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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Optical technologies for the Internet of Things era

NASA Astrophysics Data System (ADS)

Ji, Philip N.

2017-08-01

Internet of Things (IoT) is a network of interrelated physical objects that can collect and exchange data with one another through embedded electronics, software, sensors, over the Internet. It extends Internet connectivity beyond traditional networking devices to a diverse range of physical devices and everyday things that utilize embedded technologies to communicate and interact with the external environment. The IoT brings automation and efficiency improvement to everyday life, business, and society. Therefore IoT applications and market are growing rapidly. Contrary to common belief that IoT is only related to wireless technology, optical technologies actually play important roles in the growth of IoT and contribute to its advancement. Firstly, fiber optics provides the backbone for transporting large amount of data generated by IoT network in the core , metro and access networks, and in building or in the physical object. Secondly, optical switching technologies, including all-optical switching and hybrid optical-electrical switching, enable fast and high bandwidth routing in IoT data processing center. Thirdly, optical sensing and imaging delivers comprehensive information of multiple physical phenomena through monitoring various optical properties such as intensity, phase, wavelength, frequency, polarization, and spectral distribution. In particular, fiber optic sensor has the advantages of high sensitivity, low latency, and long distributed sensing range. It is also immune to electromagnetic interference, and can be implemented in harsh environment. In this paper, the architecture of IoT is described, and the optical technologies and their applications in the IoT networks are discussed with practical examples.

Investigating Student Communities with Network Analysis of Interactions in a Physics Learning Center

ERIC Educational Resources Information Center

Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

2012-01-01

Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and…

Hierarchical structural health monitoring system combining a fiber optic spinal cord network and distributed nerve cell devices

NASA Astrophysics Data System (ADS)

Minakuchi, Shu; Tsukamoto, Haruka; Takeda, Nobuo

2009-03-01

This study proposes novel hierarchical sensing concept for detecting damages in composite structures. In the hierarchical system, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with the optical fiber network through transducing mechanisms. The distributed "sensory nerve cell" devices detect the damage, and the fiber optic "spinal cord" network gathers damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of the hierarchical sensing system thorough comparison with existing fiber optic based systems and nerve systems in the animal kingdom. Then, in order to validate the proposed sensing concept, impact damage detection system for the composite structure was proposed. The sensor devices were developed based on Comparative Vacuum Monitoring (CVM) system and the Brillouin based distributed strain sensing was utilized to gather the damage signals from the distributed devices. Finally a verification test was conducted using prototype devices. Occurrence of barely visible impact damage was successfully detected and it was clearly indicated that the hierarchical system has better repairability, higher robustness, and wider monitorable area compared to existing systems utilizing embedded optical fiber sensors.

Application of smart optical fiber sensors for structural load monitoring

NASA Astrophysics Data System (ADS)

Davies, Heddwyn; Everall, Lorna A.; Gallon, Andrew M.

2001-06-01

This paper describes a smart monitoring system, incorporating optical fiber sensing techniques, capable of providing important structural information to designers and users alike. This technology has wide industrial and commercial application in areas including aerospace, civil, maritime and automotive engineering. In order to demonstrate the capability of the sensing system it has been installed in a 35m free-standing carbon fiber yacht mast, where a complete optical network of strain and temperature sensors were embedded into a composite mast and boom during lay-up. The system was able to monitor the behavior of the composite rig through a range of handling conditions. The resulting strain information can be used by engineers to improve the structural design process. Embedded fiber optic sensors have wide ranging application for structural load monitoring. Due to their small size, optical fiber sensors can be readily embedded into composite materials. Other advantages include their immediate multiplexing capability and immunity to electro-magnetic interference. The capability of this system has been demonstrated within the maritime and industrial environment, but can be adapted for any application.

Intrinsic embedded sensors for polymeric mechatronics: flexure and force sensing.

PubMed

Jentoft, Leif P; Dollar, Aaron M; Wagner, Christopher R; Howe, Robert D

2014-02-25

While polymeric fabrication processes, including recent advances in additive manufacturing, have revolutionized manufacturing, little work has been done on effective sensing elements compatible with and embedded within polymeric structures. In this paper, we describe the development and evaluation of two important sensing modalities for embedding in polymeric mechatronic and robotic mechanisms: multi-axis flexure joint angle sensing utilizing IR phototransistors, and a small (12 mm), three-axis force sensing via embedded silicon strain gages with similar performance characteristics as an equally sized metal element based sensor.

Intrinsic Embedded Sensors for Polymeric Mechatronics: Flexure and Force Sensing

PubMed Central

Jentoft, Leif P.; Dollar, Aaron M.; Wagner, Christopher R.; Howe, Robert D.

2014-01-01

While polymeric fabrication processes, including recent advances in additive manufacturing, have revolutionized manufacturing, little work has been done on effective sensing elements compatible with and embedded within polymeric structures. In this paper, we describe the development and evaluation of two important sensing modalities for embedding in polymeric mechatronic and robotic mechanisms: multi-axis flexure joint angle sensing utilizing IR phototransistors, and a small (12 mm), three-axis force sensing via embedded silicon strain gages with similar performance characteristics as an equally sized metal element based sensor. PMID:24573310

Low Power Multi-Hop Networking Analysis in Intelligent Environments.

PubMed

Etxaniz, Josu; Aranguren, Gerardo

2017-05-19

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

Low Power Multi-Hop Networking Analysis in Intelligent Environments

PubMed Central

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide. PMID:28534847

Palo Alto Research Center - Smart Embedded Network of Sensors with an Optical Readout

ScienceCinema

Raghavan, Ajay; Sahu, Saroj; Bringans, Ross; Johnson, Noble; Kiesel, Peter; Saha, Bhaskar

2018-05-18

PARC is developing new fiber optic sensors that would be embedded into batteries to monitor and measure key internal parameters during charge and discharge cycles. Two significant problems with today's best batteries are their lack of internal monitoring capabilities and their design oversizing. The lack of monitoring interferes with the ability to identify and manage performance or safety issues as they arise, which are presently managed by very conservative design oversizing and protection approaches that result in cost inefficiencies. PARC's design combines low-cost, embedded optical battery sensors and smart algorithms to overcome challenges faced by today's best battery management systems. These advanced fiber optic sensing technologies have the potential to dramatically improve the safety, performance, and life-time of energy storage systems.

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray

2011-01-01

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems.

PubMed

Etxaniz, Josu; Aranguren, Gerardo

2017-04-30

Even though home automation is a well-known research and development area, recent technological improvements in different areas such as context recognition, sensing, wireless communications or embedded systems have boosted wireless smart homes. This paper focuses on some of those areas related to home automation. The paper draws attention to wireless communications issues on embedded systems. Specifically, the paper discusses the multi-hop networking together with Bluetooth technology and latency, as a quality of service (QoS) metric. Bluetooth is a worldwide standard that provides low power multi-hop networking. It is a radio license free technology and establishes point-to-point and point-to-multipoint links, known as piconets, or multi-hop networks, known as scatternets. This way, many Bluetooth nodes can be interconnected to deploy ambient intelligent networks. This paper introduces the research on multi-hop latency done with park and sniff low power modes of Bluetooth over the test platform developed. Besides, an empirical model is obtained to calculate the latency of Bluetooth multi-hop communications over asynchronous links when links in scatternets are always in sniff or the park mode. Smart home devices and networks designers would take advantage of the models and the estimation of the delay they provide in communications along Bluetooth multi-hop networks.

Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems

PubMed Central

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

Even though home automation is a well-known research and development area, recent technological improvements in different areas such as context recognition, sensing, wireless communications or embedded systems have boosted wireless smart homes. This paper focuses on some of those areas related to home automation. The paper draws attention to wireless communications issues on embedded systems. Specifically, the paper discusses the multi-hop networking together with Bluetooth technology and latency, as a quality of service (QoS) metric. Bluetooth is a worldwide standard that provides low power multi-hop networking. It is a radio license free technology and establishes point-to-point and point-to-multipoint links, known as piconets, or multi-hop networks, known as scatternets. This way, many Bluetooth nodes can be interconnected to deploy ambient intelligent networks. This paper introduces the research on multi-hop latency done with park and sniff low power modes of Bluetooth over the test platform developed. Besides, an empirical model is obtained to calculate the latency of Bluetooth multi-hop communications over asynchronous links when links in scatternets are always in sniff or the park mode. Smart home devices and networks designers would take advantage of the models and the estimation of the delay they provide in communications along Bluetooth multi-hop networks. PMID:28468294

Middleware Architecture for Ambient Intelligence in the Networked Home

NASA Astrophysics Data System (ADS)

Georgantas, Nikolaos; Issarny, Valerie; Mokhtar, Sonia Ben; Bromberg, Yerom-David; Bianco, Sebastien; Thomson, Graham; Raverdy, Pierre-Guillaume; Urbieta, Aitor; Cardoso, Roberto Speicys

With computing and communication capabilities now embedded in most physical objects of the surrounding environment and most users carrying wireless computing devices, the Ambient Intelligence (AmI) / pervasive computing vision [28] pioneered by Mark Weiser [32] is becoming a reality. Devices carried by nomadic users can seamlessly network with a variety of devices, both stationary and mobile, both nearby and remote, providing a wide range of functional capabilities, from base sensing and actuating to rich applications (e.g., smart spaces). This then allows the dynamic deployment of pervasive applications, which dynamically compose functional capabilities accessible in the pervasive network at the given time and place of an application request.

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications.

PubMed

Karyotis, Vasileios; Tsitseklis, Konstantinos; Sotiropoulos, Konstantinos; Papavassiliou, Symeon

2018-04-15

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan-Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing.

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications

PubMed Central

Sotiropoulos, Konstantinos

2018-01-01

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan–Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing. PMID:29662043

Pervasive Monitoring—An Intelligent Sensor Pod Approach for Standardised Measurement Infrastructures

PubMed Central

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a “digital skin for planet earth”. The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making. PMID:22163537

Pervasive monitoring--an intelligent sensor pod approach for standardised measurement infrastructures.

PubMed

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a "digital skin for planet earth". The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making.

Further Structural Intelligence for Sensors Cluster Technology in Manufacturing

PubMed Central

Mekid, Samir

2006-01-01

With the ever increasing complex sensing and actuating tasks in manufacturing plants, intelligent sensors cluster in hybrid networks becomes a rapidly expanding area. They play a dominant role in many fields from macro and micro scale. Global object control and the ability to self organize into fault-tolerant and scalable systems are expected for high level applications. In this paper, new structural concepts of intelligent sensors and networks with new intelligent agents are presented. Embedding new functionalities to dynamically manage cooperative agents for autonomous machines are interesting key enabling technologies most required in manufacturing for zero defects production.

Least mean square fourth based microgrid state estimation algorithm using the internet of things technology.

PubMed

Rana, Md Masud

2017-01-01

This paper proposes an innovative internet of things (IoT) based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations.

Mobile robotic sensors for perimeter detection and tracking.

PubMed

Clark, Justin; Fierro, Rafael

2007-02-01

Mobile robot/sensor networks have emerged as tools for environmental monitoring, search and rescue, exploration and mapping, evaluation of civil infrastructure, and military operations. These networks consist of many sensors each equipped with embedded processors, wireless communication, and motion capabilities. This paper describes a cooperative mobile robot network capable of detecting and tracking a perimeter defined by a certain substance (e.g., a chemical spill) in the environment. Specifically, the contributions of this paper are twofold: (i) a library of simple reactive motion control algorithms and (ii) a coordination mechanism for effectively carrying out perimeter-sensing missions. The decentralized nature of the methodology implemented could potentially allow the network to scale to many sensors and to reconfigure when adding/deleting sensors. Extensive simulation results and experiments verify the validity of the proposed cooperative control scheme.

Probabilistic Analysis of Hierarchical Cluster Protocols for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kaj, Ingemar

Wireless sensor networks are designed to extract data from the deployment environment and combine sensing, data processing and wireless communication to provide useful information for the network users. Hundreds or thousands of small embedded units, which operate under low-energy supply and with limited access to central network control, rely on interconnecting protocols to coordinate data aggregation and transmission. Energy efficiency is crucial and it has been proposed that cluster based and distributed architectures such as LEACH are particularly suitable. We analyse the random cluster hierarchy in this protocol and provide a solution for low-energy and limited-loss optimization. Moreover, we extend these results to a multi-level version of LEACH, where clusters of nodes again self-organize to form clusters of clusters, and so on.

Virtual network embedding in cross-domain network based on topology and resource attributes

NASA Astrophysics Data System (ADS)

Zhu, Lei; Zhang, Zhizhong; Feng, Linlin; Liu, Lilan

2018-03-01

Aiming at the network architecture ossification and the diversity of access technologies issues, this paper researches the cross-domain virtual network embedding algorithm. By analysing the topological attribute from the local and global perspective of nodes in the virtual network and the physical network, combined with the local network resource property, we rank the embedding priority of the nodes with PCA and TOPSIS methods. Besides, the link load distribution is considered. Above all, We proposed an cross-domain virtual network embedding algorithm based on topology and resource attributes. The simulation results depicts that our algorithm increases the acceptance rate of multi-domain virtual network requests, compared with the existing virtual network embedding algorithm.

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2016-04-01

Networks with nodes embedded in a metric space have gained increasing interest in recent years. The effects of spatial embedding on the networks' structural characteristics, however, are rarely taken into account when studying their macroscopic properties. Here, we propose a hierarchy of null models to generate random surrogates from a given spatially embedded network that can preserve certain global and local statistics associated with the nodes' embedding in a metric space. Comparing the original network's and the resulting surrogates' global characteristics allows one to quantify to what extent these characteristics are already predetermined by the spatial embedding of the nodes and links. We apply our framework to various real-world spatial networks and show that the proposed models capture macroscopic properties of the networks under study much better than standard random network models that do not account for the nodes' spatial embedding. Depending on the actual performance of the proposed null models, the networks are categorized into different classes. Since many real-world complex networks are in fact spatial networks, the proposed approach is relevant for disentangling the underlying complex system structure from spatial embedding of nodes in many fields, ranging from social systems over infrastructure and neurophysiology to climatology.

Toward quantum plasmonic networks

DOE PAGES

Holtfrerich, M. W.; Dowran, M.; Davidson, R.; ...

2016-08-30

Here, we demonstrate the transduction of macroscopic quantum entanglement by independent, distant plasmonic structures embedded in separate thin silver films. In particular, we show that the plasmon-mediated transmission through each film conserves spatially dependent, entangled quantum images, opening the door for the implementation of parallel quantum protocols, super-resolution imaging, and quantum plasmonic sensing geometries at the nanoscale level. The conservation of quantum information by the transduction process shows that continuous variable multi-mode entanglement is momentarily transferred from entangled beams of light to the space-like separated, completely independent plasmonic structures, thus providing a first important step toward establishing a multichannel quantummore » network across separate solid-state substrates.« less

Least mean square fourth based microgrid state estimation algorithm using the internet of things technology

PubMed Central

2017-01-01

This paper proposes an innovative internet of things (IoT) based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations. PMID:28459848

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Joint Sensor: Security Test and Evaluation Embedded in a Production Network Sensor Cloud

DTIC Science & Technology

2010-12-01

read of this year’s Verizon 2010 Data Breach Investigations Report (Baker et al. 2010) may in a sense reiterate the assumptions and propagate the...in 2002. He currently serves as the program manager for the DREN. E-mail: rcampbell@hpcmo.hpc.mil References Baker, W., et al. 2010. 2010 data breach investiga...tions report. http://www.verizonbusiness.com/resources/ reports/rp_2010- data - breach -report_en_xg.pdf (ac- cessed October 13, 2010

Investigating Student Communities with Network Analysis of Interactions in a Physics Learning Center

NASA Astrophysics Data System (ADS)

Brewe, Eric; Kramer, Laird; O'Brien, George

2009-11-01

We describe our initial efforts at implementing social network analysis to visualize and quantify student interactions in Florida International University's Physics Learning Center. Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at FIU. Our implementation of a research and learning community, embedded within a course reform effort, has led to increased recruitment and retention of physics majors. Finn and Rock [1997] link the academic and social integration of students to increased rates of retention. To identify these interactions, we have initiated an investigation that utilizes social network analysis to identify primary community participants. Community interactions are then characterized through the network's density and connectivity, shedding light on learning communities and participation. Preliminary results, further research questions, and future directions utilizing social network analysis are presented.

Flat Surface Damage Detection System (FSDDS)

NASA Technical Reports Server (NTRS)

Williams, Martha; Lewis, Mark; Gibson, Tracy; Lane, John; Medelius, Pedro; Snyder, Sarah; Ciarlariello, Dan; Parks, Steve; Carrejo, Danny; Rojdev, Kristina

2013-01-01

The Flat Surface Damage Detection system (FSDDS} is a sensory system that is capable of detecting impact damages to surfaces utilizing a novel sensor system. This system will provide the ability to monitor the integrity of an inflatable habitat during in situ system health monitoring. The system consists of three main custom designed subsystems: the multi-layer sensing panel, the embedded monitoring system, and the graphical user interface (GUI). The GUI LABVIEW software uses a custom developed damage detection algorithm to determine the damage location based on the sequence of broken sensing lines. It estimates the damage size, the maximum depth, and plots the damage location on a graph. Successfully demonstrated as a stand alone technology during 2011 D-RATS. Software modification also allowed for communication with HDU avionics crew display which was demonstrated remotely (KSC to JSC} during 2012 integration testing. Integrated FSDDS system and stand alone multi-panel systems were demonstrated remotely and at JSC, Mission Operations Test using Space Network Research Federation (SNRF} network in 2012. FY13, FSDDS multi-panel integration with JSC and SNRF network Technology can allow for integration with other complementary damage detection systems.

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

Dynamic virtual optical network embedding in spectral and spatial domains over elastic optical networks with multicore fibers

NASA Astrophysics Data System (ADS)

Zhu, Ruijie; Zhao, Yongli; Yang, Hui; Tan, Yuanlong; Chen, Haoran; Zhang, Jie; Jue, Jason P.

2016-08-01

Network virtualization can eradicate the ossification of the infrastructure and stimulate innovation of new network architectures and applications. Elastic optical networks (EONs) are ideal substrate networks for provisioning flexible virtual optical network (VON) services. However, as network traffic continues to increase exponentially, the capacity of EONs will reach the physical limitation soon. To further increase network flexibility and capacity, the concept of EONs is extended into the spatial domain. How to map the VON onto substrate networks by thoroughly using the spectral and spatial resources is extremely important. This process is called VON embedding (VONE).Considering the two kinds of resources at the same time during the embedding process, we propose two VONE algorithms, the adjacent link embedding algorithm (ALEA) and the remote link embedding algorithm (RLEA). First, we introduce a model to solve the VONE problem. Then we design the embedding ability measurement of network elements. Based on the network elements' embedding ability, two VONE algorithms were proposed. Simulation results show that the proposed VONE algorithms could achieve better performance than the baseline algorithm in terms of blocking probability and revenue-to-cost ratio.

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

NASA Astrophysics Data System (ADS)

Lin, Likun

Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network monitoring sensors. In order to maintain signal quality while optimizing network resources, we find that it is essential to model and update estimates of the physical link impairments in real-time. In this thesis, we consider the key elements required to enable an agile optical network, with contributions as follows: • Control Framework: extended the SDN concept to include the optical transport network through extensions to the OpenFlow (OF) protocol. A unified SDN control plane is built to facilitate control and management capability across the electrical/packet-switched and optical/circuit-switched portions of the network seamlessly. The SDN control plane serves as a platform to abstract the resources of multilayer/multivendor networks. Through this platform, applications can dynamically request the network resources to meet their service requirements. • Use of In-situ Monitors: enabled real-time physical impairment sensing in the control plane using in-situ Optical Performance Monitoring (OPM) and bit error rate (BER) analyzers. OPM and BER values are used as quantitative indicators of the link status and are fed to the control plane through a high-speed data collection interface to form a closed-loop feedback system to enable adaptive resource allocation. • Predictive Network Model: used a network model embedded in the control layer to study the link status. The estimated results of network status is fed into the control decisions to precompute the network resources. The performance of the network model can be enhanced by the sensing results. • Real-Time Control Algorithms: investigated various dynamic resource allocation mechanisms supporting an agile optical network. Intelligent routing and wavelength switching for recovering from traffic impairments is achieved experimentally in the agile optical network within one second. A distance-adaptive spectrum allocation scheme to address transmission impairments caused by cascaded Wavelength Selective Switches (WSS) is proposed and evaluated for improving network spectral efficiency.

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

PubMed Central

Jung, Eui-Hyun; Park, Yong-Jin

2008-01-01

In recent years, a few protocol bridge research projects have been announced to enable a seamless integration of Wireless Sensor Networks (WSNs) with the TCP/IP network. These studies have ensured the transparent end-to-end communication between two network sides in the node-centric manner. Researchers expect this integration will trigger the development of various application domains. However, prior research projects have not fully explored some essential features for WSNs, especially the reusability of sensing data and the data-centric communication. To resolve these issues, we suggested a new protocol bridge system named TinyONet. In TinyONet, virtual sensors play roles as virtual counterparts of physical sensors and they dynamically group to make a functional entity, Slice. Instead of direct interaction with individual physical sensors, each sensor application uses its own WSN service provided by Slices. If a new kind of service is required in TinyONet, the corresponding function can be dynamically added at runtime. Beside the data-centric communication, it also supports the node-centric communication and the synchronous access. In order to show the effectiveness of the system, we implemented TinyONet on an embedded Linux machine and evaluated it with several experimental scenarios. PMID:27873968

Structural and functional properties of spatially embedded scale-free networks.

PubMed

Emmerich, Thorsten; Bunde, Armin; Havlin, Shlomo

2014-06-01

Scale-free networks have been studied mostly as non-spatially embedded systems. However, in many realistic cases, they are spatially embedded and these constraints should be considered. Here, we study the structural and functional properties of a model of scale-free (SF) spatially embedded networks. In our model, both the degree and the length of links follow power law distributions as found in many real networks. We show that not all SF networks can be embedded in space and that the largest degree of a node in the network is usually smaller than in nonembedded SF networks. Moreover, the spatial constraints (each node has only few neighboring nodes) introduce degree-degree anticorrelations (disassortativity) since two high degree nodes cannot stay close in space. We also find significant effects of space embedding on the hopping distances (chemical distance) and the vulnerability of the networks.

Mobile Networked Sensors for Environmental Observatories

NASA Astrophysics Data System (ADS)

Kaiser, W. J.

2005-12-01

The development of the first embedded networked sensing (ENS) systems has been rapidly followed by their successful deployment for investigations in environments ranging from forest ecosystems, to rivers and lakes, and to subsurface soil observations. As ENS systems have been deployed, many technology challenges have been successfully addressed. For example, the requirements for local and remote data access and long operating life have been encountered and solved with a novel hierarchical network architecture and unique, low power platforms. This presentation will describe this progress and also the development and applications of a new ENS system addressing the most current challenges: A robotic ENS platform providing precise, reliable, and sustained observation capability with diverse sensing capabilities that may adapt to environmental dynamics. In the development of methods for autonomous observation by networked sensors, many applications have emerged requiring spatially and temporally intensive data sampling. Examples include the mapping of forest understory solar radiation, autonomous acquisition of imaging for plant phenology, and mapping of contaminant concentration in aquatic systems. Common to these applications is the need to actively and continuously configure the location and orientation of sensors for high fidelity mapping of the spatial distribution of phenomena. To address this primary environmental observation need, a new sensing platform, Networked Infomechanical Systems (NIMS) has been developed. NIMS relies on deployed aerial infrastructure (for example, cable suspension systems) in the natural environment to permit robotic devices to precisely and reliably move or remain stationary as required at elevations that may lie directly in or above the forest canopy or within a river or stream. NIMS systems are suspended to allow devices to translate a sensor node horizontally, and also to raise and lower devices. Examples of sensors that are now carried by NIMS include sensors for visible wavelength imaging, thermal infrared temperature mapping, microclimate, solar radiation, and for water quality and physical characterization of aquatic systems. NIMS devices include compact embedded computing, wireless network connectivity to surrounding static sensors, and remote Internet access. Exploiting this onboard computing allows NIMS devices to follow precise scanning protocols and self-calibration procedures. This presentation will describe permanent facility NIMS systems deployed at the James San Jacinto Mountains Reserve. Rapidly deployable NIMS permitting short term, highly mobile experiments will also be discussed. This includes the Thermal Mapper system that simultaneously samples plant physical structure (using laser position sensing and imaging) along with plant surface temperature (using high spatial resolution thermal infrared sensing). This compact system has been applied to the investigation of thermal characteristics of alpine plants in varying soil surfaces at the White Mountains Research Station. Other NIMS applications and results to be described include novel spatial mapping of nitrate concentration and other variables in flowing streams. Finally, this presentation will also address the many future applications of observatories linking investigators with remote mobile and static sensor networks. This research is supported by the NSF0331481 ITR program. Research has been performed in collaboration with R. Ambrose, K. Bible, D. Estrin, E. Graham, M. Hamilton, M. Hanson, T. Harmon, G. Pottie, P. Rundel, M. Srivastava, and G. Sukhatme

High capacity fiber optic sensor networks using hybrid multiplexing techniques and their applications

NASA Astrophysics Data System (ADS)

Sun, Qizhen; Li, Xiaolei; Zhang, Manliang; Liu, Qi; Liu, Hai; Liu, Deming

2013-12-01

Fiber optic sensor network is the development trend of fiber senor technologies and industries. In this paper, I will discuss recent research progress on high capacity fiber sensor networks with hybrid multiplexing techniques and their applications in the fields of security monitoring, environment monitoring, Smart eHome, etc. Firstly, I will present the architecture of hybrid multiplexing sensor passive optical network (HSPON), and the key technologies for integrated access and intelligent management of massive fiber sensor units. Two typical hybrid WDM/TDM fiber sensor networks for perimeter intrusion monitor and cultural relics security are introduced. Secondly, we propose the concept of "Microstructure－Optical X Domin Refecltor (M-OXDR)" for fiber sensor network expansion. By fabricating smart micro-structures with the ability of multidimensional encoded and low insertion loss along the fiber, the fiber sensor network of simple structure and huge capacity more than one thousand could be achieved. Assisted by the WDM/TDM and WDM/FDM decoding methods respectively, we built the verification systems for long-haul and real-time temperature sensing. Finally, I will show the high capacity and flexible fiber sensor network with IPv6 protocol based hybrid fiber/wireless access. By developing the fiber optic sensor with embedded IPv6 protocol conversion module and IPv6 router, huge amounts of fiber optic sensor nodes can be uniquely addressed. Meanwhile, various sensing information could be integrated and accessed to the Next Generation Internet.

Microelectromechanical Systems

NASA Technical Reports Server (NTRS)

Gabriel, Kaigham J.

1995-01-01

Micro-electromechanical systems (MEMS) is an enabling technology that merges computation and communication with sensing and actuation to change the way people and machines interact with the physical world. MEMS is a manufacturing technology that will impact widespread applications including: miniature inertial measurement measurement units for competent munitions and personal navigation; distributed unattended sensors; mass data storage devices; miniature analytical instruments; embedded pressure sensors; non-invasive biomedical sensors; fiber-optics components and networks; distributed aerodynamic control; and on-demand structural strength. The long term goal of ARPA's MEMS program is to merge information processing with sensing and actuation to realize new systems and strategies for both perceiving and controlling systems, processes, and the environment. The MEMS program has three major thrusts: advanced devices and processes, system design, and infrastructure.

Information Fusion in Ad hoc Wireless Sensor Networks for Aircraft Health Monitoring

NASA Astrophysics Data System (ADS)

Fragoulis, Nikos; Tsagaris, Vassilis; Anastassopoulos, Vassilis

In this paper the use of an ad hoc wireless sensor network for implementing a structural health monitoring system is discussed. The network is consisted of sensors deployed throughout the aircraft. These sensors being in the form of a microelectronic chip and consisted of sensing, data processing and communicating components could be easily embedded in any mechanical aircraft component. The established sensor network, due to its ad hoc nature is easily scalable, allowing adding or removing any number of sensors. The position of the sensor nodes need not necessarily to be engineered or predetermined, giving this way the ability to be deployed in inaccessible points. Information collected from various sensors of different modalities throughout the aircraft is then fused in order to provide a more comprehensive image of the aircraft structural health. Sensor level fusion along with decision quality information is used, in order to enhance detection performance.

Mesoporous Silicate Materials in Sensing

PubMed Central

Melde, Brian J.; Johnson, Brandy J.; Charles, Paul T.

2008-01-01

Mesoporous silicas, especially those exhibiting ordered pore systems and uniform pore diameters, have shown great potential for sensing applications in recent years. Morphological control grants them versatility in the method of deployment whether as bulk powders, monoliths, thin films, or embedded in coatings. High surface areas and pore sizes greater than 2 nm make them effective as adsorbent coatings for humidity sensors. The pore networks also provide the potential for immobilization of enzymes within the materials. Functionalization of materials by silane grafting or through co-condensation of silicate precursors can be used to provide mesoporous materials with a variety of fluorescent probes as well as surface properties that aid in selective detection of specific analytes. This review will illustrate how mesoporous silicas have been applied to sensing changes in relative humidity, changes in pH, metal cations, toxic industrial compounds, volatile organic compounds, small molecules and ions, nitroenergetic compounds, and biologically relevant molecules. PMID:27873810

Embedding Open-domain Common-sense Knowledge from Text

PubMed Central

Goodwin, Travis; Harabagiu, Sanda

2017-01-01

Our ability to understand language often relies on common-sense knowledge – background information the speaker can assume is known by the reader. Similarly, our comprehension of the language used in complex domains relies on access to domain-specific knowledge. Capturing common-sense and domain-specific knowledge can be achieved by taking advantage of recent advances in open information extraction (IE) techniques and, more importantly, of knowledge embeddings, which are multi-dimensional representations of concepts and relations. Building a knowledge graph for representing common-sense knowledge in which concepts discerned from noun phrases are cast as vertices and lexicalized relations are cast as edges leads to learning the embeddings of common-sense knowledge accounting for semantic compositionality as well as implied knowledge. Common-sense knowledge is acquired from a vast collection of blogs and books as well as from WordNet. Similarly, medical knowledge is learned from two large sets of electronic health records. The evaluation results of these two forms of knowledge are promising: the same knowledge acquisition methodology based on learning knowledge embeddings works well both for common-sense knowledge and for medical knowledge Interestingly, the common-sense knowledge that we have acquired was evaluated as being less neutral than than the medical knowledge, as it often reflected the opinion of the knowledge utterer. In addition, the acquired medical knowledge was evaluated as more plausible than the common-sense knowledge, reflecting the complexity of acquiring common-sense knowledge due to the pragmatics and economicity of language. PMID:28649676

A Vision-Based Driver Nighttime Assistance and Surveillance System Based on Intelligent Image Sensing Techniques and a Heterogamous Dual-Core Embedded System Architecture

PubMed Central

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system. PMID:22736956

A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

PubMed

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

Miniaturized neural sensing and optogenetic stimulation system for behavioral studies in the rat

NASA Astrophysics Data System (ADS)

Kim, Min Hyuck; Nam, Ilho; Ryu, Youngki; Wellman, Laurie W.; Sanford, Larry D.; Yoon, Hargsoon

2015-04-01

Real time sensing of localized electrophysiological and neurochemical signals associated with spontaneous and evoked neural activity is critically important for understanding neural networks in the brain. Our goal is to enhance the functionality and flexibility of a neural sensing and stimulation system for the observation of brain activity that will enable better understanding from the level of individual cells to that of global structures. We have thus developed a miniaturized electronic system for in-vivo neurotransmitter sensing and optogenetic stimulation amenable to behavioral studies in the rat. The system contains a potentiostat, a data acquisition unit, a control unit, and a wireless data transfer unit. For the potentiostat, we applied embedded op-amps to build single potential amperometry for electrochemical sensing of dopamine. A light emitting diode is controlled by a microcontroller and pulse width modulation utilized to control optogenetic stimulation within a sub-millisecond level. In addition, this proto-typed electronic system contains a Bluetooth module for wireless data communication. In the future, an application-specific integrated circuit (ASIC) will be designed for further miniaturization of the system.

Lithium tri borate (LiB3O5) embedded polymer electret for mechanical sensing application

NASA Astrophysics Data System (ADS)

Murugan, S.; Praveen, E.; Prasad, M. V. N.; Jayakumar, K.

2017-05-01

Lithium tri borate (LiB3O5) particles were synthesized by precipitation assisted high temperature solid state reaction. The particles were embedded in chitosan polymer and used as an electret. This electret was characterized for the suitability as a sensing element in vibration accelerometer. It is observed that LiB3O5 embedded electret exhibiting piezoelectric property. The electret is also giving an isolation of > 999 MΩ at 100 Vdc, 250 Vdc, 500 Vdc and 1kVdc confirms compatible for intrinsically safe sensing alternative in vibration accelerometer.

Embedding silica and polymer fibre Bragg gratings (FBG) in plastic 3D-printed sensing patches

NASA Astrophysics Data System (ADS)

Zubel, Michal G.; Sugden, Kate; Webb, David J.; Sáez-Rodríguez, David; Nielsen, Kristian; Bang, Ole

2016-04-01

This paper reports the first demonstration of a silica fibre Bragg grating (SOFBG) embedded in an FDM 3-D printed housing to yield a dual grating temperature-compensated strain sensor. We also report the first ever integration of polymer fibre Bragg grating (POFBG) within a 3-D printed sensing patch for strain or temperature sensing. The cyclic strain performance and temperature characteristics of both devices are examined and discussed. The strain sensitivities of the sensing patches were 0.40 and 0.95 pm/μɛ for SOFBG embedded in ABS, 0.38 pm/μɛ for POFBG in PLA, and 0.15 pm/μɛ for POFBG in ABS. The strain response was linear above a threshold and repeatable. The temperature sensitivity of the SOFBG sensing patch was found to be up to 169 pm/°C, which was up to 17 times higher than for an unembedded silica grating. Unstable temperature response POFBG embedded in PLA was reported, with temperature sensitivity values varying between 30 and 40 pm/°C.

Self-organizing hierarchies in sensor and communication networks.

PubMed

Prokopenko, Mikhail; Wang, Peter; Valencia, Philip; Price, Don; Foreman, Mark; Farmer, Anthony

2005-01-01

We consider a hierarchical multicellular sensing and communication network, embedded in an ageless aerospace vehicle that is expected to detect and react to multiple impacts and damage over a wide range of impact energies. In particular, we investigate self-organization of impact boundaries enclosing critically damaged areas, and impact networks connecting remote cells that have detected noncritical impacts. Each level of the hierarchy is shown to have distinct higher-order emergent properties, desirable in self-monitoring and self-repairing vehicles. In addition, cells and communication messages are shown to need memory (hysteresis) in order to retain desirable emergent behavior within and between various hierarchical levels. Spatiotemporal robustness of self-organizing hierarchies is quantitatively measured with graph-theoretic and information-theoretic techniques, such as the Shannon entropy. This allows us to clearly identify phase transitions separating chaotic dynamics from ordered and robust patterns.

Optical fibre sensing in metals by embedment in 3D printed metallic structures

NASA Astrophysics Data System (ADS)

Maier, R. R. J.; Havermann, D.; Schneller, O.; Mathew, J.; Polyzos, D.; MacPherson, W. N.; Hand, D. P.

2014-05-01

Additive manufacturing or 3D printing of structural components in metals has potential to revolutionise the manufacturing industry. Embedded sensing in such structures opens a route towards SMART metals, providing added functionality, intelligence and enhanced performance in many components. Such embedded sensors would be capable of operating at extremely high temperatures by utilizing regenerated fibre Bragg gratings and in-fibre Fabry-Perot cavities.

A Study of Thermistor Performance within a Textile Structure.

PubMed

Hughes-Riley, Theodore; Lugoda, Pasindu; Dias, Tilak; Trabi, Christophe L; Morris, Robert H

2017-08-05

Textiles provide an ideal structure for embedding sensors for medical devices. Skin temperature measurement is one area in which a sensor textile could be particularly beneficial; pathological skin is normally very sensitive, making the comfort of anything placed on that skin paramount. Skin temperature is an important parameter to measure for a number of medical applications, including for the early detection of diabetic foot ulcer formation. To this end an electronic temperature-sensor yarn was developed by embedding a commercially available thermistor chip into the fibres of a yarn, which can be used to produce a textile or a garment. As part of this process a resin was used to encapsulate the thermistor. This protects the thermistor from mechanical and chemical stresses, and also allows the sensing yarn to be washed. Building off preliminary work, the behaviour and performance of an encapsulated thermistor has been characterised to determine the effect of encapsulation on the step response time and absolute temperature measurements. Over the temperature range of interest only a minimal effect was observed, with step response times varying between 0.01-0.35 s. A general solution is presented for the heat transfer coefficient compared to size of the micro-pod formed by the encapsulation of the thermistor. Finally, a prototype temperature-sensing sock was produced using a network of sensing yarns as a demonstrator of a system that could warn of impending ulcer formation in diabetic patients.

Social networks and links to isolation and loneliness among elderly HCBS clients.

PubMed

Medvene, Louis J; Nilsen, Kari M; Smith, Rachel; Ofei-Dodoo, Samuel; DiLollo, Anthony; Webster, Noah; Graham, Annette; Nance, Anita

2016-01-01

The purpose of this study was to explore the network types of HCBS clients based on the structural characteristics of their social networks. We also examined how the network types were associated with social isolation, relationship quality and loneliness. Forty personal interviews were carried out with HCBS clients to assess the structure of their social networks as indicated by frequency of contact with children, friends, family and participation in religious and community organizations. Hierarchical cluster analysis was conducted to identify network types. Four network types were found including: family (n = 16), diverse (n = 8), restricted (n = 8) and religious (n = 7). Family members comprised almost half of participants' social networks, and friends comprised less than one-third. Clients embedded in family, diverse and religious networks had significantly more positive relationships than clients embedded in restricted networks. Clients embedded in restricted networks had significantly higher social isolation scores and were lonelier than clients in diverse and family networks. The findings suggest that HCBS clients' isolation and loneliness are linked to the types of social networks in which they are embedded. The findings also suggest that clients embedded in restricted networks are at high risk for negative outcomes.

Automobile gross emitter screening with remote sensing data using objective-oriented neural network.

PubMed

Chen, Ho-Wen; Yang, Hsi-Hsien; Wang, Yu-Sheng

2009-11-01

One of the costs of Taiwan's massive economic development has been severe air pollution problems in many parts of the island. Since vehicle emissions are the major source of air pollution in most of Taiwan's urban areas, Taiwan's government has implemented policies to rectify the degrading air quality, especially in areas with high population density. To reduce vehicle pollution emissions an on-road remote sensing and monitoring system is used to check the exhaust emissions from gasoline engine automobiles. By identifying individual vehicles with excessive emissions for follow-up inspection and testing, air quality in the urban environment is expected to improve greatly. Because remote sensing is capable of measuring a large number of moving vehicles in a short period, it has been considered as an assessment technique in place of the stationary emission-sampling techniques. However, inherent measurement uncertainty of remote sensing instrumentation, compounded by the indeterminacy of monitoring site selection, plus the vagaries of weather, causes large errors in pollution discrimination and limits the application of the remote sensing. Many governments are still waiting for a novel data analysis methodology to clamp down on heavily emitting vehicles by using remote sensing data. This paper proposes an artificial neural network (ANN), with vehicle attributes embedded, that can be trained by genetic algorithm (GA) based on different strategies to predict vehicle emission violation. Results show that the accuracy of predicting emission violation is as high as 92%. False determinations tend to occur for vehicles aged 7-13 years, peaking at 10 years of age.

RESLanjut: The learning media for improve students understanding in embedded systems

NASA Astrophysics Data System (ADS)

Indrianto, Susanti, Meilia Nur Indah; Karina, Djunaidi

2017-08-01

The use of network in embedded system can be done with many kinds of network, with the use of mobile phones, bluetooths, modems, ethernet cards, wireless technology and so on. Using network in embedded system could help people to do remote controlling. On previous research, researchers found that many students have the ability to comprehend the basic concept of embedded system. They could also make embedded system tools but without network integration. And for that, a development is needed for the embedded system module. The embedded system practicum module design needs a prototype method in order to achieve the desired goal. The prototype method is often used in the real world. Or even, a prototype method is a part of products that consist of logic expression or external physical interface. The embedded system practicum module is meant to increase student comprehension of embedded system course, and also to encourage students to innovate on technology based tools. It is also meant to help teachers to teach the embedded system concept on the course. The student comprehension is hoped to increase with the use of practicum course.

Microstructure of the smart composite structures with embedded fiber optic sensing nerves

NASA Astrophysics Data System (ADS)

Liu, Jingyuan; Luo, Fei; Li, Changchun; Ma, Naibin

1997-11-01

The composite structures with embedded optical fiber sensors construct a smart composite structure system, which may have the characteristics of the in-service self-measurement, self- recognition and self-judgement action. In the present work, we studied the microstructures of carbon/epoxy composite laminates with embedded sensing optical fibers, and the integration of optical fiber with composites was also discussed. The preliminary experiment results show that because of the difference between the sensing optical fibers and the reinforcing fibers in their size, the microstructure of the composites with embedded optical fibers will produce partial local changes in the area of embedded optical fiber, these changes may affect the mechanical properties of composite structures. When the optical fibers are embedded parallel to the reinforcing fibers, due to the composite prepregs are formed under a press action during its curing process, the reinforcing fibers can be arranged equably around the optical fibers. But when the optical fibers are embedded perpendicularly to the reinforcement fibers, the resin rich pocket will appear in the composite laminates surrounding the embedded optical fiber. The gas holes will be easily produced in these zones which may produce a premature failure of the composite structure. The photoelastic experiments are also given in the paper.

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

PubMed Central

Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G.

2016-01-01

Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. PMID:27248512

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

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

Wang, Anbo

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

Intelligent Sensing in Dynamic Environments Using Markov Decision Process

PubMed Central

Nanayakkara, Thrishantha; Halgamuge, Malka N.; Sridhar, Prasanna; Madni, Asad M.

2011-01-01

In a network of low-powered wireless sensors, it is essential to capture as many environmental events as possible while still preserving the battery life of the sensor node. This paper focuses on a real-time learning algorithm to extend the lifetime of a sensor node to sense and transmit environmental events. A common method that is generally adopted in ad-hoc sensor networks is to periodically put the sensor nodes to sleep. The purpose of the learning algorithm is to couple the sensor’s sleeping behavior to the natural statistics of the environment hence that it can be in optimal harmony with changes in the environment, the sensors can sleep when steady environment and stay awake when turbulent environment. This paper presents theoretical and experimental validation of a reward based learning algorithm that can be implemented on an embedded sensor. The key contribution of the proposed approach is the design and implementation of a reward function that satisfies a trade-off between the above two mutually contradicting objectives, and a linear critic function to approximate the discounted sum of future rewards in order to perform policy learning. PMID:22346624

Architecture of a Service-Enabled Sensing Platform for the Environment

PubMed Central

Kotsev, Alexander; Pantisano, Francesco; Schade, Sven; Jirka, Simon

2015-01-01

Recent technological advancements have led to the production of arrays of miniaturized sensors, often embedded in existing multitasking devices (e.g., smartphones, tablets) and using a wide range of radio standards (e.g., Bluetooth, Wi-Fi, 4G cellular networks). Altogether, these technological evolutions coupled with the diffusion of ubiquitous Internet connectivity provide the base-line technology for the Internet of Things (IoT). The rapid increase of IoT devices is enabling the definition of new paradigms of data collection and introduces the concept of mobile crowd-sensing. In this respect, new sensing methodologies promise to extend the current understanding of the environment and social behaviors by leveraging citizen-contributed data for a wide range of applications. Environmental sensing can however only be successful if all the heterogeneous technologies and infrastructures work smoothly together. As a result, the interconnection and orchestration of devices is one of the central issues of the IoT paradigm. With this in mind, we propose an approach for improving the accessibility of observation data, based on interoperable standards and on-device web services. PMID:25688593

Architecture of a service-enabled sensing platform for the environment.

PubMed

Kotsev, Alexander; Pantisano, Francesco; Schade, Sven; Jirka, Simon

2015-02-13

Recent technological advancements have led to the production of arrays of miniaturized sensors, often embedded in existing multitasking devices (e.g., smartphones, tablets) and using a wide range of radio standards (e.g., Bluetooth, Wi-Fi, 4G cellular networks). Altogether, these technological evolutions coupled with the diffusion of ubiquitous Internet connectivity provide the base-line technology for the Internet of Things (IoT). The rapid increase of IoT devices is enabling the definition of new paradigms of data collection and introduces the concept of mobile crowd-sensing. In this respect, new sensing methodologies promise to extend the current understanding of the environment and social behaviors by leveraging citizen-contributed data for a wide range of applications. Environmental sensing can however only be successful if all the heterogeneous technologies and infrastructures work smoothly together. As a result, the interconnection and orchestration of devices is one of the central issues of the IoT paradigm. With this in mind, we propose an approach for improving the accessibility of observation data, based on interoperable standards and on-device web services.

Failure and recovery in dynamical networks.

PubMed

Böttcher, L; Luković, M; Nagler, J; Havlin, S; Herrmann, H J

2017-02-03

Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the network's components follow three realistic processes that capture these features: (i) spontaneous failure of a component independent of the neighborhood (internal failure), (ii) failure induced by failed neighboring nodes (external failure) and (iii) spontaneous recovery of a component. We identify a metastable domain in the global network phase diagram spanned by the model's control parameters where dramatic hysteresis effects and random switching between two coexisting states are observed. This dynamics depends on the characteristic link length of the embedded system. For the Euclidean lattice in particular, hysteresis and switching only occur in an extremely narrow region of the parameter space compared to random networks. We develop a unifying theory which links the dynamics of our model to contact processes. Our unifying framework may help to better understand controllability in spatially embedded and random networks where spontaneous recovery of components can mitigate spontaneous failure and damage spread in dynamical networks.

Connecting the snowpack to the internet of things: an IPv6 architecture for providing real-time measurements of hydrologic systems

NASA Astrophysics Data System (ADS)

Kerkez, B.; Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.

2012-12-01

We describe our improved, robust, and scalable architecture by which to rapidly instrument large-scale watersheds, while providing the resulting data in real-time. Our system consists of more than twenty wireless sensor networks and thousands of sensors, which will be deployed in the American River basin (5000 sq. km) of California. The core component of our system is known as a mote, a tiny, ultra-low-power, embedded wireless computer that can be used for any number of sensing applications. Our new generation of motes is equipped with IPv6 functionality, effectively giving each sensor in the field its own unique IP address, thus permitting users to remotely interact with the devices without going through intermediary services. Thirty to fifty motes will be deployed across 1-2 square kilometer regions to form a mesh-based wireless sensor network. Redundancy of local wireless links will ensure that data will always be able to traverse the network, even if hash wintertime conditions adversely affect some network nodes. These networks will be used to develop spatial estimates of a number of hydrologic parameters, focusing especially on snowpack. Each wireless sensor network has one main network controller, which is responsible with interacting with an embedded Linux computer to relay information across higher-powered, long-range wireless links (cell modems, satellite, WiFi) to neighboring networks and remote, offsite servers. The network manager is also responsible for providing an Internet connection to each mote. Data collected by the sensors can either be read directly by remote hosts, or stored on centralized servers for future access. With 20 such networks deployed in the American River, our system will comprise an unprecedented cyber-physical architecture for measuring hydrologic parameters in large-scale basins. The spatiotemporal density and real-time nature of the data is also expected to significantly improve operational hydrology and water resource management in the basin.

Active sensing of fatigue damage using embedded ultrasonics

NASA Astrophysics Data System (ADS)

Zagrai, Andrei; Kruse, Walter A.; Gigineishvili, Vlasi

2009-03-01

Embedded ultrasonics has demonstrated considerable utility in structural health monitoring of aeronautical vehicle. This active sensing approach has been widely used to detect and monitor cracks, delaminations, and disbonds in a broad spectrum of metallic and composite structures. However, application of the embedded ultrasonics for active sensing of incipient damage before fracture has received limited attention. The aim of this study was to investigate the suitability of embedded ultrasonics and nonlinear acoustic signatures for monitoring pre-crack fatigue damage in aerospace structural material. A harmonic load was applied to structural specimens in order to induce fatigue damage accumulation and growth. Specimens of simple geometry were considered and piezoelectric active sensors were employed for generation and reception of elastic waves. The elastic wave signatures were analyzed in the frequency domain using nonlinear impedance and nonlinear resonance methods. A relationship between fatigue severity and linear as well as nonlinear acoustic signatures was investigated and considered in the damage classification procedure. Practical aspects of the active sensing of the fatigue damage before fracture were discussed and prospective avenues for future research were suggested.

Stochastic global identification of a bio-inspired self-sensing composite UAV wing via wind tunnel experiments

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotios; Nardari, Raphael; Li, Yu-Hung; Wang, Pengchuan; Chang, Fu-Kuo

2016-04-01

In this work, the system design, integration, and wind tunnel experimental evaluation are presented for a bioinspired self-sensing intelligent composite unmanned aerial vehicle (UAV) wing. A total of 148 micro-sensors, including piezoelectric, strain, and temperature sensors, in the form of stretchable sensor networks are embedded in the layup of a composite wing in order to enable its self-sensing capabilities. Novel stochastic system identification techniques based on time series models and statistical parameter estimation are employed in order to accurately interpret the sensing data and extract real-time information on the coupled air flow-structural dynamics. Special emphasis is given to the wind tunnel experimental assessment under various flight conditions defined by multiple airspeeds and angles of attack. A novel modeling approach based on the recently introduced Vector-dependent Functionally Pooled (VFP) model structure is employed for the stochastic identification of the "global" coupled airflow-structural dynamics of the wing and their correlation with dynamic utter and stall. The obtained results demonstrate the successful system-level integration and effectiveness of the stochastic identification approach, thus opening new perspectives for the state sensing and awareness capabilities of the next generation of "fly-by-fee" UAVs.

Flight State Identification of a Self-Sensing Wing via an Improved Feature Selection Method and Machine Learning Approaches.

PubMed

Chen, Xi; Kopsaftopoulos, Fotis; Wu, Qi; Ren, He; Chang, Fu-Kuo

2018-04-29

In this work, a data-driven approach for identifying the flight state of a self-sensing wing structure with an embedded multi-functional sensing network is proposed. The flight state is characterized by the structural vibration signals recorded from a series of wind tunnel experiments under varying angles of attack and airspeeds. A large feature pool is created by extracting potential features from the signals covering the time domain, the frequency domain as well as the information domain. Special emphasis is given to feature selection in which a novel filter method is developed based on the combination of a modified distance evaluation algorithm and a variance inflation factor. Machine learning algorithms are then employed to establish the mapping relationship from the feature space to the practical state space. Results from two case studies demonstrate the high identification accuracy and the effectiveness of the model complexity reduction via the proposed method, thus providing new perspectives of self-awareness towards the next generation of intelligent air vehicles.

Frequency-Dependent Magnetic Susceptibility of Magnetite and Cobalt Ferrite Nanoparticles Embedded in PAA Hydrogel

PubMed Central

van Berkum, Susanne; Dee, Joris T.; Philipse, Albert P.; Erné, Ben H.

2013-01-01

Chemically responsive hydrogels with embedded magnetic nanoparticles are of interest for biosensors that magnetically detect chemical changes. A crucial point is the irreversible linkage of nanoparticles to the hydrogel network, preventing loss of nanoparticles upon repeated swelling and shrinking of the gel. Here, acrylic acid monomers are adsorbed onto ferrite nanoparticles, which subsequently participate in polymerization during synthesis of poly(acrylic acid)-based hydrogels (PAA). To demonstrate the fixation of the nanoparticles to the polymer, our original approach is to measure low-field AC magnetic susceptibility spectra in the 0.1 Hz to 1 MHz range. In the hydrogel, the magnetization dynamics of small iron oxide nanoparticles are comparable to those of the particles dispersed in a liquid, due to fast Néel relaxation inside the particles; this renders the ferrogel useful for chemical sensing at frequencies of several kHz. However, ferrogels holding thermally blocked iron oxide or cobalt ferrite nanoparticles show significant decrease of the magnetic susceptibility resulting from a frozen magnetic structure. This confirms that the nanoparticles are unable to rotate thermally inside the hydrogel, in agreement with their irreversible fixation to the polymer network. PMID:23673482

Spatial effects in meta-foodwebs.

PubMed

Barter, Edmund; Gross, Thilo

2017-08-30

In ecology it is widely recognised that many landscapes comprise a network of discrete patches of habitat. The species that inhabit the patches interact with each other through a foodweb, the network of feeding interactions. The meta-foodweb model proposed by Pillai et al. combines the feeding relationships at each patch with the dispersal of species between patches, such that the whole system is represented by a network of networks. Previous work on meta-foodwebs has focussed on landscape networks that do not have an explicit spatial embedding, but in real landscapes the patches are usually distributed in space. Here we compare the dispersal of a meta-foodweb on Erdős-Rényi networks, that do not have a spatial embedding, and random geometric networks, that do have a spatial embedding. We found that local structure and large network distances in spatially embedded networks, lead to meso-scale patterns of patch occupation by both specialist and omnivorous species. In particular, we found that spatial separations make the coexistence of competing species more likely. Our results highlight the effects of spatial embeddings for meta-foodweb models, and the need for new analytical approaches to them.

CNT-cement based composites: fabrication, self-sensing properties, and prospective applications to structural health monitoring

NASA Astrophysics Data System (ADS)

Rainieri, Carlo; Song, Yi; Fabbrocino, Giovanni; Schulz, Mark J.; Shanov, Vesselin

2013-08-01

Degradation phenomena can affect civil structures over their lifespan. The recent advances in nanotechnology and sensing allow to monitor the behaviour of a structure, assess its performance and identify damage at an early stage. Thus, maintenance actions can be carried out in a timely manner, improving structural reliability and safety. Structural Health Monitoring (SHM) is traditionally performed at a global level, with a limited number of sensors distributed over a relatively large area of a structure. Thus, only major damage conditions are detectable. Dense sensor networks and innovative structural neural systems, reproducing the structure and the function of the human nervous system, may overcome this drawback of current SHM systems. Miniaturization and embedment are key requirements for successful implementation of structural neural systems. Carbon nanotubes (CNTs) can play an attractive role in the development of embedded sensors and smart structural materials, since they can provide to traditional cement based materials both structural capability and measurable response to applied stresses, strains, cracks and other flaws. In this paper investigations about CNT/cement composites and their self-sensing capabilities are summarized and critically revised. The analysis of available experimental results and theoretical developments provides useful design criteria for the fabrication of CNT/cement composites optimized for SHM applications in civil engineering. Specific attention is paid to the opportunities provided by new RF plasma technologies for the functionalization of CNTs in view of sensor development and SHM applications.

A Study of Thermistor Performance within a Textile Structure

PubMed Central

Hughes-Riley, Theodore; Lugoda, Pasindu; Dias, Tilak; Trabi, Christophe L.; Morris, Robert H.

2017-01-01

Textiles provide an ideal structure for embedding sensors for medical devices. Skin temperature measurement is one area in which a sensor textile could be particularly beneficial; pathological skin is normally very sensitive, making the comfort of anything placed on that skin paramount. Skin temperature is an important parameter to measure for a number of medical applications, including for the early detection of diabetic foot ulcer formation. To this end an electronic temperature-sensor yarn was developed by embedding a commercially available thermistor chip into the fibres of a yarn, which can be used to produce a textile or a garment. As part of this process a resin was used to encapsulate the thermistor. This protects the thermistor from mechanical and chemical stresses, and also allows the sensing yarn to be washed. Building off preliminary work, the behaviour and performance of an encapsulated thermistor has been characterised to determine the effect of encapsulation on the step response time and absolute temperature measurements. Over the temperature range of interest only a minimal effect was observed, with step response times varying between 0.01–0.35 s. A general solution is presented for the heat transfer coefficient compared to size of the micro-pod formed by the encapsulation of the thermistor. Finally, a prototype temperature-sensing sock was produced using a network of sensing yarns as a demonstrator of a system that could warn of impending ulcer formation in diabetic patients. PMID:28783067

Energy-aware virtual network embedding in flexi-grid optical networks

NASA Astrophysics Data System (ADS)

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng; Chen, Bin

2018-01-01

Virtual network embedding (VNE) problem is to map multiple heterogeneous virtual networks (VN) on a shared substrate network, which mitigate the ossification of the substrate network. Meanwhile, energy efficiency has been widely considered in the network design. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the power increment of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low energy consumption. Numerical results show the functionality of the heuristic algorithm in a 24-node network.

Flexible embedding of networks

NASA Astrophysics Data System (ADS)

Fernandez-Gracia, Juan; Buckee, Caroline; Onnela, Jukka-Pekka

We introduce a model for embedding one network into another, focusing on the case where network A is much bigger than network B. Nodes from network A are assigned to the nodes in network B using an algorithm where we control the extent of localization of node placement in network B using a single parameter. Starting from an unassigned node in network A, called the source node, we first map this node to a randomly chosen node in network B, called the target node. We then assign the neighbors of the source node to the neighborhood of the target node using a random walk based approach. To assign each neighbor of the source node to one of the nodes in network B, we perform a random walk starting from the target node with stopping probability α. We repeat this process until all nodes in network A have been mapped to the nodes of network B. The simplicity of the model allows us to calculate key quantities of interest in closed form. By varying the parameter α, we are able to produce embeddings from very local (α = 1) to very global (α --> 0). We show how our calculations fit the simulated results, and we apply the model to study how social networks are embedded in geography and how the neurons of C. Elegans are embedded in the surrounding volume.

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors.

PubMed

Jenkins, R Brian; Joyce, Peter; Mechtel, Deborah

2017-01-27

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay.

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors

PubMed Central

Jenkins, R. Brian; Joyce, Peter; Mechtel, Deborah

2017-01-01

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay. PMID:28134815

Infrastructure sensing.

PubMed

Soga, Kenichi; Schooling, Jennifer

2016-08-06

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors.

Infrastructure sensing

PubMed Central

Soga, Kenichi; Schooling, Jennifer

2016-01-01

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors. PMID:27499845

Efficient embedding of complex networks to hyperbolic space via their Laplacian

PubMed Central

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-01-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction. PMID:27445157

Efficient embedding of complex networks to hyperbolic space via their Laplacian

NASA Astrophysics Data System (ADS)

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-07-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction.

Smartphones for distributed multimode sensing: biological and environmental sensing and analysis

NASA Astrophysics Data System (ADS)

Feitshans, Tyler; Williams, Robert

2013-05-01

Active and Agile Environmental and Biological sensing are becoming obligatory to generate prompt warnings for the troops and law enforcements conducting missions in hostile environments. The traditional static sensing mesh networks which provide a coarse-grained (far-field) measurement of the environmental conditions like air quality, radiation , CO2, etc … would not serve the dynamic and localized changes in the environment, which requires a fine-grained (near-field) sensing solutions. Further, sensing the biological conditions of (healthy and injured) personnel in a contaminated environment and providing a personalized analysis of the life-threatening conditions in real-time would greatly aid the success of the mission. In this vein, under SATE and YATE programs, the research team at AFRL Tec^Edge Discovery labs had demonstrated the feasibility of developing Smartphone applications , that employ a suite of external environmental and biological sensors, which provide fine-grained and customized sensing in real-time fashion. In its current state, these smartphone applications leverage a custom designed modular standalone embedded platform (with external sensors) that can be integrated seamlessly with Smartphones for sensing and further provides connectivity to a back-end data architecture for archiving, analysis and dissemination of real-time alerts. Additionally, the developed smartphone applications have been successfully tested in the field with varied environmental sensors to sense humidity, CO2/CO, wind, etc…, ; and with varied biological sensors to sense body temperature and pulse with apt real-time analysis

Investigating student communities with network analysis of interactions in a physics learning center

NASA Astrophysics Data System (ADS)

Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

2012-06-01

Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC) that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

Optical fiber sensors embedded in flexible polymer foils

NASA Astrophysics Data System (ADS)

van Hoe, Bram; van Steenberge, Geert; Bosman, Erwin; Missinne, Jeroen; Geernaert, Thomas; Berghmans, Francis; Webb, David; van Daele, Peter

2010-04-01

In traditional electrical sensing applications, multiplexing and interconnecting the different sensing elements is a major challenge. Recently, many optical alternatives have been investigated including optical fiber sensors of which the sensing elements consist of fiber Bragg gratings. Different sensing points can be integrated in one optical fiber solving the interconnection problem and avoiding any electromagnetical interference (EMI). Many new sensing applications also require flexible or stretchable sensing foils which can be attached to or wrapped around irregularly shaped objects such as robot fingers and car bumpers or which can even be applied in biomedical applications where a sensor is fixed on a human body. The use of these optical sensors however always implies the use of a light-source, detectors and electronic circuitry to be coupled and integrated with these sensors. The coupling of these fibers with these light sources and detectors is a critical packaging problem and as it is well-known the costs for packaging, especially with optoelectronic components and fiber alignment issues are huge. The end goal of this embedded sensor is to create a flexible optical sensor integrated with (opto)electronic modules and control circuitry. To obtain this flexibility, one can embed the optical sensors and the driving optoelectronics in a stretchable polymer host material. In this article different embedding techniques for optical fiber sensors are described and characterized. Initial tests based on standard manufacturing processes such as molding and laser structuring are reported as well as a more advanced embedding technique based on soft lithography processing.

Optical methods and systems for detecting a constituent in a gas containing oxygen in harsh environments

DOEpatents

Carpenter, Michael A [Scotia, NY; Sirinakis, George [Bronx, NY

2011-01-04

A method for detecting a gas phase constituent such as carbon monoxide, nitrogen dioxide, hydrogen, or hydrocarbons in a gas comprising oxygen such as air, includes providing a sensing material or film having a metal embedded in a catalytically active matrix such as gold embedded in a yttria stabilized zirconia (YSZ) matrix. The method may include annealing the sensing material at about 900.degree. C., exposing the sensing material and gas to a temperature above 400.degree. C., projecting light onto the sensing material, and detecting a change in the absorption spectrum of the sensing material due to the exposure of the sensing material to the gas in air at the temperature which causes a chemical reaction in the sensing material compared to the absorption spectrum of the sensing material in the absence of the gas. Systems employing such a method are also disclosed.

Embedded Piezoresistive Microcantilever Sensors for Chemical and Biological Sensing

NASA Astrophysics Data System (ADS)

Porter, Timothy; Eastman, Michael; Kooser, Ara; Manygoats, Kevin; Zhine, Rosalie

2003-03-01

Microcantilever sensors based on embedded piezoresisative technology offer a promising, low-cost method of sensing chemical and biological species. Here, we present data on the detection of various gaseous analytes, including volatile organic compounds (VOC's) and carbon monoxide. Also, we have used these sensors to detect the protein bovine serum albumin (BSA), a protein important in the study of human childhood diabetes.

Investigation on Smart Parts with Embedded Piezoelectric Sensors via Additive Manufacturing

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

Lin, Yirong

The goal of this proposed research is to design, fabricate, and evaluate “smart parts” with embedded sensors for energy systems. The “smart parts” will be fabricated using Electron Beam Melting (EBM) 3D printing technique with built-in piezoceramic sensors. The objectives of the proposed project are: 1) Fabricate energy system related components with embedded sensors, 2) Evaluate the mechanical properties and sensing functionalities of the “smart parts” with embedded piezoceramic sensors, and 3) Assess in-situ sensing capability of energy system parts. The second year’s research of the research is centered on fabrication of the “smart parts” with considerations of overall materialmore » property as well as demonstration of sensing functionalities. The results for the final report are presented here, including all research accomplishment, project management. Details are included such as: how the design and fabrication of sensor packaging could improve the sensor performance, demonstration of “smart parts” sensing capabilities, analysis on the elements that constitute the “smart sensors”, advanced “stop and go” fabrication process, smart injector fabrication using SLM technology, smart injector testing in combustion environments etc. Research results to date have generated several posters and papers.« less

Scheduling of network access for feedback-based embedded systems

NASA Astrophysics Data System (ADS)

Liberatore, Vincenzo

2002-07-01

nd communication capabilities. Examples range from smart dust embedded in building materials to networks of appliances in the home. Embedded devices will be deployed in unprecedented numbers, will enable pervasive distributed computing, and will radically change the way people interact with the surrounding environment [EGH00a]. The paper targets embedded systems and their real-time (RT) communication requirements. RT requirements arise from the

The role of social networks in the development of overweight and obesity among adults: a scoping review.

PubMed

Powell, Katie; Wilcox, John; Clonan, Angie; Bissell, Paul; Preston, Louise; Peacock, Marian; Holdsworth, Michelle

2015-09-30

Although it is increasingly acknowledged that social networks are important to our understanding ofoverweight and obesity, there is limited understanding about the processes by which such networks shapetheir progression. This paper reports the findings of a scoping review of the literature that sought to identify the key processes through which social networks are understood to influence the development of overweight and obesity. A scoping review was conducted. Forty five papers were included in the final review, the findings of which were synthesised to provide an overview of the main processes through which networks have been understood to influence the development of overweight and obesity. Included papers addressed a wide range of research questions framed around six types of networks: a paired network (one's spouse or intimate partner); friends and family (including work colleagues and people within social clubs); ephemeral networks in shared public spaces (such as fellow shoppers in a supermarket or diners in a restaurant); people living within the same geographical region; peers (including co-workers, fellow students, fellow participants in a weight loss programme); and cultural groups (often related toethnicity). As individuals are embedded in many of these different types of social networks at any one time, the pathways of influence from social networks to the development of patterns of overweight and obesity are likely to be complex and interrelated. Included papers addressed a diverse set of issues: body weight trends over time; body size norms or preferences; weight loss and management; physical activity patterns; and dietary patterns. Three inter-related processes were identified: social contagion (whereby the network in which people are embedded influences their weight or weight influencing behaviours), social capital (whereby sense of belonging and social support influence weight or weight influencing behaviours), and social selection (whereby a person's network might develop according to his or her weight). The findings have important implications for understanding about methods to target the spread of obesity, indicating that much greater attention needs to be paid to the social context in which people make decisions about their weight and weight influencing behaviours.

Percolation of spatially constraint networks

NASA Astrophysics Data System (ADS)

Li, Daqing; Li, Guanliang; Kosmidis, Kosmas; Stanley, H. E.; Bunde, Armin; Havlin, Shlomo

2011-03-01

We study how spatial constraints are reflected in the percolation properties of networks embedded in one-dimensional chains and two-dimensional lattices. We assume long-range connections between sites on the lattice where two sites at distance r are chosen to be linked with probability p(r)~r-δ. Similar distributions have been found in spatially embedded real networks such as social and airline networks. We find that for networks embedded in two dimensions, with 2<δ<4, the percolation properties show new intermediate behavior different from mean field, with critical exponents that depend on δ. For δ<2, the percolation transition belongs to the universality class of percolation in Erdös-Rényi networks (mean field), while for δ>4 it belongs to the universality class of percolation in regular lattices. For networks embedded in one dimension, we find that, for δ<1, the percolation transition is mean field. For 1<δ<2, the critical exponents depend on δ, while for δ>2 there is no percolation transition as in regular linear chains.

Porphyrin-Embedded Silicate Materials for Detection of Hydrocarbon Solvents

DTIC Science & Technology

2011-01-14

Sensors 2011, 11, 886-904; doi:10.3390/s110100886 sensors ISSN 1424-8220 www.mdpi.com/journal/ sensors Article Porphyrin-Embedded Silicate...Prescribed by ANSI Std Z39-18 Sensors 2011, 11 887 1. Introduction Mesoporous silicates have been widely described in sensing...absorption spectroscopy, quartz crystal microbalance ( QCM ), and FTIR have been utilized for aromatic hydrocarbon sensing applications based on these

3D printed sensing patches with embedded polymer optical fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Zubel, Michal G.; Sugden, Kate; Saez-Rodriguez, D.; Nielsen, K.; Bang, O.

2016-05-01

The first demonstration of a polymer optical fibre Bragg grating (POFBG) embedded in a 3-D printed structure is reported. Its cyclic strain performance and temperature characteristics are examined and discussed. The sensing patch has a repeatable strain sensitivity of 0.38 pm/μepsilon. Its temperature behaviour is unstable, with temperature sensitivity values varying between 30-40 pm/°C.

Energy-aware virtual network embedding in flexi-grid networks.

PubMed

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng

2017-11-27

Network virtualization technology has been proposed to allow multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network, which increases the utilization of the substrate network. Efficiently mapping VNs on the substrate network is a major challenge on account of the VN embedding (VNE) problem. Meanwhile, energy efficiency has been widely considered in the network design in terms of operation expenses and the ecological awareness. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the electricity cost of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low electricity cost. Numerical results show that the heuristic algorithm performs closely to the ILP for a small size network, and we also demonstrate its applicability to larger networks.

Fiber-Embedded Metallic Materials: From Sensing towards Nervous Behavior

PubMed Central

Saheb, Nouari; Mekid, Samir

2015-01-01

Embedding of fibers in materials has attracted serious attention from researchers and has become a new research trend. Such material structures are usually termed “smart” or more recently “nervous”. Materials can have the capability of sensing and responding to the surrounding environmental stimulus, in the former, and the capability of feeling multiple structural and external stimuli, while feeding information back to a controller for appropriate real-time action, in the latter. In this paper, embeddable fibers, embedding processes, and behavior of fiber-embedded metallic materials are reviewed. Particular emphasis has been given to embedding fiber Bragg grating (FBG) array sensors and piezo wires, because of their high potential to be used in nervous materials for structural health monitoring. Ultrasonic consolidation and laser-based layered manufacturing processes are discussed in detail because of their high potential to integrate fibers without disruption. In addition, current challenges associated with embedding fibers in metallic materials are highlighted and recommendations for future research work are set. PMID:28793689

Column generation algorithms for virtual network embedding in flexi-grid optical networks.

PubMed

Lin, Rongping; Luo, Shan; Zhou, Jingwei; Wang, Sheng; Chen, Bin; Zhang, Xiaoning; Cai, Anliang; Zhong, Wen-De; Zukerman, Moshe

2018-04-16

Network virtualization provides means for efficient management of network resources by embedding multiple virtual networks (VNs) to share efficiently the same substrate network. Such virtual network embedding (VNE) gives rise to a challenging problem of how to optimize resource allocation to VNs and to guarantee their performance requirements. In this paper, we provide VNE algorithms for efficient management of flexi-grid optical networks. We provide an exact algorithm aiming to minimize the total embedding cost in terms of spectrum cost and computation cost for a single VN request. Then, to achieve scalability, we also develop a heuristic algorithm for the same problem. We apply these two algorithms for a dynamic traffic scenario where many VN requests arrive one-by-one. We first demonstrate by simulations for the case of a six-node network that the heuristic algorithm obtains very close blocking probabilities to exact algorithm (about 0.2% higher). Then, for a network of realistic size (namely, USnet) we demonstrate that the blocking probability of our new heuristic algorithm is about one magnitude lower than a simpler heuristic algorithm, which was a component of an earlier published algorithm.

Design and implementation of a VoIP broadcasting service over embedded systems in a heterogeneous network environment.

PubMed

Leu, Jenq-Shiou; Lin, Wei-Hsiang; Hsieh, Wen-Bin; Lo, Chien-Chih

2014-01-01

As the digitization is integrated into daily life, media including video and audio are heavily transferred over the Internet nowadays. Voice-over-Internet Protocol (VoIP), the most popular and mature technology, becomes the focus attracting many researches and investments. However, most of the existing studies focused on a one-to-one communication model in a homogeneous network, instead of one-to-many broadcasting model among diverse embedded devices in a heterogeneous network. In this paper, we present the implementation of a VoIP broadcasting service on the open source-Linphone-in a heterogeneous network environment, including WiFi, 3G, and LAN networks. The proposed system featuring VoIP broadcasting over heterogeneous networks can be integrated with heterogeneous agile devices, such as embedded devices or mobile phones. VoIP broadcasting over heterogeneous networks can be integrated into modern smartphones or other embedded devices; thus when users run in a traditional AM/FM signal unreachable area, they still can receive the broadcast voice through the IP network. Also, comprehensive evaluations are conducted to verify the effectiveness of the proposed implementation.

Design and Implementation of a VoIP Broadcasting Service over Embedded Systems in a Heterogeneous Network Environment

PubMed Central

Lin, Wei-Hsiang; Hsieh, Wen-Bin; Lo, Chien-Chih

2014-01-01

As the digitization is integrated into daily life, media including video and audio are heavily transferred over the Internet nowadays. Voice-over-Internet Protocol (VoIP), the most popular and mature technology, becomes the focus attracting many researches and investments. However, most of the existing studies focused on a one-to-one communication model in a homogeneous network, instead of one-to-many broadcasting model among diverse embedded devices in a heterogeneous network. In this paper, we present the implementation of a VoIP broadcasting service on the open source—Linphone—in a heterogeneous network environment, including WiFi, 3G, and LAN networks. The proposed system featuring VoIP broadcasting over heterogeneous networks can be integrated with heterogeneous agile devices, such as embedded devices or mobile phones. VoIP broadcasting over heterogeneous networks can be integrated into modern smartphones or other embedded devices; thus when users run in a traditional AM/FM signal unreachable area, they still can receive the broadcast voice through the IP network. Also, comprehensive evaluations are conducted to verify the effectiveness of the proposed implementation. PMID:25300280

Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Motivation: Most functions within the cell emerge thanks to protein–protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable. Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions. Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction. Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. Availability: https://sites.google.com/site/carlovittoriocannistraci/home Contact: kalokagathos.agon@gmail.com or timothy.ravasi@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23812985

Reimagining Building Sensing and Control (Presentation)

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

Polese, L.

2014-06-01

Buildings are responsible for 40% of US energy consumption, and sensing and control technologies are an important element in creating a truly sustainable built environment. Motion-based occupancy sensors are often part of these control systems, but are usually altered or disabled in response to occupants' complaints, at the expense of energy savings. Can we leverage commodity hardware developed for other sectors and embedded software to produce more capable sensors for robust building controls? The National Renewable Energy Laboratory's (NREL) 'Image Processing Occupancy Sensor (IPOS)' is one example of leveraging embedded systems to create smarter, more reliable, multi-function sensors that openmore » the door to new control strategies for building heating, cooling, ventilation, and lighting control. In this keynote, we will discuss how cost-effective embedded systems are changing the state-of-the-art of building sensing and control.« less

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

A 300MHz Embedded Flash Memory with Pipeline Architecture and Offset-Free Sense Amplifiers for Dual-Core Automotive Microcontrollers

NASA Astrophysics Data System (ADS)

Kajiyama, Shinya; Fujito, Masamichi; Kasai, Hideo; Mizuno, Makoto; Yamaguchi, Takanori; Shinagawa, Yutaka

A novel 300MHz embedded flash memory for dual-core microcontrollers with a shared ROM architecture is proposed. One of its features is a three-stage pipeline read operation, which enables reduced access pitch and therefore reduces performance penalty due to conflict of shared ROM accesses. Another feature is a highly sensitive sense amplifier that achieves efficient pipeline operation with two-cycle latency one-cycle pitch as a result of a shortened sense time of 0.63ns. The combination of the pipeline architecture and proposed sense amplifiers significantly reduces access-conflict penalties with shared ROM and enhances performance of 32-bit RISC dual-core microcontrollers by 30%.

Detection of VX Simulants Using Piezoresistive Microcantilever Sensors

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

Porter, Timothy L.; Venedam, Richard J.; Kyle, Kyle

2011-05-28

Piezoresistive microcantilever sensors may be used in a variety of sensing applications, including chemical analytes and some types of biological species. These sensors employ a tiny piezoresistive microcantilever functionalized with a “sensing material” that acts as a probe for the desired analyte. In this study, the microcantilever was partially embedded into the sensing material, producing a sensor element that is highly rigid and resistant to shock, making it suitable for portable or handheld operation. The sensing material matrix used was Hypol, a hydrogel capable of preserving the bio-functionality of molecules embedded into it. This matrix was combined with acetylcholinesterase tomore » form the finished sensing material. Results of exposing these sensors to a VX simulant, malathion, are presented for both vapor and liquid environments.« less

Flight State Identification of a Self-Sensing Wing via an Improved Feature Selection Method and Machine Learning Approaches

PubMed Central

Chen, Xi; Wu, Qi; Ren, He; Chang, Fu-Kuo

2018-01-01

In this work, a data-driven approach for identifying the flight state of a self-sensing wing structure with an embedded multi-functional sensing network is proposed. The flight state is characterized by the structural vibration signals recorded from a series of wind tunnel experiments under varying angles of attack and airspeeds. A large feature pool is created by extracting potential features from the signals covering the time domain, the frequency domain as well as the information domain. Special emphasis is given to feature selection in which a novel filter method is developed based on the combination of a modified distance evaluation algorithm and a variance inflation factor. Machine learning algorithms are then employed to establish the mapping relationship from the feature space to the practical state space. Results from two case studies demonstrate the high identification accuracy and the effectiveness of the model complexity reduction via the proposed method, thus providing new perspectives of self-awareness towards the next generation of intelligent air vehicles. PMID:29710832

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

DTIC Science & Technology

2005-07-09

This final report summarizes the progress during the Phase I SBIR project entitled Embedded Electro - Optic Sensor Network for the On-Site Calibration...network based on an electro - optic field-detection technique (the Electro - optic Sensor Network, or ESN) for the performance evaluation of phased

Robustness and percolation of holes in complex networks

NASA Astrophysics Data System (ADS)

Zhou, Andu; Maletić, Slobodan; Zhao, Yi

2018-07-01

Efficient robustness and fault tolerance of complex network is significantly influenced by its connectivity, commonly modeled by the structure of pairwise relations between network elements, i.e., nodes. Nevertheless, aggregations of nodes build higher-order structures embedded in complex network, which may be more vulnerable when the fraction of nodes is removed. The structure of higher-order aggregations of nodes can be naturally modeled by simplicial complexes, whereas the removal of nodes affects the values of topological invariants, like the number of higher-dimensional holes quantified with Betti numbers. Following the methodology of percolation theory, as the fraction of nodes is removed, new holes appear, which have the role of merger between already present holes. In the present article, relationship between the robustness and homological properties of complex network is studied, through relating the graph-theoretical signatures of robustness and the quantities derived from topological invariants. The simulation results of random failures and intentional attacks on networks suggest that the changes of graph-theoretical signatures of robustness are followed by differences in the distribution of number of holes per cluster under different attack strategies. In the broader sense, the results indicate the importance of topological invariants research for obtaining further insights in understanding dynamics taking place over complex networks.

Maximizing Information Diffusion in the Cyber-physical Integrated Network †

PubMed Central

Lu, Hongliang; Lv, Shaohe; Jiao, Xianlong; Wang, Xiaodong; Liu, Juan

2015-01-01

Nowadays, our living environment has been embedded with smart objects, such as smart sensors, smart watches and smart phones. They make cyberspace and physical space integrated by their abundant abilities of sensing, communication and computation, forming a cyber-physical integrated network. In order to maximize information diffusion in such a network, a group of objects are selected as the forwarding points. To optimize the selection, a minimum connected dominating set (CDS) strategy is adopted. However, existing approaches focus on minimizing the size of the CDS, neglecting an important factor: the weight of links. In this paper, we propose a distributed maximizing the probability of information diffusion (DMPID) algorithm in the cyber-physical integrated network. Unlike previous approaches that only consider the size of CDS selection, DMPID also considers the information spread probability that depends on the weight of links. To weaken the effects of excessively-weighted links, we also present an optimization strategy that can properly balance the two factors. The results of extensive simulation show that DMPID can nearly double the information diffusion probability, while keeping a reasonable size of selection with low overhead in different distributed networks. PMID:26569254

Variable-Domain Displacement Transfer Functions for Converting Surface Strains into Deflections for Structural Deformed Shape Predictions

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2015-01-01

Variable-Domain Displacement Transfer Functions were formulated for shape predictions of complex wing structures, for which surface strain-sensing stations must be properly distributed to avoid jointed junctures, and must be increased in the high strain gradient region. Each embedded beam (depth-wise cross section of structure along a surface strain-sensing line) was discretized into small variable domains. Thus, the surface strain distribution can be described with a piecewise linear or a piecewise nonlinear function. Through discretization, the embedded beam curvature equation can be piece-wisely integrated to obtain the Variable-Domain Displacement Transfer Functions (for each embedded beam), which are expressed in terms of geometrical parameters of the embedded beam and the surface strains along the strain-sensing line. By inputting the surface strain data into the Displacement Transfer Functions, slopes and deflections along each embedded beam can be calculated for mapping out overall structural deformed shapes. A long tapered cantilever tubular beam was chosen for shape prediction analysis. The input surface strains were analytically generated from finite-element analysis. The shape prediction accuracies of the Variable- Domain Displacement Transfer Functions were then determined in light of the finite-element generated slopes and deflections, and were fofound to be comparable to the accuracies of the constant-domain Displacement Transfer Functions

ProMotE: an efficient algorithm for counting independent motifs in uncertain network topologies.

PubMed

Ren, Yuanfang; Sarkar, Aisharjya; Kahveci, Tamer

2018-06-26

Identifying motifs in biological networks is essential in uncovering key functions served by these networks. Finding non-overlapping motif instances is however a computationally challenging task. The fact that biological interactions are uncertain events further complicates the problem, as it makes the existence of an embedding of a given motif an uncertain event as well. In this paper, we develop a novel method, ProMotE (Probabilistic Motif Embedding), to count non-overlapping embeddings of a given motif in probabilistic networks. We utilize a polynomial model to capture the uncertainty. We develop three strategies to scale our algorithm to large networks. Our experiments demonstrate that our method scales to large networks in practical time with high accuracy where existing methods fail. Moreover, our experiments on cancer and degenerative disease networks show that our method helps in uncovering key functional characteristics of biological networks.

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Nanochannel Device with Embedded Nanopore: a New Approach for Single-Molecule DNA Analysis and Manipulation

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2013-03-01

Nanopore and nanochannel based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with embedded pore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a pore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We demonstrate that we can optically detect successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. In particular, we show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore, suggesting that the pore could be used as a nanoscale window through which to interrogate a nanochannel extended DNA molecule. Furthermore, electrical measurements through the nanopore are performed, indicating that DNA sensing is feasible using the nanochannel-nanopore device.

Introducing the idea of 'assumed shared food narratives' in the context of social networks: reflections from a qualitative study conducted in Nottingham, England.

PubMed

Bissell, Paul; Peacock, Marian; Holdsworth, Michelle; Powell, Katie; Wilcox, John; Clonan, Angie

2018-06-19

This study explores the ways in which social networks might shape accounts about food practices. Drawing on insights from the work of Christakis and Fowler () whose claims about the linkages between obesity and social networks have been the subject of vigorous debate in the sociological literature, we present qualitative data from a study of women's' accounts of social networks and food practices, conducted in Nottingham, England. We tentatively suggest that whilst social networks in their broadest sense, might shape what was perceived to be normal and acceptable in relation to food practices (and provide everyday discursive resources which normalise practice), the relationship between the two is more complex than the linear relationship proposed by Christakis and Fowler. Here, we introduce the idea of assumed shared food narratives (ASFNs), which, we propose, sheds light on motive talk about food practices, and which also provide practical and discursive resources to actors seeking to protect and defend against 'untoward' behaviour, in the context of public health messages around food and eating. We suggest that understanding ASFNs and the ways in which they are embedded in social networks represents a novel way of understanding food and eating practices from a sociological perspective. © 2018 Foundation for the Sociology of Health & Illness.

Embedded ubiquitous services on hospital information systems.

PubMed

Kuroda, Tomohiro; Sasaki, Hiroshi; Suenaga, Takatoshi; Masuda, Yasushi; Yasumuro, Yoshihiro; Hori, Kenta; Ohboshi, Naoki; Takemura, Tadamasa; Chihara, Kunihiro; Yoshihara, Hiroyuki

2012-11-01

A Hospital Information Systems (HIS) have turned a hospital into a gigantic computer with huge computational power, huge storage and wired/wireless local area network. On the other hand, a modern medical device, such as echograph, is a computer system with several functional units connected by an internal network named a bus. Therefore, we can embed such a medical device into the HIS by simply replacing the bus with the local area network. This paper designed and developed two embedded systems, a ubiquitous echograph system and a networked digital camera. Evaluations of the developed systems clearly show that the proposed approach, embedding existing clinical systems into HIS, drastically changes productivity in the clinical field. Once a clinical system becomes a pluggable unit for a gigantic computer system, HIS, the combination of multiple embedded systems with application software designed under deep consideration about clinical processes may lead to the emergence of disruptive innovation in the clinical field.

Mobile Monitoring and Embedded Control System for Factory Environment

PubMed Central

Lian, Kuang-Yow; Hsiao, Sung-Jung; Sung, Wen-Tsai

2013-01-01

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones. PMID:24351642

Mobile monitoring and embedded control system for factory environment.

PubMed

Lian, Kuang-Yow; Hsiao, Sung-Jung; Sung, Wen-Tsai

2013-12-17

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones.

Localized attacks on spatially embedded networks with dependencies.

PubMed

Berezin, Yehiel; Bashan, Amir; Danziger, Michael M; Li, Daqing; Havlin, Shlomo

2015-03-11

Many real world complex systems such as critical infrastructure networks are embedded in space and their components may depend on one another to function. They are also susceptible to geographically localized damage caused by malicious attacks or natural disasters. Here, we study a general model of spatially embedded networks with dependencies under localized attacks. We develop a theoretical and numerical approach to describe and predict the effects of localized attacks on spatially embedded systems with dependencies. Surprisingly, we find that a localized attack can cause substantially more damage than an equivalent random attack. Furthermore, we find that for a broad range of parameters, systems which appear stable are in fact metastable. Though robust to random failures-even of finite fraction-if subjected to a localized attack larger than a critical size which is independent of the system size (i.e., a zero fraction), a cascading failure emerges which leads to complete system collapse. Our results demonstrate the potential high risk of localized attacks on spatially embedded network systems with dependencies and may be useful for designing more resilient systems.

Structural health monitoring for DOT using magnetic shape memory alloy cables in concrete

NASA Astrophysics Data System (ADS)

Davis, Allen; Mirsayar, Mirmilad; Sheahan, Emery; Hartl, Darren

2018-03-01

Embedding shape memory alloy (SMA) wires in concrete components offers the potential to monitor their structural health via external magnetic field sensing. Currently, structural health monitoring (SHM) is dominated by acoustic emission and vibration-based methods. Thus, it is attractive to pursue alternative damage sensing techniques that may lower the cost or increase the accuracy of SHM. In this work, SHM via magnetic field detection applied to embedded magnetic shape memory alloy (MSMA) is demonstrated both experimentally and using computational models. A concrete beam containing iron-based MSMA wire is subjected to a 3-point bend test where structural damage is induced, thereby resulting in a localized phase change of the MSMA wire. Magnetic field lines passing through the embedded MSMA domain are altered by this phase change and can thus be used to detect damage within the structure. A good correlation is observed between the computational and experimental results. Additionally, the implementation of stranded MSMA cables in place of the MSMA wire is assessed through similar computational models. The combination of these computational models and their subsequent experimental validation provide sufficient support for the feasibility of SHM using magnetic field sensing via MSMA embedded components.

An Embedded Microretroreflector-Based Microfluidic Immunoassay Platform

PubMed Central

Raja, Balakrishnan; Pascente, Carmen; Knoop, Jennifer; Shakarisaz, David; Sherlock, Tim; Kemper, Steven; Kourentzi, Katerina; Renzi, Ronald F.; Hatch, Anson V.; Olano, Juan; Peng, Bi-Hung; Ruchhoeft, Paul; Willson, Richard

2017-01-01

We present a microfluidic immunoassay platform based on the use of linear microretroreflectors embedded in a transparent polymer layer as an optical sensing surface, and micron-sized magnetic particles as light-blocking labels. Retroreflectors return light directly to its source and are highly detectable using inexpensive optics. The analyte is immuno-magnetically pre-concentrated from a sample and then captured on an antibody-modified microfluidic substrate comprised of embedded microretroreflectors, thereby blocking reflected light. Fluidic force discrimination is used to increase specificity of the assay, following which a difference imaging algorithm that can see single 3 μm magnetic particles without optical calibration is used to detect and quantify signal intensity from each sub-array of retroreflectors. We demonstrate the utility of embedded microretroreflectors as a new sensing modality through a proof-of-concept immunoassay for a small, obligate intracellular bacterial pathogen, Rickettsia conorii, the causative agent of Mediterranean Spotted Fever. The combination of large sensing area, optimized surface chemistry and microfluidic protocols, automated image capture and analysis, and high sensitivity of the difference imaging results in a sensitive immunoassay with a limit of detection of roughly 4000 R. conorii per mL. PMID:27025227

Adsorption mechanism of SF6 decomposed species on pyridine-like PtN3 embedded CNT: A DFT study

NASA Astrophysics Data System (ADS)

Cui, Hao; Zhang, Xiaoxing; Chen, Dachang; Tang, Ju

2018-07-01

Metal-Nx embedded CNT have aroused considerable attention in the field of gas interaction due to their strong catalytic behavior, which provides prospective scopes for gas adsorption and sensing. Detecting SF6 decomposed species in certain devices is essential to guarantee their safe operation. In this work, we performed DFT method and simulated the adsorption of three SF6 decomposed gases (SO2, SOF2 and SO2F2) onto the PtN3 embedded CNT surface, in order to shed light on its adsorption ability and sensing mechanism. Results suggest that the CNT embedded with PtN3 center has strong interaction with these gas molecules, leading to high hybridization between Pt dopant and active atoms inner gas molecules. These interactions are assumed to be chemisorption due to the remarkable Ead and QT, thus resulting in dramatic deformations in electronic structure of PtN3-CNT near the Fermi level. Furthermore, the electronic redistribution cause the conductivity increase of proposed material in three systems, based on frontier molecular orbital theory. Our calculations attempt to suggest novel sensing material that are potentially employed in detection of SF6 decomposed components.

Enhanced Strain Measurement Range of an FBG Sensor Embedded in Seven-Wire Steel Strands.

PubMed

Kim, Jae-Min; Kim, Chul-Min; Choi, Song-Yi; Lee, Bang Yeon

2017-07-18

FBG sensors offer many advantages, such as a lack of sensitivity to electromagnetic waves, small size, high durability, and high sensitivity. However, their maximum strain measurement range is lower than the yield strain range (about 1.0%) of steel strands when embedded in steel strands. This study proposes a new FBG sensing technique in which an FBG sensor is recoated with polyimide and protected by a polyimide tube in an effort to enhance the maximum strain measurement range of FBG sensors embedded in strands. The validation test results showed that the proposed FBG sensing technique has a maximum strain measurement range of 1.73% on average, which is 1.73 times higher than the yield strain of the strands. It was confirmed that recoating the FBG sensor with polyimide and protecting the FBG sensor using a polyimide tube could effectively enhance the maximum strain measurement range of FBG sensors embedded in strands.

Damage Detection of a Concrete Column Subject to Blast Loads Using Embedded Piezoceramic Transducers.

PubMed

Xu, Kai; Deng, Qingshan; Cai, Lujun; Ho, Siuchun; Song, Gangbing

2018-04-28

Some of the most severe structural loadings come in the form of blast loads, which may be caused by severe accidents or even terrorist activities. Most commonly after exposure to explosive forces, a structure will suffer from different degrees of damage, and even progress towards a state of collapse. Therefore, damage detection of a structure subject to explosive loads is of importance. This paper proposes a new approach to damage detection of a concrete column structure subjected to blast loads using embedded piezoceramic smart aggregates (SAs). Since the sensors are embedded in the structure, the proposed active-sensing based approach is more sensitive to internal or through cracks than surface damage. In the active sensing approach, the embedded SAs act as actuators and sensors, that can respectively generate and detect stress waves. If the stress wave propagates across a crack, the energy of the wave attenuates, and the reduction of the energy compared to the healthy baseline is indicative of a damage. With a damage index matrix constructed by signals obtained from an array of SAs, cracks caused by blast loads can be detected throughout the structure. Conventional sensing methods such as the measurement of dynamic strain and acceleration were included in the experiment. Since columns are critical elements needed to prevent structural collapse, knowledge of their integrity and damage conditions is essential for safety after exposure to blast loads. In this research, a concrete column with embedded SAs was chosen as the specimen, and a series of explosive tests were conducted on the column. Experimental results reveal that surface damages, though appear severe, cause minor changes in the damage index, and through cracks result in significant increase of the damage index, demonstrating the effectiveness of the active sensing, enabled by embedded SAs, in damage monitoring of the column under blast loads, and thus providing a reliable indication of structural integrity in the event of blast loads.

Damage Detection of a Concrete Column Subject to Blast Loads Using Embedded Piezoceramic Transducers

PubMed Central

Deng, Qingshan; Cai, Lujun; Ho, Siuchun; Song, Gangbing

2018-01-01

Some of the most severe structural loadings come in the form of blast loads, which may be caused by severe accidents or even terrorist activities. Most commonly after exposure to explosive forces, a structure will suffer from different degrees of damage, and even progress towards a state of collapse. Therefore, damage detection of a structure subject to explosive loads is of importance. This paper proposes a new approach to damage detection of a concrete column structure subjected to blast loads using embedded piezoceramic smart aggregates (SAs). Since the sensors are embedded in the structure, the proposed active-sensing based approach is more sensitive to internal or through cracks than surface damage. In the active sensing approach, the embedded SAs act as actuators and sensors, that can respectively generate and detect stress waves. If the stress wave propagates across a crack, the energy of the wave attenuates, and the reduction of the energy compared to the healthy baseline is indicative of a damage. With a damage index matrix constructed by signals obtained from an array of SAs, cracks caused by blast loads can be detected throughout the structure. Conventional sensing methods such as the measurement of dynamic strain and acceleration were included in the experiment. Since columns are critical elements needed to prevent structural collapse, knowledge of their integrity and damage conditions is essential for safety after exposure to blast loads. In this research, a concrete column with embedded SAs was chosen as the specimen, and a series of explosive tests were conducted on the column. Experimental results reveal that surface damages, though appear severe, cause minor changes in the damage index, and through cracks result in significant increase of the damage index, demonstrating the effectiveness of the active sensing, enabled by embedded SAs, in damage monitoring of the column under blast loads, and thus providing a reliable indication of structural integrity in the event of blast loads. PMID:29710807

Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure

PubMed Central

Tang, Yongsheng; Wu, Zhishen

2016-01-01

Brillouin scattering-based distributed optical fiber (OF) sensing technique presents advantages for concrete structure monitoring. However, the existence of spatial resolution greatly decreases strain measurement accuracy especially around cracks. Meanwhile, the brittle feature of OF also hinders its further application. In this paper, the distributed OF sensor was firstly proposed as long-gauge sensor to improve strain measurement accuracy. Then, a new type of self-sensing fiber reinforced polymer (FRP) bar was developed by embedding the packaged long-gauge OF sensors into FRP bar, followed by experimental studies on strain sensing, temperature sensing and basic mechanical properties. The results confirmed the superior strain sensing properties, namely satisfied accuracy, repeatability and linearity, as well as excellent mechanical performance. At the same time, the temperature sensing property was not influenced by the long-gauge package, making temperature compensation easy. Furthermore, the bonding performance between self-sensing FRP bar and concrete was investigated to study its influence on the sensing. Lastly, the sensing performance was further verified with static experiments of concrete beam reinforced with the proposed self-sensing FRP bar. Therefore, the self-sensing FRP bar has potential applications for long-term structural health monitoring (SHM) as embedded sensors as well as reinforcing materials for concrete structures. PMID:26927110

Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure.

PubMed

Tang, Yongsheng; Wu, Zhishen

2016-02-25

Brillouin scattering-based distributed optical fiber (OF) sensing technique presents advantages for concrete structure monitoring. However, the existence of spatial resolution greatly decreases strain measurement accuracy especially around cracks. Meanwhile, the brittle feature of OF also hinders its further application. In this paper, the distributed OF sensor was firstly proposed as long-gauge sensor to improve strain measurement accuracy. Then, a new type of self-sensing fiber reinforced polymer (FRP) bar was developed by embedding the packaged long-gauge OF sensors into FRP bar, followed by experimental studies on strain sensing, temperature sensing and basic mechanical properties. The results confirmed the superior strain sensing properties, namely satisfied accuracy, repeatability and linearity, as well as excellent mechanical performance. At the same time, the temperature sensing property was not influenced by the long-gauge package, making temperature compensation easy. Furthermore, the bonding performance between self-sensing FRP bar and concrete was investigated to study its influence on the sensing. Lastly, the sensing performance was further verified with static experiments of concrete beam reinforced with the proposed self-sensing FRP bar. Therefore, the self-sensing FRP bar has potential applications for long-term structural health monitoring (SHM) as embedded sensors as well as reinforcing materials for concrete structures.

Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

NASA Astrophysics Data System (ADS)

Sadeghi-Goughari, M.; Mojra, A.; Sadeghi, S.

2016-02-01

Intraoperative Thermal Imaging (ITI) is a new minimally invasive diagnosis technique that can potentially locate margins of brain tumor in order to achieve maximum tumor resection with least morbidity. This study introduces a new approach to ITI based on artificial tactile sensing (ATS) technology in conjunction with artificial neural networks (ANN) and feasibility and applicability of this method in diagnosis and localization of brain tumors is investigated. In order to analyze validity and reliability of the proposed method, two simulations were performed. (i) An in vitro experimental setup was designed and fabricated using a resistance heater embedded in agar tissue phantom in order to simulate heat generation by a tumor in the brain tissue; and (ii) A case report patient with parafalcine meningioma was presented to simulate ITI in the neurosurgical procedure. In the case report, both brain and tumor geometries were constructed from MRI data and tumor temperature and depth of location were estimated. For experimental tests, a novel assisted surgery robot was developed to palpate the tissue phantom surface to measure temperature variations and ANN was trained to estimate the simulated tumor’s power and depth. Results affirm that ITI based ATS is a non-invasive method which can be useful to detect, localize and characterize brain tumors.

Force Field for Water Based on Neural Network.

PubMed

Wang, Hao; Yang, Weitao

2018-05-18

We developed a novel neural network based force field for water based on training with high level ab initio theory. The force field was built based on electrostatically embedded many-body expansion method truncated at binary interactions. Many-body expansion method is a common strategy to partition the total Hamiltonian of large systems into a hierarchy of few-body terms. Neural networks were trained to represent electrostatically embedded one-body and two-body interactions, which require as input only one and two water molecule calculations at the level of ab initio electronic structure method CCSD/aug-cc-pVDZ embedded in the molecular mechanics water environment, making it efficient as a general force field construction approach. Structural and dynamic properties of liquid water calculated with our force field show good agreement with experimental results. We constructed two sets of neural network based force fields: non-polarizable and polarizable force fields. Simulation results show that the non-polarizable force field using fixed TIP3P charges has already behaved well, since polarization effects and many-body effects are implicitly included due to the electrostatic embedding scheme. Our results demonstrate that the electrostatically embedded many-body expansion combined with neural network provides a promising and systematic way to build the next generation force fields at high accuracy and low computational costs, especially for large systems.

Next Generation RFID-Based Medical Service Management System Architecture in Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Tolentino, Randy S.; Lee, Kijeong; Kim, Yong-Tae; Park, Gil-Cheol

Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide unlimited future potentials most especially in healthcare systems. RFID is used to detect presence and location of objects while WSN is used to sense and monitor the environment. Integrating RFID with WSN not only provides identity and location of an object but also provides information regarding the condition of the object carrying the sensors enabled RFID tag. However, there isn't any flexible and robust communication infrastructure to integrate these devices into an emergency care setting. An efficient wireless communication substrate for medical devices that addresses ad hoc or fixed network formation, naming and discovery, transmission efficiency of data, data security and authentication, as well as filtration and aggregation of vital sign data need to be study and analyze. This paper proposed an efficient next generation architecture for RFID-based medical service management system in WSN that possesses the essential elements of each future medical application that are integrated with existing medical practices and technologies in real-time, remote monitoring, in giving medication, and patient status tracking assisted by embedded wearable wireless sensors which are integrated in wireless sensor network.

Embedding global and collective in a torus network with message class map based tree path selection

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

Chen, Dong; Coteus, Paul W.; Eisley, Noel A.

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computermore » program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.« less

Maintaining Privacy in Pervasive Computing - Enabling Acceptance of Sensor-based Services

NASA Astrophysics Data System (ADS)

Soppera, A.; Burbridge, T.

During the 1980s, Mark Weiser [1] predicted a world in which computing was so pervasive that devices embedded in the environment could sense their relationship to us and to each other. These tiny ubiquitous devices would continually feed information from the physical world into the information world. Twenty years ago, this vision was the exclusive territory of academic computer scientists and science fiction writers. Today this subject has become of interest to business, government, and society. Governmental authorities exercise their power through the networked environment. Credit card databases maintain our credit history and decide whether we are allowed to rent a house or obtain a loan. Mobile telephones can locate us in real time so that we do not miss calls. Within another 10 years, all sorts of devices will be connected through the network. Our fridge, our food, together with our health information, may all be networked for the purpose of maintaining diet and well-being. The Internet will move from being an infrastructure to connect computers, to being an infrastructure to connect everything [2, 3].

A seamless ubiquitous emergency medical service for crisis situations.

PubMed

Lin, Bor-Shing

2016-04-01

In crisis situations, a seamless ubiquitous communication is necessary to provide emergency medical service to save people's lives. An excellent prehospital emergency medicine provides immediate medical care to increase the survival rate of patients. On their way to the hospital, ambulance personnel must transmit real-time and uninterrupted patient information to the hospital to apprise the physician of the situation and provide options to the ambulance personnel. In emergency and crisis situations, many communication channels can be unserviceable because of damage to equipment or loss of power. Thus, data transmission over wireless communication to achieve uninterrupted network services is a major obstacle. This study proposes a mobile middleware for cognitive radio (CR) for improving the wireless communication link. CRs can sense their operating environment and optimize the spectrum usage so that the mobile middleware can integrate the existing wireless communication systems with a seamless communication service in heterogeneous network environments. Eventually, the proposed seamless mobile communication middleware was ported into an embedded system, which is compatible with the actual network environment without the need for changing the original system architecture. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Soft Somatosensitive Actuators via Embedded 3D Printing.

PubMed

Truby, Ryan L; Wehner, Michael; Grosskopf, Abigail K; Vogt, Daniel M; Uzel, Sebastien G M; Wood, Robert J; Lewis, Jennifer A

2018-04-01

Humans possess manual dexterity, motor skills, and other physical abilities that rely on feedback provided by the somatosensory system. Herein, a method is reported for creating soft somatosensitive actuators (SSAs) via embedded 3D printing, which are innervated with multiple conductive features that simultaneously enable haptic, proprioceptive, and thermoceptive sensing. This novel manufacturing approach enables the seamless integration of multiple ionically conductive and fluidic features within elastomeric matrices to produce SSAs with the desired bioinspired sensing and actuation capabilities. Each printed sensor is composed of an ionically conductive gel that exhibits both long-term stability and hysteresis-free performance. As an exemplar, multiple SSAs are combined into a soft robotic gripper that provides proprioceptive and haptic feedback via embedded curvature, inflation, and contact sensors, including deep and fine touch contact sensors. The multimaterial manufacturing platform enables complex sensing motifs to be easily integrated into soft actuating systems, which is a necessary step toward closed-loop feedback control of soft robots, machines, and haptic devices. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Embedded 32-bit Differential Pulse Voltammetry (DPV) Technique for 3-electrode Cell Sensing

NASA Astrophysics Data System (ADS)

N, Aqmar N. Z.; Abdullah, W. F. H.; Zain, Z. M.; Rani, S.

2018-03-01

This paper addresses the development of differential pulse voltammetry (DPV) embedded algorithm using an ARM cortex processor with new developed potentiostat circuit design for in-situ 3-electrode cell sensing. This project is mainly to design a low cost potentiostat for the researchers in laboratories. It is required to develop an embedded algorithm for analytical technique to be used with the designed potentiostat. DPV is one of the most familiar pulse technique method used with 3-electrode cell sensing in chemical studies. Experiment was conducted on 10mM solution of Ferricyanide using the designed potentiostat and the developed DPV algorithm. As a result, the device can generate an excitation signal of DPV from 0.4V to 1.2V and produced a peaked voltammogram with relatively small error compared to the commercial potentiostat; which is only 6.25% difference in peak potential reading. The design of potentiostat device and its DPV algorithm is verified.

Piezoresistive effect of the carbon nanotube yarn embedded axially into the 3D braided composite

NASA Astrophysics Data System (ADS)

Ma, Xin; Cao, Xiaona

2018-06-01

A new method for monitoring 3D braided composite structure health in real time by embedding the carbon nanotube yarn, based on its piezoresistivity, in the composite axially has been designed. The experimental system for piezoresistive effect detection of the carbon nanotube yarn in the 3D braided composite was built, and the sensing characteristics has been analyzed for further research. Compared with other structural health monitoring methods, the monitoring technique with carbon nanotubes yarns is more suitable for internal damage detection immediately, in addition the strength of the composite can be increased by embedding carbon nanotubes yarns. This method can also be used for strain sensing, the development of intelligent materials and structure systems.

Soft-error tolerance and energy consumption evaluation of embedded computer with magnetic random access memory in practical systems using computer simulations

NASA Astrophysics Data System (ADS)

Nebashi, Ryusuke; Sakimura, Noboru; Sugibayashi, Tadahiko

2017-08-01

We evaluated the soft-error tolerance and energy consumption of an embedded computer with magnetic random access memory (MRAM) using two computer simulators. One is a central processing unit (CPU) simulator of a typical embedded computer system. We simulated the radiation-induced single-event-upset (SEU) probability in a spin-transfer-torque MRAM cell and also the failure rate of a typical embedded computer due to its main memory SEU error. The other is a delay tolerant network (DTN) system simulator. It simulates the power dissipation of wireless sensor network nodes of the system using a revised CPU simulator and a network simulator. We demonstrated that the SEU effect on the embedded computer with 1 Gbit MRAM-based working memory is less than 1 failure in time (FIT). We also demonstrated that the energy consumption of the DTN sensor node with MRAM-based working memory can be reduced to 1/11. These results indicate that MRAM-based working memory enhances the disaster tolerance of embedded computers.

Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

PubMed Central

2015-01-01

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN2 vs immediate flash freezing (iFF) in LN2 on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen. PMID:24927040

Innovative Embedded Fiber Sensor System for Spacecraft's Health in Situ Monitoring

NASA Astrophysics Data System (ADS)

Haddad, E.; Kruzelecky, R.; Zou, J.; Wong, B.; Mohammad, N.; Thatte, G.; Jamroz, W.; Riendeau, S.

2009-01-01

Monitoring of various parameters in satellites is desirable to provide the necessary information on the condition and status of the spacecraft and its various subsystems (AOCS, thermal, propulsion, power, mechanisms etc.) throughout its lifecycle. Fiber-Optic Bragg Grating (FBG) sensors represent an alternative to current technological approaches, enabling in situ distributed dynamic health monitoring, to provide a mapping of the spacecraft strain and temperature distributions, for varying operating and orbital conditions. In addition, these sensors may be implemented in the very early spacecraft fabrication stages, as built-in testing and diagnostic tools, and then used continuously through the mission phases until the end of the spacecraft mission. This can substantially reduce the cost of ground qualification and facilitate improved spacecraft design. MPBC has developed and ground qualified a demonstrator fiber sensor network, the Fiber Sensor Demonstrator (FSD) that has been successfully integrated with ESA's Proba-2. This is scheduled to launch in the fall of 2008, and will be the first complete fiber-optic sensing system in space. The advantages of the MPBC approach include a central interrogation system that can be used to control a multi-parameter sensing incorporating various types of sensors. Using a combination of both parallel signal distribution and serial wavelength division sensor multiplexing along single strands of optical fiber enables a high sensor capacity. In a continuous effort, MPB Communications (MPBC) is developing an innovative Embedded Distributed Fiber Sensor (EDFOS) within space composite structures. It addresses the challenges of embedding very thin fiber sensors within a selected material matrix, the decoupling of the strain and temperature effects on the fiber, and the sensor distribution. The embedded sensor approach allows the sensor system to follow the status of the space structure through its entire life cycle; from fabrication and assembly, to ground testing, to the space mission itself. By providing a history of the structure, any changes are more readily discernable, and the in situ sensor information can be used to further improve the design and reliability of the structure.

An embedded stress sensor for concrete SHM based on amorphous ferromagnetic microwires.

PubMed

Olivera, Jesús; González, Margarita; Fuente, José Vicente; Varga, Rastislav; Zhukov, Arkady; Anaya, José Javier

2014-10-24

A new smart concrete aggregate design as a candidate for applications in structural health monitoring (SHM) of critical elements in civil infrastructure is proposed. The cement-based stress/strain sensor was developed by utilizing the stress/strain sensing properties of a magnetic microwire embedded in cement-based composite (MMCC). This is a contact-less type sensor that measures variations of magnetic properties resulting from stress variations. Sensors made of these materials can be designed to satisfy the specific demand for an economic way to monitor concrete infrastructure health. For this purpose, we embedded a thin magnetic microwire in the core of a cement-based cylinder, which was inserted into the concrete specimen under study as an extra aggregate. The experimental results show that the embedded MMCC sensor is capable of measuring internal compressive stress around the range of 1-30 MPa. Two stress sensing properties of the embedded sensor under uniaxial compression were studied: the peak amplitude and peak position of magnetic switching field. The sensitivity values for the amplitude and position within the measured range were 5 mV/MPa and 2.5 µs/MPa, respectively.

Simulation of Attacks for Security in Wireless Sensor Network.

PubMed

Diaz, Alvaro; Sanchez, Pablo

2016-11-18

The increasing complexity and low-power constraints of current Wireless Sensor Networks (WSN) require efficient methodologies for network simulation and embedded software performance analysis of nodes. In addition, security is also a very important feature that has to be addressed in most WSNs, since they may work with sensitive data and operate in hostile unattended environments. In this paper, a methodology for security analysis of Wireless Sensor Networks is presented. The methodology allows designing attack-aware embedded software/firmware or attack countermeasures to provide security in WSNs. The proposed methodology includes attacker modeling and attack simulation with performance analysis (node's software execution time and power consumption estimation). After an analysis of different WSN attack types, an attacker model is proposed. This model defines three different types of attackers that can emulate most WSN attacks. In addition, this paper presents a virtual platform that is able to model the node hardware, embedded software and basic wireless channel features. This virtual simulation analyzes the embedded software behavior and node power consumption while it takes into account the network deployment and topology. Additionally, this simulator integrates the previously mentioned attacker model. Thus, the impact of attacks on power consumption and software behavior/execution-time can be analyzed. This provides developers with essential information about the effects that one or multiple attacks could have on the network, helping them to develop more secure WSN systems. This WSN attack simulator is an essential element of the attack-aware embedded software development methodology that is also introduced in this work.

The Role of Percolation Theory in Developing Next Generation Smart Nanomaterials

NASA Astrophysics Data System (ADS)

Simien, Daneesh

2016-01-01

The incorporation of small volume fractions of nanoscale graphitic particles into varied base materials has been explored across fields ranging from automotive to aerospace to commercial plastics, with the goal of utilizing their enhanced thermal conductivity, electrical conductivity or mechanical strength. Percolation theory has emerged as a useful tool to aid in mapping and predicting the enhancement of properties based on the size and conductivity of incorporated single-walled carbon nanotubes relative to their less conductive base materials. These tools can aid researchers in the development of next generation smart nanomaterials. In this paper, we discuss the use of homogeneous fractions of length- or chirality-sorted single-walled carbon nanotubes (SWNTs) which are incorporated into thin film networks, and cement composites, and are evaluated in terms of their conductivity, mechanical properties and noise spectrum at critical percolation. We demonstrate that, near the percolation threshold, the conductivity of these highly characterized SWNT films exhibits a power law dependence on the network geometrical parameters. We also present our findings on the development of incorporated thin film SWNTs for the development of sensing technology for novel non-destructive failure diagnostic applications. SWNTs are able to be used as benign inclusions, capable of active sensing, when incorporated into cement-based composites for the purpose of detecting crack initiation. As such, we investigate the use of homogeneous length-sorted SWNTs that are randomly distributed in percolated networks capable of being an internal responsive net mechanism. Our findings demonstrate increased microstructure sensitivity of our networks for our shorter length nanotubes near their critical percolation threshold. This shows promise for the development of even more sensitive, embedded piezo-resistive SWNT-based sensors for preemptive failure detection technology.

Use of Student Experiments for Teaching Embedded Software Development Including HW/SW Co-Design

ERIC Educational Resources Information Center

Mitsui, H.; Kambe, H.; Koizumi, H.

2009-01-01

Embedded systems have been applied widely, not only to consumer products and industrial machines, but also to new applications such as ubiquitous or sensor networking. The increasing role of software (SW) in embedded system development has caused a great demand for embedded SW engineers, and university education for embedded SW engineering has…

Atom-Photon Coupling from Nitrogen-vacancy Centres Embedded in Tellurite Microspheres

NASA Astrophysics Data System (ADS)

Ruan, Yinlan; Gibson, Brant C.; Lau, Desmond W. M.; Greentree, Andrew D.; Ji, Hong; Ebendorff-Heidepriem, Heike; Johnson, Brett C.; Ohshima, Takeshi; Monro, Tanya M.

2015-06-01

We have developed a technique for creating high quality tellurite microspheres with embedded nanodiamonds (NDs) containing nitrogen-vacancy (NV) centres. This hybrid method allows fluorescence of the NVs in the NDs to be directly, rather than evanescently, coupled to the whispering gallery modes of the tellurite microspheres at room temperature. As a demonstration of its sensing potential, shifting of the resonance peaks is also demonstrated by coating a sphere surface with a liquid layer. This new approach is a robust way of creating cavities for use in quantum and sensing applications.

From Micro to Nano: The Evolution of Wireless Sensor-Based Health Care.

PubMed

Sarkar, Subhadeep; Misra, Sudip

2016-01-01

Over the past decade, embedded systems and microelectromechanical systems have evolved in a radical way, redefining our standard of living and enhancing the quality of life. Health care, among various other fields, has benefited vastly from this technological development. The concept of using sensors for health care purposes originated in the late 1980s when sensors were developed to measure certain physiological parameters associated with the human body. In traditional sensor nodes, the signal sources are mostly different environmental phenomena (such as temperature, vibration, and luminosity) or man-made events (such as intrusion and mobile target tracking), whereas in case of the physiological sensors, the signal source is living human tissue. These sensor nodes, as their primary sensing element, have a diaphragm that converts pressure into displacement. This displacement, in turn, is subsequently transformed into an electrical signal. The concept of wireless physiological sensor nodes, however, gained popularity in the mid-2000s, with the sensed data from the nodes transmitted to the hub via a wireless medium. The network formed by this heterogeneous set of wireless body sensor nodes is termed a wireless body-area network (WBAN). Each WBAN is essentially a composition of multiple wireless body sensor nodes and a single hub. The hub is primarily responsible for acquisition of the raw sensed data from all the component sensor nodes and first-level aggregation of the data before transmitting the aggregated data for further analysis to a remote data acquisition center. Here, we outline the evolution of WBANs in the context of modern health care and its convergence with nanotechnology.

Ultrasoft Electronics for Hyperelastic Strain, Pressure, and Direct Curvature Sensing

NASA Astrophysics Data System (ADS)

Majidi, Carmel; Kramer, Rebecca; Wood, Robert

2011-03-01

Progress in soft robotics, wearable computing, and programmable matter demands a new class of ultrasoft electronics for tactile control, contact detection, and deformation mapping. This next generation of sensors will remain electrically functional under extreme deformation without influencing the natural mechanics of the host system. Ultrasoft strain and pressure sensing has previously been demonstrated with elastomer sheets (eg. PDMS, silicone rubber) embedded with microchannels of conductive liquid (mercury, eGaIn). Building on these efforts, we introduce a novel method for direct curvature sensing that registers the location and intensity of surface curvature. An elastomer sheet is embedded with micropatterned cavities and microchannels of conductive liquid. Bending the elastomer or placing it on a curved surface leads to a change in channel cross-section and a corresponding change in its electrical resistance. In contrast to conventional methods of curvature sensing, this approach does not depend on semi-rigid components or differential strain measurement. Direct curvature sensing completes the portfolio of sensing elements required to completely map hyperelastic deformation for future soft robotics and computing. NSF MRSEC DMR-0820484.

Accurate real-time sensing tip for aqueous NO with optical fibers embedded in active hydrogel waveguide

NASA Astrophysics Data System (ADS)

Chung, Chieh-Wen; Tsai, May-Jywan; Lin, Peng-Wei; Huang, Ding-Wen; Wang, Kuan-Hsun; Chen, Yu-An; Meng, Hsin-Fei; Zan, Hsiao-Wen; Cheng, Henrich; Tong, Limin; Zhang, Lei; Horng, Sheng-Fu; Hung, Cheng-Hsiung

2018-02-01

A NO sensing tip is made by inserting two parallel optical fibers inside a poly 2-hydroxyethyl methacrylate (PolyHEMA) hydrogel waveguide mixed with the probe molecule 1, 2-Diaminoanthraquinone (DAQ). There is a length difference of 1 mm between the two fibers, and the light has to propagate through the difference from the short fiber to the long fiber. The total cross section area of the active hydrogel waveguide embedded with the fibers is only 3mm x 1.2 mm. For practical use the tip is housed in a needle for mechanical protection and the sensing tip is able to detect aqueous NO concentration around 1 μM with time resolution about 5 minutes. Such a sensing tip can be used to monitor the medical conditions inside the brain after a stroke or a brain injury.

Enhanced Strain Measurement Range of an FBG Sensor Embedded in Seven-Wire Steel Strands

PubMed Central

Kim, Jae-Min; Kim, Chul-Min; Choi, Song-Yi

2017-01-01

FBG sensors offer many advantages, such as a lack of sensitivity to electromagnetic waves, small size, high durability, and high sensitivity. However, their maximum strain measurement range is lower than the yield strain range (about 1.0%) of steel strands when embedded in steel strands. This study proposes a new FBG sensing technique in which an FBG sensor is recoated with polyimide and protected by a polyimide tube in an effort to enhance the maximum strain measurement range of FBG sensors embedded in strands. The validation test results showed that the proposed FBG sensing technique has a maximum strain measurement range of 1.73% on average, which is 1.73 times higher than the yield strain of the strands. It was confirmed that recoating the FBG sensor with polyimide and protecting the FBG sensor using a polyimide tube could effectively enhance the maximum strain measurement range of FBG sensors embedded in strands. PMID:28718826

Discriminative graph embedding for label propagation.

PubMed

Nguyen, Canh Hao; Mamitsuka, Hiroshi

2011-09-01

In many applications, the available information is encoded in graph structures. This is a common problem in biological networks, social networks, web communities and document citations. We investigate the problem of classifying nodes' labels on a similarity graph given only a graph structure on the nodes. Conventional machine learning methods usually require data to reside in some Euclidean spaces or to have a kernel representation. Applying these methods to nodes on graphs would require embedding the graphs into these spaces. By embedding and then learning the nodes on graphs, most methods are either flexible with different learning objectives or efficient enough for large scale applications. We propose a method to embed a graph into a feature space for a discriminative purpose. Our idea is to include label information into the embedding process, making the space representation tailored to the task. We design embedding objective functions that the following learning formulations become spectral transforms. We then reformulate these spectral transforms into multiple kernel learning problems. Our method, while being tailored to the discriminative tasks, is efficient and can scale to massive data sets. We show the need of discriminative embedding on some simulations. Applying to biological network problems, our method is shown to outperform baselines.

Embedding global barrier and collective in torus network with each node combining input from receivers according to class map for output to senders

DOEpatents

Chen, Dong; Coteus, Paul W; Eisley, Noel A; Gara, Alan; Heidelberger, Philip; Senger, Robert M; Salapura, Valentina; Steinmacher-Burow, Burkhard; Sugawara, Yutaka; Takken, Todd E

2013-08-27

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computer program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

Energy-efficient sensing in wireless sensor networks using compressed sensing.

PubMed

Razzaque, Mohammad Abdur; Dobson, Simon

2014-02-12

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.

Trade in and Valuation of Virtual Water Impacts in a City: A Case Study Of Flagstaff, Arizona

NASA Astrophysics Data System (ADS)

Rushforth, R.; Ruddell, B. L.

2013-12-01

An increasingly intense component of the global coupled natural and human system (CNH) is the economic trade of various types of resources and the outsourcing of resource impacts between geographically distant economic systems. The human economy's trade arrangements allow specific localities, especially cities, to exceed spatially local resource stock sustainability and footprint constraints, as evidenced in the urban metabolism literature. Each movement or trade of a resource along a network is associated with an embedded or 'virtual' exchange of indirect impacts on the inputs to the production process. The networked trade of embedded resources, therefore, is an essential human adaptation to resource limitations. Using the Embedded Resource Impact Accounting (ERA) framework, we examine the network of embedded water flows created through the trade of goods and services and economic development in Flagstaff, Arizona, and associate these flows with the creation of value in sectors of the economy

The Shale Hills Critical Zone Observatory for Embedded Sensing and Simulation

NASA Astrophysics Data System (ADS)

Duffy, C.; Davis, K.; Kane, T.; Boyer, E.

2009-04-01

The future of environmental observing systems will utilize embedded sensor networks with continuous real-time measurement of hydrologic, atmospheric, biogeochemical, and ecological variables across diverse terrestrial environments. Embedded environmental sensors, benefitting from advances in information sciences, networking technology, materials science, computing capacity, and data synthesis methods, are undergoing revolutionary change. It is now possible to field spatially-distributed, multi-node sensor networks that provide density and spatial coverage previously accessible only via numerical simulation. At the same time, computational tools are advancing rapidly to the point where it is now possible to simulate the physical processes controlling individual parcels of water and solutes through the complete terrestrial water cycle. Our goal for the Penn State Critical Zone Observatory is to apply environmental sensor arrays, integrated hydrologic models deployed and coordinated at a testbed within the Penn State Experimental Forest. The NSF-funded CZO is designed to observe the detailed space and time complexities of the water and energy cycle for a watershed and ultimately the river basin for all physical states and fluxes (groundwater, soil moisture, temperature, streamflow, latent heat, snowmelt, chemistry, isotopes etc.). Presently fully-coupled physical models are being developed that link the atmosphere-land-vegetation-subsurface system into a fully-coupled distributed system. During the last 5 years the Penn State Integrated Hydrologic Modeling System has been under development as an open-source community modeling project funded by NSF EAR/GEO and NSF CBET/ENG. PIHM represents a strategy for the formulation and solution of fully-coupled process equations at the watershed and river basin scales, and includes a tightly coupled GIS tool for data handling, domain decomposition, optimal unstructured grid generation, and model parameterization. (PIHM; http://sourceforge.net/projects/pihmmodel/; http://sourceforge.net/projects/pihmgis/ ) The CZO sensor and simulation system is being developed to have the following elements: 1) extensive, spatially-distributed smart sensor networks to gather intensive soil, geologic, hydrologic, geochemical and isotopic data; 2) spatially-explicit multiphysics models/solutions of the land-subsurface-vegetation-atmosphere system; and 3) parallel/distributed, adaptive algorithms for rapidly simulating the states of the watershed at high resolution, and 4) signal processing tools for data mining and parameter estimation. The prototype proposed sensor array and simulation system proposed is demonstrated with preliminary results from our first year.

Real-Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie; Oliver, Brett; Brickner, Christopher

2012-01-01

A document discusses the utilization of embedded clocks inside of operating network data links as an auxiliary clock source to satisfy local oscillator monitoring requirements. Modem network interfaces, typically serial network links, often contain embedded clocking information of very tight precision to recover data from the link. This embedded clocking data can be utilized by the receiving device to monitor the local oscillator for tolerance to required specifications, often important in high-integrity fault-tolerant applications. A device can utilize a received embedded clock to determine if the local or the remote device is out of tolerance by using a single link. The local device can determine if it is failing, assuming a single fault model, with two or more active links. Network fabric components, containing many operational links, can potentially determine faulty remote or local devices in the presence of multiple faults. Two methods of implementation are described. In one method, a recovered clock can be directly used to monitor the local clock as a direct replacement of an external local oscillator. This scheme is consistent with a general clock monitoring function whereby clock sources are clocking two counters and compared over a fixed interval of time. In another method, overflow/underflow conditions can be used to detect clock relationships for monitoring. These network interfaces often provide clock compensation circuitry to allow data to be transferred from the received (network) clock domain to the internal clock domain. This circuit could be modified to detect overflow/underflow conditions of the buffering required and report a fast or slow receive clock, respectively.

Simulation of Attacks for Security in Wireless Sensor Network

PubMed Central

Diaz, Alvaro; Sanchez, Pablo

2016-01-01

The increasing complexity and low-power constraints of current Wireless Sensor Networks (WSN) require efficient methodologies for network simulation and embedded software performance analysis of nodes. In addition, security is also a very important feature that has to be addressed in most WSNs, since they may work with sensitive data and operate in hostile unattended environments. In this paper, a methodology for security analysis of Wireless Sensor Networks is presented. The methodology allows designing attack-aware embedded software/firmware or attack countermeasures to provide security in WSNs. The proposed methodology includes attacker modeling and attack simulation with performance analysis (node’s software execution time and power consumption estimation). After an analysis of different WSN attack types, an attacker model is proposed. This model defines three different types of attackers that can emulate most WSN attacks. In addition, this paper presents a virtual platform that is able to model the node hardware, embedded software and basic wireless channel features. This virtual simulation analyzes the embedded software behavior and node power consumption while it takes into account the network deployment and topology. Additionally, this simulator integrates the previously mentioned attacker model. Thus, the impact of attacks on power consumption and software behavior/execution-time can be analyzed. This provides developers with essential information about the effects that one or multiple attacks could have on the network, helping them to develop more secure WSN systems. This WSN attack simulator is an essential element of the attack-aware embedded software development methodology that is also introduced in this work. PMID:27869710

Biomolecule-embedded metal-organic frameworks as an innovative sensing platform.

PubMed

Kempahanumakkagari, Sureshkumar; Kumar, Vanish; Samaddar, Pallabi; Kumar, Pawan; Ramakrishnappa, Thippeswamy; Kim, Ki-Hyun

Technological advancements combined with materials research have led to the generation of enormous types of novel substrates and materials for use in various biological/medical, energy, and environmental applications. Lately, the embedding of biomolecules in novel and/or advanced materials (e.g., metal-organic frameworks (MOFs), nanoparticles, hydrogels, graphene, and their hybrid composites) has become a vital research area in the construction of an innovative platform for various applications including sensors (or biosensors), biofuel cells, and bioelectronic devices. Due to the intriguing properties of MOFs (e.g., framework architecture, topology, and optical properties), they have contributed considerably to recent progresses in enzymatic catalysis, antibody-antigen interactions, or many other related approaches. Here, we aim to describe the different strategies for the design and synthesis of diverse biomolecule-embedded MOFs for various sensing (e.g., optical, electrochemical, biological, and miscellaneous) techniques. Additionally, the benefits and future prospective of MOFs-based biomolecular immobilization as an innovative sensing platform are discussed along with the evaluation on their performance to seek for further development in this emerging research area. Copyright © 2018. Published by Elsevier Inc.

Nanofluidic Device with Embedded Nanopore

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2014-03-01

Nanofluidic based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with nanpore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a nanopore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We demonstrate that we can detect - using fluorescent microscopy - successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. We also show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore until a certain voltage bias is added.

Wireless sensor network

NASA Astrophysics Data System (ADS)

Perotti, Jose M.; Lucena, Angel R.; Mullenix, Pamela A.; Mata, Carlos T.

2006-05-01

Current and future requirements of aerospace sensors and transducers demand the design and development of a new family of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors and transducers will possess a certain degree of intelligence in order to provide the end user with critical data in a more efficient manner. Communication between networks of traditional or next-generation sensors can be accomplished by a Wireless Sensor Network (WSN) developed by NASA's Instrumentation Branch and ASRC Aerospace Corporation at Kennedy Space Center (KSC), consisting of at least one central station and several remote stations and their associated software. The central station is application-dependent and can be implemented on different computer hardware, including industrial, handheld, or PC-104 single-board computers, on a variety of operating systems: embedded Windows, Linux, VxWorks, etc. The central stations and remote stations share a similar radio frequency (RF) core module hardware that is modular in design. The main components of the remote stations are an RF core module, a sensor interface module, batteries, and a power management module. These modules are stackable, and a common bus provides the flexibility to stack other modules for additional memory, increased processing, etc. WSN can automatically reconfigure to an alternate frequency if interference is encountered during operation. In addition, the base station will autonomously search for a remote station that was perceived to be lost, using relay stations and alternate frequencies. Several wireless remote-station types were developed and tested in the laboratory to support different sensing technologies, such as resistive temperature devices, silicon diodes, strain gauges, pressure transducers, and hydrogen leak detectors.

RF switching network: a novel technique for IR sensing

NASA Astrophysics Data System (ADS)

Mechtel, Deborah M.; Jenkins, R. Brian; Joyce, Peter J.; Nelson, Charles L.

2016-05-01

Rapid sensing of near infrared (IR) energy on a composite structure would provide information that could mitigate damage to composite structures. This paper describes a novel technique that implements photoconductive sensors in a radio frequency (RF) switching network designed to locate in real time the position and intensity of IR radiation incident on a composite structure. In the implementation described here, photoconductive sensors act as rapid response switches in a two layer RF network embedded in an FR-4 laminate. To detect radiation, phosphorous doped silicon photoconductive sensors are inserted in GHz range RF transmission lines. Photoconductive sensors use semiconductor materials that are optically sensitive at material dependent wavelengths. Incident radiation at the appropriate wavelength produces hole-electron pairs, so that the semiconductor becomes a conductor. By permitting signal propagation only when a sensor is illuminated, the RF signals are selectively routed from the lower layer transmission lines to the upper layer lines, thereby pinpointing the location and strength of incident radiation on a structure. Simulations based on a high frequency 3D planar electromagnetics model are presented and compared to experimental results. Experimental results are described for GHz range RF signal control for 300 mW and 180 mW incident energy from 975 nm and 1060 nm wavelength lasers respectively, where upon illumination, RF transmission line signal output power doubled when compared to non-illuminated results. Experimental results are reported for 100 W incident energy from a 1060 nm laser. Test results illustrate that real-time signal processing would permit a structure or vehicle to be controlled in response to incident radiation

Embedded with Facebook: DoD Faces Risks from Social Media

DTIC Science & Technology

2011-06-01

appropriate conduct. Embedded with Social Media Today Facebook is the world’s dominant social network site . Facebook boasts over 600 million active users...billion minutes on the site each month [4]. Facebook is also the most popular social network site for DoD personnel. Using our techniques for correlating...media sites [6], directing that the Non-classified Internet Protocol Router Network (NIPRNET) be configured to allow access to social media, e-mail

Silicon-embedded copper nanostructure network for high energy storage

DOEpatents

Yu, Tianyue

2018-01-23

Provided herein are nanostructure networks having high energy storage, electrochemically active electrode materials including nanostructure networks having high energy storage, as well as electrodes and batteries including the nanostructure networks having high energy storage. According to various implementations, the nanostructure networks have high energy density as well as long cycle life. In some implementations, the nanostructure networks include a conductive network embedded with electrochemically active material. In some implementations, silicon is used as the electrochemically active material. The conductive network may be a metal network such as a copper nanostructure network. Methods of manufacturing the nanostructure networks and electrodes are provided. In some implementations, metal nanostructures can be synthesized in a solution that contains silicon powder to make a composite network structure that contains both. The metal nanostructure growth can nucleate in solution and on silicon nanostructure surfaces.

Silicon-embedded copper nanostructure network for high energy storage

DOEpatents

Yu, Tianyue

2016-03-15

Provided herein are nanostructure networks having high energy storage, electrochemically active electrode materials including nanostructure networks having high energy storage, as well as electrodes and batteries including the nanostructure networks having high energy storage. According to various implementations, the nanostructure networks have high energy density as well as long cycle life. In some implementations, the nanostructure networks include a conductive network embedded with electrochemically active material. In some implementations, silicon is used as the electrochemically active material. The conductive network may be a metal network such as a copper nanostructure network. Methods of manufacturing the nanostructure networks and electrodes are provided. In some implementations, metal nanostructures can be synthesized in a solution that contains silicon powder to make a composite network structure that contains both. The metal nanostructure growth can nucleate in solution and on silicon nanostructure surfaces.

A FPGA embedded web server for remote monitoring and control of smart sensors networks.

PubMed

Magdaleno, Eduardo; Rodríguez, Manuel; Pérez, Fernando; Hernández, David; García, Enrique

2013-12-27

This article describes the implementation of a web server using an embedded Altera NIOS II IP core, a general purpose and configurable RISC processor which is embedded in a Cyclone FPGA. The processor uses the μCLinux operating system to support a Boa web server of dynamic pages using Common Gateway Interface (CGI). The FPGA is configured to act like the master node of a network, and also to control and monitor a network of smart sensors or instruments. In order to develop a totally functional system, the FPGA also includes an implementation of the time-triggered protocol (TTP/A). Thus, the implemented master node has two interfaces, the webserver that acts as an Internet interface and the other to control the network. This protocol is widely used to connecting smart sensors and actuators and microsystems in embedded real-time systems in different application domains, e.g., industrial, automotive, domotic, etc., although this protocol can be easily replaced by any other because of the inherent characteristics of the FPGA-based technology.

A FPGA Embedded Web Server for Remote Monitoring and Control of Smart Sensors Networks

PubMed Central

Magdaleno, Eduardo; Rodríguez, Manuel; Pérez, Fernando; Hernández, David; García, Enrique

2014-01-01

This article describes the implementation of a web server using an embedded Altera NIOS II IP core, a general purpose and configurable RISC processor which is embedded in a Cyclone FPGA. The processor uses the μCLinux operating system to support a Boa web server of dynamic pages using Common Gateway Interface (CGI). The FPGA is configured to act like the master node of a network, and also to control and monitor a network of smart sensors or instruments. In order to develop a totally functional system, the FPGA also includes an implementation of the time-triggered protocol (TTP/A). Thus, the implemented master node has two interfaces, the webserver that acts as an Internet interface and the other to control the network. This protocol is widely used to connecting smart sensors and actuators and microsystems in embedded real-time systems in different application domains, e.g., industrial, automotive, domotic, etc., although this protocol can be easily replaced by any other because of the inherent characteristics of the FPGA-based technology. PMID:24379047

An Embedded Stress Sensor for Concrete SHM Based on Amorphous Ferromagnetic Microwires

PubMed Central

Olivera, Jesús; González, Margarita; Fuente, José Vicente; Varga, Rastislav; Zhukov, Arkady; Anaya, José Javier

2014-01-01

A new smart concrete aggregate design as a candidate for applications in structural health monitoring (SHM) of critical elements in civil infrastructure is proposed. The cement-based stress/strain sensor was developed by utilizing the stress/strain sensing properties of a magnetic microwire embedded in cement-based composite (MMCC). This is a contact-less type sensor that measures variations of magnetic properties resulting from stress variations. Sensors made of these materials can be designed to satisfy the specific demand for an economic way to monitor concrete infrastructure health. For this purpose, we embedded a thin magnetic microwire in the core of a cement-based cylinder, which was inserted into the concrete specimen under study as an extra aggregate. The experimental results show that the embedded MMCC sensor is capable of measuring internal compressive stress around the range of 1–30 MPa. Two stress sensing properties of the embedded sensor under uniaxial compression were studied: the peak amplitude and peak position of magnetic switching field. The sensitivity values for the amplitude and position within the measured range were 5 mV/MPa and 2.5 μs/MPa, respectively. PMID:25347582

The Mathematics Education I and II Courses' Effect on Teacher Candidates' Development of Number Sense

ERIC Educational Resources Information Center

Yaman, Hakan

2015-01-01

The purpose of this research is to examine the number sense performance of the classroom teacher candidates taking the Mathematics Education I and II courses. Moreover, it investigates whether there is a change in the number sense performance of the teacher candidates following the Mathematics Education I and II courses. Embedded experimental…

Atom–Photon Coupling from Nitrogen-vacancy Centres Embedded in Tellurite Microspheres

PubMed Central

Ruan, Yinlan; Gibson, Brant C.; Lau, Desmond W. M.; Greentree, Andrew D.; Ji, Hong; Ebendorff-Heidepriem, Heike; Johnson, Brett C.; Ohshima, Takeshi; Monro, Tanya M.

2015-01-01

We have developed a technique for creating high quality tellurite microspheres with embedded nanodiamonds (NDs) containing nitrogen-vacancy (NV) centres. This hybrid method allows fluorescence of the NVs in the NDs to be directly, rather than evanescently, coupled to the whispering gallery modes of the tellurite microspheres at room temperature. As a demonstration of its sensing potential, shifting of the resonance peaks is also demonstrated by coating a sphere surface with a liquid layer. This new approach is a robust way of creating cavities for use in quantum and sensing applications. PMID:26095793

CoFe-microwires with stress-dependent magnetostriction as embedded sensing elements

NASA Astrophysics Data System (ADS)

Salem, M. M.; Nematov, M. G.; Uddin, A.; Panina, L. V.; Churyukanova, M. N.; Marchenko, A. T.

2017-10-01

Testing internal stress/strain condition of polymer composite materials is of high importance in structural health monitoring. We are presenting here a new method of monitoring internal stresses. The method can be referred to as embedded sensing technique, where the sensing element is a glass-coated ferromagnetic microwire with a specific magnetic anisotropy and stress-dependent magnetostriction. When the microwire is remagnetized the sharp voltage is induced which is characterized by high frequency harmonics. The amplitude of these harmonics sensitively depends on various stresses. The microwire of composition Co71Fe5B11Si10Cr3 with the metallic core diameter of 22.8 μm show abrupt transformation of the magnetization process under applied tensile stress owing to the stress-dependent magnetostriction.

Method and system for mesh network embedded devices

NASA Technical Reports Server (NTRS)

Wang, Ray (Inventor)

2009-01-01

A method and system for managing mesh network devices. A mesh network device with integrated features creates an N-way mesh network with a full mesh network topology or a partial mesh network topology.

Nanochannel Device with Embedded Nanopore: a New Approach for Single-Molecule DNA Analysis and Manipulation

NASA Astrophysics Data System (ADS)

Zhang, Yuning; Reisner, Walter

2012-02-01

Nanopore and nanochannel based devices are robust methods for biomolecular sensing and single DNA manipulation. Nanopore-based DNA sensing has attractive features that make it a leading candidate as a single-molecule DNA sequencing technology. Nanochannel based extension of DNA, combined with enzymatic or denaturation-based barcoding schemes, is already a powerful approach for genome analysis. We believe that there is revolutionary potential in devices that combine nanochannels with nanpore detectors. In particular, due to the fast translocation of a DNA molecule through a standard nanopore configuration, there is an unfavorable trade-off between signal and sequence resolution. With a combined nanochannel-nanopore device, based on embedding a nanopore inside a nanochannel, we can in principle gain independent control over both DNA translocation speed and sensing signal, solving the key draw-back of the standard nanopore configuration. We will discuss our recent progress on device fabrication and characterization. In particular, we demonstrate that we can detect - using fluorescent microscopy - successful translocation of DNA from the nanochannel out through the nanopore, a possible method to 'select' a given barcode for further analysis. In particular, we show that in equilibrium DNA will not escape through an embedded sub-persistence length nanopore, suggesting that the embedded pore could be used as a nanoscale window through which to interrogate a nanochannel extended DNA molecule.

[New type distributed optical fiber temperature sensor (DTS) based on Raman scattering and its' application].

PubMed

Wang, Jian-Feng; Liu, Hong-Lin; Zhang, Shu-Qin; Yu, Xiang-Dong; Sun, Zhong-Zhou; Jin, Shang-Zhong; Zhang, Zai-Xuan

2013-04-01

Basic principles, development trends and applications status of distributed optical fiber Raman temperature sensor (DTS) are introduced. Performance parameters of DTS system include the sensing optical fiber length, temperature measurement uncertainty, spatial resolution and measurement time. These parameters have a certain correlation and it is difficult to improve them at the same time by single technology. So a variety of key techniques such as Raman amplification, pulse coding technique, Raman related dual-wavelength self-correction technique and embedding optical switching technique are researched to improve the performance of the DTS system. A 1 467 nm continuous laser is used as pump laser and the light source of DTS system (1 550 nm pulse laser) is amplified. When the length of sensing optical fiber is 50 km the Raman gain is about 17 dB. Raman gain can partially compensate the transmission loss of optical fiber, so that the sensing length can reach 50 km. In DTS system using pulse coding technique, pulse laser is coded by 211 bits loop encoder and correlation calculation is used to demodulate temperature. The encoded laser signal is related, whereas the noise is not relevant. So that signal-to-noise ratio (SNR) of DTS system can be improved significantly. The experiments are carried out in DTS system with single mode optical fiber and multimode optical fiber respectively. Temperature measurement uncertainty can all reach 1 degrees C. In DTS system using Raman related dual-wavelength self-correction technique, the wavelength difference of the two light sources must be one Raman frequency shift in optical fiber. For example, wavelength of the main laser is 1 550 nm and wavelength of the second laser must be 1 450 nm. Spatial resolution of DTS system is improved to 2 m by using dual-wavelength self-correction technique. Optical switch is embedded in DTS system, so that the temperature measurement channel multiply extended and the total length of the sensing optical fiber effectively extended. Optical fiber sensor network is composed.

Closing the Gap: Cybersecurity for U.S. Forces and Commands

DTIC Science & Technology

2017-03-30

Dickson, Ph.D. Professor of Military Studies , JAWS Thesis Advisor Kevin Therrien, Col, USAF Committee Member Stephen Rogers, Colonel, USA Director...infrastructures, and includes the Internet, telecommunications networks, computer systems, and embedded processors and controllers in critical industries.”5...of information technology infrastructures, including the Internet, telecommunications networks, computer systems, and embedded processors and

Microfluidic networks embedded in a printed circuit board

NASA Astrophysics Data System (ADS)

Dong, Liangwei; Hu, Yueli

2017-07-01

In order to improve the robustness of microfluidic networks in printed circuit board (PCB)-based microfluidic platforms, a new method was presented. A pattern in a PCB was formed using hollowed-out technology. Polydimethylsiloxane was partly filled in the hollowed-out fields after mounting an adhesive tape on the bottom of the PCB, and solidified in an oven. Then, microfluidic networks were built using soft lithography technology. Microfluidic transportation and dilution operations were demonstrated using the fabricated microfluidic platform. Results show that this method can embed microfluidic networks into a PCB, and microfluidic operations can be implemented in the microfluidic networks embedded into the PCB.

Percolation of spatially constrained Erdős-Rényi networks with degree correlations.

PubMed

Schmeltzer, C; Soriano, J; Sokolov, I M; Rüdiger, S

2014-01-01

Motivated by experiments on activity in neuronal cultures [ J. Soriano, M. Rodríguez Martínez, T. Tlusty and E. Moses Proc. Natl. Acad. Sci. 105 13758 (2008)], we investigate the percolation transition and critical exponents of spatially embedded Erdős-Rényi networks with degree correlations. In our model networks, nodes are randomly distributed in a two-dimensional spatial domain, and the connection probability depends on Euclidian link length by a power law as well as on the degrees of linked nodes. Generally, spatial constraints lead to higher percolation thresholds in the sense that more links are needed to achieve global connectivity. However, degree correlations favor or do not favor percolation depending on the connectivity rules. We employ two construction methods to introduce degree correlations. In the first one, nodes stay homogeneously distributed and are connected via a distance- and degree-dependent probability. We observe that assortativity in the resulting network leads to a decrease of the percolation threshold. In the second construction methods, nodes are first spatially segregated depending on their degree and afterwards connected with a distance-dependent probability. In this segregated model, we find a threshold increase that accompanies the rising assortativity. Additionally, when the network is constructed in a disassortative way, we observe that this property has little effect on the percolation transition.

Radio frequency switching network: a technique for infrared sensing

NASA Astrophysics Data System (ADS)

Mechtel, Deborah M.; Jenkins, R. Brian; Joyce, Peter J.; Nelson, Charles L.

2016-10-01

This paper describes a unique technique that implements photoconductive sensors in a radio frequency (RF) switching network designed to locate in real-time the position and intensity of IR radiation incident on a composite structure. In the implementation described here, photoconductive sensors act as rapid response switches in a two-layer RF network embedded in an FR-4 laminate. To detect radiation, phosphorous-doped silicon photoconductive sensors are inserted in GHz range RF transmission lines. By permitting signal propagation only when a sensor is illuminated, the RF signals are selectively routed from lower layer transmission lines to upper layer lines, thereby pinpointing the location and strength of incident radiation. Simulations based on a high frequency three-dimensional planar electromagnetics model are presented and compared to the experimental results. The experimental results are described for GHz range RF signal control for 300- and 180-mW incident energy from 975- to 1060-nm wavelength lasers, respectively, where upon illumination, RF transmission line signal output power doubled when compared to nonilluminated results. The experimental results are also reported for 100-W incident energy from a 1060-nm laser. Test results illustrate real-time signal processing would permit a structure to be controlled in response to incident radiation.

Virtual Network Embedding via Monte Carlo Tree Search.

PubMed

Haeri, Soroush; Trajkovic, Ljiljana

2018-02-01

Network virtualization helps overcome shortcomings of the current Internet architecture. The virtualized network architecture enables coexistence of multiple virtual networks (VNs) on an existing physical infrastructure. VN embedding (VNE) problem, which deals with the embedding of VN components onto a physical network, is known to be -hard. In this paper, we propose two VNE algorithms: MaVEn-M and MaVEn-S. MaVEn-M employs the multicommodity flow algorithm for virtual link mapping while MaVEn-S uses the shortest-path algorithm. They formalize the virtual node mapping problem by using the Markov decision process (MDP) framework and devise action policies (node mappings) for the proposed MDP using the Monte Carlo tree search algorithm. Service providers may adjust the execution time of the MaVEn algorithms based on the traffic load of VN requests. The objective of the algorithms is to maximize the profit of infrastructure providers. We develop a discrete event VNE simulator to implement and evaluate performance of MaVEn-M, MaVEn-S, and several recently proposed VNE algorithms. We introduce profitability as a new performance metric that captures both acceptance and revenue to cost ratios. Simulation results show that the proposed algorithms find more profitable solutions than the existing algorithms. Given additional computation time, they further improve embedding solutions.

Self-Reporting Fiber-Reinforced Composites That Mimic the Ability of Biological Materials to Sense and Report Damage.

PubMed

Rifaie-Graham, Omar; Apebende, Edward A; Bast, Livia K; Bruns, Nico

2018-05-01

Sensing of damage, deformation, and mechanical forces is of vital importance in many applications of fiber-reinforced polymer composites, as it allows the structural health and integrity of composite components to be monitored and microdamage to be detected before it leads to catastrophic material failure. Bioinspired and biomimetic approaches to self-sensing and self-reporting materials are reviewed. Examples include bruising coatings and bleeding composites based on dye-filled microcapsules, hollow fibers, and vascular networks. Force-induced changes in color, fluorescence, or luminescence are achieved by mechanochromic epoxy resins, or by mechanophores and force-responsive proteins located at the interface of glass/carbon fibers and polymers. Composites can also feel strain, stress, and damage through embedded optical and electrical sensors, such as fiber Bragg grating sensors, or by resistance measurements of dispersed carbon fibers and carbon nanotubes. Bioinspired composites with the ability to show autonomously if and where they have been damaged lead to a multitude of opportunities for aerospace, automotive, civil engineering, and wind-turbine applications. They range from safety features for the detection of barely visible impact damage, to the real-time monitoring of deformation of load-bearing components. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection of Interfacial Debonding in a Rubber–Steel-Layered Structure Using Active Sensing Enabled by Embedded Piezoceramic Transducers

PubMed Central

Feng, Qian; Jiang, Jian; Liang, Yabin; Song, Gangbing

2017-01-01

Rubber–steel-layered structures are used in many engineering applications. Laminated rubber–steel bearing, as a type of seismic isolation device, is one of the most important applications of the rubber–steel-layered structures. Interfacial debonding in rubber–steel-layered structures is a typical failure mode, which can severely reduce their load-bearing capacity. In this paper, the authors developed a simple but effective active sensing approach using embedded piezoceramic transducers to provide an in-situ detection of the interfacial debonding between the rubber layers and steel plates. A sandwiched rubber–steel-layered specimen, consisting of one rubber layer and two steel plates, was fabricated as the test specimen. A novel installation technique, which allows the piezoceramic transducers to be fully embedded into the steel plates without changing the geometry and the surface conditions of the plates, was also developed in this research. The active sensing approach, in which designed stress waves can propagate between a pair of the embedded piezoceramic transducers (one as an actuator and the other one as a sensor), was employed to detect the steel–rubber debonding. When the rubber–steel debonding occurs, the debonded interfaces will attenuate the propagating stress wave, so that the amplitude of the received signal will decrease. The rubber–steel debonding was generated by pulling the two steel plates in opposite directions in a material-testing machine. The changes of the received signal before and after the debonding were characterized in a time domain and further quantified by using a wavelet packet-based energy index. Experiments on the healthy rubber–steel-layered specimen reveal that the piezoceramic-induced stress wave can propagate through the rubber layer. The destructive test on the specimen demonstrates that the piezoceramic-based active sensing approach can effectively detect the rubber–steel debonding failure in real time. The active sensing approach is often used in structures with “hard” materials, such as steel, concrete, and carbon fiber composites. This research lays a foundation for extending the active sensing approach to damage detection of structures involving “soft” materials, such as rubber. PMID:28862666

Detection of Interfacial Debonding in a Rubber-Steel-Layered Structure Using Active Sensing Enabled by Embedded Piezoceramic Transducers.

PubMed

Feng, Qian; Kong, Qingzhao; Jiang, Jian; Liang, Yabin; Song, Gangbing

2017-09-01

Rubber-steel-layered structures are used in many engineering applications. Laminated rubber-steel bearing, as a type of seismic isolation device, is one of the most important applications of the rubber-steel-layered structures. Interfacial debonding in rubber-steel-layered structures is a typical failure mode, which can severely reduce their load-bearing capacity. In this paper, the authors developed a simple but effective active sensing approach using embedded piezoceramic transducers to provide an in-situ detection of the interfacial debonding between the rubber layers and steel plates. A sandwiched rubber-steel-layered specimen, consisting of one rubber layer and two steel plates, was fabricated as the test specimen. A novel installation technique, which allows the piezoceramic transducers to be fully embedded into the steel plates without changing the geometry and the surface conditions of the plates, was also developed in this research. The active sensing approach, in which designed stress waves can propagate between a pair of the embedded piezoceramic transducers (one as an actuator and the other one as a sensor), was employed to detect the steel-rubber debonding. When the rubber-steel debonding occurs, the debonded interfaces will attenuate the propagating stress wave, so that the amplitude of the received signal will decrease. The rubber-steel debonding was generated by pulling the two steel plates in opposite directions in a material-testing machine. The changes of the received signal before and after the debonding were characterized in a time domain and further quantified by using a wavelet packet-based energy index. Experiments on the healthy rubber-steel-layered specimen reveal that the piezoceramic-induced stress wave can propagate through the rubber layer. The destructive test on the specimen demonstrates that the piezoceramic-based active sensing approach can effectively detect the rubber-steel debonding failure in real time. The active sensing approach is often used in structures with "hard" materials, such as steel, concrete, and carbon fiber composites. This research lays a foundation for extending the active sensing approach to damage detection of structures involving "soft" materials, such as rubber.

Innovation Engine for Blog Spaces

DTIC Science & Technology

2011-09-01

183 7.2.2 Architecture for mining Wikipedia as a sense-annotated corpus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183...are mined from a corpus by dictionary learning, and the representation is com- puted by sparse coding (Sec. 5.5). The topics can be embedded into a...intend to deter- mine the exact sense of a word whose surface form is unknown. This generalizes the original word sense disambiguation problem since we

Apply an Augmented Reality in a Mobile Guidance to Increase Sense of Place for Heritage Places

ERIC Educational Resources Information Center

Chang, Yu-Lien; Hou, Huei-Tse; Pan, Chao-Yang; Sung, Yao-Ting; Chang, Kuo-En

2015-01-01

Based on the sense of place theory and the design principles of guidance and interpretation, this study developed an augmented reality mobile guidance system that used a historical geo-context-embedded visiting strategy. This tool for heritage guidance and educational activities enhanced visitor sense of place. This study consisted of 3 visitor…

Embedded fiber-optic sensing for accurate internal monitoring of cell state in advanced battery management systems part 1: Cell embedding method and performance

NASA Astrophysics Data System (ADS)

Raghavan, Ajay; Kiesel, Peter; Sommer, Lars Wilko; Schwartz, Julian; Lochbaum, Alexander; Hegyi, Alex; Schuh, Andreas; Arakaki, Kyle; Saha, Bhaskar; Ganguli, Anurag; Kim, Kyung Ho; Kim, ChaeAh; Hah, Hoe Jin; Kim, SeokKoo; Hwang, Gyu-Ok; Chung, Geun-Chang; Choi, Bokkyu; Alamgir, Mohamed

2017-02-01

A key challenge hindering the mass adoption of Lithium-ion and other next-gen chemistries in advanced battery applications such as hybrid/electric vehicles (xEVs) has been management of their functional performance for more effective battery utilization and control over their life. Contemporary battery management systems (BMS) reliant on monitoring external parameters such as voltage and current to ensure safe battery operation with the required performance usually result in overdesign and inefficient use of capacity. More informative embedded sensors are desirable for internal cell state monitoring, which could provide accurate state-of-charge (SOC) and state-of-health (SOH) estimates and early failure indicators. Here we present a promising new embedded sensing option developed by our team for cell monitoring, fiber-optic sensors. High-performance large-format pouch cells with embedded fiber-optic sensors were fabricated. The first of this two-part paper focuses on the embedding method details and performance of these cells. The seal integrity, capacity retention, cycle life, compatibility with existing module designs, and mass-volume cost estimates indicate their suitability for xEV and other advanced battery applications. The second part of the paper focuses on the internal strain and temperature signals obtained from these sensors under various conditions and their utility for high-accuracy cell state estimation algorithms.

The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

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

Krishnan, J.; Mois, Kristina; Suwanmajo, Thapanar

2014-11-07

In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work,more » and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.« less

The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

NASA Astrophysics Data System (ADS)

Krishnan, J.; Mois, Kristina; Suwanmajo, Thapanar

2014-11-01

In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work, and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.

Novel Wireless-Communicating Textiles Made from Multi-Material and Minimally-Invasive Fibers

PubMed Central

Gorgutsa, Stepan; Bélanger-Garnier, Victor; Ung, Bora; Viens, Jeff; Gosselin, Benoit; LaRochelle, Sophie; Messaddeq, Younes

2014-01-01

The ability to integrate multiple materials into miniaturized fiber structures enables the realization of novel biomedical textile devices with higher-level functionalities and minimally-invasive attributes. In this work, we present novel textile fabrics integrating unobtrusive multi-material fibers that communicate through 2.4 GHz wireless networks with excellent signal quality. The conductor elements of the textiles are embedded within the fibers themselves, providing electrical and chemical shielding against the environment, while preserving the mechanical and cosmetic properties of the garments. These multi-material fibers combine insulating and conducting materials into a well-defined geometry, and represent a cost-effective and minimally-invasive approach to sensor fabrics and bio-sensing textiles connected in real time to mobile communications infrastructures, suitable for a variety of health and life science applications. PMID:25325335

Novel wireless-communicating textiles made from multi-material and minimally-invasive fibers.

PubMed

Bélanger-Garnier, Victor; Gorgutsa, Stephan; Ung, Bora; Viens, Jeff; Gosselin, Benoit; LaRochelle, Sophie; Messaddeq, Younes

2014-01-01

The ability to integrate multiple materials into miniaturized fiber structures enables the realization of novel biomedical textile devices with higher-level functionalities and minimally-invasive attributes. In this work, we present novel textile fabrics integrating unobtrusive multi-material fibers that communicate through 2.4 GHz wireless networks with excellent signal quality. The conductor elements of the textiles are embedded within the fibers themselves, providing electrical and chemical shielding against the environment, while preserving the mechanical and cosmetic properties of the garments. These multi-material fibers combine insulating and conducting materials into a well-defined geometry, and represent a cost-effective and minimally-invasive approach to sensor fabrics and bio-sensing textiles connected in real time to mobile communications infrastructures, suitable for a variety of health and life science applications.

Novel wireless-communicating textiles made from multi-material and minimally-invasive fibers.

PubMed

Gorgutsa, Stepan; Bélanger-Garnier, Victor; Ung, Bora; Viens, Jeff; Gosselin, Benoit; LaRochelle, Sophie; Messaddeq, Younes

2014-10-16

The ability to integrate multiple materials into miniaturized fiber structures enables the realization of novel biomedical textile devices with higher-level functionalities and minimally-invasive attributes. In this work, we present novel textile fabrics integrating unobtrusive multi-material fibers that communicate through 2.4 GHz wireless networks with excellent signal quality. The conductor elements of the textiles are embedded within the fibers themselves, providing electrical and chemical shielding against the environment, while preserving the mechanical and cosmetic properties of the garments. These multi-material fibers combine insulating and conducting materials into a well-defined geometry, and represent a cost-effective and minimally-invasive approach to sensor fabrics and bio-sensing textiles connected in real time to mobile communications infrastructures, suitable for a variety of health and life science applications.

Design of an Embedded CMOS Temperature Sensor for Passive RFID Tag Chips.

PubMed

Deng, Fangming; He, Yigang; Li, Bing; Zhang, Lihua; Wu, Xiang; Fu, Zhihui; Zuo, Lei

2015-05-18

This paper presents an ultra-low embedded power temperature sensor for passive RFID tags. The temperature sensor converts the temperature variation to a PTAT current, which is then transformed into a temperature-controlled frequency. A phase locked loop (PLL)-based sensor interface is employed to directly convert this temperature-controlled frequency into a corresponding digital output without an external reference clock. The fabricated sensor occupies an area of 0.021 mm2 using the TSMC 0.18 1P6M mixed-signal CMOS process. Measurement results of the embedded sensor within the tag system shows a 92 nW power dissipation under 1.0 V supply voltage at room temperature, with a sensing resolution of 0.15 °C/LSB and a sensing accuracy of -0.7/0.6 °C from -30 °C to 70 °C after 1-point calibration at 30 °C.

Data-Driven Sampling Matrix Boolean Optimization for Energy-Efficient Biomedical Signal Acquisition by Compressive Sensing.

PubMed

Wang, Yuhao; Li, Xin; Xu, Kai; Ren, Fengbo; Yu, Hao

2017-04-01

Compressive sensing is widely used in biomedical applications, and the sampling matrix plays a critical role on both quality and power consumption of signal acquisition. It projects a high-dimensional vector of data into a low-dimensional subspace by matrix-vector multiplication. An optimal sampling matrix can ensure accurate data reconstruction and/or high compression ratio. Most existing optimization methods can only produce real-valued embedding matrices that result in large energy consumption during data acquisition. In this paper, we propose an efficient method that finds an optimal Boolean sampling matrix in order to reduce the energy consumption. Compared to random Boolean embedding, our data-driven Boolean sampling matrix can improve the image recovery quality by 9 dB. Moreover, in terms of sampling hardware complexity, it reduces the energy consumption by 4.6× and the silicon area by 1.9× over the data-driven real-valued embedding.

Design of an Embedded CMOS Temperature Sensor for Passive RFID Tag Chips

PubMed Central

Deng, Fangming; He, Yigang; Li, Bing; Zhang, Lihua; Wu, Xiang; Fu, Zhihui; Zuo, Lei

2015-01-01

This paper presents an ultra-low embedded power temperature sensor for passive RFID tags. The temperature sensor converts the temperature variation to a PTAT current, which is then transformed into a temperature-controlled frequency. A phase locked loop (PLL)-based sensor interface is employed to directly convert this temperature-controlled frequency into a corresponding digital output without an external reference clock. The fabricated sensor occupies an area of 0.021 mm2 using the TSMC 0.18 1P6M mixed-signal CMOS process. Measurement results of the embedded sensor within the tag system shows a 92 nW power dissipation under 1.0 V supply voltage at room temperature, with a sensing resolution of 0.15 °C/LSB and a sensing accuracy of −0.7/0.6 °C from −30 °C to 70 °C after 1-point calibration at 30 °C. PMID:25993518

Embedded Touch Sensing Circuit Using Mutual Capacitance for Active-Matrix Organic Light-Emitting Diode Display

NASA Astrophysics Data System (ADS)

Park, Young-Ju; Seok, Su-Jeong; Park, Sang-Ho; Kim, Ohyun

2011-03-01

We propose and simulate an embedded touch sensing circuit for active-matrix organic light-emitting diode (AMOLED) displays. The circuit consists of three thin-film transistors (TFTs), one fixed capacitor, and one variable capacitor. AMOLED displays do not have a variable capacitance characteristic, so we realized a variable capacitor to detect touches in the sensing pixel by exploiting the change in the mutual capacitance between two electrodes that is caused by touch. When a dielectric substance approaches two electrodes, the electric field is shunted so that the mutual capacitance decreases. We use the existing TFT process to form the variable capacitor, so no additional process is needed. We use advanced solid-phase-crystallization TFTs because of their stability and uniformity. The proposed circuit detects multi-touch points by a scanning process.

Spacecraft Jitter Attenuation Using Embedded Piezoelectric Actuators

NASA Technical Reports Server (NTRS)

Belvin, W. Keith

1995-01-01

Remote sensing from spacecraft requires precise pointing of measurement devices in order to achieve adequate spatial resolution. Unfortunately, various spacecraft disturbances induce vibrational jitter in the remote sensing instruments. The NASA Langley Research Center has performed analysis, simulations, and ground tests to identify the more promising technologies for minimizing spacecraft pointing jitter. These studies have shown that the use of smart materials to reduce spacecraft jitter is an excellent match between a maturing technology and an operational need. This paper describes the use of embedding piezoelectric actuators for vibration control and payload isolation. In addition, recent advances in modeling, simulation, and testing of spacecraft pointing jitter are discussed.

Large-Deformation Displacement Transfer Functions for Shape Predictions of Highly Flexible Slender Aerospace Structures

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2013-01-01

Large deformation displacement transfer functions were formulated for deformed shape predictions of highly flexible slender structures like aircraft wings. In the formulation, the embedded beam (depth wise cross section of structure along the surface strain sensing line) was first evenly discretized into multiple small domains, with surface strain sensing stations located at the domain junctures. Thus, the surface strain (bending strains) variation within each domain could be expressed with linear of nonlinear function. Such piecewise approach enabled piecewise integrations of the embedded beam curvature equations [classical (Eulerian), physical (Lagrangian), and shifted curvature equations] to yield closed form slope and deflection equations in recursive forms.

Corrosion detection in reinforced concrete roadways and bridges via embedded fiber optic sensors

NASA Astrophysics Data System (ADS)

Fuhr, Peter L.; Huston, Dryver R.

1998-04-01

The problems associated with the application of chloride-based deicing agents to roadways and specifically bridges include chemical pollution and accelerated corrosion of strength members (especially the rebar) within the structure. In many instances, local ordnances are attempting to force state agencies to reduce, if not eliminate, the use of these chlorides (typically at the cost of increased driving hazards). With respect to the corrosion aspects of chloride application, cracks that occur in the roadway/bridge pavement allow water to seep into the pavement carrying the chloride to the rebar with the resultant increase in corrosion. In tandem with these efforts has been the continuing use of embedded fiber optic sensors for identification of faults or cracks within a highway structure - i.e., structural health monitoring. In this paper, we present multiple-parameter sensing fiber optic sensors which may be embedded into roadway and bridge structures to provide an internal measurement and assessment of its health. Such issues are paramount in determining if remedial or preventative maintenance should be performed on such structures. Laboratory results, comparisons with conventional sensing methods as well as a review of real-world issues in highway sensing are presented.

Study on embedding fiber Bragg grating sensor into the 3D printing structure for health monitoring

NASA Astrophysics Data System (ADS)

Li, Ruiya; Tan, Yuegang; Zhou, Zude; Fang, Liang; Chen, Yiyang

2016-10-01

3D printing technology is a rapidly developing manufacturing technology, which is known as a core technology in the third industrial revolution. With the continuous improvement of the application of 3D printing products, the health monitoring of the 3D printing structure is particularly important. Fiber Bragg grating (FBG) sensing technology is a new type of optical sensing technology with unique advantages comparing to traditional sensing technology, and it has great application prospects in structural health monitoring. In this paper, the FBG sensors embedded in the internal structure of the 3D printing were used to monitor the static and dynamic strain variation of 3D printing structure during loading process. The theoretical result and experimental result has good consistency and the characteristic frequency detected by FBG sensor is consistent with the testing results of traditional accelerator in the dynamic experiment. The results of this paper preliminary validate that FBG embedded in the 3D printing structure can effectively detecting the static and dynamic stain change of the 3D printing structure, which provide some guidance for the health monitoring of 3D printing structure.

A compact, portable and low cost generic interrogation strain sensor system using an embedded VCSEL, detector and fibre Bragg grating

NASA Astrophysics Data System (ADS)

Lee, Graham C. B.; Van Hoe, Bram; Yan, Zhijun; Maskery, Oliver; Sugden, Kate; Webb, David; Van Steenberge, Geert

2012-03-01

We present a compact, portable and low cost generic interrogation strain sensor system using a fibre Bragg grating configured in transmission mode with a vertical-cavity surface-emitting laser (VCSEL) light source and a GaAs photodetector embedded in a polymer skin. The photocurrent value is read and stored by a microcontroller. In addition, the photocurrent data is sent via Bluetooth to a computer or tablet device that can present the live data in a real time graph. With a matched grating and VCSEL, the system is able to automatically scan and lock the VCSEL to the most sensitive edge of the grating. Commercially available VCSEL and photodetector chips are thinned down to 20 μm and integrated in an ultra-thin flexible optical foil using several thin film deposition steps. A dedicated micro mirror plug is fabricated to couple the driving optoelectronics to the fibre sensors. The resulting optoelectronic package can be embedded in a thin, planar sensing sheet and the host material for this sheet is a flexible and stretchable polymer. The result is a fully embedded fibre sensing system - a photonic skin. Further investigations are currently being carried out to determine the stability and robustness of the embedded optoelectronic components.

Networks In Real Space: Characteristics and Analysis for Biology and Mechanics

NASA Astrophysics Data System (ADS)

Modes, Carl; Magnasco, Marcelo; Katifori, Eleni

Functional networks embedded in physical space play a crucial role in countless biological and physical systems, from the efficient dissemination of oxygen, blood sugars, and hormonal signals in vascular systems to the complex relaying of informational signals in the brain to the distribution of stress and strain in architecture or static sand piles. Unlike their more-studied abstract cousins, such as the hyperlinked internet, social networks, or economic and financial connections, these networks are both constrained by and intimately connected to the physicality of their real, embedding space. We report on the results of new computational and analytic approaches tailored to these physical networks with particular implications and insights for mammalian organ vasculature.

How the Air Force Should Stay Engaged in Computer Vision Technology Development

DTIC Science & Technology

2007-04-01

present individuals. The survey 29 Paddy Comyn, "Sensing Forward to a Driverless Future," The Irish...34 Military Embedded Systems (2006). Comyn, Paddy. "Sensing Forward to a Driverless Future." The Irish Times 21 February 2007. Dakley, Norman C. The

Advanced wireless mobile collaborative sensing network for tactical and strategic missions

NASA Astrophysics Data System (ADS)

Xu, Hao

2017-05-01

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

Home medical monitoring network based on embedded technology

NASA Astrophysics Data System (ADS)

Liu, Guozhong; Deng, Wenyi; Yan, Bixi; Lv, Naiguang

2006-11-01

Remote medical monitoring network for long-term monitoring of physiological variables would be helpful for recovery of patients as people are monitored at more comfortable conditions. Furthermore, long-term monitoring would be beneficial to investigate slowly developing deterioration in wellness status of a subject and provide medical treatment as soon as possible. The home monitor runs on an embedded microcomputer Rabbit3000 and interfaces with different medical monitoring module through serial ports. The network based on asymmetric digital subscriber line (ADSL) or local area network (LAN) is established and a client - server model, each embedded home medical monitor is client and the monitoring center is the server, is applied to the system design. The client is able to provide its information to the server when client's request of connection to the server is permitted. The monitoring center focuses on the management of the communications, the acquisition of medical data, and the visualization and analysis of the data, etc. Diagnosing model of sleep apnea syndrome is built basing on ECG, heart rate, respiration wave, blood pressure, oxygen saturation, air temperature of mouth cavity or nasal cavity, so sleep status can be analyzed by physiological data acquired as people in sleep. Remote medical monitoring network based on embedded micro Internetworking technology have advantages of lower price, convenience and feasibility, which have been tested by the prototype.

Development of Embedded Vascular Networks in FRP for Active/Passive Thermal Management

DTIC Science & Technology

2015-04-01

Passive Thermal Management Katarzyna...To) 30 September 2012 – 31 December 2014 4. TITLE AND SUBTITLE Development of Embedded Vascular Networks in FRP for Active/ Passive Thermal Management   5a...Active/ Passive   Thermal   Management   Reference:       EOARD  grant  (FA8655-­‐12-­‐1-­‐2144)   Investigators:    

Embedding "Getting Practical" and ASE Improving Practical Work in Triple Science LSN Network

ERIC Educational Resources Information Center

Stephenson, Kay; Chapman, Georgina

2011-01-01

With the two-year pilot of "Getting Practical" drawing to a close, new ways to embed the key messages into existing CPD programmes are being sought. In "Embedding Getting Practical," the first author describes how she has been able to do this with the courses she is involved with. In "ASE Improving Practical Work in Triple Science LSN Network,"…

Shaping Collective Functions in Privatized Agricultural Knowledge and Information Systems: The Positioning and Embedding of a Network Broker in the Dutch Dairy Sector

ERIC Educational Resources Information Center

Klerkx, Laurens; Leeuwis, Cees

2009-01-01

This paper examines new organizational arrangements that have emerged in the context of a privatized extension system. It investigates the positioning and embedding of a network broker aimed at enhancing interaction in the privatized agricultural knowledge and information system (AKIS), to assess whether tensions reported in other sectors also…

C2 at the Edge: Operating in a Disconnected Low-Bandwidth Environment

DTIC Science & Technology

2015-06-01

using their embedded Bluetooth communications capability. This thesis tests the throughput of the system at the maximum connection distances between...users with real-time chat capability of all locally available devices. 14. SUBJECT TERMS Infrastructure-less, mobile, network, Bluetooth , scatternet...thesis aims to create a communications network of smart devices, using their embedded Bluetooth communica- tions capability. This thesis tests the

The Significance of Kinship for Medical Education: Reflections on the Use of a Bespoke Social Network to Support Learners' Professional Identities.

PubMed

Hatzipanagos, Stylianos; John, Bernadette; Chiu, Yuan-Li Tiffany

2016-03-03

Social media can support and sustain communities much better than previous generations of learning technologies, where institutional barriers undermined any initiatives for embedding formal and informal learning. Some of the many types of social media have already had an impact on student learning, based on empirical evidence. One of these, social networking, has the potential to support communication in formal and informal spaces. In this paper we report on the evaluation of an institutional social network-King's Social Harmonisation Project (KINSHIP)-established to foster an improved sense of community, enhance communication, and serve as a space to model digital professionalism for students at King's College London, United Kingdom. Our evaluation focused on a study that examined students' needs and perceptions with regard to the provision of a cross-university platform. Data were collected from students, including those in the field of health and social care, in order to recommend a practical way forward to address current needs in this area. The findings indicate that the majority of the respondents were positive about using a social networking platform to develop their professional voice and profiles. Results suggest that timely promotion of the platform, emphasis on interface and learning design, and a clear identity are required in order to gain acceptance as the institutional social networking site. Empirical findings in this study project an advantage of an institutional social network such a KINSHIP over other social networks (eg, Facebook) because access is limited to staff and students and the site is mainly being used for academic purposes.

Development of a wireless MEMS multifunction sensor system and field demonstration of embedded sensors for monitoring concrete pavements : tech transfer summary.

DOT National Transportation Integrated Search

2016-08-01

Micro-electromechanical sensors and systems- (MEMS)-based and : wireless-based smart-sensing technologies have, until now, rarely : been used for monitoring pavement response in the field, and the : requirements for using such smart sensing technolog...

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

PubMed

Xiang, Lei; Wang, Qian; Nie, Dong; Zhang, Lichi; Jin, Xiyao; Qiao, Yu; Shen, Dinggang

2018-07-01

Recently, more and more attention is drawn to the field of medical image synthesis across modalities. Among them, the synthesis of computed tomography (CT) image from T1-weighted magnetic resonance (MR) image is of great importance, although the mapping between them is highly complex due to large gaps of appearances of the two modalities. In this work, we aim to tackle this MR-to-CT synthesis task by a novel deep embedding convolutional neural network (DECNN). Specifically, we generate the feature maps from MR images, and then transform these feature maps forward through convolutional layers in the network. We can further compute a tentative CT synthesis from the midway of the flow of feature maps, and then embed this tentative CT synthesis result back to the feature maps. This embedding operation results in better feature maps, which are further transformed forward in DECNN. After repeating this embedding procedure for several times in the network, we can eventually synthesize a final CT image in the end of the DECNN. We have validated our proposed method on both brain and prostate imaging datasets, by also comparing with the state-of-the-art methods. Experimental results suggest that our DECNN (with repeated embedding operations) demonstrates its superior performances, in terms of both the perceptive quality of the synthesized CT image and the run-time cost for synthesizing a CT image. Copyright © 2018. Published by Elsevier B.V.

Improving the durability of the optical fiber sensor based on strain transfer analysis

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-05-01

To realize the reliable and long-term strain detection, the durability of optical fiber sensors has attracted more and more attention. The packaging technique has been considered as an effective method, which can enhance the survival ratios of optical fiber sensors to resist the harsh construction and service environment in civil engineering. To monitor the internal strain of structures, the embedded installation is adopted. Due to the different material properties between host material and the protective layer, the monitored structure embedded with sensors can be regarded as a typical model containing inclusions. Interfacial characteristic between the sensor and host material exists obviously, and the contacted interface is prone to debonding failure induced by the large interfacial shear stress. To recognize the local interfacial debonding damage and extend the effective life cycle of the embedded sensor, strain transfer analysis of a general three-layered sensing model is conducted to investigate the failure mechanism. The perturbation of the embedded sensor on the local strain field of host material is discussed. Based on the theoretical analysis, the distribution of the interfacial shear stress along the sensing length is characterized and adopted for the diagnosis of local interfacial debonding, and the sensitive parameters influencing the interfacial shear stress are also investigated. The research in this paper explores the interfacial debonding failure mechanism of embedded sensors based on the strain transfer analysis and provides theoretical basis for enhancing the interfacial bonding properties and improving the durability of embedded optical fiber sensors.

Embedded Piezoresistive Microcantilever Sensors Functionalized for the Detection of Methyl Salicylate

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

Porter, Timothy L.; Venedam, Richard J.

2013-03-01

Sensors designed to detect the presence of methyl salicylate (MeS) have been tested. These sensors use a sensor platform based on the embedded piezoresistive microcantilever (EPM) design. Sensing materials tested in this study included the polymer poly (ethylene vinyl acetate), or PEVA as well as a composite sensing material consisting of the enzyme SA-binding protein 2, or SABP-2. The SABP-2 was immobilized within a biocompatible Hypol gel matrix. The PEVA-based sensors exhibited slower but reversible responses to MeS vapors, recovering fully to their initial state after the analyte was removed. SABP-2 sensors exhibited faster overall response to the introduction ofmore » MeS, responding nearly instantly. These sensors, however, do not recover after exposures have ended. Sensors using the SABP-2 sensing materials act instead as integrating sensors, measuring irreversibly the total MeS dose obtained.« less

Perceptualization of geometry using intelligent haptic and visual sensing

NASA Astrophysics Data System (ADS)

Weng, Jianguang; Zhang, Hui

2013-01-01

We present a set of paradigms for investigating geometric structures using haptic and visual sensing. Our principal test cases include smoothly embedded geometry shapes such as knotted curves embedded in 3D and knotted surfaces in 4D, that contain massive intersections when projected to one lower dimension. One can exploit a touch-responsive 3D interactive probe to haptically override this conflicting evidence in the rendered images, by forcing continuity in the haptic representation to emphasize the true topology. In our work, we exploited a predictive haptic guidance, a "computer-simulated hand" with supplementary force suggestion, to support intelligent exploration of geometry shapes that will smooth and maximize the probability of recognition. The cognitive load can be reduced further when enabling an attention-driven visual sensing during the haptic exploration. Our methods combine to reveal the full richness of the haptic exploration of geometric structures, and to overcome the limitations of traditional 4D visualization.

Stocks, Flows, and Distribution of Critical Metals in Embedded Electronics in Passenger Vehicles.

PubMed

Restrepo, Eliette; Løvik, Amund N; Wäger, Patrick; Widmer, Rolf; Lonka, Radek; Müller, Daniel B

2017-02-07

One of the major applications of critical metals (CMs) is in electrical and electronic equipment (EEE), which is increasingly embedded in other products, notably passenger vehicles. However, recycling strategies for future CM quantities in end-of-life vehicles (ELVs) are poorly understood, mainly due to a limited understating of the complexity of automotive embedded EEE. We introduce a harmonization of the network structure of automotive electronics that enables a comprehensive quantification of CMs in all embedded EEE in a vehicle. This network is combined with a material flow analysis along the vehicle lifecycle in Switzerland to quantify the stocks and flows of Ag, Au, Pd, Ru, Dy, La, Nd, and Co in automotive embedded EEE. In vehicles in use, we calculated 5 -2 +3 t precious metals in controllers embedded in all vehicle types and 220 -60 +90 t rare earth elements (REE); found mainly in five electric motors: alternator, starter, radiator-fan and electronic power steering motor embedded in conventional passenger vehicles and drive motor/generator embedded in hybrid and electric vehicles. Dismantling these devices before ELV shredding, as well as postshredder treatment of automobile shredder residue may increase the recovery of CMs from ELVs. Environmental and economic implications of such recycling strategies must be considered.

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

Design of nodes for embedded and ultra low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Xu, Jun; You, Bo; Cui, Juan; Ma, Jing; Li, Xin

2008-10-01

Sensor network integrates sensor technology, MEMS (Micro-Electro-Mechanical system) technology, embedded computing, wireless communication technology and distributed information management technology. It is of great value to use it where human is quite difficult to reach. Power consumption and size are the most important consideration when nodes are designed for distributed WSN (wireless sensor networks). Consequently, it is of great importance to decrease the size of a node, reduce its power consumption and extend its life in network. WSN nodes have been designed using JN5121-Z01-M01 module produced by jennic company and IEEE 802.15.4/ZigBee technology. Its new features include support for CPU sleep modes and a long-term ultra low power sleep mode for the entire node. In low power configuration the node resembles existing small low power nodes. An embedded temperature sensor node has been developed to verify and explore our architecture. The experiment results indicate that the WSN has the characteristic of high reliability, good stability and ultra low power consumption.

Wiring Together Synthetic Bacterial Consortia to Create a Biological Integrated Circuit.

PubMed

Perry, Nicolas; Nelson, Edward M; Timp, Gregory

2016-12-16

The promise of adapting biology to information processing will not be realized until engineered gene circuits, operating in different cell populations, can be wired together to express a predictable function. Here, elementary biological integrated circuits (BICs), consisting of two sets of transmitter and receiver gene circuit modules with embedded memory placed in separate cell populations, were meticulously assembled using live cell lithography and wired together by the mass transport of quorum-sensing (QS) signal molecules to form two isolated communication links (comlinks). The comlink dynamics were tested by broadcasting "clock" pulses of inducers into the networks and measuring the responses of functionally linked fluorescent reporters, and then modeled through simulations that realistically captured the protein production and molecular transport. These results show that the comlinks were isolated and each mimicked aspects of the synchronous, sequential networks used in digital computing. The observations about the flow conditions, derived from numerical simulations, and the biofilm architectures that foster or silence cell-to-cell communications have implications for everything from decontamination of drinking water to bacterial virulence.

Sensing Home: A Cost-Effective Design for Smart Home via Heterogeneous Wireless Networks

PubMed Central

Fan, Xiaohu; Huang, Hao; Qi, Shipeng; Luo, Xincheng; Zeng, Jing; Xie, Qubo; Xie, Changsheng

2015-01-01

The aging population has inspired the marketing of advanced real time devices for home health care, more and more wearable devices and mobile applications, which have emerged in this field. However, to properly collect behavior information, accurately recognize human activities, and deploy the whole system in a real living environment is a challenging task. In this paper, we propose a feasible wireless-based solution to deploy a data collection scheme, activity recognition model, feedback control and mobile integration via heterogeneous networks. We compared and found a suitable algorithm that can be run on cost-efficient embedded devices. Specifically, we use the Super Set Transformation method to map the raw data into a sparse binary matrix. Furthermore, designed front-end devices of low power consumption gather the living data of the habitant via ZigBee to reduce the burden of wiring work. Finally, we evaluated our approach and show it can achieve a theoretical time-slice accuracy of 98%. The mapping solution we propose is compatible with more wearable devices and mobile apps. PMID:26633424

Sensing Home: A Cost-Effective Design for Smart Home via Heterogeneous Wireless Networks.

PubMed

Fan, Xiaohu; Huang, Hao; Qi, Shipeng; Luo, Xincheng; Zeng, Jing; Xie, Qubo; Xie, Changsheng

2015-12-03

The aging population has inspired the marketing of advanced real time devices for home health care, more and more wearable devices and mobile applications, which have emerged in this field. However, to properly collect behavior information, accurately recognize human activities, and deploy the whole system in a real living environment is a challenging task. In this paper, we propose a feasible wireless-based solution to deploy a data collection scheme, activity recognition model, feedback control and mobile integration via heterogeneous networks. We compared and found a suitable algorithm that can be run on cost-efficient embedded devices. Specifically, we use the Super Set Transformation method to map the raw data into a sparse binary matrix. Furthermore, designed front-end devices of low power consumption gather the living data of the habitant via ZigBee to reduce the burden of wiring work. Finally, we evaluated our approach and show it can achieve a theoretical time-slice accuracy of 98%. The mapping solution we propose is compatible with more wearable devices and mobile apps.

Bio-Inspired Networking — Self-Organizing Networked Embedded Systems

NASA Astrophysics Data System (ADS)

Dressler, Falko

The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many research domains. In this article, we study the applicability of biological mechanisms and techniques in the domain of communications. In particular, we study the behavior and the challenges in networked embedded systems that are meant to self-organize in large groups of nodes. Application examples include wireless sensor networks and sensor/actuator networks. Based on a review of the needs and requirements in such networks, we study selected bio-inspired networking approaches that claim to outperform other methods in specific domains. We study mechanisms in swarm intelligence, the artificial immune system, and approaches based on investigations on the cellular signaling pathways. As a major conclusion, we derive that bio-inspired networking techniques do have advantages compared to engineering methods. Nevertheless, selection and employment must be done carefully to achieve the desired performance gains.

Computer-aided linear-circuit design.

NASA Technical Reports Server (NTRS)

Penfield, P.

1971-01-01

Usually computer-aided design (CAD) refers to programs that analyze circuits conceived by the circuit designer. Among the services such programs should perform are direct network synthesis, analysis, optimization of network parameters, formatting, storage of miscellaneous data, and related calculations. The program should be embedded in a general-purpose conversational language such as BASIC, JOSS, or APL. Such a program is MARTHA, a general-purpose linear-circuit analyzer embedded in APL.

A telehealth architecture for networked embedded systems: a case study in in vivo health monitoring.

PubMed

Dabiri, Foad; Massey, Tammara; Noshadi, Hyduke; Hagopian, Hagop; Lin, C K; Tan, Robert; Schmidt, Jacob; Sarrafzadeh, Majid

2009-05-01

The improvement in processor performance through continuous breakthroughs in transistor technology has resulted in the proliferation of lightweight embedded systems. Advances in wireless technology and embedded systems have enabled remote healthcare and telemedicine. While medical examinations could previously extract only localized symptoms through snapshots, now continuous monitoring can discretely analyze how a patient's lifestyle affects his/her physiological conditions and if additional symptoms occur under various stimuli. We demonstrate how medical applications in particular benefit from a hierarchical networking scheme that will improve the quantity and quality of ubiquitous data collection. Our Telehealth networking infrastructure provides flexibility in terms of functionality and the type of applications that it supports. We specifically present a case study that demonstrates the effectiveness of our networked embedded infrastructure in an in vivo pressure application. Experimental results of the in vivo system demonstrate how it can wirelessly transmit pressure readings measuring from 0 to 1.5 lbf/in (2) with an accuracy of 0.02 lbf/in (2). The challenges in biocompatible packaging, transducer drift, power management, and in vivo signal transmission are also discussed. This research brings researchers a step closer to continuous, real-time systemic monitoring that will allow one to analyze the dynamic human physiology.

Acid-etching technique of non-decalcified bone samples for visualizing osteocyte-lacuno-canalicular network using scanning electron microscope.

PubMed

Lampi, Tiina; Dekker, Hannah; Ten Bruggenkate, Chris M; Schulten, Engelbert A J M; Mikkonen, Jopi J W; Koistinen, Arto; Kullaa, Arja M

2018-01-01

The aim of this study was to define the acid-etching technique for bone samples embedded in polymethyl metacrylate (PMMA) in order to visualize the osteocyte lacuno-canalicular network (LCN) for scanning electron microscopy (SEM). Human jaw bone tissue samples (N = 18) were collected from the study population consisting of patients having received dental implant surgery. After collection, the bone samples were fixed in 70% ethanol and non-decalcified samples embedded routinely into polymethyl metacrylate (PMMA). The PMMA embedded specimens were acid-etched in either 9 or 37% phosphoric acid (PA) and prepared for SEM for further analysis. PMMA embedded bone specimens acid-etched by 9% PA concentration accomplishes the most informative and favorable visualization of the LCN to be observed by SEM. Etching of PMMA embedded specimens is recommendable to start with 30 s or 40 s etching duration in order to find the proper etching duration for the samples examined. Visualizing osteocytes and LCN provides a tool to study bone structure that reflects changes in bone metabolism and diseases related to bone tissue. By proper etching protocol of non-decalcified and using scanning electron microscope it is possible to visualize the morphology of osteocytes and the network supporting vitality of bone tissue.

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

PubMed

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

2017-11-01

A stretchable, transparent, and body-attachable chemical sensor is assembled from the stretchable nanocomposite network film for ultrasensitive chemical vapor sensing. The stretchable nanocomposite network film is fabricated by in situ preparation of polyaniline/MoS 2 (PANI/MoS 2 ) nanocomposite in MoS 2 suspension and simultaneously nanocomposite deposition onto prestrain elastomeric polydimethylsiloxane substrate. The assembled stretchable electronic sensor demonstrates ultrasensitive sensing performance as low as 50 ppb, robust sensing stability, and reliable stretchability for high-performance chemical vapor sensing. The ultrasensitive sensing performance of the stretchable electronic sensors could be ascribed to the synergistic sensing advantages of MoS 2 and PANI, higher specific surface area, the reliable sensing channels of interconnected network, and the effectively exposed sensing materials. It is expected to hold great promise for assembling various flexible stretchable chemical vapor sensors with ultrasensitive sensing performance, superior sensing stability, reliable stretchability, and robust portability to be potentially integrated into wearable electronics for real-time monitoring of environment safety and human healthcare. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mean Green operators of deformable fiber networks embedded in a compliant matrix and property estimates

NASA Astrophysics Data System (ADS)

Franciosi, Patrick; Spagnuolo, Mario; Salman, Oguz Umut

2018-04-01

Composites comprising included phases in a continuous matrix constitute a huge class of meta-materials, whose effective properties, whether they be mechanical, physical or coupled, can be selectively optimized by using appropriate phase arrangements and architectures. An important subclass is represented by "network-reinforced matrices," say those materials in which one or more of the embedded phases are co-continuous with the matrix in one or more directions. In this article, we present a method to study effective properties of simple such structures from which more complex ones can be accessible. Effective properties are shown, in the framework of linear elasticity, estimable by using the global mean Green operator for the entire embedded fiber network which is by definition through sample spanning. This network operator is obtained from one of infinite planar alignments of infinite fibers, which the network can be seen as an interpenetrated set of, with the fiber interactions being fully accounted for in the alignments. The mean operator of such alignments is given in exact closed form for isotropic elastic-like or dielectric-like matrices. We first exemplify how these operators relevantly provide, from classic homogenization frameworks, effective properties in the case of 1D fiber bundles embedded in an isotropic elastic-like medium. It is also shown that using infinite patterns with fully interacting elements over their whole influence range at any element concentration suppresses the dilute approximation limit of these frameworks. We finally present a construction method for a global operator of fiber networks described as interpenetrated such bundles.

Properties of centralized cooperative sensing in cognitive radio networks

NASA Astrophysics Data System (ADS)

Skokowski, Paweł; Malon, Krzysztof; Łopatka, Jerzy

2017-04-01

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

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

Real Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie (Inventor); Oliver, Brett D. (Inventor); Brickner, Christopher (Inventor)

2013-01-01

A method for clock monitoring in a network is provided. The method comprises receiving a first network clock signal at a network device and comparing the first network clock signal to a local clock signal from a primary oscillator coupled to the network device.

A new method of preparing embeddment-free sections for transmission electron microscopy: applications to the cytoskeletal framework and other three-dimensional networks.

PubMed

Capco, D G; Krochmalnic, G; Penman, S

1984-05-01

Diethylene glycol distearate is used as a removable embedding medium to produce embeddment -free sections for transmission electron microscopy. The easily cut sections of this material float and form ribbons in a water-filled knife trough and exhibit interference colors that aid in the selection of sections of equal thickness. The images obtained with embeddment -free sections are compared with those from the more conventional epoxy-embedded sections, and illustrate that embedding medium can obscure important biological structures, especially protein filament networks. The embeddment -free section methodology is well suited for morphological studies of cytoskeletal preparations obtained by extraction of cells with nonionic detergent in cytoskeletal stabilizing medium. The embeddment -free section also serves to bridge the very different images afforded by embedded sections and unembedded whole mounts.

Multimodal Interaction in Ambient Intelligence Environments Using Speech, Localization and Robotics

ERIC Educational Resources Information Center

Galatas, Georgios

2013-01-01

An Ambient Intelligence Environment is meant to sense and respond to the presence of people, using its embedded technology. In order to effectively sense the activities and intentions of its inhabitants, such an environment needs to utilize information captured from multiple sensors and modalities. By doing so, the interaction becomes more natural…

Accuracy improvement in the TDR-based localization of water leaks

NASA Astrophysics Data System (ADS)

Cataldo, Andrea; De Benedetto, Egidio; Cannazza, Giuseppe; Monti, Giuseppina; Demitri, Christian

A time domain reflectometry (TDR)-based system for the localization of water leaks has been recently developed by the authors. This system, which employs wire-like sensing elements to be installed along the underground pipes, has proven immune to the limitations that affect the traditional, acoustic leak-detection systems. Starting from the positive results obtained thus far, in this work, an improvement of this TDR-based system is proposed. More specifically, the possibility of employing a low-cost, water-absorbing sponge to be placed around the sensing element for enhancing the accuracy in the localization of the leak is addressed. To this purpose, laboratory experiments were carried out mimicking a water leakage condition, and two sensing elements (one embedded in a sponge and one without sponge) were comparatively used to identify the position of the leak through TDR measurements. Results showed that, thanks to the water retention capability of the sponge (which maintains the leaked water more localized), the sensing element embedded in the sponge leads to a higher accuracy in the evaluation of the position of the leak.

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

PubMed

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

2017-11-08

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

Improved Displacement Transfer Functions for Structure Deformed Shape Predictions Using Discretely Distributed Surface Strains

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2012-01-01

In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.

Hybrid motion sensing and experimental modal analysis using collocated smartphone camera and accelerometers

NASA Astrophysics Data System (ADS)

Ozer, Ekin; Feng, Dongming; Feng, Maria Q.

2017-10-01

State-of-the-art multisensory technologies and heterogeneous sensor networks propose a wide range of response measurement opportunities for structural health monitoring (SHM). Measuring and fusing different physical quantities in terms of structural vibrations can provide alternative acquisition methods and improve the quality of the modal testing results. In this study, a recently introduced SHM concept, SHM with smartphones, is focused to utilize multisensory smartphone features for a hybridized structural vibration response measurement framework. Based on vibration testing of a small-scale multistory laboratory model, displacement and acceleration responses are monitored using two different smartphone sensors, an embedded camera and accelerometer, respectively. Double-integration or differentiation among different measurement types is performed to combine multisensory measurements on a comparative basis. In addition, distributed sensor signals from collocated devices are processed for modal identification, and performance of smartphone-based sensing platforms are tested under different configuration scenarios and heterogeneity levels. The results of these tests show a novel and successful implementation of a hybrid motion sensing platform through multiple sensor type and device integration. Despite the heterogeneity of motion data obtained from different smartphone devices and technologies, it is shown that multisensory response measurements can be blended for experimental modal analysis. Getting benefit from the accessibility of smartphone technology, similar smartphone-based dynamic testing methodologies can provide innovative SHM solutions with mobile, programmable, and cost-free interfaces.

Detection of Membrane Puncture with Haptic Feedback using a Tip-Force Sensing Needle.

PubMed

Elayaperumal, Santhi; Bae, Jung Hwa; Daniel, Bruce L; Cutkosky, Mark R

2014-09-01

This paper presents calibration and user test results of a 3-D tip-force sensing needle with haptic feedback. The needle is a modified MRI-compatible biopsy needle with embedded fiber Bragg grating (FBG) sensors for strain detection. After calibration, the needle is interrogated at 2 kHz, and dynamic forces are displayed remotely with a voice coil actuator. The needle is tested in a single-axis master/slave system, with the voice coil haptic display at the master, and the needle at the slave end. Tissue phantoms with embedded membranes were used to determine the ability of the tip-force sensors to provide real-time haptic feedback as compared to external sensors at the needle base during needle insertion via the master/slave system. Subjects were able to determine the position of the embedded membranes with significantly better accuracy using FBG tip feedback than with base feedback using a commercial force/torque sensor (p = 0.045) or with no added haptic feedback (p = 0.0024).

Detection of Membrane Puncture with Haptic Feedback using a Tip-Force Sensing Needle

PubMed Central

Elayaperumal, Santhi; Bae, Jung Hwa; Daniel, Bruce L.; Cutkosky, Mark R.

2015-01-01

This paper presents calibration and user test results of a 3-D tip-force sensing needle with haptic feedback. The needle is a modified MRI-compatible biopsy needle with embedded fiber Bragg grating (FBG) sensors for strain detection. After calibration, the needle is interrogated at 2 kHz, and dynamic forces are displayed remotely with a voice coil actuator. The needle is tested in a single-axis master/slave system, with the voice coil haptic display at the master, and the needle at the slave end. Tissue phantoms with embedded membranes were used to determine the ability of the tip-force sensors to provide real-time haptic feedback as compared to external sensors at the needle base during needle insertion via the master/slave system. Subjects were able to determine the position of the embedded membranes with significantly better accuracy using FBG tip feedback than with base feedback using a commercial force/torque sensor (p = 0.045) or with no added haptic feedback (p = 0.0024). PMID:26509101

Embedded electronics for intelligent structures

NASA Astrophysics Data System (ADS)

Warkentin, David J.; Crawley, Edward F.

The signal, power, and communications provisions for the distributed control processing, sensing, and actuation of an intelligent structure could benefit from a method of physically embedding some electronic components. The preliminary feasibility of embedding electronic components in load-bearing intelligent composite structures is addressed. A technique for embedding integrated circuits on silicon chips within graphite/epoxy composite structures is presented which addresses the problems of electrical, mechanical, and chemical isolation. The mechanical and chemical isolation of test articles manufactured by this technique are tested by subjecting them to static and cyclic mechanical loads and a temperature/humidity/bias environment. The likely failure modes under these conditions are identified, and suggestions for further improvements in the technique are discussed.

Embedded diagnostic, prognostic, and health management system and method for a humanoid robot

NASA Technical Reports Server (NTRS)

Barajas, Leandro G. (Inventor); Strawser, Philip A (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)

2013-01-01

A robotic system includes a humanoid robot with multiple compliant joints, each moveable using one or more of the actuators, and having sensors for measuring control and feedback data. A distributed controller controls the joints and other integrated system components over multiple high-speed communication networks. Diagnostic, prognostic, and health management (DPHM) modules are embedded within the robot at the various control levels. Each DPHM module measures, controls, and records DPHM data for the respective control level/connected device in a location that is accessible over the networks or via an external device. A method of controlling the robot includes embedding a plurality of the DPHM modules within multiple control levels of the distributed controller, using the DPHM modules to measure DPHM data within each of the control levels, and recording the DPHM data in a location that is accessible over at least one of the high-speed communication networks.

Nanosensors-Cellphone Integration for Extended Chemical Sensing Network

NASA Technical Reports Server (NTRS)

Li, Jing

2011-01-01

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

Quartz and E-glass fiber self-sensing composites

NASA Astrophysics Data System (ADS)

Zolfaghar, K.; Khan, N. A.; Brooks, David; Hayes, Simon A.; Liu, Tonguy; Roca, J.; Lander, J.; Fernando, Gerard F.

1998-04-01

This paper reports on developments in the field of self- sensing fiber reinforced composites. The reinforcing fibers have been surface treated to enable them to act as light guides for short distances. The reinforcing fiber light guides were embedded in carbon fiber reinforced epoxy prepregs and processed into composites. The resultant composite was termed the self-sensing composite as any damage to these fibers or its interface would result in the attenuation of the transmitted light. The self-sensing fibers were capable of detecting a 2 J impact.

A review of earth observation using mobile personal communication devices

NASA Astrophysics Data System (ADS)

Ferster, Colin J.; Coops, Nicholas C.

2013-02-01

Earth observation using mobile personal communication devices (MPCDs) is a recent advance with considerable promise for acquiring important and timely measurements. Globally, over 5 billion people have access to mobile phones, with an increasing proportion having access to smartphones with capabilities such as a camera, microphone, global positioning system (GPS), data storage, and networked data transfer. Scientists can view these devices as embedded sensors with the potential to take measurements of the Earth's surface and processes. To advance the state of Earth observation using MPCDs, scientists need to consider terms and concepts, from a broad range of disciplines including citizen science, image analysis, and computer vision. In this paper, as a result of our literature review, we identify a number of considerations for Earth observation using MPCDs such as methods of field collection, collecting measurements over broad areas, errors and biases, data processing, and accessibility of data. Developing effective frameworks for mobile data collection with public participation and strategies for minimizing bias, in combination with advancements in image processing techniques, will offer opportunities to collect Earth sensing data across a range of scales and perspectives, complimenting airborne and spaceborne remote sensing measurements.

Wireless structural monitoring for homeland security applications

NASA Astrophysics Data System (ADS)

Kiremidjian, Garo K.; Kiremidjian, Anne S.; Lynch, Jerome P.

2004-07-01

This paper addresses the development of a robust, low-cost, low power, and high performance autonomous wireless monitoring system for civil assets such as large facilities, new construction, bridges, dams, commercial buildings, etc. The role of the system is to identify the onset, development, location and severity of structural vulnerability and damage. The proposed system represents an enabling infrastructure for addressing structural vulnerabilities specifically associated with homeland security. The system concept is based on dense networks of "intelligent" wireless sensing units. The fundamental properties of a wireless sensing unit include: (a) interfaces to multiple sensors for measuring structural and environmental data (such as acceleration, displacements, pressure, strain, material degradation, temperature, gas agents, biological agents, humidity, corrosion, etc.); (b) processing of sensor data with embedded algorithms for assessing damage and environmental conditions; (c) peer-to-peer wireless communications for information exchange among units(thus enabling joint "intelligent" processing coordination) and storage of data and processed information in servers for information fusion; (d) ultra low power operation; (e) cost-effectiveness and compact size through the use of low-cost small-size off-the-shelf components. An integral component of the overall system concept is a decision support environment for interpretation and dissemination of information to various decision makers.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

A new method of preparing embeddment-free sections for transmission electron microscopy: applications to the cytoskeletal framework and other three-dimensional networks

PubMed Central

1984-01-01

Diethylene glycol distearate is used as a removable embedding medium to produce embeddment -free sections for transmission electron microscopy. The easily cut sections of this material float and form ribbons in a water-filled knife trough and exhibit interference colors that aid in the selection of sections of equal thickness. The images obtained with embeddment -free sections are compared with those from the more conventional epoxy-embedded sections, and illustrate that embedding medium can obscure important biological structures, especially protein filament networks. The embeddment -free section methodology is well suited for morphological studies of cytoskeletal preparations obtained by extraction of cells with nonionic detergent in cytoskeletal stabilizing medium. The embeddment -free section also serves to bridge the very different images afforded by embedded sections and unembedded whole mounts. PMID:6539336

Fabrication of nano piezoelectric based vibration accelerometer for mechanical sensing

NASA Astrophysics Data System (ADS)

Murugan, S.; Prasad, M. V. N.; Jayakumar, K.

2016-05-01

An electromechanical sensor unit has been fabricated using nano PZT embedded in PVDF polymer. Such a polymer nano composite has been used as vibration sensor element and sensitivity, detection of mechanical vibration, and linearity measurements have been investigated. It is found from its performance, that this nano composite sensor is suitable for mechanical sensing applications.

Narrative change, narrative stability, and structural constraint: The case of prisoner reentry narratives

PubMed Central

Harding, David J.; Dobson, Cheyney C.; Wyse, Jessica J. B.; Morenoff, Jeffrey D.

2016-01-01

Cultural sociologists and other social scientists have increasingly used the concept of narrative as a theoretical tool to understand how individuals make sense of the links between their past, present, and future, how individuals construct social identities from cultural building blocks, and how culture shapes social action and individual behavior. Despite its richness, we contend that the narratives literature has yet to grapple with narrative change and stability when structural constraints or barriers challenge personal narratives and narrative identities. Particularly for marginalized groups, the potential incompatibility of personal narratives with daily experiences raises questions about the capacity of narratives to influence behavior and decision-making. In this study we draw on prospective longitudinal data on the reentry narratives and narrative identities of former prisoners to understand how narratives do and not change when confronted with contradictory experiences and structural constraints. We identify and describe the processes generating narrative change and stability among our subjects. These findings inform a framework for studying narrative change and stability based on four factors: the content of the narrative itself, the structural circumstances experienced by the individual, the institutional contexts in which the individual is embedded, and the social networks in which the individual is embedded. PMID:28316785

Mobile Phones Democratize and Cultivate Next-Generation Imaging, Diagnostics and Measurement Tools

PubMed Central

Ozcan, Aydogan

2014-01-01

In this article, I discuss some of the emerging applications and the future opportunities and challenges created by the use of mobile phones and their embedded components for the development of next-generation imaging, sensing, diagnostics and measurement tools. The massive volume of mobile phone users, which has now reached ~7 billion, drives the rapid improvements of the hardware, software and high-end imaging and sensing technologies embedded in our phones, transforming the mobile phone into a cost-effective and yet extremely powerful platform to run e.g., biomedical tests and perform scientific measurements that would normally require advanced laboratory instruments. This rapidly evolving and continuing trend will help us transform how medicine, engineering and sciences are practiced and taught globally. PMID:24647550

An Embedded Sensor Node Microcontroller with Crypto-Processors.

PubMed

Panić, Goran; Stecklina, Oliver; Stamenković, Zoran

2016-04-27

Wireless sensor network applications range from industrial automation and control, agricultural and environmental protection, to surveillance and medicine. In most applications, data are highly sensitive and must be protected from any type of attack and abuse. Security challenges in wireless sensor networks are mainly defined by the power and computing resources of sensor devices, memory size, quality of radio channels and susceptibility to physical capture. In this article, an embedded sensor node microcontroller designed to support sensor network applications with severe security demands is presented. It features a low power 16-bitprocessor core supported by a number of hardware accelerators designed to perform complex operations required by advanced crypto algorithms. The microcontroller integrates an embedded Flash and an 8-channel 12-bit analog-to-digital converter making it a good solution for low-power sensor nodes. The article discusses the most important security topics in wireless sensor networks and presents the architecture of the proposed hardware solution. Furthermore, it gives details on the chip implementation, verification and hardware evaluation. Finally, the chip power dissipation and performance figures are estimated and analyzed.

An Embedded Sensor Node Microcontroller with Crypto-Processors

PubMed Central

Panić, Goran; Stecklina, Oliver; Stamenković, Zoran

2016-01-01

Wireless sensor network applications range from industrial automation and control, agricultural and environmental protection, to surveillance and medicine. In most applications, data are highly sensitive and must be protected from any type of attack and abuse. Security challenges in wireless sensor networks are mainly defined by the power and computing resources of sensor devices, memory size, quality of radio channels and susceptibility to physical capture. In this article, an embedded sensor node microcontroller designed to support sensor network applications with severe security demands is presented. It features a low power 16-bitprocessor core supported by a number of hardware accelerators designed to perform complex operations required by advanced crypto algorithms. The microcontroller integrates an embedded Flash and an 8-channel 12-bit analog-to-digital converter making it a good solution for low-power sensor nodes. The article discusses the most important security topics in wireless sensor networks and presents the architecture of the proposed hardware solution. Furthermore, it gives details on the chip implementation, verification and hardware evaluation. Finally, the chip power dissipation and performance figures are estimated and analyzed. PMID:27128925

Hydrological Monitoring System Design and Implementation Based on IOT

NASA Astrophysics Data System (ADS)

Han, Kun; Zhang, Dacheng; Bo, Jingyi; Zhang, Zhiguang

In this article, an embedded system development platform based on GSM communication is proposed. Through its application in hydrology monitoring management, the author makes discussion about communication reliability and lightning protection, suggests detail solutions, and also analyzes design and realization of upper computer software. Finally, communication program is given. Hydrology monitoring system from wireless communication network is a typical practical application of embedded system, which has realized intelligence, modernization, high-efficiency and networking of hydrology monitoring management.

Circuit-Switched Memory Access in Photonic Interconnection Networks for High-Performance Embedded Computing

DTIC Science & Technology

2010-07-22

dependent , providing a natural bandwidth match between compute cores and the memory subsystem. • High Bandwidth Dcnsity. Waveguides crossing the chip...simulate this memory access architecture on a 2S6-core chip with a concentrated 64-node network lIsing detailed traces of high-performance embedded...memory modulcs, wc placc memory access poi nts (MAPs) around the pcriphery of the chip connected to thc nctwork. These MAPs, shown in Figure 4, contain

mDARAL: A Multi-Radio Version for the DARAL Routing Algorithm.

PubMed

Estévez, Francisco José; Castillo-Secilla, José María; González, Jesús; Olivares, Joaquín; Glösekötter, Peter

2017-02-09

Smart Cities are called to change the daily life of human beings. This concept permits improving the efficiency of our cities in several areas such as the use of water, energy consumption, waste treatment, and mobility both for people as well as vehicles throughout the city. This represents an interconnected scenario in which thousands of embedded devices need to work in a collaborative way both for sensing and modifying the environment properly. Under this scenario, the majority of devices will use wireless protocols for communicating among them, representing a challenge for optimizing the use of the electromagnetic spectrum. When the density of deployed nodes increases, the competition for using the physical medium becomes harder and, in consequence, traffic collisions will be higher, affecting data-rates in the communication process. This work presents mDARAL , a multi-radio routing algorithm based on the Dynamic and Adaptive Radio Algorithm ( DARAL ), which has the capability of isolating groups of nodes into sub-networks. The nodes of each sub-network will communicate among them using a dedicated radio frequency, thus isolating the use of the radio channel to a reduced number of nodes. Each sub-network will have a master node with two physical radios, one for communicating with its neighbours and the other for being the contact point among its group and other sub-networks. The communication among sub-networks is done through master nodes in a dedicated radio frequency. The algorithm works to maximize the overall performance of the network through the distribution of the traffic messages into unoccupied frequencies. The obtained results show that mDARAL achieves great improvement in terms of the number of control messages necessary to connect a node to the network, convergence time and energy consumption during the connection phase compared to DARAL .

mDARAL: A Multi-Radio Version for the DARAL Routing Algorithm

PubMed Central

Estévez, Francisco José; Castillo-Secilla, José María; González, Jesús; Olivares, Joaquín; Glösekötter, Peter

2017-01-01

Smart Cities are called to change the daily life of human beings. This concept permits improving the efficiency of our cities in several areas such as the use of water, energy consumption, waste treatment, and mobility both for people as well as vehicles throughout the city. This represents an interconnected scenario in which thousands of embedded devices need to work in a collaborative way both for sensing and modifying the environment properly. Under this scenario, the majority of devices will use wireless protocols for communicating among them, representing a challenge for optimizing the use of the electromagnetic spectrum. When the density of deployed nodes increases, the competition for using the physical medium becomes harder and, in consequence, traffic collisions will be higher, affecting data-rates in the communication process. This work presents mDARAL, a multi-radio routing algorithm based on the Dynamic and Adaptive Radio Algorithm (DARAL), which has the capability of isolating groups of nodes into sub-networks. The nodes of each sub-network will communicate among them using a dedicated radio frequency, thus isolating the use of the radio channel to a reduced number of nodes. Each sub-network will have a master node with two physical radios, one for communicating with its neighbours and the other for being the contact point among its group and other sub-networks. The communication among sub-networks is done through master nodes in a dedicated radio frequency. The algorithm works to maximize the overall performance of the network through the distribution of the traffic messages into unoccupied frequencies. The obtained results show that mDARAL achieves great improvement in terms of the number of control messages necessary to connect a node to the network, convergence time and energy consumption during the connection phase compared to DARAL. PMID:28208760

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

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

Ondrej Linda; Todd Vollmer; Jason Wright

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrainedmore » computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.« less

AEGIS: A Lightweight Firewall for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Hossain, Mohammad Sajjad; Raghunathan, Vijay

Firewalls are an essential component in today's networked computing systems (desktops, laptops, and servers) and provide effective protection against a variety of over-the-network security attacks. With the development of technologies such as IPv6 and 6LoWPAN that pave the way for Internet-connected embedded systems and sensor networks, these devices will soon be subject to (and need to be defended against) similar security threats. As a first step, this paper presents Aegis, a lightweight, rule-based firewall for networked embedded systems such as wireless sensor networks. Aegis is based on a semantically rich, yet simple, rule definition language. In addition, Aegis is highly efficient during operation, runs in a transparent manner from running applications, and is easy to maintain. Experimental results obtained using real sensor nodes and cycle-accurate simulations demonstrate that Aegis successfully performs gatekeeping of a sensor node's communication traffic in a flexible manner with minimal overheads.

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.

PubMed

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-07-15

Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k -mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k -mer co-occurrence information with recent advances in deep learning. We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k -mer embedding. We first split DNA sequences into k -mers and pre-train k -mer embedding vectors based on the co-occurrence matrix of k -mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k -mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm . tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn. Supplementary materials are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding

PubMed Central

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-01-01

Abstract Motivation: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k-mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k-mer co-occurrence information with recent advances in deep learning. Results: We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k-mer embedding. We first split DNA sequences into k-mers and pre-train k-mer embedding vectors based on the co-occurrence matrix of k-mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k-mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. Availability and implementation: The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm. Contact: tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:28881969

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

PubMed

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

2006-08-01

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

Study on algorithm of process neural network for soft sensing in sewage disposal system

NASA Astrophysics Data System (ADS)

Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

2006-11-01

A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

("Un")Doing Standards in Education with Actor-Network Theory

ERIC Educational Resources Information Center

Fenwick, Tara J.

2010-01-01

Recent critiques have drawn important attention to the depoliticized consensus and empty promises embedded in network discourses of educational policy. While acceding this critique, this discussion argues that some forms of network analysis--specifically those adopting actor-network theory (ANT) approaches--actually offer useful theoretical…

Aristotelian syllogisms

NASA Astrophysics Data System (ADS)

Ollongren, Alexander

2011-02-01

Aristotelian assertive syllogistic logic (without modalities) is embedded in the author's Lingua Cosmica. The well-known basic structures of assertions and conversions between them in this logic are represented in LINCOS. Since these representations correspond with set-theoretic operations, the latter are embedded in LINCOS as well. Based on this valid argumentation in Aristotle's sense is obtained for four important so-called perfect figures. Their constructive (intuitionistic) verifications are of a surprisingly elegant simplicity.

Application-oriented programming model for sensor networks embedded in the human body.

PubMed

Barbosa, Talles M G de A; Sene, Iwens G; da Rocha, Adson F; Nascimento, Fransisco A de O; Carvalho, Hervaldo S; Camapum, Juliana F

2006-01-01

This work presents a new programming model for sensor networks embedded in the human body which is based on the concept of multi-programming application-oriented software. This model was conceived with a top-down approach of four layers and its main goal is to allow the healthcare professionals to program and to reconfigure the network locally or by the Internet. In order to evaluate this hypothesis, a benchmarking was executed in order to allow the assessment of the mean time spent in the programming of a multi-functional sensor node used for the measurement and transmission of the electrocardiogram.

Curved Displacement Transfer Functions for Geometric Nonlinear Large Deformation Structure Shape Predictions

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran; Lung, Shun-Fat

2017-01-01

For shape predictions of structures under large geometrically nonlinear deformations, Curved Displacement Transfer Functions were formulated based on a curved displacement, traced by a material point from the undeformed position to deformed position. The embedded beam (depth-wise cross section of a structure along a surface strain-sensing line) was discretized into multiple small domains, with domain junctures matching the strain-sensing stations. Thus, the surface strain distribution could be described with a piecewise linear or a piecewise nonlinear function. The discretization approach enabled piecewise integrations of the embedded-beam curvature equations to yield the Curved Displacement Transfer Functions, expressed in terms of embedded beam geometrical parameters and surface strains. By entering the surface strain data into the Displacement Transfer Functions, deflections along each embedded beam can be calculated at multiple points for mapping the overall structural deformed shapes. Finite-element linear and nonlinear analyses of a tapered cantilever tubular beam were performed to generate linear and nonlinear surface strains and the associated deflections to be used for validation. The shape prediction accuracies were then determined by comparing the theoretical deflections with the finiteelement- generated deflections. The results show that the newly developed Curved Displacement Transfer Functions are very accurate for shape predictions of structures under large geometrically nonlinear deformations.

Stainless steel component with compressed fiber Bragg grating for high temperature sensing applications

NASA Astrophysics Data System (ADS)

Jinesh, Mathew; MacPherson, William N.; Hand, Duncan P.; Maier, Robert R. J.

2016-05-01

A smart metal component having the potential for high temperature strain sensing capability is reported. The stainless steel (SS316) structure is made by selective laser melting (SLM). A fiber Bragg grating (FBG) is embedded in to a 3D printed U-groove by high temperature brazing using a silver based alloy, achieving an axial FBG compression of 13 millistrain at room temperature. Initial results shows that the test component can be used for up to 700°C for sensing applications.

Making the City "Second Nature": Freegan "Dumpster Divers" and the Materiality of Morality.

PubMed

Barnard, Alex V

2016-01-01

How do people maintain deeply held moral identities in a seemingly immoral social environment? Cultural sociologists and social psychologists have focused on how individuals cope with contexts that make acting on moral motivations difficult by building supportive networks and embedding themselves in communities of like-minded people. In this article, however, the author argues that actors can achieve a moral "sense of one's place" through a habitus that leverages the material dimensions of place itself. In particular, he shows how one community of radical environmental activists make affirming moral identities centered on living "naturally" seem like "second nature," even in a seemingly unnatural and immoral urban environment, by reconfiguring their physical world. The author shows how nonhuman objects serve as proofs of moral labor, markers of moral boundaries, and reminders of moral values, playing both a facilitating and constraining role in moral life.

A signal processing framework for simultaneous detection of multiple environmental contaminants

NASA Astrophysics Data System (ADS)

Chakraborty, Subhadeep; Manahan, Michael P.; Mench, Matthew M.

2013-11-01

The possibility of large-scale attacks using chemical warfare agents (CWAs) has exposed the critical need for fundamental research enabling the reliable, unambiguous and early detection of trace CWAs and toxic industrial chemicals. This paper presents a unique approach for the identification and classification of simultaneously present multiple environmental contaminants by perturbing an electrochemical (EC) sensor with an oscillating potential for the extraction of statistically rich information from the current response. The dynamic response, being a function of the degree and mechanism of contamination, is then processed with a symbolic dynamic filter for the extraction of representative patterns, which are then classified using a trained neural network. The approach presented in this paper promises to extend the sensing power and sensitivity of these EC sensors by augmenting and complementing sensor technology with state-of-the-art embedded real-time signal processing capabilities.

Self-powered wireless disposable sensor for welfare application.

PubMed

Douseki, Takakuni; Tanaka, Ami

2013-01-01

A self-powered urinary incontinence sensor consisting of a flexible urine-activated battery and a wireless transmitter has been developed as an application for wireless biosensor networks. The flexible urine-activated battery is embedded in a disposal diaper and makes possible both the sensing of urine leakage and self-powered operation. An intermittent power-supply circuit that uses an electric double-layer capacitor (EDLC) with a small internal resistance suppresses the supply voltage drop due to the large internal resistance of the battery. This circuit supplies the power to a wireless transmitter. A 315-MHz-band wireless transmitter performs low-power operation. To verify the effectiveness of the circuit scheme, we fabricated a prototype sensor system. When 80 cc of urine is poured onto the diaper, the battery outputs a voltage of 1 V; and the sensor can transmit an ID signal over a distance of 5 m.

Data management for biofied building

NASA Astrophysics Data System (ADS)

Matsuura, Kohta; Mita, Akira

2015-03-01

Recently, Smart houses have been studied by many researchers to satisfy individual demands of residents. However, they are not feasible yet as they are very costly and require many sensors to be embedded into houses. Therefore, we suggest "Biofied Building". In Biofied Building, sensor agent robots conduct sensing, actuation, and control in their house. The robots monitor many parameters of human lives such as walking postures and emotion continuously. In this paper, a prototype network system and a data model for practical application for Biofied Building is pro-posed. In the system, functions of robots and servers are divided according to service flows in Biofield Buildings. The data model is designed to accumulate both the building data and the residents' data. Data sent from the robots and data analyzed in the servers are automatically registered into the database. Lastly, feasibility of this system is verified through lighting control simulation performed in an office space.

The embedded operating system project

NASA Technical Reports Server (NTRS)

Campbell, R. H.

1984-01-01

This progress report describes research towards the design and construction of embedded operating systems for real-time advanced aerospace applications. The applications concerned require reliable operating system support that must accommodate networks of computers. The report addresses the problems of constructing such operating systems, the communications media, reconfiguration, consistency and recovery in a distributed system, and the issues of realtime processing. A discussion is included on suitable theoretical foundations for the use of atomic actions to support fault tolerance and data consistency in real-time object-based systems. In particular, this report addresses: atomic actions, fault tolerance, operating system structure, program development, reliability and availability, and networking issues. This document reports the status of various experiments designed and conducted to investigate embedded operating system design issues.

Low-complexity object detection with deep convolutional neural network for embedded systems

NASA Astrophysics Data System (ADS)

Tripathi, Subarna; Kang, Byeongkeun; Dane, Gokce; Nguyen, Truong

2017-09-01

We investigate low-complexity convolutional neural networks (CNNs) for object detection for embedded vision applications. It is well-known that consolidation of an embedded system for CNN-based object detection is more challenging due to computation and memory requirement comparing with problems like image classification. To achieve these requirements, we design and develop an end-to-end TensorFlow (TF)-based fully-convolutional deep neural network for generic object detection task inspired by one of the fastest framework, YOLO.1 The proposed network predicts the localization of every object by regressing the coordinates of the corresponding bounding box as in YOLO. Hence, the network is able to detect any objects without any limitations in the size of the objects. However, unlike YOLO, all the layers in the proposed network is fully-convolutional. Thus, it is able to take input images of any size. We pick face detection as an use case. We evaluate the proposed model for face detection on FDDB dataset and Widerface dataset. As another use case of generic object detection, we evaluate its performance on PASCAL VOC dataset. The experimental results demonstrate that the proposed network can predict object instances of different sizes and poses in a single frame. Moreover, the results show that the proposed method achieves comparative accuracy comparing with the state-of-the-art CNN-based object detection methods while reducing the model size by 3× and memory-BW by 3 - 4× comparing with one of the best real-time CNN-based object detectors, YOLO. Our 8-bit fixed-point TF-model provides additional 4× memory reduction while keeping the accuracy nearly as good as the floating-point model. Moreover, the fixed- point model is capable of achieving 20× faster inference speed comparing with the floating-point model. Thus, the proposed method is promising for embedded implementations.

The Embedded Self: A Social Networks Approach to Identity Theory

ERIC Educational Resources Information Center

Walker, Mark H.; Lynn, Freda B.

2013-01-01

Despite the fact that key sociological theories of self and identity view the self as fundamentally rooted in networks of interpersonal relationships, empirical research investigating how personal network structure influences the self is conspicuously lacking. To address this gap, we examine links between network structure and role identity…

A dual-scale metal nanowire network transparent conductor for highly efficient and flexible organic light emitting diodes.

PubMed

Lee, Jinhwan; An, Kunsik; Won, Phillip; Ka, Yoonseok; Hwang, Hyejin; Moon, Hyunjin; Kwon, Yongwon; Hong, Sukjoon; Kim, Changsoon; Lee, Changhee; Ko, Seung Hwan

2017-02-02

Although solution processed metal nanowire (NW) percolation networks are a strong candidate to replace commercial indium tin oxide, their performance is limited in thin film device applications due to reduced effective electrical areas arising from the dimple structure and percolative voids that single size metal NW percolation networks inevitably possess. Here, we present a transparent electrode based on a dual-scale silver nanowire (AgNW) percolation network embedded in a flexible substrate to demonstrate a significant enhancement in the effective electrical area by filling the large percolative voids present in a long/thick AgNW network with short/thin AgNWs. As a proof of concept, the performance enhancement of a flexible phosphorescent OLED is demonstrated with the dual-scale AgNW percolation network compared to the previous mono-scale AgNWs. Moreover, we report that mechanical and oxidative robustness, which are critical for flexible OLEDs, are greatly increased by embedding the dual-scale AgNW network in a resin layer.

Ferroelectric Zinc Oxide Nanowire Embedded Flexible Sensor for Motion and Temperature Sensing.

PubMed

Shin, Sung-Ho; Park, Dae Hoon; Jung, Joo-Yun; Lee, Min Hyung; Nah, Junghyo

2017-03-22

We report a simple method to realize multifunctional flexible motion sensor using ferroelectric lithium-doped ZnO-PDMS. The ferroelectric layer enables piezoelectric dynamic sensing and provides additional motion information to more precisely discriminate different motions. The PEDOT:PSS-functionalized AgNWs, working as electrode layers for the piezoelectric sensing layer, resistively detect a change of both movement or temperature. Thus, through the optimal integration of both elements, the sensing limit, accuracy, and functionality can be further expanded. The method introduced here is a simple and effective route to realize a high-performance flexible motion sensor with integrated multifunctionalities.

Embedded Sensors and Controls to Improve Component Performance and Reliability -- Loop-scale Testbed Design Report

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

Melin, Alexander M.; Kisner, Roger A.

2016-09-01

Embedded instrumentation and control systems that can operate in extreme environments are challenging to design and operate. Extreme environments limit the options for sensors and actuators and degrade their performance. Because sensors and actuators are necessary for feedback control, these limitations mean that designing embedded instrumentation and control systems for the challenging environments of nuclear reactors requires advanced technical solutions that are not available commercially. This report details the development of testbed that will be used for cross-cutting embedded instrumentation and control research for nuclear power applications. This research is funded by the Department of Energy's Nuclear Energy Enabling Technologymore » program's Advanced Sensors and Instrumentation topic. The design goal of the loop-scale testbed is to build a low temperature pump that utilizes magnetic bearing that will be incorporated into a water loop to test control system performance and self-sensing techniques. Specifically, this testbed will be used to analyze control system performance in response to nonlinear and cross-coupling fluid effects between the shaft axes of motion, rotordynamics and gyroscopic effects, and impeller disturbances. This testbed will also be used to characterize the performance losses when using self-sensing position measurement techniques. Active magnetic bearings are a technology that can reduce failures and maintenance costs in nuclear power plants. They are particularly relevant to liquid salt reactors that operate at high temperatures (700 C). Pumps used in the extreme environment of liquid salt reactors provide many engineering challenges that can be overcome with magnetic bearings and their associated embedded instrumentation and control. This report will give details of the mechanical design and electromagnetic design of the loop-scale embedded instrumentation and control testbed.« less

Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

NASA Astrophysics Data System (ADS)

Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

2017-04-01

Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

Geometrical features assessment of liver's tumor with application of artificial neural network evolved by imperialist competitive algorithm.

PubMed

Keshavarz, M; Mojra, A

2015-05-01

Geometrical features of a cancerous tumor embedded in biological soft tissue, including tumor size and depth, are a necessity in the follow-up procedure and making suitable therapeutic decisions. In this paper, a new socio-politically motivated global search strategy which is called imperialist competitive algorithm (ICA) is implemented to train a feed forward neural network (FFNN) to estimate the tumor's geometrical characteristics (FFNNICA). First, a viscoelastic model of liver tissue is constructed by using a series of in vitro uniaxial and relaxation test data. Then, 163 samples of the tissue including a tumor with different depths and diameters are generated by making use of PYTHON programming to link the ABAQUS and MATLAB together. Next, the samples are divided into 123 samples as training dataset and 40 samples as testing dataset. Training inputs of the network are mechanical parameters extracted from palpation of the tissue through a developing noninvasive technology called artificial tactile sensing (ATS). Last, to evaluate the FFNNICA performance, outputs of the network including tumor's depth and diameter are compared with desired values for both training and testing datasets. Deviations of the outputs from desired values are calculated by a regression analysis. Statistical analysis is also performed by measuring Root Mean Square Error (RMSE) and Efficiency (E). RMSE in diameter and depth estimations are 0.50 mm and 1.49, respectively, for the testing dataset. Results affirm that the proposed optimization algorithm for training neural network can be useful to characterize soft tissue tumors accurately by employing an artificial palpation approach. Copyright © 2015 John Wiley & Sons, Ltd.

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Abas, Faizulsalihin bin; Takayama, Shigeru

2015-02-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1992-01-01

Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

Adsorption of gas molecules on Cu impurities embedded monolayer MoS2: A first- principles study

NASA Astrophysics Data System (ADS)

Zhao, B.; Li, C. Y.; Liu, L. L.; Zhou, B.; Zhang, Q. K.; Chen, Z. Q.; Tang, Z.

2016-09-01

Adsorption of small gas molecules (O2, NO, NO2 and NH3) on transition-metal Cu atom embedded monolayer MoS2 was investigated by first-principles calculations based on the density-functional theory (DFT). The embedded Cu atom is strongly constrained on the sulfur vacancy of monolayer MoS2 with a high diffusion barrier. The stable adsorption geometry, charge transfer and electronic structures of these gas molecules on monolayer MoS2 embedded with transition-metal Cu atom are discussed in detail. It is found that the monolayer MoS2 with embedded Cu atom can effectively capture these gas molecules with high adsorption energy. The NH3 molecule acts as electron donor after adsorption, which is different from the other gas molecules (O2, NO, and NO2). The results suggest that MoS2-Cu system may be promising for future applications in gas molecules sensing and catalysis, which is similar to those of the transition-metal embedded graphene.

An integrated compact airborne multispectral imaging system using embedded computer

NASA Astrophysics Data System (ADS)

Zhang, Yuedong; Wang, Li; Zhang, Xuguo

2015-08-01

An integrated compact airborne multispectral imaging system using embedded computer based control system was developed for small aircraft multispectral imaging application. The multispectral imaging system integrates CMOS camera, filter wheel with eight filters, two-axis stabilized platform, miniature POS (position and orientation system) and embedded computer. The embedded computer has excellent universality and expansibility, and has advantages in volume and weight for airborne platform, so it can meet the requirements of control system of the integrated airborne multispectral imaging system. The embedded computer controls the camera parameters setting, filter wheel and stabilized platform working, image and POS data acquisition, and stores the image and data. The airborne multispectral imaging system can connect peripheral device use the ports of the embedded computer, so the system operation and the stored image data management are easy. This airborne multispectral imaging system has advantages of small volume, multi-function, and good expansibility. The imaging experiment results show that this system has potential for multispectral remote sensing in applications such as resource investigation and environmental monitoring.

A Polygon Model for Wireless Sensor Network Deployment with Directional Sensing Areas

PubMed Central

Wu, Chun-Hsien; Chung, Yeh-Ching

2009-01-01

The modeling of the sensing area of a sensor node is essential for the deployment algorithm of wireless sensor networks (WSNs). In this paper, a polygon model is proposed for the sensor node with directional sensing area. In addition, a WSN deployment algorithm is presented with topology control and scoring mechanisms to maintain network connectivity and improve sensing coverage rate. To evaluate the proposed polygon model and WSN deployment algorithm, a simulation is conducted. The simulation results show that the proposed polygon model outperforms the existed disk model and circular sector model in terms of the maximum sensing coverage rate. PMID:22303159

Embedding of electrodes within a microchannel interfacing a permselective medium for sensing and active control of the concentration-polarization layer

NASA Astrophysics Data System (ADS)

Yossifon, Gilad; Park, Sinwook

2016-11-01

Previously, it has been shown that for a prescribed system, the diffusion length may be affected by any number of mechanisms including natural and forced convection, electroosmotic flow of the second kind and electro-convective instability. In all of the above mentioned cases the length of the diffusion layer is indirectly prescribed by the complicated competition between several mechanisms which are primarily dictated by the various system parameters and applied voltage. In contrast, we suggest that by embedding electrodes/heaters within a microchannel interfacing a permselective medium, the diffusion layer length may be controlled regardless of the dominating overlimiting current mechanism and system parameters. As well as demonstrating that the simple presence of electrodes can enhance mixing via induced-charge electrokinetic effects, we also offer a means of externally activating embedded electrodes and heaters to maintain external, dynamic control of the diffusion length. Such control is particularly important in applications requiring intense ion transport, such as electrodialysis. At the same time, we will also investigate means of suppressing these mechanisms which is of fundamental importance for sensing applications.

An Efficient Semi-fragile Watermarking Scheme for Tamper Localization and Recovery

NASA Astrophysics Data System (ADS)

Hou, Xiang; Yang, Hui; Min, Lianquan

2018-03-01

To solve the problem that remote sensing images are vulnerable to be tampered, a semi-fragile watermarking scheme was proposed. Binary random matrix was used as the authentication watermark, which was embedded by quantizing the maximum absolute value of directional sub-bands coefficients. The average gray level of every non-overlapping 4×4 block was adopted as the recovery watermark, which was embedded in the least significant bit. Watermarking detection could be done directly without resorting to the original images. Experimental results showed our method was robust against rational distortions to a certain extent. At the same time, it was fragile to malicious manipulation, and realized accurate localization and approximate recovery of the tampered regions. Therefore, this scheme can protect the security of remote sensing image effectively.

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Time-Centric Models For Designing Embedded Cyber-physical Systems

DTIC Science & Technology

2009-10-09

Time -centric Models For Designing Embedded Cyber- physical Systems John C. Eidson Edward A. Lee Slobodan Matic Sanjit A. Seshia Jia Zou Electrical... Time -centric Models For Designing Embedded Cyber-physical Systems ∗ John C. Eidson , Edward A. Lee, Slobodan Matic, Sanjit A. Seshia, Jia Zou...implementations, such a uniform notion of time cannot be precisely realized. Time triggered networks [10] and time synchronization [9] can be used to

The Significance of Kinship for Medical Education: Reflections on the Use of a Bespoke Social Network to Support Learners’ Professional Identities

PubMed Central

2016-01-01

Background Social media can support and sustain communities much better than previous generations of learning technologies, where institutional barriers undermined any initiatives for embedding formal and informal learning. Some of the many types of social media have already had an impact on student learning, based on empirical evidence. One of these, social networking, has the potential to support communication in formal and informal spaces. Objective In this paper we report on the evaluation of an institutional social network—King's Social Harmonisation Project (KINSHIP)—established to foster an improved sense of community, enhance communication, and serve as a space to model digital professionalism for students at King’s College London, United Kingdom. Methods Our evaluation focused on a study that examined students’ needs and perceptions with regard to the provision of a cross-university platform. Data were collected from students, including those in the field of health and social care, in order to recommend a practical way forward to address current needs in this area. Results The findings indicate that the majority of the respondents were positive about using a social networking platform to develop their professional voice and profiles. Results suggest that timely promotion of the platform, emphasis on interface and learning design, and a clear identity are required in order to gain acceptance as the institutional social networking site. Conclusions Empirical findings in this study project an advantage of an institutional social network such a KINSHIP over other social networks (eg, Facebook) because access is limited to staff and students and the site is mainly being used for academic purposes. PMID:27731848

Earth sensing: from ice to the Internet of Things

NASA Astrophysics Data System (ADS)

Martinez, K.

2017-12-01

The evolution of technology has led to improvements in our ability to use sensors for earth science research. Radio communications have improved in terms of range and power use. Miniaturisation means we now use 32 bit processors with embedded memory, storage and interfaces. Sensor technology makes it simpler to integrate devices such as accelerometers, compasses, gas and biosensors. Programming languages have developed so that it has become easier to create software for these systems. This combined with the power of the processors has made research into advanced algorithms and communications feasible. The term environmental sensor networks describes these advanced systems which are designed specifically to take sensor measurements in the natural environment. Through a decade of research into sensor networks, deployed mainly in glaciers, many areas of this still emerging technology have been explored. From deploying the first subglacial sensor probes with custom electronics and protocols we learnt tuning to harsh environments and energy management. More recently installing sensor systems in the mountains of Scotland has shown that standards have allowed complete internet and web integration. This talk will discuss the technologies used in a range of recent deployments in Scotland and Iceland focussed on creating new data streams for cryospheric and climate change research.

Long-Term Animal Observation by Wireless Sensor Networks with Sound Recognition

NASA Astrophysics Data System (ADS)

Liu, Ning-Han; Wu, Chen-An; Hsieh, Shu-Ju

Due to wireless sensor networks can transmit data wirelessly and can be disposed easily, they are used in the wild to monitor the change of environment. However, the lifetime of sensor is limited by the battery, especially when the monitored data type is audio, the lifetime is very short due to a huge amount of data transmission. By intuition, sensor mote analyzes the sensed data and decides not to deliver them to server that can reduce the expense of energy. Nevertheless, the ability of sensor mote is not powerful enough to work on complicated methods. Therefore, it is an urgent issue to design a method to keep analyzing speed and accuracy under the restricted memory and processor. This research proposed an embedded audio processing module in the sensor mote to extract and analyze audio features in advance. Then, through the estimation of likelihood of observed animal sound by the frequencies distribution, only the interesting audio data are sent back to server. The prototype of WSN system is built and examined in the wild to observe frogs. According to the results of experiments, the energy consumed by sensors through our method can be reduced effectively to prolong the observing time of animal detecting sensors.

Spatio-temporal propagation of cascading overload failures in spatially embedded networks

NASA Astrophysics Data System (ADS)

Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

2016-01-01

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

Spatio-temporal propagation of cascading overload failures in spatially embedded networks

PubMed Central

Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

2016-01-01

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

Hybrid architecture for building secure sensor networks

NASA Astrophysics Data System (ADS)

Owens, Ken R., Jr.; Watkins, Steve E.

2012-04-01

Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

A Piezoelectric Passive Wireless Sensor for Monitoring Strain

NASA Technical Reports Server (NTRS)

Zou, Xiyue; Ferri, Paul N.; Hogan, Ben; Mazzeo, Aaron D.; Hull. Patrick V.

2017-01-01

Interest in passive wireless sensing has grown over the past few decades to meet demands in structural health monitoring.(Deivasigamani et al., 2013; Wilson and Juarez, 2014) This work describes a passive wireless sensor for monitoring strain, which does not have an embedded battery or chip. Without an embedded battery, the passive wireless sensor has the potential to maintain its functionality over long periods in remote/harsh environments. This work also focuses on monitoring small strain (less than 1000 micro-?). The wireless sensing system includes a reader unit, a coil-like transponder, and a sensing unit. It operates in the Megahertz (MHz) frequency range, which allows for a few centimeters of separation between the reader and sensing unit during measurements. The sensing unit is a strain-sensitive piezoelectric resonator that maximizes the energy efficiency at the resonance frequency, so it converts nanoscale mechanical variations to detectable differences in electrical signal. In response to an external loading, the piezoelectric sensor breaks from its original electromechanical equilibrium, and the resonant frequency shifts as the system reaches a new balanced equilibrium. In this work, the fixture of the sensing unit is a small, sticker-like package that converts the surface strain of a test material to measurable shifts in resonant frequencies. Furthermore, electromechanical modeling provides a lumped-parameter model of the system to describe and predict the measured wireless signals of the sensor. Detailed characterization demonstrates how this wireless sensor has resolution comparable to that of conventional wired strain sensors for monitoring small strain.

Cascading Failures and Recovery in Networks of Networks

NASA Astrophysics Data System (ADS)

Havlin, Shlomo

Network science have been focused on the properties of a single isolated network that does not interact or depends on other networks. In reality, many real-networks, such as power grids, transportation and communication infrastructures interact and depend on other networks. I will present a framework for studying the vulnerability and the recovery of networks of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes like certain locations play a role in two networks -multiplex. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. I will present analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. I will show, that the general theory has many novel features that are not present in the classical network theory. When recovery of components is possible global spontaneous recovery of the networks and hysteresis phenomena occur and the theory suggests an optimal repairing strategy of system of systems. I will also show that interdependent networks embedded in space are significantly more vulnerable compared to non embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences.Thus, analyzing data of real network of networks is highly required to understand the system vulnerability. DTRA, ONR, Israel Science Foundation.

Laboratory validation of MEMS-based sensors for post-earthquake damage assessment image

NASA Astrophysics Data System (ADS)

Pozzi, Matteo; Zonta, Daniele; Santana, Juan; Colin, Mikael; Saillen, Nicolas; Torfs, Tom; Amditis, Angelos; Bimpas, Matthaios; Stratakos, Yorgos; Ulieru, Dumitru; Bairaktaris, Dimitirs; Frondistou-Yannas, Stamatia; Kalidromitis, Vasilis

2011-04-01

The evaluation of seismic damage is today almost exclusively based on visual inspection, as building owners are generally reluctant to install permanent sensing systems, due to their high installation, management and maintenance costs. To overcome this limitation, the EU-funded MEMSCON project aims to produce small size sensing nodes for measurement of strain and acceleration, integrating Micro-Electro-Mechanical Systems (MEMS) based sensors and Radio Frequency Identification (RFID) tags in a single package that will be attached to reinforced concrete buildings. To reduce the impact of installation and management, data will be transmitted to a remote base station using a wireless interface. During the project, sensor prototypes were produced by assembling pre-existing components and by developing ex-novo miniature devices with ultra-low power consumption and sensing performance beyond that offered by sensors available on the market. The paper outlines the device operating principles, production scheme and working at both unit and network levels. It also reports on validation campaigns conducted in the laboratory to assess system performance. Accelerometer sensors were tested on a reduced scale metal frame mounted on a shaking table, back to back with reference devices, while strain sensors were embedded in both reduced and full-scale reinforced concrete specimens undergoing increasing deformation cycles up to extensive damage and collapse. The paper assesses the economical sustainability and performance of the sensors developed for the project and discusses their applicability to long-term seismic monitoring.

Design and FPGA implementation for MAC layer of Ethernet PON

NASA Astrophysics Data System (ADS)

Zhu, Zengxi; Lin, Rujian; Chen, Jian; Ye, Jiajun; Chen, Xinqiao

2004-04-01

Ethernet passive optical network (EPON), which represents the convergence of low-cost, high-bandwidth and supporting multiple services, appears to be one of the best candidates for the next-generation access network. The work of standardizing EPON as a solution for access network is still underway in the IEEE802.3ah Ethernet in the first mile (EFM) task force. The final release is expected in 2004. Up to now, there has been no standard application specific integrated circuit (ASIC) chip available which fulfills the functions of media access control (MAC) layer of EPON. The MAC layer in EPON system has many functions, such as point-to-point emulation (P2PE), Ethernet MAC functionality, multi-point control protocol (MPCP), network operation, administration and maintenance (OAM) and link security. To implement those functions mentioned above, an embedded real-time operating system (RTOS) and a flexible programmable logic device (PLD) with an embedded processor are used. The software and hardware functions in MAC layer are realized through programming embedded microprocessor and field programmable gate array(FPGA). Finally, some experimental results are given in this paper. The method stated here can provide a valuable reference for developing EPON MAC layer ASIC.

Electronic Cortisol Detection Using an Antibody-Embedded Polymer Coupled to a Field-Effect Transistor.

PubMed

Jang, Hyun-June; Lee, Taein; Song, Jian; Russell, Luisa; Li, Hui; Dailey, Jennifer; Searson, Peter C; Katz, Howard E

2018-05-16

A field-effect transistor-based cortisol sensor was demonstrated in physiological conditions. An antibody-embedded polymer on the remote gate was proposed to overcome the Debye length issue (λ D ). The sensing membrane was made by linking poly(styrene- co-methacrylic acid) (PSMA) with anticortisol before coating the modified polymer on the remote gate. The embedded receptor in the polymer showed sensitivity from 10 fg/mL to 10 ng/mL for cortisol and a limit of detection (LOD) of 1 pg/mL in 1× PBS where λ D is 0.2 nm. A LOD of 1 ng/mL was shown in lightly buffered artificial sweat. Finally, a sandwich ELISA confirmed the antibody binding activity of antibody-embedded PSMA.

Strain and dynamic measurements using fiber optic sensors embedded into graphite/epoxy tubes

NASA Technical Reports Server (NTRS)

Dehart, D. W.; Doederlein, T.; Koury, J.; Rogowski, R. S.; Heyman, J. S.; Holben, M. S., Jr.

1989-01-01

Graphite/epoxy tubes were fabricated with embedded optical fibers to evaluate the feasibility of monitoring strains with a fiber optic technique. Resistance strain gauges were attached to the tubes to measure strain at four locations along the tube for comparison with the fiber optic sensors. Both static and dynamic strain measurements were made with excellent agreement between the embedded fiber optic strain sensor and the strain gauges. Strain measurements of 10(exp -7) can be detected with the optical phase locked loop (OPLL) system using optical fiber. Because of their light weight, compatibility with composites, immunity to electromagnetic interference, and based on the static and dynamic results obtained, fiber optic sensors embedded in composites may be useful as the sensing component of smart structures.

Social networks as embedded complex adaptive systems.

PubMed

Benham-Hutchins, Marge; Clancy, Thomas R

2010-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

Crosstalk-aware virtual network embedding over inter-datacenter optical networks with few-mode fibers

NASA Astrophysics Data System (ADS)

Huang, Haibin; Guo, Bingli; Li, Xin; Yin, Shan; Zhou, Yu; Huang, Shanguo

2017-12-01

Virtualization of datacenter (DC) infrastructures enables infrastructure providers (InPs) to provide novel services like virtual networks (VNs). Furthermore, optical networks have been employed to connect the metro-scale geographically distributed DCs. The synergistic virtualization of the DC infrastructures and optical networks enables the efficient VN service over inter-DC optical networks (inter-DCONs). While the capacity of the used standard single-mode fiber (SSMF) is limited by their nonlinear characteristics. Thus, mode-division multiplexing (MDM) technology based on few-mode fibers (FMFs) could be employed to increase the capacity of optical networks. Whereas, modal crosstalk (XT) introduced by optical fibers and components deployed in the MDM optical networks impacts the performance of VN embedding (VNE) over inter-DCONs with FMFs. In this paper, we propose a XT-aware VNE mechanism over inter-DCONs with FMFs. The impact of XT is considered throughout the VNE procedures. The simulation results show that the proposed XT-aware VNE can achieves better performances of blocking probability and spectrum utilization compared to conventional VNE mechanisms.

Embedded Web Technology: Applying World Wide Web Standards to Embedded Systems

NASA Technical Reports Server (NTRS)

Ponyik, Joseph G.; York, David W.

2002-01-01

Embedded Systems have traditionally been developed in a highly customized manner. The user interface hardware and software along with the interface to the embedded system are typically unique to the system for which they are built, resulting in extra cost to the system in terms of development time and maintenance effort. World Wide Web standards have been developed in the passed ten years with the goal of allowing servers and clients to intemperate seamlessly. The client and server systems can consist of differing hardware and software platforms but the World Wide Web standards allow them to interface without knowing about the details of system at the other end of the interface. Embedded Web Technology is the merging of Embedded Systems with the World Wide Web. Embedded Web Technology decreases the cost of developing and maintaining the user interface by allowing the user to interface to the embedded system through a web browser running on a standard personal computer. Embedded Web Technology can also be used to simplify an Embedded System's internal network.

Development of EPA Protocol Information Enquiry Service System Based on Embedded ARM Linux

NASA Astrophysics Data System (ADS)

Peng, Daogang; Zhang, Hao; Weng, Jiannian; Li, Hui; Xia, Fei

Industrial Ethernet is a new technology for industrial network communications developed in recent years. In the field of industrial automation in China, EPA is the first standard accepted and published by ISO, and has been included in the fourth edition IEC61158 Fieldbus of NO.14 type. According to EPA standard, Field devices such as industrial field controller, actuator and other instruments are all able to realize communication based on the Ethernet standard. The Atmel AT91RM9200 embedded development board and open source embedded Linux are used to develop an information inquiry service system of EPA protocol based on embedded ARM Linux in this paper. The system is capable of designing an EPA Server program for EPA data acquisition procedures, the EPA information inquiry service is available for programs in local or remote host through Socket interface. The EPA client can access data and information of other EPA equipments on the EPA network when it establishes connection with the monitoring port of the server.

Liquid-Embedded Elastomer Electronics

NASA Astrophysics Data System (ADS)

Kramer, Rebecca; Majidi, Carmel; Park, Yong-Lae; Paik, Jamie; Wood, Robert

2012-02-01

Hyperelastic sensors are fabricated by embedding a silicone rubber film with microchannels of conductive liquid. In the case of soft tactile sensors, pressing the surface of the elastomer will deform the cross-section of underlying channels and change their electrical resistance. Soft pressure sensors may be employed in a variety of applications. For example, a network of pressure sensors can serve as artificial skin by yielding detailed information about contact pressures. This concept was demonstrated in a hyperelastic keypad, where perpendicular conductive channels form a quasi-planar network within an elastomeric matrix that registers the location, intensity and duration of applied pressure. In a second demonstration, soft curvature sensors were used for joint angle proprioception. Because the sensors are soft and stretchable, they conform to the host without interfering with the natural mechanics of motion. This marked the first use of liquid-embedded elastomer electronics to monitor human or robotic motion. Finally, liquid-embedded elastomers may be implemented as conductors in applications that call for flexible or stretchable circuitry, such as robotic origami.

Wireless Computing Architecture III

DTIC Science & Technology

2013-09-01

MIMO Multiple-Input and Multiple-Output MIMO /CON MIMO with concurrent hannel access and estimation MU- MIMO Multiuser MIMO OFDM Orthogonal...compressive sensing \\; a design for concurrent channel estimation in scalable multiuser MIMO networking; and novel networking protocols based on machine...Network, Antenna Arrays, UAV networking, Angle of Arrival, Localization MIMO , Access Point, Channel State Information, Compressive Sensing 16

Polythiophene-fullerene based photodetectors: tuning of spectral response and application in photoluminescence based (bio)chemical sensors.

PubMed

Nalwa, Kanwar S; Cai, Yuankun; Thoeming, Aaron L; Shinar, Joseph; Shinar, Ruth; Chaudhary, Sumit

2010-10-01

A photoluminescence (PL)-based oxygen and glucose sensor utilizing inorganic or organic light emitting diode as the light source, and polythiophene: fullerene type bulk-heterojunction devices as photodetectors, for both intensity and decay-time based monitoring of the sensing element's PL. The sensing element is based on the oxygen-sensitive dye Pt-octaethylporphyrin embedded in a polystyrene matrix.

A light and faster regional convolutional neural network for object detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

2018-07-01

Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

An algorithm of a real time image tracking system using a camera with pan/tilt motors on an embedded system

NASA Astrophysics Data System (ADS)

Kim, Hie-Sik; Nam, Chul; Ha, Kwan-Yong; Ayurzana, Odgeral; Kwon, Jong-Won

2005-12-01

The embedded systems have been applied to many fields, including households and industrial sites. The user interface technology with simple display on the screen was implemented more and more. The user demands are increasing and the system has more various applicable fields due to a high penetration rate of the Internet. Therefore, the demand for embedded system is tend to rise. An embedded system for image tracking was implemented. This system is used a fixed IP for the reliable server operation on TCP/IP networks. Using an USB camera on the embedded Linux system developed a real time broadcasting of video image on the Internet. The digital camera is connected at the USB host port of the embedded board. All input images from the video camera are continuously stored as a compressed JPEG file in a directory at the Linux web-server. And each frame image data from web camera is compared for measurement of displacement Vector. That used Block matching algorithm and edge detection algorithm for past speed. And the displacement vector is used at pan/tilt motor control through RS232 serial cable. The embedded board utilized the S3C2410 MPU, which used the ARM 920T core form Samsung. The operating system was ported to embedded Linux kernel and mounted of root file system. And the stored images are sent to the client PC through the web browser. It used the network function of Linux and it developed a program with protocol of the TCP/IP.

Co Modeling and Co Synthesis of Safety Critical Multi threaded Embedded Software for Multi Core Embedded Platforms

DTIC Science & Technology

2017-03-20

computation, Prime Implicates, Boolean Abstraction, real- time embedded software, software synthesis, correct by construction software design , model...types for time -dependent data-flow networks". J.-P. Talpin, P. Jouvelot, S. Shukla. ACM-IEEE Conference on Methods and Models for System Design ...information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing   data sources, gathering and

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

DTIC Science & Technology

2005-05-01

made. 4. Do military decision makers identify / analyze adverse consequences presently? Few do based on this research and most don’t do it effectively ...A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM...ENS/05-01 A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM

Spatial Compressive Sensing for Strain Data Reconstruction from Sparse Sensors

DTIC Science & Technology

2014-10-01

optical fiber Bragg grating (or FBG ) sensors embedded in the plate. For the sake of simplicity, we assume that the FBGs are embedded in the radial...direction, as shown by the yellow lines in Fig. 10. The yellow lines are the direction along which strain is being measured. We considered FBGs here...however, strain gages emplaced along these lines can also be envisioned. FBGs are strain-measuring sensors that use the principle of low coherence

3D printing of highly elastic strain sensors using polyurethane/multiwall carbon nanotube composites

NASA Astrophysics Data System (ADS)

Christ, Josef F.; Hohimer, Cameron J.; Aliheidari, Nahal; Ameli, Amir; Mo, Changki; Pötschke, Petra

2017-04-01

As the desire for wearable electronics increases and the soft robotics industry advances, the need for novel sensing materials has also increased. Recently, there have been many attempts at producing novel materials, which exhibit piezoresistive behavior. However, one of the major shortcomings in strain sensing technologies is in the fabrication of such sensors. While there is significant research and literature covering the various methods for developing piezoresistive materials, fabricating complex sensor platforms is still a manufacturing challenge. Here, we report a facile method to fabricate multidirectional embedded strain sensors using additive manufacturing technology. Pure thermoplastic polyurethane (TPU) and TPU/multiwall carbon nanotubes (MWCNT) nanocomposites were 3D printed in tandem using a low-cost multi-material FDM printer to fabricate uniaxial and biaxial strain sensors with conductive paths embedded within the insulative TPU platform. The sensors were then subjected to a series of cyclic strain loads. The results revealed excellent piezoresistive responses of the sensors with cyclic repeatability in both the axial and transverse directions and in response to strains as high as 50%. Further, while strain-softening did occur in the embedded printed strain sensors, it was predictable and similar to the results found in the literature for bulk polymer nanocomposites. This works demonstrates the possibility of manufacturing embedded and multidirectional flexible strain sensors using an inexpensive and versatile method, with potential applications in soft robotics and flexible electronics and health monitoring.

Embedded fiber-optic sensing for accurate internal monitoring of cell state in advanced battery management systems part 2: Internal cell signals and utility for state estimation

NASA Astrophysics Data System (ADS)

Ganguli, Anurag; Saha, Bhaskar; Raghavan, Ajay; Kiesel, Peter; Arakaki, Kyle; Schuh, Andreas; Schwartz, Julian; Hegyi, Alex; Sommer, Lars Wilko; Lochbaum, Alexander; Sahu, Saroj; Alamgir, Mohamed

2017-02-01

A key challenge hindering the mass adoption of Lithium-ion and other next-gen chemistries in advanced battery applications such as hybrid/electric vehicles (xEVs) has been management of their functional performance for more effective battery utilization and control over their life. Contemporary battery management systems (BMS) reliant on monitoring external parameters such as voltage and current to ensure safe battery operation with the required performance usually result in overdesign and inefficient use of capacity. More informative embedded sensors are desirable for internal cell state monitoring, which could provide accurate state-of-charge (SOC) and state-of-health (SOH) estimates and early failure indicators. Here we present a promising new embedded sensing option developed by our team for cell monitoring, fiber-optic (FO) sensors. High-performance large-format pouch cells with embedded FO sensors were fabricated. This second part of the paper focuses on the internal signals obtained from these FO sensors. The details of the method to isolate intercalation strain and temperature signals are discussed. Data collected under various xEV operational conditions are presented. An algorithm employing dynamic time warping and Kalman filtering was used to estimate state-of-charge with high accuracy from these internal FO signals. Their utility for high-accuracy, predictive state-of-health estimation is also explored.

Simulating Operation of a Complex Sensor Network

NASA Technical Reports Server (NTRS)

Jennings, Esther; Clare, Loren; Woo, Simon

2008-01-01

Simulation Tool for ASCTA Microsensor Network Architecture (STAMiNA) ["ASCTA" denotes the Advanced Sensors Collaborative Technology Alliance.] is a computer program for evaluating conceptual sensor networks deployed over terrain to provide military situational awareness. This or a similar program is needed because of the complexity of interactions among such diverse phenomena as sensing and communication portions of a network, deployment of sensor nodes, effects of terrain, data-fusion algorithms, and threat characteristics. STAMiNA is built upon a commercial network-simulator engine, with extensions to include both sensing and communication models in a discrete-event simulation environment. Users can define (1) a mission environment, including terrain features; (2) objects to be sensed; (3) placements and modalities of sensors, abilities of sensors to sense objects of various types, and sensor false alarm rates; (4) trajectories of threatening objects; (5) means of dissemination and fusion of data; and (6) various network configurations. By use of STAMiNA, one can simulate detection of targets through sensing, dissemination of information by various wireless communication subsystems under various scenarios, and fusion of information, incorporating such metrics as target-detection probabilities, false-alarm rates, and communication loads, and capturing effects of terrain and threat.

[Study on artificial neural network combined with multispectral remote sensing imagery for forest site evaluation].

PubMed

Gong, Yin-Xi; He, Cheng; Yan, Fei; Feng, Zhong-Ke; Cao, Meng-Lei; Gao, Yuan; Miao, Jie; Zhao, Jin-Long

2013-10-01

Multispectral remote sensing data containing rich site information are not fully used by the classic site quality evaluation system, as it merely adopts artificial ground survey data. In order to establish a more effective site quality evaluation system, a neural network model which combined remote sensing spectra factors with site factors and site index relations was established and used to study the sublot site quality evaluation in the Wangyedian Forest Farm in Inner Mongolia Province, Chifeng City. Based on the improved back propagation artificial neural network (BPANN), this model combined multispectral remote sensing data with sublot survey data, and took larch as example, Through training data set sensitivity analysis weak or irrelevant factor was excluded, the size of neural network was simplified, and the efficiency of network training was improved. This optimal site index prediction model had an accuracy up to 95.36%, which was 9.83% higher than that of the neural network model based on classic sublot survey data, and this shows that using multi-spectral remote sensing and small class survey data to determine the status of larch index prediction model has the highest predictive accuracy. The results fully indicate the effectiveness and superiority of this method.

An Experimental Study on Static and Dynamic Strain Sensitivity of Embeddable Smart Concrete Sensors Doped with Carbon Nanotubes for SHM of Large Structures.

PubMed

Meoni, Andrea; D'Alessandro, Antonella; Downey, Austin; García-Macías, Enrique; Rallini, Marco; Materazzi, A Luigi; Torre, Luigi; Laflamme, Simon; Castro-Triguero, Rafael; Ubertini, Filippo

2018-03-09

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.

An Experimental Study on Static and Dynamic Strain Sensitivity of Embeddable Smart Concrete Sensors Doped with Carbon Nanotubes for SHM of Large Structures

PubMed Central

Meoni, Andrea; D’Alessandro, Antonella; García-Macías, Enrique; Rallini, Marco; Materazzi, A. Luigi; Torre, Luigi; Laflamme, Simon; Castro-Triguero, Rafael

2018-01-01

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications. PMID:29522498

Flexible Structural-Health-Monitoring Sheets

NASA Technical Reports Server (NTRS)

Qing, Xinlin; Kuo, Fuo

2008-01-01

A generic design for a type of flexible structural-health-monitoring sheet with multiple sensor/actuator types and a method of manufacturing such sheets has been developed. A sheet of this type contains an array of sensing and/or actuation elements, associated wires, and any other associated circuit elements incorporated into various flexible layers on a thin, flexible substrate. The sheet can be affixed to a structure so that the array of sensing and/or actuation elements can be used to analyze the structure in accordance with structural-health-monitoring techniques. Alternatively, the sheet can be designed to be incorporated into the body of the structure, especially if the structure is made of a composite material. Customarily, structural-health monitoring is accomplished by use of sensors and actuators arrayed at various locations on a structure. In contrast, a sheet of the present type can contain an entire sensor/actuator array, making it unnecessary to install each sensor and actuator individually on or in a structure. Sensors of different types such as piezoelectric and fiber-optic can be embedded in the sheet to form a hybrid sensor network. Similarly, the traces for electric communication can be deposited on one or two layers as required, and an entirely separate layer can be employed to shield the sensor elements and traces.

Aquatic Debris Detection Using Embedded Camera Sensors

PubMed Central

Wang, Yong; Wang, Dianhong; Lu, Qian; Luo, Dapeng; Fang, Wu

2015-01-01

Aquatic debris monitoring is of great importance to human health, aquatic habitats and water transport. In this paper, we first introduce the prototype of an aquatic sensor node equipped with an embedded camera sensor. Based on this sensing platform, we propose a fast and accurate debris detection algorithm. Our method is specifically designed based on compressive sensing theory to give full consideration to the unique challenges in aquatic environments, such as waves, swaying reflections, and tight energy budget. To upload debris images, we use an efficient sparse recovery algorithm in which only a few linear measurements need to be transmitted for image reconstruction. Besides, we implement the host software and test the debris detection algorithm on realistically deployed aquatic sensor nodes. The experimental results demonstrate that our approach is reliable and feasible for debris detection using camera sensors in aquatic environments. PMID:25647741

Spatio-temporal networks: reachability, centrality and robustness.

PubMed

Williams, Matthew J; Musolesi, Mirco

2016-06-01

Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.

Dynamics of influence and social balance in spatially-embedded regular and random networks

NASA Astrophysics Data System (ADS)

Singh, P.; Sreenivasan, S.; Szymanski, B.; Korniss, G.

2015-03-01

Structural balance - the tendency of social relationship triads to prefer specific states of polarity - can be a fundamental driver of beliefs, behavior, and attitudes on social networks. Here we study how structural balance affects deradicalization in an otherwise polarized population of leftists and rightists constituting the nodes of a low-dimensional social network. Specifically, assuming an externally moderating influence that converts leftists or rightists to centrists with probability p, we study the critical value p =pc , below which the presence of metastable mixed population states exponentially delay the achievement of centrist consensus. Above the critical value, centrist consensus is the only fixed point. Complementing our previously shown results for complete graphs, we present results for the process on low-dimensional networks, and show that the low-dimensional embedding of the underlying network significantly affects the critical value of probability p. Intriguingly, on low-dimensional networks, the critical value pc can show non-monotonicity as the dimensionality of the network is varied. We conclude by analyzing the scaling behavior of temporal variation of unbalanced triad density in the network for different low-dimensional network topologies. Supported in part by ARL NS-CTA, ONR, and ARO.

Spatial effects in real networks: Measures, null models, and applications

NASA Astrophysics Data System (ADS)

Ruzzenenti, Franco; Picciolo, Francesco; Basosi, Riccardo; Garlaschelli, Diego

2012-12-01

Spatially embedded networks are shaped by a combination of purely topological (space-independent) and space-dependent formation rules. While it is quite easy to artificially generate networks where the relative importance of these two factors can be varied arbitrarily, it is much more difficult to disentangle these two architectural effects in real networks. Here we propose a solution to this problem, by introducing global and local measures of spatial effects that, through a comparison with adequate null models, effectively filter out the spurious contribution of nonspatial constraints. Our filtering allows us to consistently compare different embedded networks or different historical snapshots of the same network. As a challenging application we analyze the World Trade Web, whose topology is known to depend on geographic distances but is also strongly determined by nonspatial constraints (degree sequence or gross domestic product). Remarkably, we are able to detect weak but significant spatial effects both locally and globally in the network, showing that our method succeeds in retrieving spatial information even when nonspatial factors dominate. We finally relate our results to the economic literature on gravity models and trade globalization.

Hybrid brain-computer interface for biomedical cyber-physical system application using wireless embedded EEG systems.

PubMed

Chai, Rifai; Naik, Ganesh R; Ling, Sai Ho; Nguyen, Hung T

2017-01-07

One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels. In addition, a microcontroller based head-mounted battery-operated wireless EEG sensor combined with a separate embedded system is used to enhance portability, convenience and cost effectiveness. This experiment has been conducted with five healthy participants and five patients with tetraplegia. Generally, the results show comparable classification accuracies between healthy subjects and tetraplegia patients. For the offline artificial neural network classification for the target group of patients with tetraplegia, the hybrid BCI system combines three mental tasks, three SSVEP frequencies and eyes closed, with average classification accuracy at 74% and average information transfer rate (ITR) of the system of 27 bits/min. For the real-time testing of the intentional signal on patients with tetraplegia, the average success rate of detection is 70% and the speed of detection varies from 2 to 4 s.

Integrated Hydrologic Science and Environmental Engineering Observatory: CLEANER's Vision for the WATERS Network

NASA Astrophysics Data System (ADS)

Montgomery, J. L.; Minsker, B. S.; Schnoor, J.; Haas, C.; Bonner, J.; Driscoll, C.; Eschenbach, E.; Finholt, T.; Glass, J.; Harmon, T.; Johnson, J.; Krupnik, A.; Reible, D.; Sanderson, A.; Small, M.; van Briesen, J.

2006-05-01

With increasing population and urban development, societies grow more and more concerned over balancing the need to maintain adequate water supplies with that of ensuring the quality of surface and groundwater resources. For example, multiple stressors such as overfishing, runoff of nutrients from agricultural fields and confined animal feeding lots, and pathogens in urban stormwater can often overwhelm a single water body. Mitigating just one of these problems often depends on understanding how it relates to others and how stressors can vary in temporal and spatial scales. Researchers are now in a position to answer questions about multiscale, spatiotemporally distributed hydrologic and environmental phenomena through the use of remote and embedded networked sensing technologies. It is now possible for data streaming from sensor networks to be integrated by a rich cyberinfrastructure encompassing the innovative computing, visualization, and information archiving strategies needed to cope with the anticipated onslaught of data, and to turn that data around in the form of real-time water quantity and quality forecasting. Recognizing this potential, NSF awarded $2 million to a coalition of 12 institutions in July 2005 to establish the CLEANER Project Office (Collaborative Large-Scale Engineering Analysis Network for Environmental Research; http://cleaner.ncsa.uiuc.edu). Over the next two years the project office, in coordination with CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.; http://www.cuahsi.org), will work together to develop a plan for a WATer and Environmental Research Systems Network (WATERS Network), which is envisioned to be a collaborative scientific exploration and engineering analysis network, using high performance tools and infrastructure, to transform our scientific understanding of how water quantity, quality, and related earth system processes are affected by natural and human-induced changes to the environment. This presentation will give an overview of the draft CLEANER program plans for the WATERS Network and next steps.

Ion track based tunable device as humidity sensor: a neural network approach

NASA Astrophysics Data System (ADS)

Sharma, Mamta; Sharma, Anuradha; Bhattacherjee, Vandana

2013-01-01

Artificial Neural Network (ANN) has been applied in statistical model development, adaptive control system, pattern recognition in data mining, and decision making under uncertainty. The nonlinear dependence of any sensor output on the input physical variable has been the motivation for many researchers to attempt unconventional modeling techniques such as neural networks and other machine learning approaches. Artificial neural network (ANN) is a computational tool inspired by the network of neurons in biological nervous system. It is a network consisting of arrays of artificial neurons linked together with different weights of connection. The states of the neurons as well as the weights of connections among them evolve according to certain learning rules.. In the present work we focus on the category of sensors which respond to electrical property changes such as impedance or capacitance. Recently, sensor materials have been embedded in etched tracks due to their nanometric dimensions and high aspect ratio which give high surface area available for exposure to sensing material. Various materials can be used for this purpose to probe physical (light intensity, temperature etc.), chemical (humidity, ammonia gas, alcohol etc.) or biological (germs, hormones etc.) parameters. The present work involves the application of TEMPOS structures as humidity sensors. The sample to be studied was prepared using the polymer electrolyte (PEO/NH4ClO4) with CdS nano-particles dispersed in the polymer electrolyte. In the present research we have attempted to correlate the combined effects of voltage and frequency on impedance of humidity sensors using a neural network model and results have indicated that the mean absolute error of the ANN Model for the training data was 3.95% while for the validation data it was 4.65%. The corresponding values for the LR model were 8.28% and 8.35% respectively. It was also demonstrated the percentage improvement of the ANN Model with respect to the linear regression model. This demonstrates the suitability of neural networks to perform such modeling.

A Spectrum Sensing Network for Cognitive PMSE Systems

NASA Astrophysics Data System (ADS)

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

2012-09-01

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

Breaking down the barriers of using strong authentication and encryption in resource constrained embedded systems

NASA Astrophysics Data System (ADS)

Knobler, Ron; Scheffel, Peter; Jackson, Scott; Gaj, Kris; Kaps, Jens Peter

2013-05-01

Various embedded systems, such as unattended ground sensors (UGS), are deployed in dangerous areas, where they are subject to compromise. Since numerous systems contain a network of devices that communicate with each other (often times with commercial off the shelf [COTS] radios), an adversary is able to intercept messages between system devices, which jeopardizes sensitive information transmitted by the system (e.g. location of system devices). Secret key algorithms such as AES are a very common means to encrypt all system messages to a sufficient security level, for which lightweight implementations exist for even very resource constrained devices. However, all system devices must use the appropriate key to encrypt and decrypt messages from each other. While traditional public key algorithms (PKAs), such as RSA and Elliptic Curve Cryptography (ECC), provide a sufficiently secure means to provide authentication and a means to exchange keys, these traditional PKAs are not suitable for very resource constrained embedded systems or systems which contain low reliability communication links (e.g. mesh networks), especially as the size of the network increases. Therefore, most UGS and other embedded systems resort to pre-placed keys (PPKs) or other naïve schemes which greatly reduce the security and effectiveness of the overall cryptographic approach. McQ has teamed with the Cryptographic Engineering Research Group (CERG) at George Mason University (GMU) to develop an approach using revolutionary cryptographic techniques that provides both authentication and encryption, but on resource constrained embedded devices, without the burden of large amounts of key distribution or storage.

Good Communication: The Other Social Network for Successful IT Organizations

ERIC Educational Resources Information Center

Trubitt, Lisa; Overholtzer, Jeff

2009-01-01

Social networks of the electronic variety have become thoroughly embedded in contemporary culture. People have woven these networks into their daily routines, using Facebook, Twitter, LinkedIn, online gaming environments, and other tools to build and maintain complex webs of professional and personal relationships. Chief Information Officers…

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2014-09-30

underwater acoustic communication technologies for autonomous distributed underwater networks , through innovative signal processing, coding, and...4. TITLE AND SUBTITLE Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and...coding: 3) OFDM modulated dynamic coded cooperation in underwater acoustic channels; 3 Localization, Networking , and Testbed: 4) On-demand

Optical chaos and hybrid WDM/TDM based large capacity quasi-distributed sensing network with real-time fiber fault monitoring.

PubMed

Luo, Yiyang; Xia, Li; Xu, Zhilin; Yu, Can; Sun, Qizhen; Li, Wei; Huang, Di; Liu, Deming

2015-02-09

An optical chaos and hybrid wavelength division multiplexing/time division multiplexing (WDM/TDM) based large capacity quasi-distributed sensing network with real-time fiber fault monitoring is proposed. Chirped fiber Bragg grating (CFBG) intensity demodulation is adopted to improve the dynamic range of the measurements. Compared with the traditional sensing interrogation methods in time, radio frequency and optical wavelength domains, the measurand sensing and the precise locating of the proposed sensing network can be simultaneously interrogated by the relative amplitude change (RAC) and the time delay of the correlation peak in the cross-correlation spectrum. Assisted with the WDM/TDM technology, hundreds of sensing units could be potentially multiplexed in the multiple sensing fiber lines. Based on the proof-of-concept experiment for axial strain measurement with three sensing fiber lines, the strain sensitivity up to 0.14% RAC/με and the precise locating of the sensors are achieved. Significantly, real-time fiber fault monitoring in the three sensing fiber lines is also implemented with a spatial resolution of 2.8 cm.

Nitrogen-doped graphene network supported copper nanoparticles encapsulated with graphene shells for surface-enhanced Raman scattering

NASA Astrophysics Data System (ADS)

Zhang, Xiang; Shi, Chunsheng; Liu, Enzuo; Li, Jiajun; Zhao, Naiqin; He, Chunnian

2015-10-01

In this study, we demonstrated nitrogen-doped graphene network supported few-layered graphene shell encapsulated Cu nanoparticles (NPs) (Cu@G-NGNs) as a sensing platform, which were constructed by a simple and scalable in situ chemical vapor deposition (CVD) technique with the assistance of a self-assembled three-dimensional (3D) NaCl template. Compared with pure Cu NPs and graphene decorated Cu NPs, the graphene shells can strengthen the plasmonic coupling between graphene and Cu, thereby contributing to an obvious improvement in the local electromagnetic field that was validated by finite element numerical simulations, while the 3D nitrogen-doped graphene walls with a large surface area facilitated molecule adsorption and the doped nitrogen atoms embedded in the graphene lattice can reduce the surface energy of the system. With these merits, a good surface enhanced Raman spectroscopy (SERS) activity of the 3D Cu@G-NGN painting film on glass was demonstrated using rhodamine 6G and crystal violet as model analytes, exhibiting a satisfactory sensitivity, reproducibility and stability. As far as we know, this is the first report on the in situ synthesis of nitrogen-doped graphene/copper nanocomposites and this facile and low-cost Cu-based strategy tends to be a good supplement to Ag and Au based substrates for SERS applications.In this study, we demonstrated nitrogen-doped graphene network supported few-layered graphene shell encapsulated Cu nanoparticles (NPs) (Cu@G-NGNs) as a sensing platform, which were constructed by a simple and scalable in situ chemical vapor deposition (CVD) technique with the assistance of a self-assembled three-dimensional (3D) NaCl template. Compared with pure Cu NPs and graphene decorated Cu NPs, the graphene shells can strengthen the plasmonic coupling between graphene and Cu, thereby contributing to an obvious improvement in the local electromagnetic field that was validated by finite element numerical simulations, while the 3D nitrogen-doped graphene walls with a large surface area facilitated molecule adsorption and the doped nitrogen atoms embedded in the graphene lattice can reduce the surface energy of the system. With these merits, a good surface enhanced Raman spectroscopy (SERS) activity of the 3D Cu@G-NGN painting film on glass was demonstrated using rhodamine 6G and crystal violet as model analytes, exhibiting a satisfactory sensitivity, reproducibility and stability. As far as we know, this is the first report on the in situ synthesis of nitrogen-doped graphene/copper nanocomposites and this facile and low-cost Cu-based strategy tends to be a good supplement to Ag and Au based substrates for SERS applications. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr04259c

Additively Manufactured IN718 Components with Wirelessly Powered and Interrogated Embedded Sensing

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

Attridge, Paul; Bajekal, Sanjay; Klecka, Michael

A methodology is described for embedding commercial-off-the-shelf sensors together with wireless communication and power circuit elements using direct laser metal sintered additively manufactured components. Physics based models of the additive manufacturing processes and sensor/wireless level performance models guided the design and embedment processes. A combination of cold spray deposition and laser engineered net shaping was used to fashion the transmitter/receiving elements and embed the sensors, thereby providing environmental protection and component robustness/survivability for harsh conditions. By design, this complement of analog and digital sensors were wirelessly powered and interrogated using a health and utilization monitoring system; enabling real-time, in situmore » prognostics and diagnostics.« less

Qualification of a truly distributed fiber optic technique for strain and temperature measurements in concrete structures

NASA Astrophysics Data System (ADS)

Henault, J. M.; Salin, J.; Moreau, G.; Delepine-Lesoille, S.; Bertand, J.; Taillade, F.; Quiertant, M.; Benzarti, K.

2011-04-01

Structural health monitoring is a key factor in life cycle management of infrastructures. Truly distributed fiber optic sensors are able to provide relevant information on large structures, such as nuclear power plants or nuclear waste disposal facilities. The sensing chain includes an optoelectronic unit and a sensing cable made of one or more optical fibers. A new instrument based on Optical Frequency Domain Reflectometry (OFDR), enables to perform temperature and strain measurements with a centimeter scale spatial resolution over hundred of meters and with a level of precision equal to 1 μ strain and 0.1 °C. Several sensing cables are designed with different materials targeting to last for decades, either embedded in the concrete or attached to the surface of the structure. They must ensure an optimal transfer of temperature and strain from the concrete matrix to the optical fiber. Based on the European guide FD CEN/TR 14748 "Non-destructive testing - Methodology for qualification of non-destructive tests", a qualification method was developed. Tests were carried out using various sensing cables embedded in the volume or fixed to the surface of plain concrete specimens and representative-scale reinforced concrete structural elements. Measurements were performed with an OFDR instrument, while mechanical solicitations were imposed to the concrete element. Preliminary experiments seem very promising since measurements performed with distributed sensing systems are found comparable to values obtained with conventional sensors used in civil engineering and with the Strength of Materials Modelling. Moreover, the distributed sensing system makes it possible to detect and localize cracks appearing in concrete during the mechanical loading.

A bio-molecular inspired electronic architecture: bio-based device concepts for enhanced sensing (Invited Paper)

NASA Astrophysics Data System (ADS)

Woolard, Dwight L.; Luo, Ying; Gelmont, Boris L.; Globus, Tatiana; Jensen, James O.

2005-05-01

A biological(bio)-molecular inspired electronic architecture is presented that offers the potential for defining nanoscale sensor platforms with enhanced capabilities for sensing terahertz (THz) frequency bio-signatures. This architecture makes strategic use of integrated biological elements to enable communication and high-level function within densely-packed nanoelectronic systems. In particular, this architecture introduces a new paradigm for establishing hybrid Electro-THz-Optical (ETO) communication channels where the THz-frequency spectral characteristics that are uniquely associated with the embedded bio-molecules are utilized directly. Since the functionality of this architecture is built upon the spectral characteristics of bio-molecules, this immediately allows for defining new methods for enhanced sensing of THz bio-signatures. First, this integrated sensor concept greatly facilitates the collection of THz bio-signatures associated with embedded bio-molecules via interactions with the time-dependent signals propagating through the nanoelectronic circuit. Second, it leads to a new Multi-State Spectral Sensing (MS3) approach where bio-signature information can be collected from multiple metastable state conformations. This paper will also introduce a new class of prototype devices that utilize THz-sensitive bio-molecules to achieve molecular-level sensing and functionality. Here, new simulation results are presented for a class of bio-molecular components that exhibit the prescribed type of ETO characteristics required for realizing integrated sensor platforms. Most noteworthy, this research derives THz spectral bio-signatures for organic molecules that are amenable to photo-induced metastable-state conformations and establishes an initial scientific foundation and design blueprint for an enhanced THz bio-signature sensing capability.

Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...

A recurrent neural network for nonlinear optimization with a continuously differentiable objective function and bound constraints.

PubMed

Liang, X B; Wang, J

2000-01-01

This paper presents a continuous-time recurrent neural-network model for nonlinear optimization with any continuously differentiable objective function and bound constraints. Quadratic optimization with bound constraints is a special problem which can be solved by the recurrent neural network. The proposed recurrent neural network has the following characteristics. 1) It is regular in the sense that any optimum of the objective function with bound constraints is also an equilibrium point of the neural network. If the objective function to be minimized is convex, then the recurrent neural network is complete in the sense that the set of optima of the function with bound constraints coincides with the set of equilibria of the neural network. 2) The recurrent neural network is primal and quasiconvergent in the sense that its trajectory cannot escape from the feasible region and will converge to the set of equilibria of the neural network for any initial point in the feasible bound region. 3) The recurrent neural network has an attractivity property in the sense that its trajectory will eventually converge to the feasible region for any initial states even at outside of the bounded feasible region. 4) For minimizing any strictly convex quadratic objective function subject to bound constraints, the recurrent neural network is globally exponentially stable for almost any positive network parameters. Simulation results are given to demonstrate the convergence and performance of the proposed recurrent neural network for nonlinear optimization with bound constraints.

Neuron-Inspired Interpenetrative Network Composed of Cobalt-Phosphorus-Derived Nanoparticles Embedded within Porous Carbon Nanotubes for Efficient Hydrogen Production.

PubMed

Shen, Juanxia; Yang, Zhi; Ge, Mengzhan; Li, Ping; Nie, Huagui; Cai, Qiran; Gu, Cancan; Yang, Keqin; Huang, Shaoming

2016-07-13

The ongoing search for cheap and efficient hydrogen evolution reaction (HER) electrocatalysts to replace currently used catalysts based on Pt or its alloys has been considered as an prevalent strategy to produce renewable and clean hydrogen energy. Herein, inspired by the neuron structure in biological systems, we demonstrate a novel fabrication strategy via a simple two-step method for the synthesis of a neuronlike interpenetrative nanocomposite network of Co-P embedded in porous carbon nanotubes (NIN-Co-P/PCNTs). It is found that the interpenetrative network provides a natural transport path to accelerate the hydrogen production process. The embedded-type structure improves the utilization ratio of Co-P and the hollow, tubelike, and porous structure of PCNTs further promote charge and reactant transport. These factors allow the as-prepared NIN-Co-P/PCNTs to achieve a onset potential low to 43 mV, a Tafel slope as small as 40 mV/decade, an excellent stability, and a high turnover frequency value of 3.2 s(-1) at η = 0.2 V in acidic conditions. These encouraging properties derived from the neuronlike interpenetrative network structure might offer new inspiration for the preparation of more nanocomposites for applications in other catalytic and optoelectronic field.

Invisible but Essential: The Role of Professional Networks in Promoting Faculty Agency in Career Advancement

ERIC Educational Resources Information Center

Niehaus, Elizabeth; O'Meara, KerryAnn

2015-01-01

The benefits of professional networks are largely invisible to the people embedded in them (O'Reilly 1991), yet professional networks may provide key benefits for faculty careers. The purpose of the study reported here was to explore the role of professional networks in faculty agency in career advancement, specifically focusing on the overall…

Is It Time for a US Cyber Force?

DTIC Science & Technology

2015-02-17

network of information technology (IT) and resident data, including the Internet , telecommunications networks, computer systems, and embedded processors...and controllers.13 JP 3-12 further goes on to explain cyberspace in terms of three layers: physical network, logical network, and cyber- persona .14...zero day) vulnerabilities against Microsoft operating system code using trusted hardware vendor certificates to cloak their presence. Though not

A Reinforcement Sensor Embedded Vertical Handoff Controller for Vehicular Heterogeneous Wireless Networks

PubMed Central

Li, Limin; Xu, Yubin; Soong, Boon-Hee; Ma, Lin

2013-01-01

Vehicular communication platforms that provide real-time access to wireless networks have drawn more and more attention in recent years. IEEE 802.11p is the main radio access technology that supports communication for high mobility terminals, however, due to its limited coverage, IEEE 802.11p is usually deployed by coupling with cellular networks to achieve seamless mobility. In a heterogeneous cellular/802.11p network, vehicular communication is characterized by its short time span in association with a wireless local area network (WLAN). Moreover, for the media access control (MAC) scheme used for WLAN, the network throughput dramatically decreases with increasing user quantity. In response to these compelling problems, we propose a reinforcement sensor (RFS) embedded vertical handoff control strategy to support mobility management. The RFS has online learning capability and can provide optimal handoff decisions in an adaptive fashion without prior knowledge. The algorithm integrates considerations including vehicular mobility, traffic load, handoff latency, and network status. Simulation results verify that the proposed algorithm can adaptively adjust the handoff strategy, allowing users to stay connected to the best network. Furthermore, the algorithm can ensure that RSUs are adequate, thereby guaranteeing a high quality user experience. PMID:24193101

Brand communities embedded in social networks.

PubMed

Zaglia, Melanie E

2013-02-01

Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social networks. The netnographic approach yields strong evidence of this existence; leading to a better understanding of such embedded brand communities, their peculiarities, and motivational drivers for participation; therefore the findings contribute to theory by combining two separate research streams. Due to the advantages of social networks, brand management is now able to implement brand communities with less time and financial effort; however, choosing the appropriate brand community type, cultivating consumers' interaction, and staying tuned to this social engagement are critical factors to gain anticipated brand outcomes.

On a phase diagram for random neural networks with embedded spike timing dependent plasticity.

PubMed

Turova, Tatyana S; Villa, Alessandro E P

2007-01-01

This paper presents an original mathematical framework based on graph theory which is a first attempt to investigate the dynamics of a model of neural networks with embedded spike timing dependent plasticity. The neurons correspond to integrate-and-fire units located at the vertices of a finite subset of 2D lattice. There are two types of vertices, corresponding to the inhibitory and the excitatory neurons. The edges are directed and labelled by the discrete values of the synaptic strength. We assume that there is an initial firing pattern corresponding to a subset of units that generate a spike. The number of activated externally vertices is a small fraction of the entire network. The model presented here describes how such pattern propagates throughout the network as a random walk on graph. Several results are compared with computational simulations and new data are presented for identifying critical parameters of the model.

Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn Tae

2016-01-01

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model. PMID:27669249

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

Framework and implementation of a continuous network-wide health monitoring system for roadways

NASA Astrophysics Data System (ADS)

Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar

2014-03-01

According to the 2013 ASCE report card America's infrastructure scores only a D+. There are more than four million miles of roads (grade D) in the U.S. requiring a broad range of maintenance activities. The nation faces a monumental problem of infrastructure management in the scheduling and implementation of maintenance and repair operations, and in the prioritization of expenditures within budgetary constraints. The efficient and effective performance of these operations however is crucial to ensuring roadway safety, preventing catastrophic failures, and promoting economic growth. There is a critical need for technology that can cost-effectively monitor the condition of a network-wide road system and provide accurate, up-to-date information for maintenance activity prioritization. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project provides a framework and the sensing capability to complement periodical localized inspections to continuous network-wide health monitoring. Research focused on the development of a cost-effective, lightweight package of multi-modal sensor systems compatible with this framework. An innovative software infrastructure is created that collects, processes, and evaluates these large time-lapse multi-modal data streams. A GIS-based control center manages multiple inspection vehicles and the data for further analysis, visualization, and decision making. VOTERS' technology can monitor road conditions at both the surface and sub-surface levels while the vehicle is navigating through daily traffic going about its normal business, thereby allowing for network-wide frequent assessment of roadways. This deterioration process monitoring at unprecedented time and spatial scales provides unique experimental data that can be used to improve life-cycle cost analysis models.

Applied research of embedded WiFi technology in the motion capture system

NASA Astrophysics Data System (ADS)

Gui, Haixia

2012-04-01

Embedded wireless WiFi technology is one of the current wireless hot spots in network applications. This paper firstly introduces the definition and characteristics of WiFi. With the advantages of WiFi such as using no wiring, simple operation and stable transmission, this paper then gives a system design for the application of embedded wireless WiFi technology in the motion capture system. Also, it verifies the effectiveness of design in the WiFi-based wireless sensor hardware and software program.

Web Service Architecture Framework for Embedded Devices

ERIC Educational Resources Information Center

Yanzick, Paul David

2009-01-01

The use of Service Oriented Architectures, namely web services, has become a widely adopted method for transfer of data between systems across the Internet as well as the Enterprise. Adopting a similar approach to embedded devices is also starting to emerge as personal devices and sensor networks are becoming more common in the industry. This…

Carbon nanotube-embedded advanced aerospace composites for early-stage damage sensing

NASA Astrophysics Data System (ADS)

Nataraj, Latha; Coatney, Michael; Cain, Jason; Hall, Asha

2018-03-01

Fiber reinforced polymer (FRP) composites featuring outstanding fatigue performance, high specific stiffness and strength, and low density have evolved as critical structural materials in aerospace applications. Microscale damage such as fiber breakage, matrix cracking, and delamination could occur in layered composites compromising structural integrity, emphasizing the critical need to monitor structural health. Early damage detection would lead to enhanced reliability, lifetime, and performance while minimizing maintenance time, leading to enormous scientific and technical interest in realizing physically stable, quick responding, and cost effective strain sensing materials, devices, and techniques with high sensitivity over a broad range of the practical strain spectrum. Today's most commonly used strain sensing techniques are metal foil strain gauges and optical fiber sensors. Metal foil gauges offer high stability and cost-effectiveness but can only be surface-mounted and have a low gauge factor. Optical fibers require expensive instrumentation, are mostly insensitive to cracks parallel to the fiber orientation and may lead to crack initiation as the diameter is larger than that of the reinforcement fibers. Carbon nanotubes (CNTs) have attracted much attention due to high aspect ratio and superior electrical, thermal, and mechanical properties. CNTs embedded in layered composites have improved performance. A variety of CNT architectures and configurations have shown improved piezoresistive behavior and stability for sensing applications. However, scaling up and commercialization remain serious challenges. The current study investigates a simple, cost effective and repeatable technique for highly sensitive, stable, linear and repeatable strain sensing for damage detection by integrating CNT laminates into composites.

Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network.

PubMed

Wu, Yonghui; Jiang, Min; Lei, Jianbo; Xu, Hua

2015-01-01

Rapid growth in electronic health records (EHRs) use has led to an unprecedented expansion of available clinical data in electronic formats. However, much of the important healthcare information is locked in the narrative documents. Therefore Natural Language Processing (NLP) technologies, e.g., Named Entity Recognition that identifies boundaries and types of entities, has been extensively studied to unlock important clinical information in free text. In this study, we investigated a novel deep learning method to recognize clinical entities in Chinese clinical documents using the minimal feature engineering approach. We developed a deep neural network (DNN) to generate word embeddings from a large unlabeled corpus through unsupervised learning and another DNN for the NER task. The experiment results showed that the DNN with word embeddings trained from the large unlabeled corpus outperformed the state-of-the-art CRF's model in the minimal feature engineering setting, achieving the highest F1-score of 0.9280. Further analysis showed that word embeddings derived through unsupervised learning from large unlabeled corpus remarkably improved the DNN with randomized embedding, denoting the usefulness of unsupervised feature learning.

Isolated planar gyroscope with internal radial sensing and actuation

NASA Technical Reports Server (NTRS)

Challoner, A. Dorian (Inventor); Shcheglov, Kirill V. (Inventor)

2006-01-01

The present invention discloses an inertial sensor comprising a planar mechanical resonator with embedded sensing and actuation for substantially in-plane vibration and having a central rigid support for the resonator. At least one excitation or torquer electrode is disposed within an interior of the resonator to excite in-plane vibration of the resonator and at least one sensing or pickoff electrode is disposed within the interior of the resonator for sensing the motion of the excited resonator. In one embodiment, the planar resonator includes a plurality of slots in an annular pattern; in another embodiment, the planar mechanical resonator comprises four masses; each embodiment having a simple degenerate pair of in-plane vibration modes.

Chemochromic Detector for Sensing Gas Leakage and Process for Producing the Same

NASA Technical Reports Server (NTRS)

Williams, Martha K. (Inventor); Captain, Janine E. (Inventor); Roberson, Luke B. (Inventor); Tate, LaNetra Clayton (Inventor)

2015-01-01

A chemochromic sensor for detecting a combustible gas, such as hydrogen, includes a chemochromic pigment and a textile polymer. The textile material includes a chemochromic pigment operably responsive to a combustible gas. The combustible gas sensing textile material can be made by melt spinning, solution spinning, or other similar techniques. In a preferred embodiment carbon nanotubes are used with the textile material which will increase the material strength and alter the thermal and/or electrical properties. These textiles woven into fabrics can provide garments not only with hydrogen sensing capabilities but the carbon nanotubes will allow for a range of sensing capabilities to be embedded (i.e. gas, health, and electronic monitors) within the garments.

Artificial neural networks as quantum associative memory

NASA Astrophysics Data System (ADS)

Hamilton, Kathleen; Schrock, Jonathan; Imam, Neena; Humble, Travis

We present results related to the recall accuracy and capacity of Hopfield networks implemented on commercially available quantum annealers. The use of Hopfield networks and artificial neural networks as content-addressable memories offer robust storage and retrieval of classical information, however, implementation of these models using currently available quantum annealers faces several challenges: the limits of precision when setting synaptic weights, the effects of spurious spin-glass states and minor embedding of densely connected graphs into fixed-connectivity hardware. We consider neural networks which are less than fully-connected, and also consider neural networks which contain multiple sparsely connected clusters. We discuss the effect of weak edge dilution on the accuracy of memory recall, and discuss how the multiple clique structure affects the storage capacity. Our work focuses on storage of patterns which can be embedded into physical hardware containing n < 1000 qubits. This work was supported by the United States Department of Defense and used resources of the Computational Research and Development Programs as Oak Ridge National Laboratory under Contract No. DE-AC0500OR22725 with the U. S. Department of Energy.

Embedded fiber optic sensors for monitoring processing, quality and structural health of resin transfer molded components

NASA Astrophysics Data System (ADS)

Keulen, C.; Rocha, B.; Yildiz, M.; Suleman, A.

2011-07-01

Due to their small size and flexibility fiber optics can be embedded into composite materials with little negative effect on strength and reliability of the host material. Fiber optic sensors such as Fiber Bragg Gratings (FBG) or Etched Fiber Sensors (EFS) can be used to detect a number of relevant parameters such as flow, degree of cure, quality and structural health throughout the life of a composite component. With a detection algorithm these embedded sensors can be used to detect damage in real time while the component remains in service. This paper presents the research being conducted on the use of fiber optic sensors for process and Structural Health Monitoring (SHM) of Resin Transfer Molded (RTM) composite structures. Fiber optic sensors are used at all life stages of an RTM composite panel. A laboratory scale RTM apparatus was developed with the capability of visually monitoring the resin filling process. A technique for embedding fiber optic sensors with this apparatus has also been developed. Both FBGs and EFSs have been embedded in composite panels using the apparatus. EFSs to monitor the fabrication process, specifically resin flow have been embedded and shown to be capable of detecting the presence of resin at various locations as it is injected into the mold. Simultaneously these sensors were multiplexed on the same fiber with FBGs, which have the ability to measure strain. Since multiple sensors can be multiplexed on a single fiber the number of ingress/egress locations required per sensor can be significantly reduced. To characterize the FBGs for strain detection tensile test specimens with embedded FBG sensors have been produced. These specimens have been instrumented with a resistive strain gauge for benchmarking. Both specimens and embedded sensors were characterized through tensile testing. Furthermore FBGs have been embedded into composite panels in a manner that is conducive to detection of Lamb waves generated with a centrally located PZT. To sense Lamb waves a high speed, high precision sensing technique is required to acquire data from embedded FBGs due to the high velocities and small strain amplitudes of these guided waves. A technique based on a filter consisting of a tunable FBG was developed. Since this filter is not dependant on moving parts, tests executed with this filter concluded with the detection of Lamb waves, removing the influence of temperature and operational strains. A damage detection algorithm was developed to detect and localize cracks and delaminations.

Towards Multifunctional Characteristics of Embedded Structures With Carbon Nanotube Yarns

NASA Technical Reports Server (NTRS)

Hernandez, Corey D.; Gates, Thomas S.; Kahng, Seun K.

2006-01-01

This paper presents recent results on research of achieving multifunctional structures utilizing Carbon Nanotube (CNT) yarns. The investigation centers on creating composite structures with CNT yarns to simultaneously achieve increases in mechanical strength and the ability to sense strain. The CNT yarns used in our experiments are of the single-ply and two-ply variety with the single-ply yarns having diameters on the order of 10-20 m. The yarns are embedded in silicon rubber and polyurethane test specimens. Mechanical tests show an increase in modulus of elasticity, with an additional weight increase of far less than one-percent. Sensing characteristics of the yarns are investigated on stainless steel test beams in an electrical bridge configuration, and are observed to have a strain sensitivity of 0.7mV/V/1000 micro-strain. Also reported are measurements of the average strain distribution along the direction of the CNT yarns on square silicon rubber membranes.

Interferometric fiber-optic sensor embedded in a spark plug for in-cylinder pressure measurement in engines.

PubMed

Bae, Taehan; Atkins, Robert A; Taylor, Henry F; Gibler, William N

2003-02-20

Pressure sensing in an internal combustion engine with an intrinsic fiber Fabry-Perot interferometer (FFPI) integrated with a spark plug is demonstrated for the first time. The spark plug was used for the ignition of the cylinder in which it was mounted. The FFPI element, protected with a copper/gold coating, was embedded in a groove in the spark-plug housing. Gas pressure inthe engine induced longitudinal strain in this housing, which was also experienced by the fiber-optic sensing element. The sensor was monitored with a signal conditioning unit containing a chirped distributed-feedback laser. Pressure sensitivities as high as 0.00339 radians round-trip phase shift per pounds per square inch of pressure were observed. Measured pressure versus time traces showed good agreement with those from a piezoelectric reference sensor mounted in the same engine cylinder.

Interferometric Fiber-Optic Sensor Embedded in a Spark Plug for In-Cylinder Pressure Measurement in Engines

NASA Astrophysics Data System (ADS)

Bae, Taehan; Atkins, Robert A.; Taylor, Henry F.; Gibler, William N.

2003-02-01

Pressure sensing in an internal combustion engine with an intrinsic fiber Fabry-Perot interferometer (FFPI) integrated with a spark plug is demonstrated for the first time. The spark plug was used for the ignition of the cylinder in which it was mounted. The FFPI element, protected with a copper /gold coating, was embedded in a groove in the spark-plug housing. Gas pressure in the engine induced longitudinal strain in this housing, which was also experienced by the fiber-optic sensing element. The sensor was monitored with a signal conditioning unit containing a chirped distributed-feedback laser. Pressure sensitivities as high as 0.00339 radians round-trip phase shift per pounds per square inch of pressure were observed. Measured pressure versus time traces showed good agreement with those from a piezoelectric reference sensor mounted in the same engine cylinder.

An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

NASA Astrophysics Data System (ADS)

Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

2018-01-01

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

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

PubMed Central

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

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype. PMID:22438732

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

PubMed

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

2012-01-01

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

Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

NASA Astrophysics Data System (ADS)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.

Embedded Thermal Control for Spacecraft Subsystems Miniaturization

NASA Technical Reports Server (NTRS)

Didion, Jeffrey R.

2014-01-01

Optimization of spacecraft size, weight and power (SWaP) resources is an explicit technical priority at Goddard Space Flight Center. Embedded Thermal Control Subsystems are a promising technology with many cross cutting NSAA, DoD and commercial applications: 1.) CubeSatSmallSat spacecraft architecture, 2.) high performance computing, 3.) On-board spacecraft electronics, 4.) Power electronics and RF arrays. The Embedded Thermal Control Subsystem technology development efforts focus on component, board and enclosure level devices that will ultimately include intelligent capabilities. The presentation will discuss electric, capillary and hybrid based hardware research and development efforts at Goddard Space Flight Center. The Embedded Thermal Control Subsystem development program consists of interrelated sub-initiatives, e.g., chip component level thermal control devices, self-sensing thermal management, advanced manufactured structures. This presentation includes technical status and progress on each of these investigations. Future sub-initiatives, technical milestones and program goals will be presented.

Geometry correction Algorithm for UAV Remote Sensing Image Based on Improved Neural Network

NASA Astrophysics Data System (ADS)

Liu, Ruian; Liu, Nan; Zeng, Beibei; Chen, Tingting; Yin, Ninghao

2018-03-01

Aiming at the disadvantage of current geometry correction algorithm for UAV remote sensing image, a new algorithm is proposed. Adaptive genetic algorithm (AGA) and RBF neural network are introduced into this algorithm. And combined with the geometry correction principle for UAV remote sensing image, the algorithm and solving steps of AGA-RBF are presented in order to realize geometry correction for UAV remote sensing. The correction accuracy and operational efficiency is improved through optimizing the structure and connection weight of RBF neural network separately with AGA and LMS algorithm. Finally, experiments show that AGA-RBF algorithm has the advantages of high correction accuracy, high running rate and strong generalization ability.

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

PubMed

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

2017-11-07

In this work, the influence of carbon nanotube (CNT) hybridization on ultraviolet (UV) and gas sensing properties of individual and networked ZnO nanowires (NWs) is investigated in detail. The CNT concentration was varied to achieve optimal conditions for the hybrid with improved sensing properties. In case of CNT decorated ZnO nanonetworks, the influence of relative humidity (RH) and applied bias voltage on the UV sensing properties was thoroughly studied. By rising the CNT content to about 2.0 wt% (with respect to the entire ZnO network) the UV sensing response is considerably increased from 150 to 7300 (about 50 times). With respect to gas sensing, the ZnO-CNT networks demonstrate an excellent selectivity as well as a high gas response to NH 3 vapor. A response of 430 to 50 ppm at room temperature was obtained, with an estimated detection limit of about 0.4 ppm. Based on those results, several devices consisting of individual ZnO NWs covered with CNTs were fabricated using a FIB/SEM system. The highest sensing performance was obtained for the finest NW with diameter (D) of 100 nm,  with a response of about 4 to 10 ppm NH 3 vapor at room temperature.

The Role of Small Significant Networks and Leadership in the Institutional Embedding of SoTL

ERIC Educational Resources Information Center

Verwoord, Roselynn; Poole, Gary

2016-01-01

Drawing on the concepts of emergent and appointed leadership, this article expands on the role of social networks in SoTL (Roxå and Mårtensson 2009, 2012); Williams et al. [Williams, et al. 2013) by examining the nature of these networks, relationships between these networks, and support for them, in order to theorize how institutions can foster…

A mobile sensing system for structural health monitoring: design and validation

NASA Astrophysics Data System (ADS)

Zhu, Dapeng; Yi, Xiaohua; Wang, Yang; Lee, Kok-Meng; Guo, Jiajie

2010-05-01

This paper describes a new approach using mobile sensor networks for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper first describes the design of a mobile sensing node that is capable of maneuvering on structures built with ferromagnetic materials. The mobile sensing node can also attach/detach an accelerometer onto/from the structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments. Two mobile sensing nodes are adopted for navigating on a steel portal frame and providing dense acceleration measurements. Transmissibility function analysis is conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes in the use of mobile sensors for future structural health monitoring.

Sulfophenyl-Functionalized Reduced Graphene Oxide Networks on Electrospun 3D Scaffold for Ultrasensitive NO₂ Gas Sensor.

PubMed

Zou, Bin; Guo, Yunlong; Shen, Nannan; Xiao, Anshan; Li, Mingjun; Zhu, Liang; Wan, Pengbo; Sun, Xiaoming

2017-12-19

Ultrasensitive room temperature real-time NO₂ sensors are highly desirable due to potential threats on environmental security and personal respiratory. Traditional NO₂ gas sensors with highly operated temperatures (200-600 °C) and limited reversibility are mainly constructed from semiconducting oxide-deposited ceramic tubes or inter-finger probes. Herein, we report the functionalized graphene network film sensors assembled on an electrospun three-dimensional (3D) nanonetwork skeleton for ultrasensitive NO₂ sensing. The functional 3D scaffold was prepared by electrospinning interconnected polyacrylonitrile (PAN) nanofibers onto a nylon window screen to provide a 3D nanonetwork skeleton. Then, the sulfophenyl-functionalized reduced graphene oxide (SFRGO) was assembled on the electrospun 3D nanonetwork skeleton to form SFRGO network films. The assembled functionalized graphene network film sensors exhibit excellent NO₂ sensing performance (10 ppb to 20 ppm) at room temperature, reliable reversibility, good selectivity, and better sensing cycle stability. These improvements can be ascribed to the functionalization of graphene with electron-withdrawing sulfophenyl groups, the high surface-to-volume ratio, and the effective sensing channels from SFRGO wrapping onto the interconnected 3D scaffold. The SFRGO network-sensing film has the advantages of simple preparation, low cost, good processability, and ultrasensitive NO₂ sensing, all advantages that can be utilized for potential integration into smart windows and wearable electronic devices for real-time household gas sensors.

Nitrogen-doped graphene network supported copper nanoparticles encapsulated with graphene shells for surface-enhanced Raman scattering.

PubMed

Zhang, Xiang; Shi, Chunsheng; Liu, Enzuo; Li, Jiajun; Zhao, Naiqin; He, Chunnian

2015-10-28

In this study, we demonstrated nitrogen-doped graphene network supported few-layered graphene shell encapsulated Cu nanoparticles (NPs) (Cu@G-NGNs) as a sensing platform, which were constructed by a simple and scalable in situ chemical vapor deposition (CVD) technique with the assistance of a self-assembled three-dimensional (3D) NaCl template. Compared with pure Cu NPs and graphene decorated Cu NPs, the graphene shells can strengthen the plasmonic coupling between graphene and Cu, thereby contributing to an obvious improvement in the local electromagnetic field that was validated by finite element numerical simulations, while the 3D nitrogen-doped graphene walls with a large surface area facilitated molecule adsorption and the doped nitrogen atoms embedded in the graphene lattice can reduce the surface energy of the system. With these merits, a good surface enhanced Raman spectroscopy (SERS) activity of the 3D Cu@G-NGN painting film on glass was demonstrated using rhodamine 6G and crystal violet as model analytes, exhibiting a satisfactory sensitivity, reproducibility and stability. As far as we know, this is the first report on the in situ synthesis of nitrogen-doped graphene/copper nanocomposites and this facile and low-cost Cu-based strategy tends to be a good supplement to Ag and Au based substrates for SERS applications.

A feasibility study on embedded micro-electromechanical sensors and systems (MEMS) for monitoring highway structures.

DOT National Transportation Integrated Search

2011-06-01

Micro-electromechanical systems (MEMS) provide vast improvements over existing sensing methods in the context of structural health monitoring (SHM) of highway infrastructure systems, including improved system reliability, improved longevity and enhan...

An Embedded Systems Laboratory to Support Rapid Prototyping of Robotics and the Internet of Things

ERIC Educational Resources Information Center

Hamblen, J. O.; van Bekkum, G. M. E.

2013-01-01

This paper describes a new approach for a course and laboratory designed to allow students to develop low-cost prototypes of robotic and other embedded devices that feature Internet connectivity, I/O, networking, a real-time operating system (RTOS), and object-oriented C/C++. The application programming interface (API) libraries provided permit…

Laser SRS tracker for reverse prototyping tasks

NASA Astrophysics Data System (ADS)

Kolmakov, Egor; Redka, Dmitriy; Grishkanich, Aleksandr; Tsvetkov, Konstantin

2017-10-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of chip and microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments.

PubMed

Mora, Higinio; Gil, David; Terol, Rafael Muñoz; Azorín, Jorge; Szymanski, Julian

2017-10-10

The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other 'things' ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers' heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries.

Implementation of a High-Speed FPGA and DSP Based FFT Processor for Improving Strain Demodulation Performance in a Fiber-Optic-Based Sensing System

NASA Technical Reports Server (NTRS)

Farley, Douglas L.

2005-01-01

NASA's Aviation Safety and Security Program is pursuing research in on-board Structural Health Management (SHM) technologies for purposes of reducing or eliminating aircraft accidents due to system and component failures. Under this program, NASA Langley Research Center (LaRC) is developing a strain-based structural health-monitoring concept that incorporates a fiber optic-based measuring system for acquiring strain values. This fiber optic-based measuring system provides for the distribution of thousands of strain sensors embedded in a network of fiber optic cables. The resolution of strain value at each discrete sensor point requires a computationally demanding data reduction software process that, when hosted on a conventional processor, is not suitable for near real-time measurement. This report describes the development and integration of an alternative computing environment using dedicated computing hardware for performing the data reduction. Performance comparison between the existing and the hardware-based system is presented.

An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments

PubMed Central

Szymanski, Julian

2017-01-01

The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers’ heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries. PMID:28994743

Frogs, fish and forestry: An integrated watershed network paradigm conserves biodiversity and ecological services

Treesearch

Hartwell H. Welsh Jr.

2011-01-01

Successfully addressing the multitude of stresses influencing forest catchments, their native biota, and the vital ecological services they provide humanity will require adapting an integrated view that incorporates the full range of natural and anthropogenic disturbances acting on these landscapes and their embedded fluvial networks. The concepts of dendritic networks...

Productive Tensions in a Cross-Cultural Peer Mentoring Women's Network: A Social Capital Perspective

ERIC Educational Resources Information Center

Esnard, Talia; Cobb-Roberts, Deirdre; Agosto, Vonzell; Karanxha, Zorka; Beck, Makini; Wu, Ke; Unterreiner, Ann

2015-01-01

A growing body of researchers documents the unique barriers women face in their academic career progression and the significance of mentoring networks for advancement of their academic trajectories as faculty. However, few researchers explore the embedded tensions and conflicts in the social processes and relations of mentoring networks, and the…

Multireceiver Acoustic Communications in Time-Varying Environments

DTIC Science & Technology

2014-06-01

Canberra, ACT, 2012, pp. 1–7. [7] W. Chen and F. Yanjun, “Physical layer design consideration for underwater acoustic sensor networks ,”3rd IEEE Int...analysis of underwater acoustic MIMO communications,”OCEANS, Sydney, NSW, 2010, pp. 1–8. [9] Wines lab (2013). Wireless networks and embedded... NETWORKS ......................................................................3 B. CHALLENGES OF UNDERWATER ACOUSTIC COMMUNICATIONS

Photonic crystal borax competitive binding carbohydrate sensing motif†

PubMed Central

Cui, Qingzhou; Muscatello, Michelle M. Ward; Asher, Sanford A.

2009-01-01

We developed a photonic crystal sensing method for diol containing species such as carbohydrates based on a poly(vinyl alcohol) (PVA) hydrogel containing an embedded crystalline colloidal array (CCA). The polymerized CCA (PCCA) diffracts visible light. We show that in the presence of borax the diffraction wavelength shifts as the concentration of glucose changes. The diffraction shifts result from the competitive binding of glucose to borate, which reduces the concentration of borate bound to the PVA diols. PMID:19381378

Method for Estimating Operational Loads on Aerospace Structures Using Span-Wisely Distributed Surface Strains

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2013-01-01

This report presents a new method for estimating operational loads (bending moments, shear loads, and torques) acting on slender aerospace structures using distributed surface strains (unidirectional strains). The surface strain-sensing stations are to be evenly distributed along each span-wise strain-sensing line. A depth-wise cross section of the structure along each strain-sensing line can then be considered as an imaginary embedded beam. The embedded beam was first evenly divided into multiple small domains with domain junctures matching the strain-sensing stations. The new method is comprised of two steps. The first step is to determine the structure stiffness (bending or torsion) using surface strains obtained from a simple bending (or torsion) loading case, for which the applied bending moment (or torque) is known. The second step is to use the strain-determined structural stiffness (bending or torsion), and a new set of surface strains induced by any other loading case to calculate the associated operational loads (bending moments, shear loads, or torques). Performance of the new method for estimating operational loads was studied in light of finite-element analyses of several example structures subjected to different loading conditions. The new method for estimating operational loads was found to be fairly accurate, and is very promising for applications to the flight load monitoring of flying vehicles with slender wings.

LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

NASA Astrophysics Data System (ADS)

See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

2016-04-01

The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.

Smart Sensing and Recognition Based on Models of Neural Networks

DTIC Science & Technology

1990-11-15

9P-o ,yY𔄃-’. AD-A230 701 University of Pensylvania Philadelphia, PA 19104-6390 SMART SENSING AND RECOGNITION BASED ON MODELS OF NEURAL NETWORKS ... networks , photonic 1 implementations, nonlinear dynamical signal processing 9 ABSTRACT (Continue on reverse if necessary and identify by block number...not develop in isolation but in synergism with sensory organs and their feature forming networks . This means that development of artificial pattern

The structure of the lipid-embedded potassium channel voltage sensor determined by double-electron–electron resonance spectroscopy

PubMed Central

Vamvouka, Magdalini; Cieslak, John; Van Eps, Ned; Hubbell, Wayne; Gross, Adrian

2008-01-01

A four-pulse electron paramagnetic resonance experiment was used to measure long-range inter-subunit distances in reconstituted KvAP, a voltage-dependent potassium (Kv) channel. The measurements have allowed us to reach the following five conclusions about the native structure of the voltage sensor of KvAP. First, the S1 helix of the voltage sensor engages in a helix packing interaction with the pore domain. Second, the crystallographically observed antiparallel helix-turn-helix motif of the voltage-sensing paddle is retained in the membrane-embedded voltage sensor. Third, the paddle is oriented in such a way as to expose one face to the pore domain and the opposite face to the membrane. Fourth, the paddle and the pore domain appear to be separated by a gap that is sufficiently wide for lipids to penetrate between the two domains. Fifth, the critical voltage-sensing arginine residues on the paddle appear to be lipid exposed. These results demonstrate the importance of the membrane for the native structure of Kv channels, suggest that lipids are an integral part of their native structure, and place the voltage-sensing machinery into a complex lipid environment near the pore domain. PMID:18287283

Light focusing using epsilon-near-zero metamaterials

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

Zhu, Weiren, E-mail: weiren.zhu@monash.edu; Premaratne, Malin; Si, Li-Ming, E-mail: lms@bit.edu.cn

2013-11-15

We present a strategy of focusing light using epsilon-near-zero metamaterials with embedded dielectric cylinder. The focusing mechanism is analytically investigated, and its accuracy is substantiated by rigorous full-wave simulations. It is found that the focusing intensity is highly depend on the embedded medium and its size, and the magnetic field amplitude of the focused beam itself can reach as high as 98.2 times the incident field. Owing to its versatility, the proposed light focusing system is sure to find applications in fields such as bio-sensing and in nonlinear optics.

Optimization of Selected Remote Sensing Algorithms for Embedded NVIDIA Kepler GPU Architecture

NASA Technical Reports Server (NTRS)

Riha, Lubomir; Le Moigne, Jacqueline; El-Ghazawi, Tarek

2015-01-01

This paper evaluates the potential of embedded Graphic Processing Units in the Nvidias Tegra K1 for onboard processing. The performance is compared to a general purpose multi-core CPU and full fledge GPU accelerator. This study uses two algorithms: Wavelet Spectral Dimension Reduction of Hyperspectral Imagery and Automated Cloud-Cover Assessment (ACCA) Algorithm. Tegra K1 achieved 51 for ACCA algorithm and 20 for the dimension reduction algorithm, as compared to the performance of the high-end 8-core server Intel Xeon CPU with 13.5 times higher power consumption.

Curvature and temperature of complex networks.

PubMed

Krioukov, Dmitri; Papadopoulos, Fragkiskos; Vahdat, Amin; Boguñá, Marián

2009-09-01

We show that heterogeneous degree distributions in observed scale-free topologies of complex networks can emerge as a consequence of the exponential expansion of hidden hyperbolic space. Fermi-Dirac statistics provides a physical interpretation of hyperbolic distances as energies of links. The hidden space curvature affects the heterogeneity of the degree distribution, while clustering is a function of temperature. We embed the internet into the hyperbolic plane and find a remarkable congruency between the embedding and our hyperbolic model. Besides proving our model realistic, this embedding may be used for routing with only local information, which holds significant promise for improving the performance of internet routing.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Distributed Sensing and Processing for Multi-Camera Networks

NASA Astrophysics Data System (ADS)

Sankaranarayanan, Aswin C.; Chellappa, Rama; Baraniuk, Richard G.

Sensor networks with large numbers of cameras are becoming increasingly prevalent in a wide range of applications, including video conferencing, motion capture, surveillance, and clinical diagnostics. In this chapter, we identify some of the fundamental challenges in designing such systems: robust statistical inference, computationally efficiency, and opportunistic and parsimonious sensing. We show that the geometric constraints induced by the imaging process are extremely useful for identifying and designing optimal estimators for object detection and tracking tasks. We also derive pipelined and parallelized implementations of popular tools used for statistical inference in non-linear systems, of which multi-camera systems are examples. Finally, we highlight the use of the emerging theory of compressive sensing in reducing the amount of data sensed and communicated by a camera network.

Network dynamics of 3D engineered neuronal cultures: a new experimental model for in-vitro electrophysiology.

PubMed

Frega, Monica; Tedesco, Mariateresa; Massobrio, Paolo; Pesce, Mattia; Martinoia, Sergio

2014-06-30

Despite the extensive use of in-vitro models for neuroscientific investigations and notwithstanding the growing field of network electrophysiology, all studies on cultured cells devoted to elucidate neurophysiological mechanisms and computational properties, are based on 2D neuronal networks. These networks are usually grown onto specific rigid substrates (also with embedded electrodes) and lack of most of the constituents of the in-vivo like environment: cell morphology, cell-to-cell interaction and neuritic outgrowth in all directions. Cells in a brain region develop in a 3D space and interact with a complex multi-cellular environment and extracellular matrix. Under this perspective, 3D networks coupled to micro-transducer arrays, represent a new and powerful in-vitro model capable of better emulating in-vivo physiology. In this work, we present a new experimental paradigm constituted by 3D hippocampal networks coupled to Micro-Electrode-Arrays (MEAs) and we show how the features of the recorded network dynamics differ from the corresponding 2D network model. Further development of the proposed 3D in-vitro model by adding embedded functionalized scaffolds might open new prospects for manipulating, stimulating and recording the neuronal activity to elucidate neurophysiological mechanisms and to design bio-hybrid microsystems.

Network dynamics of 3D engineered neuronal cultures: a new experimental model for in-vitro electrophysiology

PubMed Central

Frega, Monica; Tedesco, Mariateresa; Massobrio, Paolo; Pesce, Mattia; Martinoia, Sergio

2014-01-01

Despite the extensive use of in-vitro models for neuroscientific investigations and notwithstanding the growing field of network electrophysiology, all studies on cultured cells devoted to elucidate neurophysiological mechanisms and computational properties, are based on 2D neuronal networks. These networks are usually grown onto specific rigid substrates (also with embedded electrodes) and lack of most of the constituents of the in-vivo like environment: cell morphology, cell-to-cell interaction and neuritic outgrowth in all directions. Cells in a brain region develop in a 3D space and interact with a complex multi-cellular environment and extracellular matrix. Under this perspective, 3D networks coupled to micro-transducer arrays, represent a new and powerful in-vitro model capable of better emulating in-vivo physiology. In this work, we present a new experimental paradigm constituted by 3D hippocampal networks coupled to Micro-Electrode-Arrays (MEAs) and we show how the features of the recorded network dynamics differ from the corresponding 2D network model. Further development of the proposed 3D in-vitro model by adding embedded functionalized scaffolds might open new prospects for manipulating, stimulating and recording the neuronal activity to elucidate neurophysiological mechanisms and to design bio-hybrid microsystems. PMID:24976386

Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding

PubMed Central

Ghanbari, Yasser; Smith, Alex R.; Schultz, Robert T.; Verma, Ragini

2014-01-01

Diffusion tensor imaging (DTI) offers rich insights into the physical characteristics of white matter (WM) fiber tracts and their development in the brain, facilitating a network representation of brain’s traffic pathways. Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging. The high dimensionality of these connectivity networks necessitates the development of methods that identify the connectivity building blocks or sub-network components that characterize the underlying variation in the population. In addition, the projection of the subject networks into the basis set provides a low dimensional representation of it, that teases apart different sources of variation in the sample, facilitating variation-specific statistical analysis. We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive basis set, as well as, additional basis sets representing variational sources in the population like age and pathology. The proposed framework is applied to a study of diffusion-based connectivity in subjects with autism that shows localized sparse sub-networks which mostly capture the changes related to pathology and developmental variations. PMID:25037933

Instrumentation for sensing moisture content of material using a transient thermal pulse

NASA Technical Reports Server (NTRS)

Yang, L. C. (Inventor)

1981-01-01

Instrumentation is developed for sensing moisture content of material using a transient thermal pulse and is comprised of a sensing probe having a sensing element in the form of a ribbon excited by a constant current pulse to increase the temperature, and therefore the resistance, of the ribbon linearly. Moisture in web material limits the increase of temperature during the pulse in proportion to the moisture content. This increase in temperature produces a proportional increase in resistivity which is measured with a Wheatsone bridge as a change in voltage displayed by a measurement display unit. The probe is glued in a shallow groove of a lucite bar and connected to copper pins embedded in the bar.

Steganographic embedding in containers-images

NASA Astrophysics Data System (ADS)

Nikishova, A. V.; Omelchenko, T. A.; Makedonskij, S. A.

2018-05-01

Steganography is one of the approaches to ensuring the protection of information transmitted over the network. But a steganographic method should vary depending on a used container. According to statistics, the most widely used containers are images and the most common image format is JPEG. Authors propose a method of data embedding into a frequency area of images in format JPEG 2000. It is proposed to use the method of Benham-Memon- Yeo-Yeung, in which instead of discrete cosine transform, discrete wavelet transform is used. Two requirements for images are formulated. Structure similarity is chosen to obtain quality assessment of data embedding. Experiments confirm that requirements satisfaction allows achieving high quality assessment of data embedding.

A QoS-guaranteed coverage precedence routing algorithm for wireless sensor networks.

PubMed

Jiang, Joe-Air; Lin, Tzu-Shiang; Chuang, Cheng-Long; Chen, Chia-Pang; Sun, Chin-Hong; Juang, Jehn-Yih; Lin, Jiun-Chuan; Liang, Wei-Wen

2011-01-01

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively.

Coordinated traffic incident management using the I-Net embedded sensor architecture

NASA Astrophysics Data System (ADS)

Dudziak, Martin J.

1999-01-01

The I-Net intelligent embedded sensor architecture enables the reconfigurable construction of wide-area remote sensing and data collection networks employing diverse processing and data acquisition modules communicating over thin- server/thin-client protocols. Adaptive initially for operation using mobile remotely-piloted vehicle platforms such as small helicopter robots such as the Hornet and Ascend-I, the I-Net architecture lends itself to a critical problem in the management of both spontaneous and planned traffic congestion and rerouting over major interstate thoroughfares such as the I-95 Corridor. Pre-programmed flight plans and ad hoc operator-assisted navigation of the lightweight helicopter, using an auto-pilot and gyroscopic stabilization augmentation units, allows daytime or nighttime over-the-horizon flights of the unit to collect and transmit real-time video imagery that may be stored or transmitted to other locations. With on-board GPS and ground-based pattern recognition capabilities to augment the standard video collection process, this approach enables traffic management and emergency response teams to plan and assist real-time in the adjustment of traffic flows in high- density or congested areas or during dangerous road conditions such as during ice, snow, and hurricane storms. The I-Net architecture allows for integration of land-based and roadside sensors within a comprehensive automated traffic management system with communications to and form an airborne or other platform to devices in the network other than human-operated desktop computers, thereby allowing more rapid assimilation and response for critical data. Experiments have been conducted using several modified platforms and standard video and still photographic equipment. Current research and development is focused upon modification of the modular instrumentation units in order to accommodate faster loading and reloading of equipment onto the RPV, extension of the I-Net architecture to enable RPV-to-RPV signaling and control, and refinement of safety and emergency mechanisms to handle RPV mechanical failure during flight.

Bidirectional QoS support for novelty detection applications based on hierarchical wireless sensor network model

NASA Astrophysics Data System (ADS)

Edwards, Mark; Hu, Fei; Kumar, Sunil

2004-10-01

The research on the Novelty Detection System (NDS) (called as VENUS) at the authors' universities has generated exciting results. For example, we can detect an abnormal behavior (such as cars thefts from the parking lot) from a series of video frames based on the cognitively motivated theory of habituation. In this paper, we would like to describe the implementation strategies of lower layer protocols for using large-scale Wireless Sensor Networks (WSN) to NDS with Quality-of-Service (QoS) support. Wireless data collection framework, consisting of small and low-power sensor nodes, provides an alternative mechanism to observe the physical world, by using various types of sensing capabilities that include images (and even videos using Panoptos), sound and basic physical measurements such as temperature. We do not want to lose any 'data query command' packets (in the downstream direction: sink-to-sensors) or have any bit-errors in them since they are so important to the whole sensor network. In the upstream direction (sensors-to-sink), we may tolerate the loss of some sensing data packets. But the 'interested' sensing flow should be assigned a higher priority in terms of multi-hop path choice, network bandwidth allocation, and sensing data packet generation frequency (we hope to generate more sensing data packet for that novel event in the specified network area). The focus of this paper is to investigate MAC-level Quality of Service (QoS) issue in Wireless Sensor Networks (WSN) for Novelty Detection applications. Although QoS has been widely studied in other types of networks including wired Internet, general ad hoc networks and mobile cellular networks, we argue that QoS in WSN has its own characteristics. In wired Internet, the main QoS parameters include delay, jitter and bandwidth. In mobile cellular networks, two most common QoS metrics are: handoff call dropping probability and new call blocking probability. Since the main task of WSN is to detect and report events, the most important QoS parameters should include sensing data packet transmission reliability, lifetime extension degree from sensor sleeping control, event detection latency, congestion reduction level through removal of redundant sensing data. In this paper, we will focus on the following bi-directional QoS topics: (1) Downstream (sink-to-sensor) QoS: Reliable data query command forwarding to particular sensor(s). In other words, we do not want to lose the query command packets; (2) Upstream (sensor-to-sink) QoS: transmission of sensed data with priority control. The more interested data that can help in novelty detection should be transmitted on an optimal path with higher reliability. We propose the use of Differentiated Data Collection. Due to the large-scale nature and resource constraints of typical wireless sensor networks, such as limited energy, small memory (typically RAM < 4K bytes) and short communication range, the above problems become even more challenging. Besides QoS support issue, we will also describe our low-energy Sensing Data Transmission network Architecture. Our research results show the scalability and energy-efficiency of our proposed WSN QoS schemes.

Broken Detailed Balance of Filament Dynamics in Active Networks

NASA Astrophysics Data System (ADS)

Schmidt, Christoph F.; Gladrow, Jannes; Fakhri, Nikta; Mackintosh, Fred C.; Broedersz, Chase

Endogenous embedded semiflexible filaments such as microtubules, or added filaments such as single- walled carbon nanotubes can be used as novel tools to noninvasively track equilibrium and nonequilibrium fluctuations in biopolymer networks. We analytically calculated shape fluctuations of semi- flexible probe filaments in a viscoelastic environment, driven out of equilibrium by motor activity. Transverse bending fluctuations of the probe filaments can be decomposed into dynamic normal modes. We find that these modes no longer evolve independently under non-equilibrium driving. This effective mode coupling results in nonzero circulatory currents in a conformational phase space, reflecting a violation of detailed balance. We present predictions for the characteristic frequencies associated with these currents and investigate how the temporal signatures of motor activity determine mode correlations, which we find to be consistent with recent experiments on microtubules embedded in cytoskeletal networks.

Mobile Phone Middleware Architecture for Energy and Context Awareness in Location-Based Services

PubMed Central

Galeana-Zapién, Hiram; Torres-Huitzil, César; Rubio-Loyola, Javier

2014-01-01

The disruptive innovation of smartphone technology has enabled the development of mobile sensing applications leveraged on specialized sensors embedded in the device. These novel mobile phone applications rely on advanced sensor information processes, which mainly involve raw data acquisition, feature extraction, data interpretation and transmission. However, the continuous accessing of sensing resources to acquire sensor data in smartphones is still very expensive in terms of energy, particularly due to the periodic use of power-intensive sensors, such as the Global Positioning System (GPS) receiver. The key underlying idea to design energy-efficient schemes is to control the duty cycle of the GPS receiver. However, adapting the sensing rate based on dynamic context changes through a flexible middleware has received little attention in the literature. In this paper, we propose a novel modular middleware architecture and runtime environment to directly interface with application programming interfaces (APIs) and embedded sensors in order to manage the duty cycle process based on energy and context aspects. The proposed solution has been implemented in the Android software stack. It allows continuous location tracking in a timely manner and in a transparent way to the user. It also enables the deployment of sensing policies to appropriately control the sampling rate based on both energy and perceived context. We validate the proposed solution taking into account a reference location-based service (LBS) architecture. A cloud-based storage service along with online mobility analysis tools have been used to store and access sensed data. Experimental measurements demonstrate the feasibility and efficiency of our middleware, in terms of energy and location resolution. PMID:25513821

Mobile phone middleware architecture for energy and context awareness in location-based services.

PubMed

Galeana-Zapién, Hiram; Torres-Huitzil, César; Rubio-Loyola, Javier

2014-12-10

The disruptive innovation of smartphone technology has enabled the development of mobile sensing applications leveraged on specialized sensors embedded in the device. These novel mobile phone applications rely on advanced sensor information processes, which mainly involve raw data acquisition, feature extraction, data interpretation and transmission. However, the continuous accessing of sensing resources to acquire sensor data in smartphones is still very expensive in terms of energy, particularly due to the periodic use of power-intensive sensors, such as the Global Positioning System (GPS) receiver. The key underlying idea to design energy-efficient schemes is to control the duty cycle of the GPS receiver. However, adapting the sensing rate based on dynamic context changes through a flexible middleware has received little attention in the literature. In this paper, we propose a novel modular middleware architecture and runtime environment to directly interface with application programming interfaces (APIs) and embedded sensors in order to manage the duty cycle process based on energy and context aspects. The proposed solution has been implemented in the Android software stack. It allows continuous location tracking in a timely manner and in a transparent way to the user. It also enables the deployment of sensing policies to appropriately control the sampling rate based on both energy and perceived context. We validate the proposed solution taking into account a reference location-based service (LBS) architecture. A cloud-based storage service along with online mobility analysis tools have been used to store and access sensed data. Experimental measurements demonstrate the feasibility and efficiency of our middleware, in terms of energy and location resolution.

Dispersed Sensing Networks in Nano-Engineered Polymer Composites: From Static Strain Measurement to Ultrasonic Wave Acquisition

PubMed Central

Li, Yehai; Wang, Kai

2018-01-01

Self-sensing capability of composite materials has been the core of intensive research over the years and particularly boosted up by the recent quantum leap in nanotechnology. The capacity of most existing self-sensing approaches is restricted to static strains or low-frequency structural vibration. In this study, a new breed of functionalized epoxy-based composites is developed and fabricated, with a graphene nanoparticle-enriched, dispersed sensing network, whereby to self-perceive broadband elastic disturbance from static strains, through low-frequency vibration to guided waves in an ultrasonic regime. Owing to the dispersed and networked sensing capability, signals can be captured at any desired part of the composites. Experimental validation has demonstrated that the functionalized composites can self-sense strains, outperforming conventional metal foil strain sensors with a significantly enhanced gauge factor and a much broader response bandwidth. Precise and fast self-response of the composites to broadband ultrasonic signals (up to 440 kHz) has revealed that the composite structure itself can serve as ultrasound sensors, comparable to piezoceramic sensors in performance, whereas avoiding the use of bulky cables and wires as used in a piezoceramic sensor network. This study has spotlighted promising potentials of the developed approach to functionalize conventional composites with a self-sensing capability of high-sensitivity yet minimized intrusion to original structures. PMID:29724032

Mainstream economics and sense-making.

PubMed

Salvatore, Sergio; Davanzati, Guglielmo Forges; Potì, Silvia; Ruggieri, Ruggero

2009-06-01

This work presents a semiotic approach to the economy, underlining that any economic phenomena is at the same time a communicative act as it is contingent to sense-making. The article discusses this topic by focusing on a specific phenomenon studied by economics: the underground economy. It shows that the conceptualization of the underground economy in terms of sense-making processes offers a thought-provoking perspective for theoretical development. More in general, the discussion proposed makes it clear that in order to deepen our vision of economic phenomena in a more thoughtful and realistic way we need to rethink these phenomena as being reciprocally and circularly embedded in the semiotic flow of life. The economy is within sense-making and it is shaped by it; at the same time sense-making is within the economy, as its semiotic substance.

Unique Reactivity of Transition Metal Atoms Embedded in Graphene to CO, NO, O₂ and O Adsorption: A First-Principles Investigation.

PubMed

Chu, Minmin; Liu, Xin; Sui, Yanhui; Luo, Jie; Meng, Changgong

2015-10-27

Taking the adsorption of CO, NO, O₂ and O as probes, we investigated the electronic structure of transition metal atoms (TM, TM = Fe, Co, Ni, Cu and Zn) embedded in graphene by first-principles-based calculations. We showed that these TM atoms can be effectively stabilized on monovacancy defects on graphene by forming plausible interactions with the C atoms associated with dangling bonds. These interactions not only give rise to high energy barriers for the diffusion and aggregation of the embedded TM atoms to withstand the interference of reaction environments, but also shift the energy levels of TM-d states and regulate the reactivity of the embedded TM atoms. The adsorption of CO, NO, O₂ and O correlates well with the weight averaged energy level of TM-d states, showing the crucial role of interfacial TM-C interactions on manipulating the reactivity of embedded TM atoms. These findings pave the way for the developments of effective monodispersed atomic TM composites with high stability and desired performance for gas sensing and catalytic applications.

Analytical theory of polymer-network-mediated interaction between colloidal particles

PubMed Central

Di Michele, Lorenzo; Zaccone, Alessio; Eiser, Erika

2012-01-01

Nanostructured materials based on colloidal particles embedded in a polymer network are used in a variety of applications ranging from nanocomposite rubbers to organic-inorganic hybrid solar cells. Further, polymer-network-mediated colloidal interactions are highly relevant to biological studies whereby polymer hydrogels are commonly employed to probe the mechanical response of living cells, which can determine their biological function in physiological environments. The performance of nanomaterials crucially relies upon the spatial organization of the colloidal particles within the polymer network that depends, in turn, on the effective interactions between the particles in the medium. Existing models based on nonlocal equilibrium thermodynamics fail to clarify the nature of these interactions, precluding the way toward the rational design of polymer-composite materials. In this article, we present a predictive analytical theory of these interactions based on a coarse-grained model for polymer networks. We apply the theory to the case of colloids partially embedded in cross-linked polymer substrates and clarify the origin of attractive interactions recently observed experimentally. Monte Carlo simulation results that quantitatively confirm the theoretical predictions are also presented. PMID:22679289

Magnetic Skyrmion as a Nonlinear Resistive Element: A Potential Building Block for Reservoir Computing

NASA Astrophysics Data System (ADS)

Prychynenko, Diana; Sitte, Matthias; Litzius, Kai; Krüger, Benjamin; Bourianoff, George; Kläui, Mathias; Sinova, Jairo; Everschor-Sitte, Karin

2018-01-01

Inspired by the human brain, there is a strong effort to find alternative models of information processing capable of imitating the high energy efficiency of neuromorphic information processing. One possible realization of cognitive computing involves reservoir computing networks. These networks are built out of nonlinear resistive elements which are recursively connected. We propose that a Skyrmion network embedded in magnetic films may provide a suitable physical implementation for reservoir computing applications. The significant key ingredient of such a network is a two-terminal device with nonlinear voltage characteristics originating from magnetoresistive effects, such as the anisotropic magnetoresistance or the recently discovered noncollinear magnetoresistance. The most basic element for a reservoir computing network built from "Skyrmion fabrics" is a single Skyrmion embedded in a ferromagnetic ribbon. In order to pave the way towards reservoir computing systems based on Skyrmion fabrics, we simulate and analyze (i) the current flow through a single magnetic Skyrmion due to the anisotropic magnetoresistive effect and (ii) the combined physics of local pinning and the anisotropic magnetoresistive effect.

On the Embedded Complementarity of Agent-Based and Aggregate Reasoning in Students' Developing Understanding of Dynamic Systems

ERIC Educational Resources Information Center

Stroup, Walter M.; Wilensky, Uri

2014-01-01

Placed in the larger context of broadening the engagement with systems dynamics and complexity theory in school-aged learning and teaching, this paper is intended to introduce, situate, and illustrate--with results from the use of network supported participatory simulations in classrooms--a stance we call "embedded complementarity" as an…

Investigation on strain sensing properties of carbon-based nanocomposites for structural aircraft applications

NASA Astrophysics Data System (ADS)

Lamberti, Patrizia; Spinelli, Giovanni; Tucci, Vincenzo; Guadagno, Liberata; Vertuccio, Luigi; Russo, Salvatore

2016-05-01

The mechanical and electrical properties of a thermosetting epoxy resin particularly indicated for the realization of structural aeronautic components and reinforced with multiwalled carbon nanotubes (MWCNTs, at 0.3 wt%) are investigated for specimens subjected to cycles and different levels of applied strain (i.e. ɛ) loaded both in axial tension and flexural mode. It is found that the piezoresistive behavior of the resulting nanocomposite evaluated in terms of variation of the electrical resistance is strongly affected by the applied mechanical stress mainly due to the high sensibility and consequent rearrangement of the electrical percolating network formed by MWCNTs in the composite at rest or even under a small strain. In fact, the variations in electrical resistance that occur during the mechanical stress are correlated to the deformation exhibited by the nanocomposites. In particular, the overall response of electrical resistance of the composite is characterized by a linear increase with the strain at least in the region of elastic deformation of the material in which the gauge factor (i.e. G.F.) of the sensor is usually evaluated. Therefore, the present study aims at investigating the possible use of the nanotechnology for application of embedded sensor systems in composite structures thus having capability of self-sensing and of responding to the surrounding environmental changes, which are some fundamental requirements especially for structural aircraft monitoring applications.

Workplace Learning in Informal Networks

ERIC Educational Resources Information Center

Milligan, Colin; Littlejohn, Allison; Margaryan, Anoush

2014-01-01

Learning does not stop when an individual leaves formal education, but becomes increasingly informal, and deeply embedded within other activities such as work. This article describes the challenges of informal learning in knowledge intensive industries, highlighting the important role of personal learning networks. The article argues that…

Health monitoring of Binzhou Yellow River highway bridge using fiber Bragg gratings

NASA Astrophysics Data System (ADS)

Ou, Jinping; Zhao, Xuefeng; Li, Hui; Zhou, Zhi; Zhang, Zhichun; Wang, Chuan

2005-05-01

Binzhou yellow river Highway Bridge with 300 meter span and 768 meter length is located in the Shandong province of China and is the first cable stayed bridge with three towers along the yellow river, one of the biggest rivers in China. In order to monitoring the strain and temperature of the bridge and evaluate the health condition, one fiber Bragg grating sensing network consists of about one hundred and thirty FBG sensors mounted in 31 monitoring sections respectively, had been built during three years time. Signal cables of sensors were led to central control room located near the main tower. One four-channel FBG interrogator was used to read the wavelengths from all the sensors, associated with four computer-controlled optic switches connected to each channel. One program was written to control the interrogator and optic switches simultaneously, and ensure signal input precisely. The progress of the monitoring can be controlled through the internet. The sensors embedded were mainly used to monitor the strain and temperature of the steel cable and reinforced concrete beam. PE jacket opening embedding technique of steel cable had been developed to embed FBG sensors safely, and ensure the reliability of the steel cable opened at the same time. Data obtained during the load test can show the strain and temperature status of elements were in good condition. The data obtained via internet since the bridge's opening to traffic shown the bridge under various load such as traffic load, wind load were in good condition.

Towards Resilient Critical Infrastructures: Application of Type-2 Fuzzy Logic in Embedded Network Security Cyber Sensor

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

Ondrej Linda; Todd Vollmer; Jim Alves-Foss

2011-08-01

Resiliency and cyber security of modern critical infrastructures is becoming increasingly important with the growing number of threats in the cyber-environment. This paper proposes an extension to a previously developed fuzzy logic based anomaly detection network security cyber sensor via incorporating Type-2 Fuzzy Logic (T2 FL). In general, fuzzy logic provides a framework for system modeling in linguistic form capable of coping with imprecise and vague meanings of words. T2 FL is an extension of Type-1 FL which proved to be successful in modeling and minimizing the effects of various kinds of dynamic uncertainties. In this paper, T2 FL providesmore » a basis for robust anomaly detection and cyber security state awareness. In addition, the proposed algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental cyber-security test-bed.« less

Airplane detection in remote sensing images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

2018-03-01

Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

Energy efficient wireless sensor network for structural health monitoring using distributed embedded piezoelectric transducers

NASA Astrophysics Data System (ADS)

Li, Peng; Olmi, Claudio; Song, Gangbing

2010-04-01

Piezoceramic based transducers are widely researched and used for structural health monitoring (SHM) systems due to the piezoceramic material's inherent advantage of dual sensing and actuation. Wireless sensor network (WSN) technology benefits from advances made in piezoceramic based structural health monitoring systems, allowing easy and flexible installation, low system cost, and increased robustness over wired system. However, piezoceramic wireless SHM systems still faces some drawbacks, one of these is that the piezoceramic based SHM systems require relatively high computational capabilities to calculate damage information, however, battery powered WSN sensor nodes have strict power consumption limitation and hence limited computational power. On the other hand, commonly used centralized processing networks require wireless sensors to transmit all data back to the network coordinator for analysis. This signal processing procedure can be problematic for piezoceramic based SHM applications as it is neither energy efficient nor robust. In this paper, we aim to solve these problems with a distributed wireless sensor network for piezoceramic base structural health monitoring systems. Three important issues: power system, waking up from sleep impact detection, and local data processing, are addressed to reach optimized energy efficiency. Instead of sweep sine excitation that was used in the early research, several sine frequencies were used in sequence to excite the concrete structure. The wireless sensors record the sine excitations and compute the time domain energy for each sine frequency locally to detect the energy change. By comparing the data of the damaged concrete frame with the healthy data, we are able to find out the damage information of the concrete frame. A relative powerful wireless microcontroller was used to carry out the sampling and distributed data processing in real-time. The distributed wireless network dramatically reduced the data transmission between wireless sensor and the wireless coordinator, which in turn reduced the power consumption of the overall system.

Peru Subduction Zone Seismic Experiment (PeruSZE): Preliminary Results From a Seismic Network Between Mollendo and Lake Titicaca, Peru.

NASA Astrophysics Data System (ADS)

Guy, R.; Stubailo, I.; Skinner, S.; Phillips, K.; Foote, E.; Lukac, M.; Aguilar, V.; Tavera, H.; Audin, L.; Husker, A.; Clayton, R.; Davis, P. M.

2008-12-01

This work describes preliminary results from a 50 station broadband seismic network recently installed from the coast to the high Andes in Peru. UCLA's Center for Embedded Network Sensing (CENS) and Caltech's Tectonic Observatory are collaborating with the IRD (French L'Institut de Recherche pour le Developpement) and the Institute of Geophysics, in Lima Peru in a broadband seismic experiment that will study the transition from steep to shallow slab subduction. The currently installed line has stations located above the steep subduction zone at a spacing of about 6 km. In 2009 we plan to install a line of 50 stations north from this line along the crest of the Andes, crossing the transition from steep to shallow subduction. A further line from the end of that line back to the coast, completing a U shaped array, is in the planning phase. The network is wirelessly linked using multi-hop network software designed by computer scientists in CENS in which data is transmitted from station to station, and collected at Internet drops, from where it is transmitted over the Internet to CENS each night. The instrument installation in Peru is almost finished and we have been receiving data daily from 10 stations (out of total 50) since June 2008. The rest are recording on-site while the RF network is being completed. The software system provides dynamic link quality based routing, reliable data delivery, and a disruption tolerant shell interface for managing the system from UCLA without the need to travel to Peru. The near real-time data delivery also allows immediate detection of any problems at the sites. We are building a seismic data and GPS quality control toolset that would greatly minimize the station's downtime by alerting the users of any possible problems.

The Emergence of Embedded Relations and Group Formation in Networks of Competition

ERIC Educational Resources Information Center

Thye, Shane R.; Lawler, Edward J.; Yoon, Jeongkoo

2011-01-01

This study examines how and when small networks of self-interested agents generate a group tie or affiliation at the network level. A group affiliation is formed when actors (a) perceive themselves as members of a group and (b) share resources with each other despite an underlying competitive structure. We apply a concept of structural cohesion to…

A solution for two-dimensional mazes with use of chaotic dynamics in a recurrent neural network model.

PubMed

Suemitsu, Yoshikazu; Nara, Shigetoshi

2004-09-01

Chaotic dynamics introduced into a neural network model is applied to solving two-dimensional mazes, which are ill-posed problems. A moving object moves from the position at t to t + 1 by simply defined motion function calculated from firing patterns of the neural network model at each time step t. We have embedded several prototype attractors that correspond to the simple motion of the object orienting toward several directions in two-dimensional space in our neural network model. Introducing chaotic dynamics into the network gives outputs sampled from intermediate state points between embedded attractors in a state space, and these dynamics enable the object to move in various directions. System parameter switching between a chaotic and an attractor regime in the state space of the neural network enables the object to move to a set target in a two-dimensional maze. Results of computer simulations show that the success rate for this method over 300 trials is higher than that of random walk. To investigate why the proposed method gives better performance, we calculate and discuss statistical data with respect to dynamical structure.

Embedding recurrent neural networks into predator-prey models.

PubMed

Moreau, Yves; Louiès, Stephane; Vandewalle, Joos; Brenig, Leon

1999-03-01

We study changes of coordinates that allow the embedding of ordinary differential equations describing continuous-time recurrent neural networks into differential equations describing predator-prey models-also called Lotka-Volterra systems. We transform the equations for the neural network first into quasi-monomial form (Brenig, L. (1988). Complete factorization and analytic solutions of generalized Lotka-Volterra equations. Physics Letters A, 133(7-8), 378-382), where we express the vector field of the dynamical system as a linear combination of products of powers of the variables. In practice, this transformation is possible only if the activation function is the hyperbolic tangent or the logistic sigmoid. From this quasi-monomial form, we can directly transform the system further into Lotka-Volterra equations. The resulting Lotka-Volterra system is of higher dimension than the original system, but the behavior of its first variables is equivalent to the behavior of the original neural network. We expect that this transformation will permit the application of existing techniques for the analysis of Lotka-Volterra systems to recurrent neural networks. Furthermore, our results show that Lotka-Volterra systems are universal approximators of dynamical systems, just as are continuous-time neural networks.

High Sensitivity Stress Sensor Based on Hybrid Materials

NASA Technical Reports Server (NTRS)

Cao, Xian-An (Inventor)

2014-01-01

A sensing device is used to detect the spatial distributions of stresses applied by physical contact with the surface of the sensor or induced by pressure, temperature gradients, and surface absorption. The sensor comprises a hybrid active layer that includes luminophores doped in a polymeric or organic host, altogether embedded in a matrix. Under an electrical bias, the sensor simultaneously converts stresses into electrical and optical signals. Among many applications, the device may be used for tactile sensing and biometric imaging.

Embedded Efficiency: A Social Networks Approach to Popular Support and Dark Network Structure

DTIC Science & Technology

2016-03-01

Raab in “Dark networks as problems ,” (2003) where dark refers to illegal and, covert and bright refers to legal and overt. Throughout this report these...Milward, Jörg Raab, “Dark Networks as Organizational Problems : Elements of a Theory,” International Public Management Journal 9, no.3 ( 2006): 333–360...Emirbayer and Jeff Goodwin, “Network Analysis, Culture and the Problem of Agency,” American Journal of Sociology Vol. 99, No. 6 (May 1994): 1436. 35 Ibid

Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition.

PubMed

Jauregi Unanue, Iñigo; Zare Borzeshi, Ehsan; Piccardi, Massimo

2017-12-01

Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word "embeddings". (i) To create a highly accurate DNR and CCE system that avoids conventional, time-consuming feature engineering. (ii) To create richer, more specialized word embeddings by using health domain datasets such as MIMIC-III. (iii) To evaluate our systems over three contemporary datasets. Two deep learning methods, namely the Bidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF model is set as the baseline to compare the deep learning systems to a traditional machine learning approach. The same features are used for all the models. We have obtained the best results with the Bidirectional LSTM-CRF model, which has outperformed all previously proposed systems. The specialized embeddings have helped to cover unusual words in DrugBank and MedLine, but not in the i2b2/VA dataset. We present a state-of-the-art system for DNR and CCE. Automated word embeddings has allowed us to avoid costly feature engineering and achieve higher accuracy. Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary. Copyright © 2017 Elsevier Inc. All rights reserved.

Structural health monitoring and remote sensing of transportation infrastructure using embedded frequency selective surfaces.

DOT National Transportation Integrated Search

2014-07-01

The objective of this project was to investigate the use of Frequency Selective Surfaces (FSS) for structural health monitoring applications. Frequency Selective Surfaces (FSS) have long been used in the RF/microwave community to control scattering f...

Smart composites with embedded shape memory alloy actuators and fibre Bragg grating sensors: activation and control

NASA Astrophysics Data System (ADS)

Balta, J. A.; Bosia, F.; Michaud, V.; Dunkel, G.; Botsis, J.; Månson, J.-A.

2005-08-01

This paper describes the production of an adaptive composite by embedding thin pre-strained shape memory alloy actuators into a Kevlar-epoxy host material. In order to combine the activation and sensing capabilities, fibre Bragg grating sensors are also embedded into the specimens, and the strain measured in situ during activation. The effect of manufacturing conditions, and hence of the initial stress state in the composite before activation, on the magnitude of the measured strains is discussed. The results of stress and strain simulations are compared with experimental data, and guidelines are provided for the optimization of the composite. Finally, a pilot experiment is carried out to provide an example of how a strain-stabilizing feedback mechanism can be implemented in the smart structure.

Time lagged ordinal partition networks for capturing dynamics of continuous dynamical systems

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

McCullough, Michael; Iu, Herbert Ho-Ching; Small, Michael

2015-05-15

We investigate a generalised version of the recently proposed ordinal partition time series to network transformation algorithm. First, we introduce a fixed time lag for the elements of each partition that is selected using techniques from traditional time delay embedding. The resulting partitions define regions in the embedding phase space that are mapped to nodes in the network space. Edges are allocated between nodes based on temporal succession thus creating a Markov chain representation of the time series. We then apply this new transformation algorithm to time series generated by the Rössler system and find that periodic dynamics translate tomore » ring structures whereas chaotic time series translate to band or tube-like structures—thereby indicating that our algorithm generates networks whose structure is sensitive to system dynamics. Furthermore, we demonstrate that simple network measures including the mean out degree and variance of out degrees can track changes in the dynamical behaviour in a manner comparable to the largest Lyapunov exponent. We also apply the same analysis to experimental time series generated by a diode resonator circuit and show that the network size, mean shortest path length, and network diameter are highly sensitive to the interior crisis captured in this particular data set.« less

Compressive sensing based wireless sensor for structural health monitoring

NASA Astrophysics Data System (ADS)

Bao, Yuequan; Zou, Zilong; Li, Hui

2014-03-01

Data loss is a common problem for monitoring systems based on wireless sensors. Reliable communication protocols, which enhance communication reliability by repetitively transmitting unreceived packets, is one approach to tackle the problem of data loss. An alternative approach allows data loss to some extent and seeks to recover the lost data from an algorithmic point of view. Compressive sensing (CS) provides such a data loss recovery technique. This technique can be embedded into smart wireless sensors and effectively increases wireless communication reliability without retransmitting the data. The basic idea of CS-based approach is that, instead of transmitting the raw signal acquired by the sensor, a transformed signal that is generated by projecting the raw signal onto a random matrix, is transmitted. Some data loss may occur during the transmission of this transformed signal. However, according to the theory of CS, the raw signal can be effectively reconstructed from the received incomplete transformed signal given that the raw signal is compressible in some basis and the data loss ratio is low. This CS-based technique is implemented into the Imote2 smart sensor platform using the foundation of Illinois Structural Health Monitoring Project (ISHMP) Service Tool-suite. To overcome the constraints of limited onboard resources of wireless sensor nodes, a method called random demodulator (RD) is employed to provide memory and power efficient construction of the random sampling matrix. Adaptation of RD sampling matrix is made to accommodate data loss in wireless transmission and meet the objectives of the data recovery. The embedded program is tested in a series of sensing and communication experiments. Examples and parametric study are presented to demonstrate the applicability of the embedded program as well as to show the efficacy of CS-based data loss recovery for real wireless SHM systems.

Novel silica surface charge density mediated control of the optical properties of embedded optically active materials and its application for fiber optic pH sensing at elevated temperatures.

PubMed

Wang, Congjun; Ohodnicki, Paul R; Su, Xin; Keller, Murphy; Brown, Thomas D; Baltrus, John P

2015-02-14

Silica and silica incorporated nanocomposite materials have been extensively studied for a wide range of applications. Here we demonstrate an intriguing optical effect of silica that, depending on the solution pH, amplifies or attenuates the optical absorption of a variety of embedded optically active materials with very distinct properties, such as plasmonic Au nanoparticles, non-plasmonic Pt nanoparticles, and the organic dye rhodamine B (not a pH indicator), coated on an optical fiber. Interestingly, the observed optical response to varying pH appears to follow the surface charge density of the silica matrix for all the three different optically active materials. To the best of our knowledge, this optical effect has not been previously reported and it appears universal in that it is likely that any optically active material can be incorporated into the silica matrix to respond to solution pH or surface charge density variations. A direct application of this effect is for optical pH sensing which has very attractive features that can enable minimally invasive, remote, real time and continuous distributed pH monitoring. Particularly, as demonstrated here, using highly stable metal nanoparticles embedded in an inorganic silica matrix can significantly improve the capability of pH sensing in extremely harsh environments which is of increasing importance for applications in unconventional oil and gas resource recovery, carbon sequestration, water quality monitoring, etc. Our approach opens a pathway towards possible future development of robust optical pH sensors for the most demanding environmental conditions. The newly discovered optical effect of silica also offers the potential for control of the optical properties of optically active materials for a range of other potential applications such as electrochromic devices.

2-Dimensional micro-network of boron-doped diamond film: fabrication and electrochemical sensing application.

PubMed

Luo, Daibing; Wu, Liangzhuan; Zhi, Jinfang

2010-09-21

By means of delicate and conventional methods based on photolithography and hot filament chemical vapor deposition (HFCVD) technology, a novel boron-doped diamond micro-network (BDDMN) film was fabricated, and this micro-structure showed excellent electrochemical sensing properties.

Resolving Structural Variability in Network Models and the Brain

PubMed Central

Klimm, Florian; Bassett, Danielle S.; Carlson, Jean M.; Mucha, Peter J.

2014-01-01

Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling—in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the statistical inference of brain network structure from neuroimaging data. PMID:24675546

Deep neural network-based domain adaptation for classification of remote sensing images

NASA Astrophysics Data System (ADS)

Ma, Li; Song, Jiazhen

2017-10-01

We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

Fog-Based Two-Phase Event Monitoring and Data Gathering in Vehicular Sensor Networks

PubMed Central

Yang, Fan; Su, Jinsong; Zhou, Qifeng; Wang, Tian; Zhang, Lu; Xu, Yifan

2017-01-01

Vehicular nodes are equipped with more and more sensing units, and a large amount of sensing data is generated. Recently, more and more research considers cooperative urban sensing as the heart of intelligent and green city traffic management. The key components of the platform will be a combination of a pervasive vehicular sensing system, as well as a central control and analysis system, where data-gathering is a fundamental component. However, the data-gathering and monitoring are also challenging issues in vehicular sensor networks because of the large amount of data and the dynamic nature of the network. In this paper, we propose an efficient continuous event-monitoring and data-gathering framework based on fog nodes in vehicular sensor networks. A fog-based two-level threshold strategy is adopted to suppress unnecessary data upload and transmissions. In the monitoring phase, nodes sense the environment in low cost sensing mode and generate sensed data. When the probability of the event is high and exceeds some threshold, nodes transfer to the event-checking phase, and some nodes would be selected to transfer to the deep sensing mode to generate more accurate data of the environment. Furthermore, it adaptively adjusts the threshold to upload a suitable amount of data for decision making, while at the same time suppressing unnecessary message transmissions. Simulation results showed that the proposed scheme could reduce more than 84 percent of the data transmissions compared with other existing algorithms, while it detects the events and gathers the event data. PMID:29286320

Method and composition in which metal hydride particles are embedded in a silica network

DOEpatents

Heung, Leung K.

1999-01-01

A silica embedded metal hydride composition and a method for making such a composition. The composition is made via the following process: A quantity of fumed silica is blended with water to make a paste. After adding metal hydride particles, the paste is dried to form a solid. According to one embodiment of the invention, the solid is ground into granules for use of the product in hydrogen storage. Alternatively, the paste can be molded into plates or cylinders and then dried for use of the product as a hydrogen filter. Where mechanical strength is required, the paste can be impregnated in a porous substrate or wire network.

Flexible transparent conducting hybrid film using a surface-embedded copper nanowire network: a highly oxidation-resistant copper nanowire electrode for flexible optoelectronics.

PubMed

Im, Hyeon-Gyun; Jung, Soo-Ho; Jin, Jungho; Lee, Dasom; Lee, Jaemin; Lee, Daewon; Lee, Jung-Yong; Kim, Il-Doo; Bae, Byeong-Soo

2014-10-28

We report a flexible high-performance conducting film using an embedded copper nanowire transparent conducting electrode; this material can be used as a transparent electrode platform for typical flexible optoelectronic devices. The monolithic composite structure of our transparent conducting film enables simultaneously an outstanding oxidation stability of the copper nanowire network (14 d at 80 °C), an exceptionally smooth surface topography (R(rms) < 2 nm), and an excellent opto-electrical performances (Rsh = 25 Ω sq(-1) and T = 82%). A flexible organic light emitting diode device is fabricated on the transparent conducting film to demonstrate its potential as a flexible copper nanowire electrode platform.

Embedded I&C for Extreme Environments

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

Kisner, Roger A.

2016-04-01

This project uses embedded instrumentation and control (I&C) technologies to demonstrate potential performance gains of nuclear power plant components in extreme environments. Extreme environments include high temperature, radiation, high pressure, high vibration, and high EMI conditions. For extreme environments, performance gains arise from moment-to-moment sensing of local variables and immediate application of local feedback control. Planning for embedding I&C during early system design phases contrasts with the traditional, serial design approach that incorporates minimal I&C after mechanical and electrical design is complete. The demonstration application involves the development and control of a novel, proof-of-concept motor/pump design. The motor and pumpmore » combination operate within the fluid environment, eliminating the need for rotating seals. Actively controlled magnetic bearings also replace failure-prone mechanical contact bearings that typically suspend rotating components. Such as design has the potential to significantly enhance the reliability and life of the pumping system and would not be possible without embedded I&C.« less

Design, manufacture and testing of an FBG-instrumented composite wing

NASA Astrophysics Data System (ADS)

Abouzeida, E.; Quinones, V.; Gowayed, Y.; Soobramaney, P.; Flowers, G.; Black, R. J.; Costa, J. M.; Faridian, F.; Moslehi, B.

2014-02-01

In this work, our research team investigated the efficacy of using optical static and dynamic strain sensing with embedded Fiber Bragg Gratings (FBGs) in structural health monitoring (SHM) of a model composite airplane wing. A one-fourth scale model of a T38 airplane wing was designed and manufactured using fabric reinforced polymer matrix composites with FBG sensors embedded under the top layer of the composite. The accuracy and durability of the sensors were evaluated at the coupon and structural levels utilizing static and dynamic testing. Strain measurements using embedded FBGs with an optical interrogator were found to be in agreement with values measured using other strain measuring devices and with results obtained using finite element analysis (ANSYS®). Preferred locations for the FBG sensors were identified in accordance with contour maps of internal strain distributions resulting from critical load cases. Manufacturing techniques used to address handling, survivability and durability of the embedded sensors during and post manufacturing of the composites were evaluated and optimized.

Sensitivity vector fields in time-delay coordinate embeddings: theory and experiment.

PubMed

Sloboda, A R; Epureanu, B I

2013-02-01

Identifying changes in the parameters of a dynamical system can be vital in many diagnostic and sensing applications. Sensitivity vector fields (SVFs) are one way of identifying such parametric variations by quantifying their effects on the morphology of a dynamical system's attractor. In many cases, SVFs are a more effective means of identification than commonly employed modal methods. Previously, it has only been possible to construct SVFs for a given dynamical system when a full set of state variables is available. This severely restricts SVF applicability because it may be cost prohibitive, or even impossible, to measure the entire state in high-dimensional systems. Thus, the focus of this paper is constructing SVFs with only partial knowledge of the state by using time-delay coordinate embeddings. Local models are employed in which the embedded states of a neighborhood are weighted in a way referred to as embedded point cloud averaging. Application of the presented methodology to both simulated and experimental time series demonstrates its utility and reliability.

Amperometric Biosensors Based on 3-Dimensional Hydrogel-Forming Epoxy Networks

DTIC Science & Technology

1993-05-24

are epoxy- embedded and contained in a 0.3mm diameter biocompatible polyimide tubing. The ensemble of epoxy-embedded fiber tips is coated with the...electrode is then overcoated with a biocompatible film. The electrode’s sensitivity is 2.5xI0 2 A cm’ 2 M 1. It can be stored at 40 C for 4 months with no

An Adaptive Data Gathering Scheme for Multi-Hop Wireless Sensor Networks Based on Compressed Sensing and Network Coding.

PubMed

Yin, Jun; Yang, Yuwang; Wang, Lei

2016-04-01

Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering--CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes--MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme.

Design and Test of a Soft Plantar Force Measurement System for Gait Detection

PubMed Central

Zhang, Xuefeng; Zhao, Yulong; Duan, Zhengyong; Liu, Yan

2012-01-01

This work describes a plantar force measurement system. The MEMS pressure sensor, as the key sensing element, is designed, fabricated and embedded into a flexible silicon oil-filled bladder made of silicon rubber to constitute a single sensing unit. A conditioning circuit is designed for signal processing and data acquisition. The characteristics of the plantar force sensing unit are investigated by both static and dynamic tests. A comparison of characteristics between the proposed plantar force sensing unit and a commercial flexible force sensor is presented. A practical experiment of plantar force measurement has been carried out to validate the system. The results demonstrate that the proposed measurement system has a potential for success in the application of plantar force measurement during normal gait. PMID:23208558

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

PubMed

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

2017-07-22

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

Experimental and Computational Studies of Sound Transmission in a Branching Airway Network Embedded in a Compliant Viscoelastic Medium

PubMed Central

Dai, Zoujun; Peng, Ying; Mansy, Hansen A.; Sandler, Richard H.; Royston, Thomas J.

2015-01-01

Breath sounds are often used to aid in the diagnosis of pulmonary disease. Mechanical and numerical models could be used to enhance our understanding of relevant sound transmission phenomena. Sound transmission in an airway mimicking phantom was investigated using a mechanical model with a branching airway network embedded in a compliant viscoelastic medium. The Horsfield self-consistent model for the bronchial tree was adopted to topologically couple the individual airway segments into the branching airway network. The acoustics of the bifurcating airway segments were measured by microphones and calculated analytically. Airway phantom surface motion was measured using scanning laser Doppler vibrometry. Finite element simulations of sound transmission in the airway phantom were performed. Good agreement was achieved between experiments and simulations. The validated computational approach can provide insight into sound transmission simulations in real lungs. PMID:26097256

Experimental and computational studies of sound transmission in a branching airway network embedded in a compliant viscoelastic medium

NASA Astrophysics Data System (ADS)

Dai, Zoujun; Peng, Ying; Mansy, Hansen A.; Sandler, Richard H.; Royston, Thomas J.

2015-03-01

Breath sounds are often used to aid in the diagnosis of pulmonary disease. Mechanical and numerical models could be used to enhance our understanding of relevant sound transmission phenomena. Sound transmission in an airway mimicking phantom was investigated using a mechanical model with a branching airway network embedded in a compliant viscoelastic medium. The Horsfield self-consistent model for the bronchial tree was adopted to topologically couple the individual airway segments into the branching airway network. The acoustics of the bifurcating airway segments were measured by microphones and calculated analytically. Airway phantom surface motion was measured using scanning laser Doppler vibrometry. Finite element simulations of sound transmission in the airway phantom were performed. Good agreement was achieved between experiments and simulations. The validated computational approach can provide insight into sound transmission simulations in real lungs.

Brand communities embedded in social networks☆

PubMed Central

Zaglia, Melanie E.

2013-01-01

Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social networks. The netnographic approach yields strong evidence of this existence; leading to a better understanding of such embedded brand communities, their peculiarities, and motivational drivers for participation; therefore the findings contribute to theory by combining two separate research streams. Due to the advantages of social networks, brand management is now able to implement brand communities with less time and financial effort; however, choosing the appropriate brand community type, cultivating consumers’ interaction, and staying tuned to this social engagement are critical factors to gain anticipated brand outcomes. PMID:23564989

Model of a Soft Robotic Actuator with Embedded Fluidic Network

NASA Astrophysics Data System (ADS)

Gamus, Benny; Or, Yizhar; Gat, Amir

2017-11-01

Soft robotics is an emerging bio-inspired concept of actuation, with promising applications for robotic locomotion and manipulation. Focusing on actuation by pressurized embedded fluidic networks, we present analytic formulation and closed-form solutions of an elastic actuator with pressurized fluidic networks. In this work we account for the effects of solid inertia and elasticity, as well as fluid viscosity, which allows modelling the system's step-response and frequency response as well as suggesting mode elimination and isolation techniques. We also present and model the application of viscous-peeling as an actuation mechanism, simplifying the fabrication process by eliminating the need for internal cavities. The theoretical results describing the viscous-elastic-inertial dynamics of the actuator are illustrated by experiments. The approach presented in this work may pave the way for the design and implementation of soft robotic legged locomotion that exploits dynamic effects.

Broken Detailed Balance of Filament Dynamics in Active Networks

NASA Astrophysics Data System (ADS)

Gladrow, J.; Fakhri, N.; MacKintosh, F. C.; Schmidt, C. F.; Broedersz, C. P.

2016-06-01

Myosin motor proteins drive vigorous steady-state fluctuations in the actin cytoskeleton of cells. Endogenous embedded semiflexible filaments such as microtubules, or added filaments such as single-walled carbon nanotubes are used as novel tools to noninvasively track equilibrium and nonequilibrium fluctuations in such biopolymer networks. Here, we analytically calculate shape fluctuations of semiflexible probe filaments in a viscoelastic environment, driven out of equilibrium by motor activity. Transverse bending fluctuations of the probe filaments can be decomposed into dynamic normal modes. We find that these modes no longer evolve independently under nonequilibrium driving. This effective mode coupling results in nonzero circulatory currents in a conformational phase space, reflecting a violation of detailed balance. We present predictions for the characteristic frequencies associated with these currents and investigate how the temporal signatures of motor activity determine mode correlations, which we find to be consistent with recent experiments on microtubules embedded in cytoskeletal networks.

Multi-crop area estimation and mapping on a microprocessor/mainframe network

NASA Technical Reports Server (NTRS)

Sheffner, E.

1985-01-01

The data processing system is outlined for a 1985 test aimed at determining the performance characteristics of area estimation and mapping procedures connected with the California Cooperative Remote Sensing Project. The project is a joint effort of the USDA Statistical Reporting Service-Remote Sensing Branch, the California Department of Water Resources, NASA-Ames Research Center, and the University of California Remote Sensing Research Program. One objective of the program was to study performance when data processing is done on a microprocessor/mainframe network under operational conditions. The 1985 test covered the hardware, software, and network specifications and the integration of these three components. Plans for the year - including planned completion of PEDITOR software, testing of software on MIDAS, and accomplishment of data processing on the MIDAS-VAX-CRAY network - are discussed briefly.

Development of a 2-channel embedded infrared fiber-optic temperature sensor using silver halide optical fibers.

PubMed

Yoo, Wook Jae; Jang, Kyoung Won; Seo, Jeong Ki; Moon, Jinsoo; Han, Ki-Tek; Park, Jang-Yeon; Park, Byung Gi; Lee, Bongsoo

2011-01-01

A 2-channel embedded infrared fiber-optic temperature sensor was fabricated using two identical silver halide optical fibers for accurate thermometry without complicated calibration processes. In this study, we measured the output voltages of signal and reference probes according to temperature variation over a temperature range from 25 to 225 °C. To decide the temperature of the water, the difference between the amounts of infrared radiation emitted from the two temperature sensing probes was measured. The response time and the reproducibility of the fiber-optic temperature sensor were also obtained. Thermometry with the proposed sensor is immune to changes if parameters such as offset voltage, ambient temperature, and emissivity of any warm object. In particular, the temperature sensing probe with silver halide optical fibers can withstand a high temperature/pressure and water-chemistry environment. It is expected that the proposed sensor can be further developed to accurately monitor temperature in harsh environments.

Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

Wang, Wenkai; Li, Husheng; Sun, Yan(Lindsay); Han, Zhu

2009-12-01

Cognitive radio is a revolutionary paradigm to migrate the spectrum scarcity problem in wireless networks. In cognitive radio networks, collaborative spectrum sensing is considered as an effective method to improve the performance of primary user detection. For current collaborative spectrum sensing schemes, secondary users are usually assumed to report their sensing information honestly. However, compromised nodes can send false sensing information to mislead the system. In this paper, we study the detection of untrustworthy secondary users in cognitive radio networks. We first analyze the case when there is only one compromised node in collaborative spectrum sensing schemes. Then we investigate the scenario that there are multiple compromised nodes. Defense schemes are proposed to detect malicious nodes according to their reporting histories. We calculate the suspicious level of all nodes based on their reports. The reports from nodes with high suspicious levels will be excluded in decision-making. Compared with existing defense methods, the proposed scheme can effectively differentiate malicious nodes and honest nodes. As a result, it can significantly improve the performance of collaborative sensing. For example, when there are 10 secondary users, with the primary user detection rate being equal to 0.99, one malicious user can make the false alarm rate [InlineEquation not available: see fulltext.] increase to 72%. The proposed scheme can reduce it to 5%. Two malicious users can make [InlineEquation not available: see fulltext.] increase to 85% and the proposed scheme reduces it to 8%.

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

PubMed Central

Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong

2014-01-01

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. PMID:25384005

Embedded Data Processor and Portable Computer Technology testbeds

NASA Technical Reports Server (NTRS)

Alena, Richard; Liu, Yuan-Kwei; Goforth, Andre; Fernquist, Alan R.

1993-01-01

Attention is given to current activities in the Embedded Data Processor and Portable Computer Technology testbed configurations that are part of the Advanced Data Systems Architectures Testbed at the Information Sciences Division at NASA Ames Research Center. The Embedded Data Processor Testbed evaluates advanced microprocessors for potential use in mission and payload applications within the Space Station Freedom Program. The Portable Computer Technology (PCT) Testbed integrates and demonstrates advanced portable computing devices and data system architectures. The PCT Testbed uses both commercial and custom-developed devices to demonstrate the feasibility of functional expansion and networking for portable computers in flight missions.

The 3 R's of Learning Time: Rethink, Reshape, Reclaim

ERIC Educational Resources Information Center

Sackey, Shera Carter

2012-01-01

The Learning School Alliance is a network of schools collaborating about professional practice. The network embodies Learning Forward's purpose to advance effective job-embedded professional learning that leads to student outcomes. A key component of Learning Forward's Standards for Professional Learning is a focus on collaborative learning,…

Design and evaluation of an Internet based data repository and visualization system for science education

NASA Astrophysics Data System (ADS)

Dalphond, James M.

In modern classrooms, scientific probes are often used in science labs to engage students in inquiry-based learning. Many of these probes will never leave the classroom, closing the door on real world experimentation that may engage students. Also, these tools do not encourage students to share data across classrooms or schools. To address these limitations, we have developed a web-based system for collecting, storing, and visualizing sensor data, as well as a hardware package to interface existing classroom probes. This system, The Internet System for Networked Sensor Experimentation (iSENSE), was created to address these limitations. Development of the system began in 2007 and has proceeded through four phases: proof-of-concept prototype, technology demonstration, initial classroom deployment, and classroom testing. User testing and feedback during these phases guided development of the system. This thesis includes lessons learned during development and evaluation of the system in the hands of teachers and students. We developed three evaluations of this practical use. The first evaluation involved working closely with teachers to encourage them to integrate activities using the iSENSE system into their existing curriculum. We were looking for strengths of the approach and ease of integration. Second, we developed three "Activity Labs," which teachers used as embedded assessments. In these activities, students were asked to answer questions based on experiments or visualizations already entered into the iSENSE website. Lastly, teachers were interviewed after using the system to determine what they found valuable. This thesis makes contributions in two areas. It shows how an iterative design process was used to develop a system used in a science classroom, and it presents an analysis of the educational impact of the system on teachers and students.

Gitai go: the art of deepening everyday life through exceeding codes.

PubMed

Traversa, Rosa

2010-06-01

The present commentary is focused on exploring holistic ways to approach sense-making processes by following the usage of specific Japanese mimic words, Gitai go, and describing how its functioning cannot be disengaged from an embodied lens to approach language-in-use. In fact, according to Komatsu's (2010) discussion about the extension of meaning derived from Gitai go and its intrinsic flexible characteristics, it is possible--in terms of semiotics--to inquire into vaguely coded systems of mutual understanding, trying to make sense of the general functioning of signs through their peculiar ambiguity as well as their potential to evoke a vivid negotiation of meaning. This seems to show the openness of meaning highlighted by Gitai go, as it is to be referred to the logic of multiplicity deeply linked with the actors' feelings in the setting that could in general terms be labeled as the carnal knowledge. Furthermore, it has been arguing about the complexity of daily life experience and its close relation to a concept of "ordinary art", as the active involvement people show in imagining, changing and creating their personal experience of the world is always performed in their day-by-day frameworks, deeply suggesting a unique strive for appropriating-negotiating-contesting networks of meanings. And this is to be approached as an artistic mode of experiencing, since art too is just embedded in this ever-emerging ambivalence coming from the complex we call "ordinary life" and relating to our deep feelings of facing our futures. Along these lines I suggest that a particular role exists in communicative messages for what is labeled as "redundant" or "superfluous"--since the ambivalence of those messages explicates the dialogical frame of sense-making, in everyday life as a concept of art.

Dynamic characterization, monitoring and control of rotating flexible beam-mass structures via piezo-embedded techniques

NASA Technical Reports Server (NTRS)

Lai, Steven H.-Y.

1992-01-01

A variational principle and a finite element discretization technique were used to derive the dynamic equations for a high speed rotating flexible beam-mass system embedded with piezo-electric materials. The dynamic equation thus obtained allows the development of finite element models which accommodate both the original structural element and the piezoelectric element. The solutions of finite element models provide system dynamics needed to design a sensing system. The characterization of gyroscopic effect and damping capacity of smart rotating devices are addressed. Several simulation examples are presented to validate the analytical solution.

Remote Sensing Image Classification Applied to the First National Geographical Information Census of China

NASA Astrophysics Data System (ADS)

Yu, Xin; Wen, Zongyong; Zhu, Zhaorong; Xia, Qiang; Shun, Lan

2016-06-01

Image classification will still be a long way in the future, although it has gone almost half a century. In fact, researchers have gained many fruits in the image classification domain, but there is still a long distance between theory and practice. However, some new methods in the artificial intelligence domain will be absorbed into the image classification domain and draw on the strength of each to offset the weakness of the other, which will open up a new prospect. Usually, networks play the role of a high-level language, as is seen in Artificial Intelligence and statistics, because networks are used to build complex model from simple components. These years, Bayesian Networks, one of probabilistic networks, are a powerful data mining technique for handling uncertainty in complex domains. In this paper, we apply Tree Augmented Naive Bayesian Networks (TAN) to texture classification of High-resolution remote sensing images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples. Since 2013, China government has started the first national geographical information census project, which mainly interprets geographical information based on high-resolution remote sensing images. Therefore, this paper tries to apply Bayesian network to remote sensing image classification, in order to improve image interpretation in the first national geographical information census project. In the experiment, we choose some remote sensing images in Beijing. Experimental results demonstrate TAN outperform than Naive Bayesian Classifier (NBC) and Maximum Likelihood Classification Method (MLC) in the overall classification accuracy. In addition, the proposed method can reduce the workload of field workers and improve the work efficiency. Although it is time consuming, it will be an attractive and effective method for assisting office operation of image interpretation.

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

NASA Astrophysics Data System (ADS)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

Distributed multifunctional sensor network for composite structural state sensing

NASA Astrophysics Data System (ADS)

Qing, Xinlin P.; Wang, Yishou; Gao, Limin; Kumar, Amrita

2012-04-01

Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and strong designability. In order to take full advantages of composite materials, there is a need to develop an embeddable multifunctional sensing system to allow a structure to "feel" and "think" its structural state. In this paper, the concept of multifunctional sensor network integrated with a structure, similar to the human nervous system, has been developed. Different types of network sensors are permanently integrated within a composite structure to sense structural strain, temperature, moisture, aerodynamic pressure; monitor external impact on the structure; and detect structural damages. Utilizing this revolutionary concept, future composite structures can be designed and manufactured to provide multiple modes of information, so that the structures have the capabilities for intelligent sensing, environmental adaptation and multi-functionality. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the paper.

Remote sensing and the Mississippi high accuracy reference network

NASA Technical Reports Server (NTRS)

Mick, Mark; Alexander, Timothy M.; Woolley, Stan

1994-01-01

Since 1986, NASA's Commercial Remote Sensing Program (CRSP) at Stennis Space Center has supported commercial remote sensing partnerships with industry. CRSP's mission is to maximize U.S. market exploitation of remote sensing and related space-based technologies and to develop advanced technical solutions for spatial information requirements. Observation, geolocation, and communications technologies are converging and their integration is critical to realize the economic potential for spatial informational needs. Global positioning system (GPS) technology enables a virtual revolution in geopositionally accurate remote sensing of the earth. A majority of states are creating GPS-based reference networks, or high accuracy reference networks (HARN). A HARN can be defined for a variety of local applications and tied to aerial or satellite observations to provide an important contribution to geographic information systems (GIS). This paper details CRSP's experience in the design and implementation of a HARN in Mississippi and the design and support of future applications of integrated earth observations, geolocation, and communications technology.

Network Analysis of Earth's Co-Evolving Geosphere and Biosphere

NASA Astrophysics Data System (ADS)

Hazen, R. M.; Eleish, A.; Liu, C.; Morrison, S. M.; Meyer, M.; Consortium, K. D.

2017-12-01

A fundamental goal of Earth science is the deep understanding of Earth's dynamic, co-evolving geosphere and biosphere through deep time. Network analysis of geo- and bio- `big data' provides an interactive, quantitative, and predictive visualization framework to explore complex and otherwise hidden high-dimension features of diversity, distribution, and change in the evolution of Earth's geochemistry, mineralogy, paleobiology, and biochemistry [1]. Networks also facilitate quantitative comparison of different geological time periods, tectonic settings, and geographical regions, as well as different planets and moons, through network metrics, including density, centralization, diameter, and transitivity.We render networks by employing data related to geographical, paragenetic, environmental, or structural relationships among minerals, fossils, proteins, and microbial taxa. An important recent finding is that the topography of many networks reflects parameters not explicitly incorporated in constructing the network. For example, networks for minerals, fossils, and protein structures reveal embedded qualitative time axes, with additional network geometries possibly related to extinction and/or other punctuation events (see Figure). Other axes related to chemical activities and volatile fugacities, as well as pressure and/or depth of formation, may also emerge from network analysis. These patterns provide new insights into the way planets evolve, especially Earth's co-evolving geosphere and biosphere. 1. Morrison, S.M. et al. (2017) Network analysis of mineralogical systems. American Mineralogist 102, in press. Figure Caption: A network of Phanerozoic Era fossil animals from the past 540 million years includes blue, red, and black circles (nodes) representing family-level taxa and grey lines (links) between coexisting families. Age information was not used in the construction of this network; nevertheless an intrinsic timeline is embedded in the network topology. In addition, two mass extinction events appear as "pinch points" in the network.

Process and Structural Health Monitoring of Composite Structures with Embedded Fiber Optic Sensors and Piezoelectric Transducers

NASA Astrophysics Data System (ADS)

Keulen, Casey James

Advanced composite materials are becoming increasingly more valuable in a plethora of engineering applications due to properties such as tailorability, low specific strength and stiffness and resistance to fatigue and corrosion. Compared to more traditional metallic and ceramic materials, advanced composites such as carbon, aramid or glass reinforced plastic are relatively new and still require research to optimize their capabilities. Three areas that composites stand to benefit from improvement are processing, damage detection and life prediction. Fiber optic sensors and piezoelectric transducers show great potential for advances in these areas. This dissertation presents the research performed on improving the efficiency of advanced composite materials through the use of embedded fiber optic sensors and surface mounted piezoelectric transducers. Embedded fiber optic sensors are used to detect the presence of resin during the injection stage of resin transfer molding, monitor the degree of cure and predict the remaining useful life while in service. A sophisticated resin transfer molding apparatus was developed with the ability of embedding fiber optics into the composite and a glass viewing window so that resin flow sensors could be verified visually. A novel technique for embedding optical fiber into both 2- and 3-D structures was developed. A theoretical model to predict the remaining useful life was developed and a systematic test program was conducted to verify this model. A network of piezoelectric transducers was bonded to a composite panel in order to develop a structural health monitoring algorithm capable of detecting and locating damage in a composite structure. A network configuration was introduced that allows for a modular expansion of the system to accommodate larger structures and an algorithm based on damage progression history was developed to implement the network. The details and results of this research are contained in four manuscripts that are included in Appendices A-D while the body of the dissertation provides background information and a summary of the results.

Self-Sensing of Position-Related Loads in Continuous Carbon Fibers-Embedded 3D-Printed Polymer Structures Using Electrical Resistance Measurement

PubMed Central

Luan, Congcong; Shen, Hongyao; Fu, Jianzhong

2018-01-01

Condition monitoring in polymer composites and structures based on continuous carbon fibers show overwhelming advantages over other potentially competitive sensing technologies in long-gauge measurements due to their great electromechanical behavior and excellent reinforcement property. Although carbon fibers have been developed as strain- or stress-sensing agents in composite structures through electrical resistance measurements, the electromechanical behavior under flexural loads in terms of different loading positions still lacks adequate research, which is the most common situation in practical applications. This study establishes the relationship between the fractional change in electrical resistance of carbon fibers and the external loads at different loading positions along the fibers’ longitudinal direction. An approach for real-time monitoring of flexural loads at different loading positions was presented simultaneously based on this relationship. The effectiveness and feasibility of the approach were verified by experiments on carbon fiber-embedded three-dimensional (3D) printed thermoplastic polymer beam. The error in using the provided approach to monitor the external loads at different loading positions was less than 1.28%. The study fully taps the potential of continuous carbon fibers as long-gauge sensory agents and reinforcement in the 3D-printed polymer structures. PMID:29584665

Development and characterization of silicone embedded distributed piezoelectric sensors for contact detection

NASA Astrophysics Data System (ADS)

Acer, Merve; Salerno, Marco; Agbeviade, Kossi; Paik, Jamie

2015-07-01

Tactile sensing transfers complex interactive information in a most intuitive sense. Such a populated set of data from the environment and human interactions necessitates various degrees of information from both modular and distributed areas. A sensor design that could provide such types of feedback becomes challenging when the target component has a nonuniform, agile, high resolution, and soft surface. This paper presents an innovative methodology for the manufacture of novel soft sensors that have a high resolution sensing array due to the sensitivity of ceramic piezoelectric (PZT) elements, while uncommonly matched with the high stretchability of the soft substrate and electrode design. Further, they have a low profile and their transfer function is easy to tune by changing the material and thickness of the soft substrate in which the PZTs are embedded. In this manuscript, we present experimental results of the soft sensor prototypes: PZTs arranged in a four by two array form, measuring 1.5-2.3 mm in thickness, with the sensitivity in the range of 0.07-0.12 of the normalized signal change per unit force. We have conducted extensive tests under dynamic loading conditions that include impact, step and cyclic. The presented prototype's mechanical and functional capacities are promising for applications in biomedical systems where soft, wearable and high precision sensors are needed.

A eutectic-alloy-infused soft actuator with sensing, tunable degrees of freedom, and stiffness properties

NASA Astrophysics Data System (ADS)

Hao, Yufei; Wang, Tianmiao; Xie, Zhexin; Sun, Wenguang; Liu, Zemin; Fang, Xi; Yang, Minxuan; Wen, Li

2018-02-01

This paper presents a soft actuator embedded with two types of eutectic alloys which enable sensing, tunable mechanical degrees of freedom (DOF), and variable stiffness properties. To modulate the stiffness of the actuator, we embedded a low melting point alloy (LMPA) in the bottom portion of the soft actuator. Different sections of the LMPA could be selectively melted by the Ni-Cr wires twined underneath. To acquire the curvature information, EGaIn (eutectic gallium indium) was infused into a microchannel surrounding the chambers of the soft actuator. Systematic experiments were performed to characterize the stiffness, tunable DOF, and sensing the bending curvature. We found that the average bending force and elasticity modulus could be increased about 35 and 4000 times, respectively, with the LMPA in a solid state. The entire LMPA could be melted from a solid to a liquid state within 12 s. In particular, up to six different motion patterns could be achieved under each pneumatic pressure of the soft actuator. Furthermore, the kinematics of the actuator under different motion patterns could be obtained by a mathematical model whose input was provided by the EGaIn sensor. For demonstration purposes, a two-fingered gripper was fabricated to grasp various objects by adjusting the DOF and mechanical stiffness.

Performance analysis of wireless sensor networks in geophysical sensing applications

NASA Astrophysics Data System (ADS)

Uligere Narasimhamurthy, Adithya

Performance is an important criteria to consider before switching from a wired network to a wireless sensing network. Performance is especially important in geophysical sensing where the quality of the sensing system is measured by the precision of the acquired signal. Can a wireless sensing network maintain the same reliability and quality metrics that a wired system provides? Our work focuses on evaluating the wireless GeoMote sensor motes that were developed by previous computer science graduate students at Mines. Specifically, we conducted a set of experiments, namely WalkAway and Linear Array experiments, to characterize the performance of the wireless motes. The motes were also equipped with the Sticking Heartbeat Aperture Resynchronization Protocol (SHARP), a time synchronization protocol developed by a previous computer science graduate student at Mines. This protocol should automatically synchronize the mote's internal clocks and reduce time synchronization errors. We also collected passive data to evaluate the response of GeoMotes to various frequency components associated with the seismic waves. With the data collected from these experiments, we evaluated the performance of the SHARP protocol and compared the performance of our GeoMote wireless system against the industry standard wired seismograph system (Geometric-Geode). Using arrival time analysis and seismic velocity calculations, we set out to answer the following question. Can our wireless sensing system (GeoMotes) perform similarly to a traditional wired system in a realistic scenario?

Method of producing an inertial sensor

NASA Technical Reports Server (NTRS)

Shcheglov, Kirill V. (Inventor); Challoner, A. Dorian (Inventor)

2008-01-01

The present invention discloses an inertial sensor comprising a planar mechanical resonator with embedded sensing and actuation for substantially in-plane vibration and having a central rigid support for the resonator. At least one excitation or torquer electrode is disposed within an interior of the resonator to excite in-plane vibration of the resonator and at least one sensing or pickoff electrode is disposed within the interior of the resonator for sensing the motion of the excited resonator. In one embodiment, the planar resonator includes a plurality of slots in an annular pattern; in another embodiment, the planar mechanical resonator comprises four masses; each embodiment having a simple degenerate pair of in-plane vibration modes.

Unlearning of Mixed States in the Hopfield Model —Extensive Loading Case—

NASA Astrophysics Data System (ADS)

Hayashi, Kao; Hashimoto, Chinami; Kimoto, Tomoyuki; Uezu, Tatsuya

2018-05-01

We study the unlearning of mixed states in the Hopfield model for the extensive loading case. Firstly, we focus on case I, where several embedded patterns are correlated with each other, whereas the rest are uncorrelated. Secondly, we study case II, where patterns are divided into clusters in such a way that patterns in any cluster are correlated but those in two different clusters are not correlated. By using the replica method, we derive the saddle point equations for order parameters under the ansatz of replica symmetry. The same equations are also derived by self-consistent signal-to-noise analysis in case I. In both cases I and II, we find that when the correlation between patterns is large, the network loses its ability to retrieve the embedded patterns and, depending on the parameters, a confused memory, which is a mixed state and/or spin glass state, emerges. By unlearning the mixed state, the network acquires the ability to retrieve the embedded patterns again in some parameter regions. We find that to delete the mixed state and to retrieve the embedded patterns, the coefficient of unlearning should be chosen appropriately. We perform Markov chain Monte Carlo simulations and find that the simulation and theoretical results agree reasonably well, except for the spin glass solution in a parameter region due to the replica symmetry breaking. Furthermore, we find that the existence of many correlated clusters reduces the stabilities of both embedded patterns and mixed states.

Directly coupled vs conventional time domain reflectometry in soils

USDA-ARS?s Scientific Manuscript database

Time domain reflectometry (TDR), a technique for estimation of soil water, measures the travel time of an electromagnetic pulse on electrodes embedded in the soil, but has limited application in commercial agriculture due to costs, labor, and sensing depth. Conventional TDR systems have employed ana...

What if Teachers Learn in the Classroom?

ERIC Educational Resources Information Center

Soini, Tiina; Pietarinen, Janne; Pyhältö, Kirsi

2016-01-01

This study focuses on exploring teacher learning in terms of teachers' professional agency embedded in the classroom. Teachers' sense of professional agency is related to perceiving instruction as a bidirectional process, use of students as a resource for professional learning and continuous reflection on teaching practices. Accordingly, the…

Camera network video summarization

NASA Astrophysics Data System (ADS)

Panda, Rameswar; Roy-Chowdhury, Amit K.

2017-05-01

Networks of vision sensors are deployed in many settings, ranging from security needs to disaster response to environmental monitoring. Many of these setups have hundreds of cameras and tens of thousands of hours of video. The difficulty of analyzing such a massive volume of video data is apparent whenever there is an incident that requires foraging through vast video archives to identify events of interest. As a result, video summarization, that automatically extract a brief yet informative summary of these videos, has attracted intense attention in the recent years. Much progress has been made in developing a variety of ways to summarize a single video in form of a key sequence or video skim. However, generating a summary from a set of videos captured in a multi-camera network still remains as a novel and largely under-addressed problem. In this paper, with the aim of summarizing videos in a camera network, we introduce a novel representative selection approach via joint embedding and capped l21-norm minimization. The objective function is two-fold. The first is to capture the structural relationships of data points in a camera network via an embedding, which helps in characterizing the outliers and also in extracting a diverse set of representatives. The second is to use a capped l21-norm to model the sparsity and to suppress the influence of data outliers in representative selection. We propose to jointly optimize both of the objectives, such that embedding can not only characterize the structure, but also indicate the requirements of sparse representative selection. Extensive experiments on standard multi-camera datasets well demonstrate the efficacy of our method over state-of-the-art methods.

MicroRNA-integrated and network-embedded gene selection with diffusion distance.

PubMed

Huang, Di; Zhou, Xiaobo; Lyon, Christopher J; Hsueh, Willa A; Wong, Stephen T C

2010-10-29

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways.

Fiber Optic Sensor Embedment Study for Multi-Parameter Strain Sensing

PubMed Central

Drissi-Habti, Monssef; Raman, Venkadesh; Khadour, Aghiad; Timorian, Safiullah

2017-01-01

The fiber optic sensors (FOSs) are commonly used for large-scale structure monitoring systems for their small size, noise free and low electrical risk characteristics. Embedded fiber optic sensors (FOSs) lead to micro-damage in composite structures. This damage generation threshold is based on the coating material of the FOSs and their diameter. In addition, embedded FOSs are aligned parallel to reinforcement fibers to avoid micro-damage creation. This linear positioning of distributed FOS fails to provide all strain parameters. We suggest novel sinusoidal sensor positioning to overcome this issue. This method tends to provide multi-parameter strains in a large surface area. The effectiveness of sinusoidal FOS positioning over linear FOS positioning is studied under both numerical and experimental methods. This study proves the advantages of the sinusoidal positioning method for FOS in composite material’s bonding. PMID:28333117

Magnetic-field sensing coil embedded in ceramic for measuring ambient magnetic field

DOEpatents

Takahashi, Hironori

2004-02-10

A magnetic pick-up coil for measuring magnetic field with high specific sensitivity, optionally with an electrostatic shield (24), having coupling elements (22) with high winding packing ratio, oriented in multiple directions, and embedded in ceramic material for structural support and electrical insulation. Elements of the coil are constructed from green ceramic sheets (200) and metallic ink deposited on surfaces and in via holes of the ceramic sheets. The ceramic sheets and the metallic ink are co-fired to create a monolithic hard ceramic body (20) with metallized traces embedded in, and placed on exterior surfaces of, the hard ceramic body. The compact and rugged coil can be used in a variety of environments, including hostile conditions involving ultra-high vacuum, high temperatures, nuclear and optical radiation, chemical reactions, and physically demanding surroundings, occurring either individually or in combinations.

Real-time optimizations for integrated smart network camera

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Lienard, Bruno; Meessen, Jerome; Delaigle, Jean-Francois

2005-02-01

We present an integrated real-time smart network camera. This system is composed of an image sensor, an embedded PC based electronic card for image processing and some network capabilities. The application detects events of interest in visual scenes, highlights alarms and computes statistics. The system also produces meta-data information that could be shared between other cameras in a network. We describe the requirements of such a system and then show how the design of the system is optimized to process and compress video in real-time. Indeed, typical video-surveillance algorithms as background differencing, tracking and event detection should be highly optimized and simplified to be used in this hardware. To have a good adequation between hardware and software in this light embedded system, the software management is written on top of the java based middle-ware specification established by the OSGi alliance. We can integrate easily software and hardware in complex environments thanks to the Java Real-Time specification for the virtual machine and some network and service oriented java specifications (like RMI and Jini). Finally, we will report some outcomes and typical case studies of such a camera like counter-flow detection.

Coevolution of Cooperation and Partner Rewiring Range in Spatial Social Networks

NASA Astrophysics Data System (ADS)

Khoo, Tommy; Fu, Feng; Pauls, Scott

2016-11-01

In recent years, there has been growing interest in the study of coevolutionary games on networks. Despite much progress, little attention has been paid to spatially embedded networks, where the underlying geographic distance, rather than the graph distance, is an important and relevant aspect of the partner rewiring process. It thus remains largely unclear how individual partner rewiring range preference, local vs. global, emerges and affects cooperation. Here we explicitly address this issue using a coevolutionary model of cooperation and partner rewiring range preference in spatially embedded social networks. In contrast to local rewiring, global rewiring has no distance restriction but incurs a one-time cost upon establishing any long range link. We find that under a wide range of model parameters, global partner switching preference can coevolve with cooperation. Moreover, the resulting partner network is highly degree-heterogeneous with small average shortest path length while maintaining high clustering, thereby possessing small-world properties. We also discover an optimum availability of reputation information for the emergence of global cooperators, who form distant partnerships at a cost to themselves. From the coevolutionary perspective, our work may help explain the ubiquity of small-world topologies arising alongside cooperation in the real world.

In situ TEM study of lithiation behavior of silicon nanoparticles attached to and embedded in a carbon matrix.

PubMed

Gu, Meng; Li, Ying; Li, Xiaolin; Hu, Shenyang; Zhang, Xiangwu; Xu, Wu; Thevuthasan, Suntharampillai; Baer, Donald R; Zhang, Ji-Guang; Liu, Jun; Wang, Chongmin

2012-09-25

Rational design of silicon and carbon nanocomposite with a special topological feature has been demonstrated to be a feasible way for mitigating the capacity fading associated with the large volume change of silicon anode in lithium ion batteries. Although the lithiation behavior of silicon and carbon as individual components has been well understood, lithium ion transport behavior across a network of silicon and carbon is still lacking. In this paper, we probe the lithiation behavior of silicon nanoparticles attached to and embedded in a carbon nanofiber using in situ TEM and continuum mechanical calculation. We found that aggregated silicon nanoparticles show contact flattening upon initial lithiation, which is characteristically analogous to the classic sintering of powder particles by a neck-growth mechanism. As compared with the surface-attached silicon particles, particles embedded in the carbon matrix show delayed lithiation. Depending on the strength of the carbon matrix, lithiation of the embedded silicon nanoparticles can lead to the fracture of the carbon fiber. These observations provide insights on lithium ion transport in the network-structured composite of silicon and carbon and ultimately provide fundamental guidance for mitigating the failure of batteries due to the large volume change of silicon anodes.

Disease named entity recognition from biomedical literature using a novel convolutional neural network.

PubMed

Zhao, Zhehuan; Yang, Zhihao; Luo, Ling; Wang, Lei; Zhang, Yin; Lin, Hongfei; Wang, Jian

2017-12-28

Automatic disease named entity recognition (DNER) is of utmost importance for development of more sophisticated BioNLP tools. However, most conventional CRF based DNER systems rely on well-designed features whose selection is labor intensive and time-consuming. Though most deep learning methods can solve NER problems with little feature engineering, they employ additional CRF layer to capture the correlation information between labels in neighborhoods which makes them much complicated. In this paper, we propose a novel multiple label convolutional neural network (MCNN) based disease NER approach. In this approach, instead of the CRF layer, a multiple label strategy (MLS) first introduced by us, is employed. First, the character-level embedding, word-level embedding and lexicon feature embedding are concatenated. Then several convolutional layers are stacked over the concatenated embedding. Finally, MLS strategy is applied to the output layer to capture the correlation information between neighboring labels. As shown by the experimental results, MCNN can achieve the state-of-the-art performance on both NCBI and CDR corpora. The proposed MCNN based disease NER method achieves the state-of-the-art performance with little feature engineering. And the experimental results show the MLS strategy's effectiveness of capturing the correlation information between labels in the neighborhood.

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks

PubMed Central

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-01-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites’ operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95.1% of the cases. PMID:28368319

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks.

PubMed

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-04-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites' operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95 . 1 % of the cases.

Mechanical and Vibration Testing of Carbon Fiber Composite Material with Embedded Piezoelectric Sensors

NASA Technical Reports Server (NTRS)

Duffy, Kirsten P.; Lerch, Bradley A.; Wilmoth, Nathan G.; Kray, Nicholas; Gemeinhardt, Gregory

2012-01-01

Piezoelectric materials have been proposed as a means of decreasing turbomachinery blade vibration either through a passive damping scheme, or as part of an active vibration control system. For polymer matrix fiber composite (PMFC) blades, the piezoelectric elements could be embedded within the blade material, protecting the brittle piezoceramic material from the airflow and from debris. Before implementation of a piezoelectric element within a PMFC blade, the effect on PMFC mechanical properties needs to be understood. This study attempts to determine how the inclusion of a packaged piezoelectric patch affects the material properties of the PMFC. Composite specimens with embedded piezoelectric patches were tested in four-point bending, short beam shear, and flatwise tension configurations. Results show that the embedded piezoelectric material does decrease the strength of the composite material, especially in flatwise tension, attributable to failure at the interface or within the piezoelectric element itself. In addition, the sensing properties of the post-cured embedded piezoelectric materials were tested, and performed as expected. The piezoelectric materials include a non-flexible patch incorporating solid piezoceramic material, and two flexible patch types incorporating piezoelectric fibers. The piezoceramic material used in these patches was Navy Type-II PZT.

Developing a New Wireless Sensor Network Platform and Its Application in Precision Agriculture

PubMed Central

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of “smart dust” offer great advantages due to their small size, low power consumption, easy integration and support for “green” applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network. PMID:22346622

Fast decision algorithms in low-power embedded processors for quality-of-service based connectivity of mobile sensors in heterogeneous wireless sensor networks.

PubMed

Jaraíz-Simón, María D; Gómez-Pulido, Juan A; Vega-Rodríguez, Miguel A; Sánchez-Pérez, Juan M

2012-01-01

When a mobile wireless sensor is moving along heterogeneous wireless sensor networks, it can be under the coverage of more than one network many times. In these situations, the Vertical Handoff process can happen, where the mobile sensor decides to change its connection from a network to the best network among the available ones according to their quality of service characteristics. A fitness function is used for the handoff decision, being desirable to minimize it. This is an optimization problem which consists of the adjustment of a set of weights for the quality of service. Solving this problem efficiently is relevant to heterogeneous wireless sensor networks in many advanced applications. Numerous works can be found in the literature dealing with the vertical handoff decision, although they all suffer from the same shortfall: a non-comparable efficiency. Therefore, the aim of this work is twofold: first, to develop a fast decision algorithm that explores the entire space of possible combinations of weights, searching that one that minimizes the fitness function; and second, to design and implement a system on chip architecture based on reconfigurable hardware and embedded processors to achieve several goals necessary for competitive mobile terminals: good performance, low power consumption, low economic cost, and small area integration.

Developing a new wireless sensor network platform and its application in precision agriculture.

PubMed

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of "smart dust" offer great advantages due to their small size, low power consumption, easy integration and support for "green" applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network.

Synchronizability of random rectangular graphs

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

Estrada, Ernesto, E-mail: ernesto.estrada@strath.ac.uk; Chen, Guanrong

2015-08-15

Random rectangular graphs (RRGs) represent a generalization of the random geometric graphs in which the nodes are embedded into hyperrectangles instead of on hypercubes. The synchronizability of RRG model is studied. Both upper and lower bounds of the eigenratio of the network Laplacian matrix are determined analytically. It is proven that as the rectangular network is more elongated, the network becomes harder to synchronize. The synchronization processing behavior of a RRG network of chaotic Lorenz system nodes is numerically investigated, showing complete consistence with the theoretical results.

Reconstruction of an infrared band of meteorological satellite imagery with abductive networks

NASA Technical Reports Server (NTRS)

Singer, Harvey A.; Cockayne, John E.; Versteegen, Peter L.

1995-01-01

As the current fleet of meteorological satellites age, the accuracy of the imagery sensed on a spectral channel of the image scanning system is continually and progressively degraded by noise. In time, that data may even become unusable. We describe a novel approach to the reconstruction of the noisy satellite imagery according to empirical functional relationships that tie the spectral channels together. Abductive networks are applied to automatically learn the empirical functional relationships between the data sensed on the other spectral channels to calculate the data that should have been sensed on the corrupted channel. Using imagery unaffected by noise, it is demonstrated that abductive networks correctly predict the noise-free observed data.

a Probabilistic Embedding Clustering Method for Urban Structure Detection

NASA Astrophysics Data System (ADS)

Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

2017-09-01

Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

OFSETH: smart medical textile for continuous monitoring of respiratory motions under magnetic resonance imaging.

PubMed

De Jonckheere, J; Narbonneau, F; Jeanne, M; Kinet, D; Witt, J; Krebber, K; Paquet, B; Depre, A; Logier, R

2009-01-01

The potential impact of optical fiber sensors embedded into medical textiles for the continuous monitoring of the patient during Magnetic Resonance Imaging is presented. We report on two pure optical sensing technologies for respiratory movements monitoring - a macro bending sensor and a Bragg grating sensor, designed to measure the elongation due to abdominal and thoracic motions during breathing. We demonstrate that the two sensors can successfully sense textile elongation between, 0% and 3%, while maintaining the stretching properties of the textile substrates for a good comfort of the patient.

Highly compressible fluorescent particles for pressure sensing in liquids

NASA Astrophysics Data System (ADS)

Cellini, F.; Peterson, S. D.; Porfiri, M.

2017-05-01

Pressure sensing in liquids is important for engineering applications ranging from industrial processing to naval architecture. Here, we propose a pressure sensor based on highly compressible polydimethylsiloxane foam particles embedding fluorescent Nile Red molecules. The particles display pressure sensitivities as low as 0.0018 kPa-1, which are on the same order of magnitude of sensitivities reported in commercial pressure-sensitive paints for air flows. We envision the application of the proposed sensor in particle image velocimetry toward an improved understanding of flow kinetics in liquids.

Compact VLSI neural computer integrated with active pixel sensor for real-time ATR applications

NASA Astrophysics Data System (ADS)

Fang, Wai-Chi; Udomkesmalee, Gabriel; Alkalai, Leon

1997-04-01

A compact VLSI neural computer integrated with an active pixel sensor has been under development to mimic what is inherent in biological vision systems. This electronic eye- brain computer is targeted for real-time machine vision applications which require both high-bandwidth communication and high-performance computing for data sensing, synergy of multiple types of sensory information, feature extraction, target detection, target recognition, and control functions. The neural computer is based on a composite structure which combines Annealing Cellular Neural Network (ACNN) and Hierarchical Self-Organization Neural Network (HSONN). The ACNN architecture is a programmable and scalable multi- dimensional array of annealing neurons which are locally connected with their local neurons. Meanwhile, the HSONN adopts a hierarchical structure with nonlinear basis functions. The ACNN+HSONN neural computer is effectively designed to perform programmable functions for machine vision processing in all levels with its embedded host processor. It provides a two order-of-magnitude increase in computation power over the state-of-the-art microcomputer and DSP microelectronics. A compact current-mode VLSI design feasibility of the ACNN+HSONN neural computer is demonstrated by a 3D 16X8X9-cube neural processor chip design in a 2-micrometers CMOS technology. Integration of this neural computer as one slice of a 4'X4' multichip module into the 3D MCM based avionics architecture for NASA's New Millennium Program is also described.

A Study of the Ethernet Troughput Performance of the Embedded System

NASA Astrophysics Data System (ADS)

Duan, Zhi-Yu; Zhao, Zhao-Wang

2007-09-01

An ethernet acceleration solution developed for the NIOS II Embedded System in astronomical applications - Mason Express is introduced in this paper. By manually constructing the proper network protocol headers and directly driving the hardware, Mason Express goes around the performance bottleneck of the Light Weighted IP stack (LWIP), and achieves up to 90Mb/s unidirectional data troughput rate from the embedded system board to the data collecting computer. With the LWIP stack, the maximum data rate is about 10.57Mb/s. Mason Express is a total software solution and no hardware changes required, neither does it affect the uCOS II operating system nor the LWIP stack, and can be implemented with or without any embedded operating system. It maximally protects the intelligence investment of the users.

Implementation of Networking-by-Touch to Small Unit, Network-Enabled Operations

DTIC Science & Technology

2010-09-01

Monitoring – Telemanipulation ............... 54  5.  Entertainment and Educational Applications...................... 55  6.  Tactile Displays Embedded...military situational awareness systems, text and graphics applications, medical applications, entertainment and educational applications...25] ) Electromechanical transducer Electromagnetic field sensors Computer driver 21 Now, consider another simple scenario: John loves music

Networked Teacher Professional Development: The Case of Globaloria

ERIC Educational Resources Information Center

Whitehouse, Pamela

2011-01-01

The purpose of this paper is to explore a teacher professional development program embedded in a networked learning environment, and to offer an emerging model and analytic matrix of 21st century teacher professional development. The Globaloria program is based on theories of learning by design and facilitates teachers and students as they create…

Architectures for Device Aware Network

DTIC Science & Technology

2005-03-01

68 b. PDA in DAN Mode ............................................................. 69 c. Cell Phone in DAN Mode...68 Figure 15. PDA in DAN Mode - Reduced Resolution Image ..................................... 69 Figure 16. Cell Phone in DAN Mode -No Image...computer, notebook computer, cell phone and a host of networked embedded systems) may have extremely differing capabilities and resources to retrieve and

The Key Roles in the Informal Organization: A Network Analysis Perspective

ERIC Educational Resources Information Center

de Toni, Alberto F.; Nonino, Fabio

2010-01-01

Purpose: The purpose of this paper is to identify the key roles embedded in the informal organizational structure (informal networks) and to outline their contribution in the companies' performance. A major objective of the research is to find and characterize a new key informal role that synthesises problem solving, expertise, and accessibility…

Metal-superconductor transition in low-dimensional superconducting clusters embedded in two-dimensional electron systems

NASA Astrophysics Data System (ADS)

Bucheli, D.; Caprara, S.; Castellani, C.; Grilli, M.

2013-02-01

Motivated by recent experimental data on thin film superconductors and oxide interfaces, we propose a random-resistor network apt to describe the occurrence of a metal-superconductor transition in a two-dimensional electron system with disorder on the mesoscopic scale. We consider low-dimensional (e.g. filamentary) structures of a superconducting cluster embedded in the two-dimensional network and we explore the separate effects and the interplay of the superconducting structure and of the statistical distribution of local critical temperatures. The thermal evolution of the resistivity is determined by a numerical calculation of the random-resistor network and, for comparison, a mean-field approach called effective medium theory (EMT). Our calculations reveal the relevance of the distribution of critical temperatures for clusters with low connectivity. In addition, we show that the presence of spatial correlations requires a modification of standard EMT to give qualitative agreement with the numerical results. Applying the present approach to an LaTiO3/SrTiO3 oxide interface, we find that the measured resistivity curves are compatible with a network of spatially dense but loosely connected superconducting islands.

Collecting and distributing wearable sensor data: an embedded personal area network to local area network gateway server.

PubMed

Neuhaeuser, Jakob; D'Angelo, Lorenzo T

2013-01-01

The goal of the concept and of the device presented in this contribution is to be able to collect sensor data from wearable sensors directly, automatically and wirelessly and to make them available over a wired local area network. Several concepts in e-health and telemedicine make use of portable and wearable sensors to collect movement or activity data. Usually these data are either collected via a wireless personal area network or using a connection to the user's smartphone. However, users might not carry smartphones on them while inside a residential building such as a nursing home or a hospital, but also within their home. Also, in such areas the use of other wireless communication technologies might be limited. The presented system is an embedded server which can be deployed in several rooms in order to ensure live data collection in bigger buildings. Also, the collection of data batches recorded out of range, as soon as a connection is established, is also possible. Both, the system concept and the realization are presented.

Performance evaluation of multi-channel wireless mesh networks with embedded systems.

PubMed

Lam, Jun Huy; Lee, Sang-Gon; Tan, Whye Kit

2012-01-01

Many commercial wireless mesh network (WMN) products are available in the marketplace with their own proprietary standards, but interoperability among the different vendors is not possible. Open source communities have their own WMN implementation in accordance with the IEEE 802.11s draft standard, Linux open80211s project and FreeBSD WMN implementation. While some studies have focused on the test bed of WMNs based on the open80211s project, none are based on the FreeBSD. In this paper, we built an embedded system using the FreeBSD WMN implementation that utilizes two channels and evaluated its performance. This implementation allows the legacy system to connect to the WMN independent of the type of platform and distributes the load between the two non-overlapping channels. One channel is used for the backhaul connection and the other one is used to connect to the stations to wireless mesh network. By using the power efficient 802.11 technology, this device can also be used as a gateway for the wireless sensor network (WSN).

Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

PubMed Central

Kümmel, Anne; Panke, Sven; Heinemann, Matthias

2006-01-01

As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data. PMID:16788595

End-to-End ASR-Free Keyword Search From Speech

NASA Astrophysics Data System (ADS)

Audhkhasi, Kartik; Rosenberg, Andrew; Sethy, Abhinav; Ramabhadran, Bhuvana; Kingsbury, Brian

2017-12-01

End-to-end (E2E) systems have achieved competitive results compared to conventional hybrid hidden Markov model (HMM)-deep neural network based automatic speech recognition (ASR) systems. Such E2E systems are attractive due to the lack of dependence on alignments between input acoustic and output grapheme or HMM state sequence during training. This paper explores the design of an ASR-free end-to-end system for text query-based keyword search (KWS) from speech trained with minimal supervision. Our E2E KWS system consists of three sub-systems. The first sub-system is a recurrent neural network (RNN)-based acoustic auto-encoder trained to reconstruct the audio through a finite-dimensional representation. The second sub-system is a character-level RNN language model using embeddings learned from a convolutional neural network. Since the acoustic and text query embeddings occupy different representation spaces, they are input to a third feed-forward neural network that predicts whether the query occurs in the acoustic utterance or not. This E2E ASR-free KWS system performs respectably despite lacking a conventional ASR system and trains much faster.