog Neural Networks: A Pathway to Trusted and Robust Analog/RF ICs.

    Science.gov (United States)

    Maliuk, Dzmitry; Makris, Yiorgos

    2015-08-01

    We discuss the design of an experimentation platform intended for prototyping low-cost analog neural networks for on-chip integration with analog/RF circuits. The objective of such integration is to support various tasks, such as self-test, self-tuning, and trust/aging monitoring, which require classification of analog measurements obtained from on-chip sensors. Particular emphasis is given to cost-efficient implementation reflected in: 1) low energy and area budgets of circuits dedicated to neural networks; 2) robust learning in presence of analog inaccuracies; and 3) long-term retention of learned functionality. Our chip consists of a reconfigurable array of synapses and neurons operating below threshold and featuring sub-μW power consumption. The synapse circuits employ dual-mode weight storage: 1) a dynamic mode, for fast bidirectional weight updates during training and 2) a nonvolatile mode, for permanent storage of learned functionality. We discuss a robust learning strategy, and we evaluate the system performance on several benchmark problems, such as the XOR2-6 and two-spirals classification tasks.

  17. Toward an Interdisciplinary Understanding of Sensory Dysfunction in Autism Spectrum Disorder: An Integration of the Neural and Symptom Literatures

    OpenAIRE

    Schauder, Kimberly B.; Bennetto, Loisa

    2016-01-01

    Sensory processing differences have long been associated with autism spectrum disorder (ASD), and they have recently been added to the diagnostic criteria for the disorder. The focus on sensory processing in ASD research has increased substantially in the last decade. This research has been approached from two different perspectives: the first focuses on characterizing the symptoms that manifest in response to real world sensory stimulation, and the second focuses on the neural pathways and m...

  18. Wireless radio a history

    CERN Document Server

    Coe, Lewis

    2006-01-01

    ""Informative...recommended""--Choice; ""interesting...a good read...well worth reading""--Contact Magazine. This history first looks at Marconi's wireless communications system and then explores its many applications, including marine radio, cellular telephones, police and military uses, television and radar. Radio collecting is also discussed, and brief biographies are provided for the major figures in the development and use of the wireless.

  19. WiMax taking wireless to the max

    CERN Document Server

    Pareek, Deepak

    2006-01-01

    With market value expected to reach 5 billion by 2007 and the endorsement of some of the biggest names in telecommunications, World Interoperability for Microwave Access (WiMAX) is poised to change the broadband wireless landscape. But how much of WiMAX's touted potential is merely hype? Now that several pre-WiMAX networks have been deployed, what are the operators saying about QoS and ROI? How and when will device manufacturers integrate WiMAX into their products? What is the business case for using WiMAX rather than any number of other established wireless alternatives?WiMAX: Taking Wireless

  20. Wireless cardiac action potential transmission with ultrasonically inserted silicon microprobes

    International Nuclear Information System (INIS)

    Shen, C J; Ramkumar, A; Lal, A; Gilmour, R F Jr

    2011-01-01

    This paper reports on the integration of ultrasonically inserted horn-shaped cardiac probes with wireless transmission of 3D cardiac action potential measurement for applications in ex vivo preparations such as monitoring the onset of ventricular fibrillation. Ultrasonically inserted silicon horn probes permit reduced penetration force during insertion, allowing silicon, a brittle material, to penetrate cardiac tissue. The probes also allow recording from multiple sites that are lithographically defined. An application-specific integrated circuit has been designed with a 40 dB amplifying stage and a frequency modulating oscillator at 95 MHz to wirelessly transmit the recorded action potentials. This ultrasonically inserted microprobe wireless system demonstrates the initial results in wireless monitoring of 3D action potential propagation, and the extraction of parameters of interest including the action potential duration and diastolic interval

  1. Wireless Networks: New Meaning to Ubiquitous Computing.

    Science.gov (United States)

    Drew, Wilfred, Jr.

    2003-01-01

    Discusses the use of wireless technology in academic libraries. Topics include wireless networks; standards (IEEE 802.11); wired versus wireless; why libraries implement wireless technology; wireless local area networks (WLANs); WLAN security; examples of wireless use at Indiana State University and Morrisville College (New York); and useful…

  2. The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

    Science.gov (United States)

    Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

    2018-06-01

    Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

  3. Application of wireless sensor network technology in logistics information system

    Science.gov (United States)

    Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

    2017-04-01

    This paper introduces the basic concepts of active RFID (WSN-ARFID) based on wireless sensor networks and analyzes the shortcomings of the existing RFID-based logistics monitoring system. Integrated wireless sensor network technology and the scrambling point of RFID technology. A new real-time logistics detection system based on WSN and RFID, a model of logistics system based on WSN-ARFID is proposed, and the feasibility of this technology applied to logistics field is analyzed.

  4. Integrating artificial neural networks and empirical correlations for the prediction of water-subcooled critical heat flux

    International Nuclear Information System (INIS)

    Mazzola, A.

    1997-01-01

    The critical heat flux (CHF) is an important parameter for the design of nuclear reactors, heat exchangers and other boiling heat transfer units. Recently, the CHF in water-subcooled flow boiling at high mass flux and subcooling has been thoroughly studied in relation to the cooling of high-heat-flux components in thermonuclear fusion reactors. Due to the specific thermal-hydraulic situation, very few of the existing correlations, originally developed for operating conditions typical of pressurized water reactors, are able to provide consistent predictions of water-subcooled-flow-boiling CHF at high heat fluxes. Therefore, alternative predicting techniques are being investigated. Among these, artificial neural networks (ANN) have the advantage of not requiring a formal model structure to fit the experimental data; however, their main drawbacks are the loss of model transparency ('black-box' character) and the lack of any indicator for evaluating accuracy and reliability of the ANN answer when 'never-seen' patterns are presented. In the present work, the prediction of CHF is approached by a hybrid system which couples a heuristic correlation with a neural network. The ANN role is to predict a datum-dependent parameter required by the analytical correlation; ; this parameter was instead set to a constant value obtained by usual best-fitting techniques when a pure analytical approach was adopted. Upper and lower boundaries can be possibly assigned to the parameter value, thus avoiding the case of unexpected and unpredictable answer failure. The present approach maintains the advantage of the analytical model analysis, and it partially overcomes the 'black-box' character typical of the straight application of ANNs because the neural network role is limited to the correlation tuning. The proposed methodology allows us to achieve accurate results and it is likely to be suitable for thermal-hydraulic and heat transfer data processing. (author)

  5. Development of fast wireless detection system for fixed offshore platform

    Science.gov (United States)

    Li, Zhigang; Yu, Yan; Jiao, Dong; Wang, Jie; Li, Zhirui; Ou, Jinping

    2011-04-01

    Offshore platforms' security is concerned since in 1950s and 1960s, and in the early 1980s some important specifications and standards are built, and all these provide technical basis of fixed platform design, construction, installation and evaluation. With the condition that more and more platforms are in serving over age, the research about the evaluation and detection technology of offshore platform has been a hotspot, especially underwater detection, and assessment method based on the finite element calculation. For fixed platform structure detection, conventional NDT methods, such as eddy current, magnetic powder, permeate, X-ray and ultrasonic, etc, are generally used. These techniques are more mature, intuitive, but underwater detection needs underwater robot, the necessary supporting tools of auxiliary equipment, and trained professional team, thus resources and cost used are considerable, installation time of test equipment is long. This project presents a new kind of fast wireless detection and damage diagnosis system for fixed offshore platform using wireless sensor networks, that is, wireless sensor nodes can be put quickly on the offshore platform, detect offshore platform structure global status by wireless communication, and then make diagnosis. This system is operated simply, suitable for offshore platform integrity states rapid assessment. The designed system consists in intelligence acquisition equipment and 8 wireless collection nodes, the whole system has 64 collection channels, namely every wireless collection node has eight 16-bit accuracy of A/D channels. Wireless collection node, integrated with vibration sensing unit, embedded low-power micro-processing unit, wireless transceiver unit, large-capacity power unit, and GPS time synchronization unit, can finish the functions such as vibration data collection, initial analysis, data storage, data wireless transmission. Intelligence acquisition equipment, integrated with high

  6. 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.

  7. Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange

    Science.gov (United States)

    Jahangoshai Rezaee, Mustafa; Jozmaleki, Mehrdad; Valipour, Mahsa

    2018-01-01

    One of the main features to invest in stock exchange companies is their financial performance. On the other hand, conventional evaluation methods such as data envelopment analysis are not only a retrospective process, but are also a process, which are incomplete and ineffective approaches to evaluate the companies in the future. To remove this problem, it is required to plan an expert system for evaluating organizations when the online data are received from stock exchange market. This paper deals with an approach for predicting the online financial performance of companies when data are received in different time's intervals. The proposed approach is based on integrating fuzzy C-means (FCM), data envelopment analysis (DEA) and artificial neural network (ANN). The classical FCM method is unable to update the number of clusters and their members when the data are changed or the new data are received. Hence, this method is developed in order to make dynamic features for the number of clusters and clusters members in classical FCM. Then, DEA is used to evaluate DMUs by using financial ratios to provide targets in neural network. Finally, the designed network is trained and prepared for predicting companies' future performance. The data on Tehran Stock Market companies for six consecutive years (2007-2012) are used to show the abilities of the proposed approach.

  8. Integrated built-in-test false and missed alarms reduction based on forward infinite impulse response & recurrent finite impulse response dynamic neural networks

    Science.gov (United States)

    Cui, Yiqian; Shi, Junyou; Wang, Zili

    2017-11-01

    Built-in tests (BITs) are widely used in mechanical systems to perform state identification, whereas the BIT false and missed alarms cause trouble to the operators or beneficiaries to make correct judgments. Artificial neural networks (ANN) are previously used for false and missed alarms identification, which has the features such as self-organizing and self-study. However, these ANN models generally do not incorporate the temporal effect of the bottom-level threshold comparison outputs and the historical temporal features are not fully considered. To improve the situation, this paper proposes a new integrated BIT design methodology by incorporating a novel type of dynamic neural networks (DNN) model. The new DNN model is termed as Forward IIR & Recurrent FIR DNN (FIRF-DNN), where its component neurons, network structures, and input/output relationships are discussed. The condition monitoring false and missed alarms reduction implementation scheme based on FIRF-DNN model is also illustrated, which is composed of three stages including model training, false and missed alarms detection, and false and missed alarms suppression. Finally, the proposed methodology is demonstrated in the application study and the experimental results are analyzed.

  9. A Wireless Implantable Switched-Capacitor Based Optogenetic Stimulating System

    Science.gov (United States)

    Lee, Hyung-Min; Kwon, Ki-Yong; Li, Wen

    2015-01-01

    This paper presents a power-efficient implantable optogenetic interface using a wireless switched-capacitor based stimulating (SCS) system. The SCS efficiently charges storage capacitors directly from an inductive link and periodically discharges them into an array of micro-LEDs, providing high instantaneous power without affecting wireless link and system supply voltage. A custom-designed computer interface in LabVIEW environment wirelessly controls stimulation parameters through the inductive link, and an optrode array enables simultaneous neural recording along with optical stimulation. The 4-channel SCS system prototype has been implemented in a 0.35-μm CMOS process and combined with the optrode array. In vivo experiments involving light-induced local field potentials verified the efficacy of the SCS system. An implantable version of the SCS system with flexible hermetic sealing is under development for chronic experiments. PMID:25570099

  10. Evolution of Heterogeneous Wireless Networks

    DEFF Research Database (Denmark)

    Zhang, Q.; Fitzek, Frank; Katz, Marcos

    2006-01-01

    Mobile and wireless content, services and networks - Short-term and long-term development trends......Mobile and wireless content, services and networks - Short-term and long-term development trends...

  11. Path integration of head direction: updating a packet of neural activity at the correct speed using axonal conduction delays.

    Science.gov (United States)

    Walters, Daniel; Stringer, Simon; Rolls, Edmund

    2013-01-01

    The head direction cell system is capable of accurately updating its current representation of head direction in the absence of visual input. This is known as the path integration of head direction. An important question is how the head direction cell system learns to perform accurate path integration of head direction. In this paper we propose a model of velocity path integration of head direction in which the natural time delay of axonal transmission between a linked continuous attractor network and competitive network acts as a timing mechanism to facilitate the correct speed of path integration. The model effectively learns a "look-up" table for the correct speed of path integration. In simulation, we show that the model is able to successfully learn two different speeds of path integration across two different axonal conduction delays, and without the need to alter any other model parameters. An implication of this model is that, by learning look-up tables for each speed of path integration, the model should exhibit a degree of robustness to damage. In simulations, we show that the speed of path integration is not significantly affected by degrading the network through removing a proportion of the cells that signal rotational velocity.

  12. Extreme-Environment Silicon-Carbide (SiC) Wireless Sensor Suite

    Science.gov (United States)

    Yang, Jie

    2015-01-01

    Phase II objectives: Develop an integrated silicon-carbide wireless sensor suite capable of in situ measurements of critical characteristics of NTP engine; Compose silicon-carbide wireless sensor suite of: Extreme-environment sensors center, Dedicated high-temperature (450 deg C) silicon-carbide electronics that provide power and signal conditioning capabilities as well as radio frequency modulation and wireless data transmission capabilities center, An onboard energy harvesting system as a power source.

  13. Optimization of visible-light optical wireless systems: Network-centric versus user-centric designs

    OpenAIRE

    Li, Xuan; Zhang, Rong; Hanzo, Lajos

    2018-01-01

    In order to counteract the explosive escalation of wireless tele-traffic, the communication spectrum has been gradually expanded from the conventional radio frequency (RF) band to the optical wireless (OW) domain. By integrating the classic RF band relying on diverse radio techniques and optical bands, the next-generation heterogeneous networks (HetNets) are expected to offer a potential solution for supporting the ever-increasing wireless tele-traffic. Owing to its abundant unlicensed spectr...

  14. Wireless Communications for Monitoring Nuclear Material Processes Part 2: Wireless In-plant Data Transmission

    International Nuclear Information System (INIS)

    Braina, F.; Goncalves, J.M.C.; Versino, C.; Heppleston, M.; Ottesen, C.; Schoeneman, B.; Tolk, K.

    2008-01-01

    The wireless transmission of data from sensors, monitoring both static and dynamic safeguards processes, is highly appealing for the simple fact that there are no wires. In a nuclear safeguards regime, this has the implied benefits of low-cost installations, versatile configurations, and the elimination of conduits to inspect. However, with the implied solutions of wireless, we are presented with a new set of problems for system implementation and operation management, in particular (1) Radio Frequency (RF) interference and (2) security in information transmission. These problems are addressable. This paper looks at the clear benefits of wireless technologies and the cautions regarding the possible pitfalls of poorly applied technology, discusses the integration of radio frequency in existing and new facilities, provides high-level considerations for information security, and reviews prospects for the future

  15. Tradeoff Analysis for Combat Service Support Wireless Communications Alternatives

    Energy Technology Data Exchange (ETDEWEB)

    Burnette, John R.; Thibodeau, Christopher C.; Greitzer, Frank L.

    2002-02-28

    As the Army moves toward more mobile and agile forces and continued sustainment of numerous high-cost legacy logistics management systems, the requirement for wireless connectivity and a wireless network to supporting organizations has become ever more critical. There are currently several Army communications initiatives underway to resolve this wireless connectivity issue. However, to fully appreciate and understand the value of these initiatives, a Tradeoff Analysis is needed. The present study seeks to identify and assess solutions. The analysis identified issues that impede Interim Brigade Combat Team (IBCT) communication system integration and outlined core requirements for sharing of logistics data between the field and Army battle command systems. Then, the analysis examined wireless communication alternatives as possible solutions for IBCT logistics communications problems. The current baseline system was compared with possible alternatives involving tactical radio systems, wireless/near term digital radio, cellular satellite, and third-generation (3G) wireless technologies. Cellular satellite and 3G wireless technologies offer clear advantages and should be considered for later IBCTs.

  16. OPTICAL WIRELESS COMMUNICATION SYSTEM

    Directory of Open Access Journals (Sweden)

    JOSHUA L.Y. CHIENG

    2016-02-01

    Full Text Available The growing demand of bandwidth in this modern internet age has been testing the existing telecommunication infrastructures around the world. With broadband speeds moving towards the region of Gbps and Tbps, many researches have begun on the development of using optical wireless technology as feasible and future methods to the current wireless technology. Unlike the existing radio frequency wireless applications, optical wireless uses electromagnetic spectrums that are unlicensed and free. With that, this project aim to understand and gain better understanding of optical wireless communication system by building an experimental and simulated model. The quality of service and system performance will be investigated and reviewed. This project employs laser diode as the propagation medium and successfully transferred audio signals as far as 15 meters. On its quality of service, results of the project model reveal that the bit error rate increases, signal-to-noise ratio and quality factor decreases as the link distance between the transmitter and receiver increases. OptiSystem was used to build the simulated model and MATLAB was used to assist signal-to-noise ratio calculations. By comparing the simulated and experimental receiver’s power output, the experimental model’s efficiency is at 66.3%. Other than the system’s performance, challenges and factors affecting the system have been investigated and discussed. Such challenges include beam divergence, misalignment and particle absorption.

  17. 199. Disrupted Integration in Early Psychosis: A Preliminary Exploration of the Relationship Between Neural Synchronization and Higher Order Cognition in a First-Episode Psychosis Sample.

    Science.gov (United States)

    Leonhardt, Bethany; Vohs, Jennifer; Lysaker, Paul; Bartolomeo, Lisa; O’Donnell, Brian; Breier, Alan

    2017-01-01

    Abstract Background: Disruptions in the ability to integrate information into complex ideas needed to make sense of and recover from psychiatric challenges are considered a core source of dysfunction in schizophrenia spectrum disorders (SSD). These disruptions are believed to take place at the level of basic brain functioning through neural synchrony and neurocognitive functioning in which information is encountered, encoded and available for memory and at the level of higher order cognition in which ideas are formed and reflected upon. In this study, we sought to explore the link of difficulties in integration at the level of basic brain functioning with integration at the level of self-reflectivity and insight in first episode patients. The role of disrupted integration has particular importance in early phases of illness, as it may impact the likelihood that an individual is able to move toward recovery. As more work is done in early intervention in SSD, it is pivotal that underlying factors that impact ability to recover are investigated. Methods: To assess the ability to integrate information at the level of basic brain function we used electroencephalography (EEG) collected using an Auditory Steady State Response (ASSR) and the Brief Assessment of Cognition in Schizophrenia (BACS). To assess integration at the level of conscious reflection we used the Metacognition Assessment Scale Abbreviated and insight we used the Scale to Assess Awareness of Mental Disorders (SUMD). Participants were 14 adults with first episode psychosis. Results: Pearson correlations were calculated to assess the relationship of EEG power across a range of frequency bands and neurocognition with MAS-A total scores and SUMD insight score. These revealed that the MAS-A total score was significantly negatively correlated with gamma activity, and was positively correlated with BACS total score. SUMD insight was significantly positively correlated with gamma activity, and negatively

  18. Ubiquitous Wireless Smart Sensing and Control

    Science.gov (United States)

    Wagner, Raymond

    2013-01-01

    Need new technologies to reliably and safely have humans interact within sensored environments (integrated user interfaces, physical and cognitive augmentation, training, and human-systems integration tools). Areas of focus include: radio frequency identification (RFID), motion tracking, wireless communication, wearable computing, adaptive training and decision support systems, and tele-operations. The challenge is developing effective, low cost/mass/volume/power integrated monitoring systems to assess and control system, environmental, and operator health; and accurately determining and controlling the physical, chemical, and biological environments of the areas and associated environmental control systems.

  19. Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

    Science.gov (United States)

    He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

    2016-03-01

    In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Reduced tract integrity of the model for social communication is a neural substrate of social communication deficits in autism spectrum disorder.

    Science.gov (United States)

    Lo, Yu-Chun; Chen, Yu-Jen; Hsu, Yung-Chin; Tseng, Wen-Yih Isaac; Gau, Susan Shur-Fen

    2017-05-01

    Autism spectrum disorder (ASD) is a neurodevelopmental disorder with social communication deficits as one of the core symptoms. Recently, a five-level model for the social communication has been proposed in which white matter tracts corresponding to each level of the model are identified. Given that the model for social communication subserves social language functions, we hypothesized that the tract integrity of the model for social communication may be reduced in ASD, and the reduction may be related to social communication deficits. Sixty-two right-handed boys with ASD and 55 typically developing (TD) boys received clinical evaluations, intelligence tests, the Social Communication Questionnaire (SCQ), and MRI scans. Generalized fractional anisotropy (GFA) was measured by diffusion spectrum imaging to indicate the microstructural integrity of the tracts for each level of the social communication model. Group difference in the tract integrity and its relationship with the SCQ subscales of social communication and social interaction were investigated. We found that the GFA values of the superior longitudinal fasciculus III (SLF III, level 1) and the frontal aslant tracts (FAT, level 2) were decreased in ASD compared to TD. Moreover, the GFA values of the SLF III and the FAT were associated with the social interaction subscale in ASD. The tract integrity of the model for social communication is reduced in ASD, and the reduction is associated with impaired social interaction. Our results support that reduced tract integrity of the model for social communication might be a neural substrate of social communication deficits in ASD. © 2016 Association for Child and Adolescent Mental Health.

  1. Experimental validation of wireless communication with chaos

    Energy Technology Data Exchange (ETDEWEB)

    Ren, Hai-Peng; Bai, Chao; Liu, Jian [Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xian University of Technology, Xian 710048 (China); Baptista, Murilo S.; Grebogi, Celso [Institute for Complex System and Mathematical Biology, SUPA, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

    2016-08-15

    The constraints of a wireless physical media, such as multi-path propagation and complex ambient noises, prevent information from being communicated at low bit error rate. Surprisingly, it has only recently been shown that, from a theoretical perspective, chaotic signals are optimal for communication. It maximises the receiver signal-to-noise performance, consequently minimizing the bit error rate. This work demonstrates numerically and experimentally that chaotic systems can in fact be used to create a reliable and efficient wireless communication system. Toward this goal, we propose an impulsive control method to generate chaotic wave signals that encode arbitrary binary information signals and an integration logic together with the match filter capable of decreasing the noise effect over a wireless channel. The experimental validation is conducted by inputting the signals generated by an electronic transmitting circuit to an electronic circuit that emulates a wireless channel, where the signals travel along three different paths. The output signal is decoded by an electronic receiver, after passing through a match filter.

  2. Wireless sensor networks principles, design and applications

    CERN Document Server

    Yang, Shuang-Hua

    2014-01-01

    Wireless Sensor Networks presents the latest practical solutions to the design issues presented in wireless-sensor-network-based systems. Novel features of the text, distributed throughout, include workable solutions, demonstration systems and case studies of the design and application of wireless sensor networks (WSNs) based on the first-hand research and development experience of the author, and the chapters on real applications: building fire safety protection; smart home automation; and logistics resource management. Case studies and applications illustrate the practical perspectives of: ·         sensor node design; ·         embedded software design; ·         routing algorithms; ·         sink node positioning; ·         co-existence with other wireless systems; ·         data fusion; ·         security; ·         indoor location tracking; ·         integrating with radio-frequency identification; and ·         In...

  3. Experimental validation of wireless communication with chaos

    International Nuclear Information System (INIS)

    Ren, Hai-Peng; Bai, Chao; Liu, Jian; Baptista, Murilo S.; Grebogi, Celso

    2016-01-01

    The constraints of a wireless physical media, such as multi-path propagation and complex ambient noises, prevent information from being communicated at low bit error rate. Surprisingly, it has only recently been shown that, from a theoretical perspective, chaotic signals are optimal for communication. It maximises the receiver signal-to-noise performance, consequently minimizing the bit error rate. This work demonstrates numerically and experimentally that chaotic systems can in fact be used to create a reliable and efficient wireless communication system. Toward this goal, we propose an impulsive control method to generate chaotic wave signals that encode arbitrary binary information signals and an integration logic together with the match filter capable of decreasing the noise effect over a wireless channel. The experimental validation is conducted by inputting the signals generated by an electronic transmitting circuit to an electronic circuit that emulates a wireless channel, where the signals travel along three different paths. The output signal is decoded by an electronic receiver, after passing through a match filter.

  4. Experimental validation of wireless communication with chaos.

    Science.gov (United States)

    Ren, Hai-Peng; Bai, Chao; Liu, Jian; Baptista, Murilo S; Grebogi, Celso

    2016-08-01

    The constraints of a wireless physical media, such as multi-path propagation and complex ambient noises, prevent information from being communicated at low bit error rate. Surprisingly, it has only recently been shown that, from a theoretical perspective, chaotic signals are optimal for communication. It maximises the receiver signal-to-noise performance, consequently minimizing the bit error rate. This work demonstrates numerically and experimentally that chaotic systems can in fact be used to create a reliable and efficient wireless communication system. Toward this goal, we propose an impulsive control method to generate chaotic wave signals that encode arbitrary binary information signals and an integration logic together with the match filter capable of decreasing the noise effect over a wireless channel. The experimental validation is conducted by inputting the signals generated by an electronic transmitting circuit to an electronic circuit that emulates a wireless channel, where the signals travel along three different paths. The output signal is decoded by an electronic receiver, after passing through a match filter.

  5. Reduction of Carbon Footprint and Energy Efficiency Improvement in Aluminum Production by Use of Novel Wireless Instrumentation Integrated with Mathematical Modeling

    Energy Technology Data Exchange (ETDEWEB)

    James W. Evans

    2012-04-11

    The work addressed the greenhouse gas emission and electrical energy consumption of the aluminum industry. The objective was to provide a means for reducing both through the application of wireless instrumentation, coupled to mathematical modeling. Worldwide the aluminum industry consumes more electrical energy than all activities in many major countries (e.g. the UK) and emits more greenhouse gasses (e.g. than France). Most of these excesses are in the 'primary production' of aluminum; that is the conversion of aluminum oxide to metal in large electrolytic cells operating at hundreds of thousands of amps. An industry-specific GHG emission has been the focus of the work. The electrolytic cells periodically, but at irregular intervals, experience an upset condition known as an 'anode effect'. During such anode effects the cells emit fluorinated hydrocarbons (PFCs, which have a high global warming potential) at a rate far greater than in normal operation. Therefore curbing anode effects will reduce GHG emissions. Prior work had indicated that the distribution of electrical current within the cell experiences significant shifts in the minutes before an anode effect. The thrust of the present work was to develop technology that could detect and report this early warning of an anode effect so that the control computer could minimize GHG emissions. A system was developed to achieve this goal and, in collaboration with Alcoa, was tested on two cells at an Alcoa plant in Malaga, Washington. The project has also pointed to the possibility of additional improvements that could result from the work. Notable among these is an improvement in efficiency that could result in an increase in cell output at little extra operating cost. Prospects for commercialization have emerged in the form of purchase orders for further installations. The work has demonstrated that a system for monitoring the current of individual anodes in an aluminum cell is practical

  6. Wireless communications resource management

    CERN Document Server

    Lee, B; Seo, H

    2009-01-01

    Wireless technologies continue to evolve to address the insatiable demand for faster response times, larger bandwidth, and reliable transmission. Yet as the industry moves toward the development of post 3G systems, engineers have consumed all the affordable physical layer technologies discovered to date. This has necessitated more intelligent and optimized utilization of available wireless resources. Wireless Communications Resource Managem ent, Lee, Park, and Seo cover all aspects of this critical topic, from the preliminary concepts and mathematical tools to detailed descriptions of all the resource management techniques. Readers will be able to more effectively leverage limited spectrum and maximize device battery power, as well as address channel loss, shadowing, and multipath fading phenomena.

  7. Wireless physical layer security

    Science.gov (United States)

    Poor, H. Vincent; Schaefer, Rafael F.

    2017-01-01

    Security in wireless networks has traditionally been considered to be an issue to be addressed separately from the physical radio transmission aspects of wireless systems. However, with the emergence of new networking architectures that are not amenable to traditional methods of secure communication such as data encryption, there has been an increase in interest in the potential of the physical properties of the radio channel itself to provide communications security. Information theory provides a natural framework for the study of this issue, and there has been considerable recent research devoted to using this framework to develop a greater understanding of the fundamental ability of the so-called physical layer to provide security in wireless networks. Moreover, this approach is also suggestive in many cases of coding techniques that can approach fundamental limits in practice and of techniques for other security tasks such as authentication. This paper provides an overview of these developments.

  8. Terabit Wireless Communication Challenges

    Science.gov (United States)

    Hwu, Shian U.

    2012-01-01

    This presentation briefly discusses a research effort on Terabit Wireless communication systems for possible space applications. Recently, terahertz (THz) technology (300-3000 GHz frequency) has attracted a great deal of interest from academia and industry. This is due to a number of interesting features of THz waves, including the nearly unlimited bandwidths available, and the non-ionizing radiation nature which does not damage human tissues and DNA with minimum health threat. Also, as millimeter-wave communication systems mature, the focus of research is, naturally, moving to the THz range. Many scientists regard THz as the last great frontier of the electromagnetic spectrum, but finding new applications outside the traditional niches of radio astronomy, Earth and planetary remote sensing, and molecular spectroscopy particularly in biomedical imaging and wireless communications has been relatively slow. Radiologists find this area of study so attractive because t-rays are non-ionizing, which suggests no harm is done to tissue or DNA. They also offer the possibility of performing spectroscopic measurements over a very wide frequency range, and can even capture signatures from liquids and solids. According to Shannon theory, the broad bandwidth of the THz frequency bands can be used for terabit-per-second (Tb/s) wireless communication systems. This enables several new applications, such as cell phones with 360 degrees autostereoscopic displays, optic-fiber replacement, and wireless Tb/s file transferring. Although THz technology could satisfy the demand for an extremely high data rate, a number of technical challenges need to be overcome before its development. This presentation provides an overview the state-of-the- art in THz wireless communication and the technical challenges for an emerging application in Terabit wireless systems. The main issue for THz wave propagation is the high atmospheric attenuation, which is dominated by water vapor absorption in the THz

  9. Wireless sensor platform

    Science.gov (United States)

    Joshi, Pooran C.; Killough, Stephen M.; Kuruganti, Phani Teja

    2017-08-08

    A wireless sensor platform and methods of manufacture are provided. The platform involves providing a plurality of wireless sensors, where each of the sensors is fabricated on flexible substrates using printing techniques and low temperature curing. Each of the sensors can include planar sensor elements and planar antennas defined using the printing and curing. Further, each of the sensors can include a communications system configured to encode the data from the sensors into a spread spectrum code sequence that is transmitted to a central computer(s) for use in monitoring an area associated with the sensors.

  10. Wireless Testbed Bonsai

    Science.gov (United States)

    2006-02-01

    wireless sensor device network, and a about 200 Stargate nodes higher-tier multi-hop peer- to-peer 802.11b wireless network. Leading up to the full ExScal...deployment, we conducted spatial scaling tests on our higher-tier protocols on a 7 × 7 grid of Stargates nodes 45m and with 90m separations respectively...onW and its scaled version W̃ . III. EXPERIMENTAL SETUP Description of Kansei testbed. A stargate is a single board linux-based computer [7]. It uses a

  11. Wireless telecommunication systems

    CERN Document Server

    Terré, Michel; Vivier, Emmanuelle

    2013-01-01

    Wireless telecommunication systems generate a huge amount of interest. In the last two decades, these systems have experienced at least three major technological leaps, and it has become impossible to imagine how society was organized without them. In this book, we propose a macroscopic approach on wireless systems, and aim at answering key questions about power, data rates, multiple access, cellular engineering and access networks architectures.We present a series of solved problems, whose objective is to establish the main elements of a global link budget in several radiocommunicati

  12. Pervasive wireless environments

    CERN Document Server

    Yang, Jie; Trappe, Wade; Cheng, Jerry

    2014-01-01

    This Springer Brief provides a new approach to prevent user spoofing by using the physical properties associated with wireless transmissions to detect the presence of user spoofing. The most common method, applying cryptographic authentication, requires additional management and computational power that cannot be deployed consistently. The authors present the new approach by offering a summary of the recent research and exploring the benefits and potential challenges of this method. This brief discusses the feasibility of launching user spoofing attacks and their impact on the wireless and sen

  13. Wireless optical telecommunications

    CERN Document Server

    Bouchet, Olivier

    2013-01-01

    Wireless optical communication refers to communication based on the unguided propagation of optical waves. The past 30 years have seen significant improvements in this technique - a wireless communication solution for the current millennium - that offers an alternative to radio systems; a technique that could gain attractiveness due to recent concerns regarding the potential effects of radiofrequency waves on human health.The aim of this book is to look at the free space optics that are already used for the exchange of current information; its many benefits, such as incorporating chan

  14. Sustainable wireless networks

    CERN Document Server

    Zheng, Zhongming; Xuemin

    2013-01-01

    This brief focuses on network planning and resource allocation by jointly considering cost and energy sustainability in wireless networks with sustainable energy. The characteristics of green energy and investigating existing energy-efficient green approaches for wireless networks with sustainable energy is covered in the first part of this brief. The book then addresses the random availability and capacity of the energy supply. The authors explore how to maximize the energy sustainability of the network and minimize the failure probability that the mesh access points (APs) could deplete their

  15. Data converters for wireless standards

    CERN Document Server

    Shi, Chunlei

    2002-01-01

    Wireless communication is witnessing tremendous growth with proliferation of different standards covering wide, local and personal area networks (WAN, LAN and PAN). The trends call for designs that allow 1) smooth migration to future generations of wireless standards with higher data rates for multimedia applications, 2) convergence of wireless services allowing access to different standards from the same wireless device, 3) inter-continental roaming. This requires designs that work across multiple wireless standards, can easily be reused, achieve maximum hardware share at a minimum power consumption levels particularly for mobile battery-operated devices.

  16. Proceedings of Wireless Technology in the Electric Power Industry Workshop

    International Nuclear Information System (INIS)

    2001-01-01

    A one-day workshop was conducted at EPRI Charlotte to identify technology issues related to wireless technology in nuclear power plants. The meeting concluded with a roundtable discussion to determine what projects could be conducted to address opportunities and gaps in this technology; the three projects recommended for further investigation were a risk analysis, development of a technology strategy, and development of guidelines for reliable implementation of wireless technologies. The Proceedings CD includes workshop presentations in PowerPoint format. The presentations cover the following topics: (1) Wireless Project at TXU: Integration of Voice, Data, and Video; (2) Radio Upgrade Project at Public Service Electric and Gas Company (PSE and G) of New Jersey; and (3) Operational Experience with Wireless Communication at Nuclear Plants

  17. 75 FR 8400 - In the Matter of Certain Wireless Communications System Server Software, Wireless Handheld...

    Science.gov (United States)

    2010-02-24

    ... Communications System Server Software, Wireless Handheld Devices and Battery Packs; Notice of Investigation... within the United States after importation of certain wireless communications system server software... certain wireless communications system server software, wireless handheld devices or battery packs that...

  18. 75 FR 43206 - In the Matter of Certain Wireless Communications System Server Software, Wireless Handheld...

    Science.gov (United States)

    2010-07-23

    ... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-706] In the Matter of Certain Wireless Communications System Server Software, Wireless Handheld Devices and Battery Packs: Notice of Commission... United States after importation of certain wireless communications system server software, wireless...

  19. Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

    Science.gov (United States)

    Takiyama, Ken

    2017-12-01

    How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

  20. Wireless powering of e -swimmers

    Science.gov (United States)

    Roche, Jérome; Carrara, Serena; Sanchez, Julien; Lannelongue, Jérémy; Loget, Gabriel; Bouffier, Laurent; Fischer, Peer; Kuhn, Alexander

    2014-10-01

    Miniaturized structures that can move in a controlled way in solution and integrate various functionalities are attracting considerable attention due to the potential applications in fields ranging from autonomous micromotors to roving sensors. Here we introduce a concept which allows, depending on their specific design, the controlled directional motion of objects in water, combined with electronic functionalities such as the emission of light, sensing, signal conversion, treatment and transmission. The approach is based on electric field-induced polarization, which triggers different chemical reactions at the surface of the object and thereby its propulsion. This results in a localized electric current that can power in a wireless way electronic devices in water, leading to a new class of electronic swimmers (e-swimmers).