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.

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

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.

Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network

PubMed Central

Paek, Jeongyeup; Hicks, John; Coe, Sharon; Govindan, Ramesh

2014-01-01

This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet's built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Jacinto Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions. PMID:25171121

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

Image-based environmental monitoring sensor application using an embedded wireless sensor network.

PubMed

Paek, Jeongyeup; Hicks, John; Coe, Sharon; Govindan, Ramesh

2014-08-28

This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet's built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Cannot Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions.

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.

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.

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.

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.

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.

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

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.

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.

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

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.

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.

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.

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.

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

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.

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.

Energy efficient sensor network implementations

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

Frigo, Janette R; Raby, Eric Y; Brennan, Sean M

In this paper, we discuss a low power embedded sensor node architecture we are developing for distributed sensor network systems deployed in a natural environment. In particular, we examine the sensor node for energy efficient processing-at-the-sensor. We analyze the following modes of operation; event detection, sleep(wake-up), data acquisition, data processing modes using low power, high performance embedded technology such as specialized embedded DSP processors and a low power FPGAs at the sensing node. We use compute intensive sensor node applications: an acoustic vehicle classifier (frequency domain analysis) and a video license plate identification application (learning algorithm) as a case study.more » We report performance and total energy usage for our system implementations and discuss the system architecture design trade offs.« less

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.

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

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.

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

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.

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.

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.

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.

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

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

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.

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.

On an LAS-integrated soft PLC system based on WorldFIP fieldbus.

PubMed

Liang, Geng; Li, Zhijun; Li, Wen; Bai, Yan

2012-01-01

Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

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.

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…

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.

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.

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…

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

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

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.

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.

Implementation of an RBF neural network on embedded systems: real-time face tracking and identity verification.

PubMed

Yang, Fan; Paindavoine, M

2003-01-01

This paper describes a real time vision system that allows us to localize faces in video sequences and verify their identity. These processes are image processing techniques based on the radial basis function (RBF) neural network approach. The robustness of this system has been evaluated quantitatively on eight video sequences. We have adapted our model for an application of face recognition using the Olivetti Research Laboratory (ORL), Cambridge, UK, database so as to compare the performance against other systems. We also describe three hardware implementations of our model on embedded systems based on the field programmable gate array (FPGA), zero instruction set computer (ZISC) chips, and digital signal processor (DSP) TMS320C62, respectively. We analyze the algorithm complexity and present results of hardware implementations in terms of the resources used and processing speed. The success rates of face tracking and identity verification are 92% (FPGA), 85% (ZISC), and 98.2% (DSP), respectively. For the three embedded systems, the processing speeds for images size of 288 /spl times/ 352 are 14 images/s, 25 images/s, and 4.8 images/s, respectively.

Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application

NASA Astrophysics Data System (ADS)

Zhang, De-gan; Zhang, Xiao-dan

2012-11-01

With the growth of the amount of information manipulated by embedded application systems, which are embedded into devices and offer access to the devices on the internet, the requirements of saving the information systemically is necessary so as to fulfil access from the client and the local processing more efficiently. For supporting mobile applications, a design and implementation solution of embedded un-interruptible power supply (UPS) system (in brief, EUPSS) is brought forward for long-distance monitoring and controlling of UPS based on Web. The implementation of system is based on ATmega161, RTL8019AS and Arm chips with TCP/IP protocol suite for communication. In the embedded UPS system, an embedded file system is designed and implemented which saves the data and index information on a serial EEPROM chip in a structured way and communicates with a microcontroller unit through I2C bus. By embedding the file system into UPS system or other information appliances, users can access and manipulate local data on the web client side. Embedded file system on chips will play a major role in the growth of IP networking. Based on our experiment tests, the mobile users can easily monitor and control UPS in different places of long-distance. The performance of EUPSS has satisfied the requirements of all kinds of Web-based mobile applications.

Seamless Tracing of Human Behavior Using Complementary Wearable and House-Embedded Sensors

PubMed Central

Augustyniak, Piotr; Smoleń, Magdalena; Mikrut, Zbigniew; Kańtoch, Eliasz

2014-01-01

This paper presents a multimodal system for seamless surveillance of elderly people in their living environment. The system uses simultaneously a wearable sensor network for each individual and premise-embedded sensors specific for each environment. The paper demonstrates the benefits of using complementary information from two types of mobility sensors: visual flow-based image analysis and an accelerometer-based wearable network. The paper provides results for indoor recognition of several elementary poses and outdoor recognition of complex movements. Instead of complete system description, particular attention was drawn to a polar histogram-based method of visual pose recognition, complementary use and synchronization of the data from wearable and premise-embedded networks and an automatic danger detection algorithm driven by two premise- and subject-related databases. The novelty of our approach also consists in feeding the databases with real-life recordings from the subject, and in using the dynamic time-warping algorithm for measurements of distance between actions represented as elementary poses in behavioral records. The main results of testing our method include: 95.5% accuracy of elementary pose recognition by the video system, 96.7% accuracy of elementary pose recognition by the accelerometer-based system, 98.9% accuracy of elementary pose recognition by the combined accelerometer and video-based system, and 80% accuracy of complex outdoor activity recognition by the accelerometer-based wearable system. PMID:24787640

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.

The research and application of multi-biometric acquisition embedded system

NASA Astrophysics Data System (ADS)

Deng, Shichao; Liu, Tiegen; Guo, Jingjing; Li, Xiuyan

2009-11-01

The identification technology based on multi-biometric can greatly improve the applicability, reliability and antifalsification. This paper presents a multi-biometric system bases on embedded system, which includes: three capture daughter boards are applied to obtain different biometric: one each for fingerprint, iris and vein of the back of hand; FPGA (Field Programmable Gate Array) is designed as coprocessor, which uses to configure three daughter boards on request and provides data path between DSP (digital signal processor) and daughter boards; DSP is the master processor and its functions include: control the biometric information acquisition, extracts feature as required and responsible for compare the results with the local database or data server through network communication. The advantages of this system were it can acquire three different biometric in real time, extracts complexity feature flexibly in different biometrics' raw data according to different purposes and arithmetic and network interface on the core-board will be the solution of big data scale. Because this embedded system has high stability, reliability, flexibility and fit for different data scale, it can satisfy the demand of multi-biometric recognition.

Energy Harvesting for Structural Health Monitoring Sensor Networks

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

Park, G.; Farrar, C. R.; Todd, M. D.

2007-02-26

This report has been developed based on information exchanges at a 2.5-day workshop on energy harvesting for embedded structural health monitoring (SHM) sensing systems that was held June 28-30, 2005, at Los Alamos National Laboratory. The workshop was hosted by the LANL/UCSD Engineering Institute (EI). This Institute is an education- and research-focused collaboration between Los Alamos National Laboratory (LANL) and the University of California, San Diego (UCSD), Jacobs School of Engineering. A Statistical Pattern Recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portionmore » of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized, followed by a discussion of SHM sensor network paradigms, power requirements for these networks and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. This discussion also addresses current energy harvesting applications and system integration issues. The report concludes by defining some future research directions and possible technology demonstrations that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes.« less

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

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.

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…

Remote Diagnosis of the International Space Station Utilizing Telemetry Data

NASA Technical Reports Server (NTRS)

Deb, Somnath; Ghoshal, Sudipto; Malepati, Venkat; Domagala, Chuck; Patterson-Hine, Ann; Alena, Richard; Norvig, Peter (Technical Monitor)

2000-01-01

Modern systems such as fly-by-wire aircraft, nuclear power plants, manufacturing facilities, battlefields, etc., are all examples of highly connected network enabled systems. Many of these systems are also mission critical and need to be monitored round the clock. Such systems typically consist of embedded sensors in networked subsystems that can transmit data to central (or remote) monitoring stations. Moreover, many legacy are safety systems were originally not designed for real-time onboard diagnosis, but a critical and would benefit from such a solution. Embedding additional software or hardware in such systems is often considered too intrusive and introduces flight safety and validation concerns. Such systems can be equipped to transmit the sensor data to a remote-processing center for continuous health monitoring. At Qualtech Systems, we are developing a Remote Diagnosis Server (RDS) that can support multiple simultaneous diagnostic sessions from a variety of remote subsystems.

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.

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.

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.

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

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

Wireless and embedded carbon nanotube networks for damage detection in concrete structures

NASA Astrophysics Data System (ADS)

Saafi, Mohamed

2009-09-01

Concrete structures undergo an uncontrollable damage process manifesting in the form of cracks due to the coupling of fatigue loading and environmental effects. In order to achieve long-term durability and performance, continuous health monitoring systems are needed to make critical decisions regarding operation, maintenance and repairs. Recent advances in nanostructured materials such as carbon nanotubes have opened the door for new smart and advanced sensing materials that could effectively be used in health monitoring of structures where wireless and real time sensing could provide information on damage development. In this paper, carbon nanotube networks were embedded into a cement matrix to develop an in situ wireless and embedded sensor for damage detection in concrete structures. By wirelessly measuring the change in the electrical resistance of the carbon nanotube networks, the progress of damage can be detected and monitored. As a proof of concept, wireless cement-carbon nanotube sensors were embedded into concrete beams and subjected to monotonic and cyclic loading to evaluate the effect of damage on their response. Experimental results showed that the wireless response of the embedded nanotube sensors changes due to the formation of cracks during loading. In addition, the nanotube sensors were able to detect the initiation of damage at an early stage of loading.

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).

Flexible communications for battlespace 2000

NASA Astrophysics Data System (ADS)

Seiler, Thomas M.

2000-08-01

The advent of software-defined radios (products of DSP) with embedded processors capable of performing, communications functions (i.e., modulation) makes it possible for networks of radios to operate efficiently by changing its transmission characteristics (waveform) to fit the input data bandwidth requirements commensurate with received Eb/N0. It is also now feasible to have embedded within the network of radios a networking system capable of allocating bandwidth in accordance with current needs and priorities. The subject of battlefield networking can now also be addressed. A system with the multiple degrees of freedom (e.g., ability to manually and automatically change communications parameters to improve communications performance, spectrum management and the ability to incorporate different mission processing support) will provide the warfighter, those who support the warfighter and the rapidly expanding mission of our armed forces (i.e., peacekeeping, anti-terrorism) to meet an ever-changing mission and operational environment. This paper will address how such a robust communications system will enhance the mission of the specialist and make the products of his efforts a real-time tool for the shooter who must operate within the digitized battlespace.

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

Study and Application of Remote Data Moving Transmission under the Network Convergence

NASA Astrophysics Data System (ADS)

Zhiguo, Meng; Du, Zhou

The data transmission is an important problem in remote applications. Advance of network convergence has help to select and use data transmission model. The embedded system and data management platform is a key of the design. With communication module, interface technology and the transceiver which has independent intellectual property rights connected broadband network and mobile network seamlessly. Using the distribution system of mobile base station to realize the wireless transmission, using public networks to implement the data transmission, making the distant information system break through area restrictions and realizing transmission of the moving data, it has been fully recognized in long-distance medical care applications.

A mobile mapping system for spatial information based on DGPS/EGIS

NASA Astrophysics Data System (ADS)

Pei, Ling; Wang, Qing; Gu, Juan

2007-11-01

With the rapid developments of mobile device and wireless communication, it brings a new challenge for acquiring the spatial information. A mobile mapping system based on differential global position system (DGPS) integrated with embedded geographic information system (EGIS) is designed. A mobile terminal adapts to various GPS differential environments such as single base mode and network GPS mode like Virtual Reference Station (VRS) and Master- Auxiliary Concept (MAC) by the mobile communication technology. The spatial information collected through DGPS is organized in an EGIS running in the embedded device. A set of mobile terminal in real-time DGPS based on GPRS adopting multithreading technique of serial port in manner of simulating overlapped I/O operating is developed, further more, the GPS message analysis and checkout based on Strategy Pattern for various receivers are included in the process of development. A mobile terminal accesses to the GPS network successfully by NTRIP (Networked Transport of RTCM via Internet Protocol) compliance. Finally, the accuracy and reliability of the mobile mapping system are proved by a lot of testing in 9 provinces all over the country.

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

Computational identification of obligatorily autocatalytic replicators embedded in metabolic networks

PubMed Central

Kun, Ádám; Papp, Balázs; Szathmáry, Eörs

2008-01-01

Background If chemical A is necessary for the synthesis of more chemical A, then A has the power of replication (such systems are known as autocatalytic systems). We provide the first systems-level analysis searching for small-molecular autocatalytic components in the metabolisms of diverse organisms, including an inferred minimal metabolism. Results We find that intermediary metabolism is invariably autocatalytic for ATP. Furthermore, we provide evidence for the existence of additional, organism-specific autocatalytic metabolites in the forms of coenzymes (NAD+, coenzyme A, tetrahydrofolate, quinones) and sugars. Although the enzymatic reactions of a number of autocatalytic cycles are present in most of the studied organisms, they display obligatorily autocatalytic behavior in a few networks only, hence demonstrating the need for a systems-level approach to identify metabolic replicators embedded in large networks. Conclusion Metabolic replicators are apparently common and potentially both universal and ancestral: without their presence, kick-starting metabolic networks is impossible, even if all enzymes and genes are present in the same cell. Identification of metabolic replicators is also important for attempts to create synthetic cells, as some of these autocatalytic molecules will presumably be needed to be added to the system as, by definition, the system cannot synthesize them without their initial presence. PMID:18331628

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.

Development and application of remote video monitoring system for combine harvester based on embedded Linux

NASA Astrophysics Data System (ADS)

Chen, Jin; Wang, Yifan; Wang, Xuelei; Wang, Yuehong; Hu, Rui

2017-01-01

Combine harvester usually works in sparsely populated areas with harsh environment. In order to achieve the remote real-time video monitoring of the working state of combine harvester. A remote video monitoring system based on ARM11 and embedded Linux is developed. The system uses USB camera for capturing working state video data of the main parts of combine harvester, including the granary, threshing drum, cab and cut table. Using JPEG image compression standard to compress video data then transferring monitoring screen to remote monitoring center over the network for long-range monitoring and management. At the beginning of this paper it describes the necessity of the design of the system. Then it introduces realization methods of hardware and software briefly. And then it describes detailedly the configuration and compilation of embedded Linux operating system and the compiling and transplanting of video server program are elaborated. At the end of the paper, we carried out equipment installation and commissioning on combine harvester and then tested the system and showed the test results. In the experiment testing, the remote video monitoring system for combine harvester can achieve 30fps with the resolution of 800x600, and the response delay in the public network is about 40ms.

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.

Digital interface of electronic transformers based on embedded system

NASA Astrophysics Data System (ADS)

Shang, Qiufeng; Qi, Yincheng

2008-10-01

Benefited from digital interface of electronic transformers, information sharing and system integration in substation can be realized. An embedded system-based digital output scheme of electronic transformers is proposed. The digital interface is designed with S3C44B0X 32bit RISC microprocessor as the hardware platform. The μCLinux operation system (OS) is transplanted on ARM7 (S3C44B0X). Applying Ethernet technology as the communication mode in the substation automation system is a new trend. The network interface chip RTL8019AS is adopted. Data transmission is realized through the in-line TCP/IP protocol of uClinux embedded OS. The application result and character analysis show that the design can meet the real-time and reliability requirements of IEC60044-7/8 electronic voltage/current instrument transformer standards.

Embedded resource accounting for coupled natural-human systems: An application to water resource impacts of the western U.S. electrical energy trade

NASA Astrophysics Data System (ADS)

Ruddell, Benjamin L.; Adams, Elizabeth A.; Rushforth, Richard; Tidwell, Vincent C.

2014-10-01

In complex coupled natural-human systems (CNH), multitype networks link social, environmental, and economic systems with flows of matter, energy, information, and value. Embedded Resource Accounting (ERA) is a systems analysis framework that includes the indirect connections of a multitype CNH network. ERA is conditioned on perceived system boundaries, which may vary according to the accountant's point of view. Both direct and indirect impacts are implicit whenever two subnetworks interact in such a system; the ratio of two subnetworks' impacts is the embedded intensity. For trade in the services of water, this is understood as the indirect component of a water footprint, and as "virtual water" trade. ERA is a generalization of input-output, footprint, and substance flow methods, and is a type of life cycle analysis. This paper presents results for the water and electrical energy system in the western U.S. This system is dominated by California, which outsources the majority of its water footprint of electrical energy. Electricity trade increases total water consumption for electricity production in the western U.S. by 15% and shifts water use to water-stressed Colorado River Basin States. A systemic underaccounting for water footprints occurs because state-level processes discount a portion of the water footprint occurring outside of the state boundary.

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.

Structural health monitoring using smart optical fiber sensors

NASA Astrophysics Data System (ADS)

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

2001-04-01

This paper describes the potential of a smart monitoring system, incorporating optical fiber sensing techniques, to provide important structural information to designers and users alike. This technology has application in all areas including aerospace, civil, maritime and automotive engineering. In order to demonstrate the capability of the sensing system it has been installed in a 35 m 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 and the resulting strain information could be used by engineers to improve the structural design process. The optical strain sensor system comprises of three main components: the sensor network, the opto-electronic data acquisition unit (OFSSS) and the external PC which acts as a data log and display. 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 electromagnetic interference. The capability of this system has been demonstrated within the maritime environment, but can be adapted for any application.

Intelligent manipulation technique for multi-branch robotic systems

NASA Technical Reports Server (NTRS)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

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

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

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.

Multichannel Convolutional Neural Network for Biological Relation Extraction.

PubMed

Quan, Chanqin; Hua, Lei; Sun, Xiao; Bai, Wenjun

2016-01-01

The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are susceptible to the issues of "vocabulary gap" and data sparseness and the unattainable automation process in feature extraction. To address aforementioned issues, in this work, we propose a multichannel convolutional neural network (MCCNN) for automated biomedical relation extraction. The proposed model has the following two contributions: (1) it enables the fusion of multiple (e.g., five) versions in word embeddings; (2) the need for manual feature engineering can be obviated by automated feature learning with convolutional neural network (CNN). We evaluated our model on two biomedical relation extraction tasks: drug-drug interaction (DDI) extraction and protein-protein interaction (PPI) extraction. For DDI task, our system achieved an overall f -score of 70.2% compared to the standard linear SVM based system (e.g., 67.0%) on DDIExtraction 2013 challenge dataset. And for PPI task, we evaluated our system on Aimed and BioInfer PPI corpus; our system exceeded the state-of-art ensemble SVM system by 2.7% and 5.6% on f -scores.

Construct mine environment monitoring system based on wireless mesh network

NASA Astrophysics Data System (ADS)

Chen, Xin; Ge, Gengyu; Liu, Yinmei; Cheng, Aimin; Wu, Jun; Fu, Jun

2018-04-01

The system uses wireless Mesh network as a network transmission medium, and strive to establish an effective and reliable underground environment monitoring system. The system combines wireless network technology and embedded technology to monitor the internal data collected in the mine and send it to the processing center for analysis and environmental assessment. The system can be divided into two parts: the main control network module and the data acquisition terminal, and the SPI bus technology is used for mutual communication between them. Multi-channel acquisition and control interface design Data acquisition and control terminal in the analog signal acquisition module, digital signal acquisition module, and digital signal output module. The main control network module running Linux operating system, in which the transplant SPI driver, USB card driver and AODV routing protocol. As a result, the internal data collection and reporting of the mine are realized.

The embedded operating system project

NASA Technical Reports Server (NTRS)

Campbell, R. H.

1985-01-01

The design and construction of embedded operating systems for real-time advanced aerospace applications was investigated. The applications require reliable operating system support that must accommodate computer networks. Problems that arise in the construction of such operating systems, reconfiguration, consistency and recovery in a distributed system, and the issues of real-time processing are reported. A thesis that provides theoretical foundations for the use of atomic actions to support fault tolerance and data consistency in real-time object-based system is included. The following items are addressed: (1) atomic actions and fault-tolerance issues; (2) operating system structure; (3) program development; (4) a reliable compiler for path Pascal; and (5) mediators, a mechanism for scheduling distributed system processes.

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.

Advanced microprocessor based power protection system using artificial neural network techniques

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

Chen, Z.; Kalam, A.; Zayegh, A.

This paper describes an intelligent embedded microprocessor based system for fault classification in power system protection system using advanced 32-bit microprocessor technology. The paper demonstrates the development of protective relay to provide overcurrent protection schemes for fault detection. It also describes a method for power fault classification in three-phase system based on the use of neural network technology. The proposed design is implemented and tested on a single line three phase power system in power laboratory. Both the hardware and software development are described in detail.

Developing a multimodal biometric authentication system using soft computing methods.

PubMed

Malcangi, Mario

2015-01-01

Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.

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.

A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

PubMed Central

Mozumdar, Mohammad; Song, Zhen Yu; Lavagno, Luciano; Sangiovanni-Vincentelli, Alberto L.

2014-01-01

The Model Based Design (MBD) approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs) are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL) simulation. PMID:24960083

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

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.

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.

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.

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.

System Control Applications of Low-Power Radio Frequency Devices

NASA Astrophysics Data System (ADS)

van Rensburg, Roger

2017-09-01

This paper conceptualizes a low-power wireless sensor network design for application employment to reduce theft of portable computer devices used in educational institutions today. The aim of this study is to design and develop a reliable and robust wireless network that can eradicate accessibility of a device’s human interface. An embedded system supplied by an energy harvesting source, installed on the portable computer device, may represent one of multiple slave nodes which request regular updates from a standalone master station. A portable computer device which is operated in an undesignated area or in a field perimeter where master to slave communication is restricted, indicating a possible theft scenario, will initiate a shutdown of its operating system and render the device unusable. Consequently, an algorithm in the device firmware may ensure the necessary steps are executed to track the device, irrespective whether the device is enabled. Design outcomes thus far indicate that a wireless network using low-power embedded hardware, is feasible for anti-theft applications. By incorporating one of the latest Bluetooth low-energy, ANT+, ZigBee or Thread wireless technologies, an anti-theft system may be implemented that has the potential to reduce major portable computer device theft in institutions of digitized learning.

Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows.

PubMed

Moussawi, A; Derzsy, N; Lin, X; Szymanski, B K; Korniss, G

2017-09-15

Cascading failures are a critical vulnerability of complex information or infrastructure networks. Here we investigate the properties of load-based cascading failures in real and synthetic spatially-embedded network structures, and propose mitigation strategies to reduce the severity of damages caused by such failures. We introduce a stochastic method for optimal heterogeneous distribution of resources (node capacities) subject to a fixed total cost. Additionally, we design and compare the performance of networks with N-stable and (N-1)-stable network-capacity allocations by triggering cascades using various real-world node-attack and node-failure scenarios. We show that failure mitigation through increased node protection can be effectively achieved against single-node failures. However, mitigating against multiple node failures is much more difficult due to the combinatorial increase in possible sets of initially failing nodes. We analyze the robustness of the system with increasing protection, and find that a critical tolerance exists at which the system undergoes a phase transition, and above which the network almost completely survives an attack. Moreover, we show that cascade-size distributions measured in this region exhibit a power-law decay. Finally, we find a strong correlation between cascade sizes induced by individual nodes and sets of nodes. We also show that network topology alone is a weak predictor in determining the progression of cascading failures.

Embedded parallel processing based ground control systems for small satellite telemetry

NASA Technical Reports Server (NTRS)

Forman, Michael L.; Hazra, Tushar K.; Troendly, Gregory M.; Nickum, William G.

1994-01-01

The use of networked terminals which utilize embedded processing techniques results in totally integrated, flexible, high speed, reliable, and scalable systems suitable for telemetry and data processing applications such as mission operations centers (MOC). Synergies of these terminals, coupled with the capability of terminal to receive incoming data, allow the viewing of any defined display by any terminal from the start of data acquisition. There is no single point of failure (other than with network input) such as exists with configurations where all input data goes through a single front end processor and then to a serial string of workstations. Missions dedicated to NASA's ozone measurements program utilize the methodologies which are discussed, and result in a multimission configuration of low cost, scalable hardware and software which can be run by one flight operations team with low risk.

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

Reliability analysis for the smart grid : from cyber control and communication to physical manifestations of failure.

DOT National Transportation Integrated Search

2010-01-01

The Smart Grid is a cyber-physical system comprised of physical components, such as transmission lines and generators, and a : network of embedded systems deployed for their cyber control. Our objective is to qualitatively and quantitatively analyze ...

Interorganizational networks: fundamental to the Accreditation Canada program.

PubMed

Mitchell, Jonathan I; Nicklin, Wendy; MacDonald, Bernadette

2014-01-01

Within the Canadian healthcare system, the term population-accountable health network defines the use of collective resources to optimize the health of a population through integrated interventions. The leadership of these networks has also been identified as a critical factor, highlighting the need for creative management of resources in determining effective, balanced sets of interventions. In this article, using specific principles embedded in the Accreditation Canada program, the benefits of a network approach are highlighted, including knowledge sharing, improving the consistency of practice through standards, and a broader systems-and-population view of healthcare delivery across the continuum of care. The implications for Canadian health leaders to leverage the benefits of interorganizational networks are discussed.

FPGA-based multiprocessor system for injection molding control.

PubMed

Muñoz-Barron, Benigno; Morales-Velazquez, Luis; Romero-Troncoso, Rene J; Rodriguez-Donate, Carlos; Trejo-Hernandez, Miguel; Benitez-Rangel, Juan P; Osornio-Rios, Roque A

2012-10-18

The plastic industry is a very important manufacturing sector and injection molding is a widely used forming method in that industry. The contribution of this work is the development of a strategy to retrofit control of an injection molding machine based on an embedded system microprocessors sensor network on a field programmable gate array (FPGA) device. Six types of embedded processors are included in the system: a smart-sensor processor, a micro fuzzy logic controller, a programmable logic controller, a system manager, an IO processor and a communication processor. Temperature, pressure and position are controlled by the proposed system and experimentation results show its feasibility and robustness. As validation of the present work, a particular sample was successfully injected.

Design of Plant Eco-physiology Monitoring System Based on Embedded Technology

NASA Astrophysics Data System (ADS)

Li, Yunbing; Wang, Cheng; Qiao, Xiaojun; Liu, Yanfei; Zhang, Xinlu

A real time system has been developed to collect plant's growth information comprehensively. Plant eco-physiological signals can be collected and analyzed effectively. The system adopted embedded technology: wireless sensors network collect the eco-physiological information. Touch screen and ARM microprocessor make the system work independently without PC. The system is versatile and all parameters can be set by the touch screen. Sensors' intelligent compensation can be realized in this system. Information can be displayed by either graphically or in table mode. The ARM microprocessor provides the interface to connect with the internet, so the system support remote monitoring and controlling. The system has advantages of friendly interface, flexible construction and extension. It's a good tool for plant's management.

Using the network to achieve energy efficiency

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

Giglio, M.

1995-12-01

Novell, the third largest software company in the world, has developed Netware Embedded Systems Technology (NEST). NEST will take the network deeper into non-traditional computing environments and will imbed networking into more intelligent devices. Ultimately, this will lead to energy efficiencies in the office. NEST can make point-of-sale terminals, alarm systems, televisions, traffic controls, printers, lights, fax machines, copiers, HVAC controls, PBX machines, etc., either intelligent or more intelligent than they are currently. The mission statement for this particular group is to integrate over 30 million new intelligent devices into the workplace and the home with Novell networks by 1997.more » Computing trends have progressed from mainframes in the 1960s to keys, security systems, and airplanes in the year 2000. In fact, the new Boeing 777 has NEST in it, and it also has network servers on board. NEST enables the embedded network with the ability to put intelligence into devices. This gives one more control of the devices from wherever one is. For example, the pharmaceutical industry could use NEST to coordinate what the consumer is buying, what is in the warehouse, what the manufacturing plant is tooled for, and so on. Through NEST technology, the pharmaceutical industry now uses a camera that takes pictures of the pills. It can see whether an {open_quotes}overdose{close_quotes} or {open_quotes}underdose{close_quotes} of a particular type of pill is being manufactured. The plant can be shut down and corrections made immediately.« less

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.

Dynamic voltage and frequency scaling for on-demand performance and availability of biomedical embedded systems.

PubMed

Raskovic, Dejan; Giessel, David

2009-11-01

The goal of the study presented in this paper is to develop an embedded biomedical system capable of delivering maximum performance on demand, while maintaining the optimal energy efficiency whenever possible. Several hardware and software solutions are presented allowing the system to intelligently change the power supply voltage and frequency in runtime. The resulting system allows use of more energy-efficient components, operates most of the time in its most battery-efficient mode, and provides means to quickly change the operation mode while maintaining reliable performance. While all of these techniques extend battery life, the main benefit is on-demand availability of computational performance using a system that is not excessive. Biomedical applications, perhaps more than any other application, require battery operation, favor infrequent battery replacements, and can benefit from increased performance under certain conditions (e.g., when anomaly is detected) that makes them ideal candidates for this approach. In addition, if the system is a part of a body area network, it needs to be light, inexpensive, and adaptable enough to satisfy changing requirements of the other nodes in the network.

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.

A formal protocol test procedure for the Survivable Adaptable Fiber Optic Embedded Network (SAFENET)

NASA Astrophysics Data System (ADS)

High, Wayne

1993-03-01

This thesis focuses upon a new method for verifying the correct operation of a complex, high speed fiber optic communication network. These networks are of growing importance to the military because of their increased connectivity, survivability, and reconfigurability. With the introduction and increased dependence on sophisticated software and protocols, it is essential that their operation be correct. Because of the speed and complexity of fiber optic networks being designed today, they are becoming increasingly difficult to test. Previously, testing was accomplished by application of conformance test methods which had little connection with an implementation's specification. The major goal of conformance testing is to ensure that the implementation of a profile is consistent with its specification. Formal specification is needed to ensure that the implementation performs its intended operations while exhibiting desirable behaviors. The new conformance test method presented is based upon the System of Communicating Machine model which uses a formal protocol specification to generate a test sequence. The major contribution of this thesis is the application of the System of Communicating Machine model to formal profile specifications of the Survivable Adaptable Fiber Optic Embedded Network (SAFENET) standard which results in the derivation of test sequences for a SAFENET profile. The results applying this new method to SAFENET's OSI and Lightweight profiles are presented.

A recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure.

PubMed

Liao, Fuyuan; Jan, Yih-Kuen

2012-06-01

This paper presents a recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure. Recurrence is a fundamental property of many dynamical systems, which can be explored in phase spaces constructed from observational time series. A visualization tool of recurrence analysis called recurrence plot (RP) has been proved to be highly effective to detect transitions in the dynamics of the system. However, it was found that delay embedding can produce spurious structures in RPs. Network-based concepts have been applied for the analysis of nonlinear time series recently. We demonstrate that time series with different types of dynamics exhibit distinct global clustering coefficients and distributions of local clustering coefficients and that the global clustering coefficient is robust to the embedding parameters. We applied the approach to study skin blood flow oscillations (BFO) response to loading pressure. The results showed that global clustering coefficients of BFO significantly decreased in response to loading pressure (p<0.01). Moreover, surrogate tests indicated that such a decrease was associated with a loss of nonlinearity of BFO. Our results suggest that the recurrence network approach can practically quantify the nonlinear dynamics of BFO.

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.

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.

SMART Layer and SMART Suitcase for structural health monitoring applications

NASA Astrophysics Data System (ADS)

Lin, Mark; Qing, Xinlin; Kumar, Amrita; Beard, Shawn J.

2001-06-01

Knowledge of integrity of in-service structures can greatly enhance their safety and reliability and lower structural maintenance cost. Current practices limit the extent of real-time knowledge that can be obtained from structures during inspection, are labor-intensive and thereby increase life-cycle costs. Utilization of distributed sensors integrated with the structure is a viable and cost-effective means of monitoring the structure and reducing inspection costs. Acellent Technologies is developing a novel system for actively and passively interrogating the health of a structure through an integrated network of sensors and actuators. Acellent's system comprises of SMART Layers, SMART Suitcase and diagnostic software. The patented SMART Layer is a thin dielectric film with an embedded network of distributed piezoelectric actuators/sensors that can be surface-mounted on metallic structures or embedded inside composite structures. The SMART Suitcase is a portable diagnostic unit designed with multiple sensor/actuator channels to interface with the SMART Layer, generate diagnostic signals from actuators and record measurements from the embedded sensors. With appropriate diagnostic software, Acellent's system can be used for monitoring structural condition and for detecting damage while the structures are in service. This paper enumerates on the SMART Layer and SMART Suitcase and their applicability to composite and metal structures.

Embedded 100 Gbps Photonic Components

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

Kuznia, Charlie

This innovation to fiber optic component technology increases the performance, reduces the size and reduces the power consumption of optical communications within dense network systems, such as advanced distributed computing systems and data centers. VCSEL technology is enabling short-reach (< 100 m) and >100 Gbps optical interconnections over multi-mode fiber in commercial applications.

Feedback control system based on a remote operated PID controller implemented using mbed NXP LPC1768 development board

NASA Astrophysics Data System (ADS)

Pricop, Emil; Zamfir, Florin; Paraschiv, Nicolae

2015-11-01

Process control is a challenging research topic for both academia and industry for a long time. Controllers evolved from the classical SISO approach to modern fuzzy or neuro-fuzzy embedded devices with networking capabilities, however PID algorithms are still used in the most industrial control loops. In this paper, we focus on the implementation of a PID controller using mbed NXP LPC1768 development board. This board integrates a powerful ARM Cortex- M3 core and has networking capabilities. The implemented controller can be remotely operated by using an Internet connection and a standard Web browser. The main advantages of the proposed embedded system are customizability, easy operation and very low power consumption. The experimental results obtained by using a simulated process are analysed and shows that the implementation can be done with success in industrial applications.

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.

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.

A versatile sensor network for urban search and rescue operations

NASA Astrophysics Data System (ADS)

Känsälä, Klaus; Korkalainen, Marko; Mäyrä, Aki

2011-11-01

The presentation is based in the research work carried out in EU funded project SGL for USaR (Second Generation Locator for Urban Search and Rescue Operations). The aim of this project is to develop wireless standalone communication system with embedded sensor network which can be globally used in rescue operations after accidents or terrorist attacks. The system should be able to operate without external support for several days: it should have autonomy with power supply and communication. The devices must be lightweight so that rescue team can easily carry them and finally they must be easy to install and use. The range of the wireless communication must cover an area of several square kilometers. The embedded sensor system must be able to detect sings of life but also detect hazards threatening the rescue operators thus preventing more accidents. It should also support positioning and digital mapping as well as the management of the search and rescue operation. This sensor network for urban search and rescue operations has been tested on a field conditions and it has proven to be robust and reliable and provides an energy efficient way of communication and positioning on harsh conditions.

Acoustic Techniques for Structural Health Monitoring

NASA Astrophysics Data System (ADS)

Frankenstein, B.; Augustin, J.; Hentschel, D.; Schubert, F.; Köhler, B.; Meyendorf, N.

2008-02-01

Future safety and maintenance strategies for industrial components and vehicles are based on combinations of monitoring systems that are permanently attached to or embedded in the structure, and periodic inspections. The latter belongs to conventional nondestructive evaluation (NDE) and can be enhanced or partially replaced by structural health monitoring systems. However, the main benefit of this technology for the future will consist of systems that can be differently designed based on improved safety philosophies, including continuous monitoring. This approach will increase the efficiency of inspection procedures at reduced inspection times. The Fraunhofer IZFP Dresden Branch has developed network nodes, miniaturized transmitter and receiver systems for active and passive acoustical techniques and sensor systems that can be attached to or embedded into components or structures. These systems have been used to demonstrate intelligent sensor networks for the monitoring of aerospace structures, railway systems, wind energy generators, piping system and other components. Material discontinuities and flaws have been detected and monitored during full scale fatigue testing. This paper will discuss opportunities and future trends in nondestructive evaluation and health monitoring based on new sensor principles and advanced microelectronics. It will outline various application examples of monitoring systems based on acoustic techniques and will indicate further needs for research and development.

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems.

PubMed

Munera, Eduardo; Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Noguera, Juan Fco Blanes

2015-07-24

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client's requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client's requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

Proceedings of the ARO Planning Workshop on Embedded Systems and Network Security Held in Raleigh, North Carolina on February 22-23, 2007

DTIC Science & Technology

2007-10-28

Shin (U Mich) John Stankovic (UVA) Phil Koopman (CMU) Wenliang Du (Syracuse U.) Virgil Gligor (UMD) Radha Poovendran ( UW ) Adrian Perrig (CMU...Department of Computer Sciences, University of Wisconsin, Madison , WI 53706, USA Email: suman@cs.wisc.edu 1 Introduction Wireless communication...NetworkinG Systems (WiNGS) Laboratory Wireless localization Madison municipal WiFi mesh network • • 9 square miles area • 200+ APs 2 Wireless AP radio

FPGA-Based Multiprocessor System for Injection Molding Control

PubMed Central

Muñoz-Barron, Benigno; Morales-Velazquez, Luis; Romero-Troncoso, Rene J.; Rodriguez-Donate, Carlos; Trejo-Hernandez, Miguel; Benitez-Rangel, Juan P.; Osornio-Rios, Roque A.

2012-01-01

The plastic industry is a very important manufacturing sector and injection molding is a widely used forming method in that industry. The contribution of this work is the development of a strategy to retrofit control of an injection molding machine based on an embedded system microprocessors sensor network on a field programmable gate array (FPGA) device. Six types of embedded processors are included in the system: a smart-sensor processor, a micro fuzzy logic controller, a programmable logic controller, a system manager, an IO processor and a communication processor. Temperature, pressure and position are controlled by the proposed system and experimentation results show its feasibility and robustness. As validation of the present work, a particular sample was successfully injected. PMID:23202036

Meeting the Challenge of Distributed Real-Time & Embedded (DRE) Systems

DTIC Science & Technology

2012-05-10

IP RTOS Middleware Middleware Services DRE Applications Operating Sys & Protocols Hardware & Networks Middleware Middleware Services DRE...Services COTS & standards-based middleware, language, OS , network, & hardware platforms • Real-time CORBA (TAO) middleware • ADAPTIVE Communication...SPLs) F-15 product variant A/V 8-B product variant F/A 18 product variant UCAV product variant Software Produce-Line Hardware (CPU, Memory, I/O) OS

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

PubMed

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

2018-01-01

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

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.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Active Disaster Response System for a Smart Building

PubMed Central

Lin, Chun-Yen; Chu, Edward T.-H; Ku, Lun-Wei; Liu, Jane W. S.

2014-01-01

Disaster warning and surveillance systems have been widely applied to help the public be aware of an emergency. However, existing warning systems are unable to cooperate with household appliances or embedded controllers; that is, they cannot provide enough time for preparedness and evacuation, especially for disasters like earthquakes. In addition, the existing warning and surveillance systems are not responsible for collecting sufficient information inside a building for relief workers to conduct a proper rescue action after a disaster happens. In this paper, we describe the design and implementation of a proof of concept prototype, named the active disaster response system (ADRS), which automatically performs emergency tasks when an earthquake happens. ADRS can interpret Common Alerting Protocol (CAP) messages, published by an official agency, and actuate embedded controllers to perform emergency tasks to respond to the alerts. Examples of emergency tasks include opening doors and windows and cutting off power lines and gas valves. In addition, ADRS can maintain a temporary network by utilizing the embedded controllers; hence, victims trapped inside a building are still able to post emergency messages if the original network is disconnected. We conducted a field trial to evaluate the effectiveness of ADRS after an earthquake happened. Our results show that compared to manually operating emergency tasks, ADRS can reduce the operation time by up to 15 s, which is long enough for people to get under sturdy furniture, or to evacuate from the third floor to the first floor, or to run more than 100 m. PMID:25237897

A REST-ful interpretation for embedded modular systems based on open architecture

NASA Astrophysics Data System (ADS)

Lyke, James

2016-05-01

The much-anticipated revolution of the "Internet of things" (IoT) is expected to generate one trillion internet devices within the next 15 years, mostly in the form of simple wireless sensor devices. While this revolution promises to transform silicon markets and drive a number of disruptive changes in society, it is also the case that the protocols, complexity, and security issues of extremely large dynamic, co-mingled networks is still poorly understood. Furthermore, embedded system developers, to include military and aerospace users, have largely ignored the potential (good and bound) of the cloudlike, possibly intermingling networks having variable structure to how future systems might be engineered. In this paper, we consider a new interpretation of IoT inspired modular architecture strategies involving the representational state transfer (REST) model, in which dynamic networks with variable structure employ stateless application programming interface (API) concepts. The power of the method, which extends concepts originally developed for space plug-and-play avionics, is that it allows for the fluid co-mingling of hardware and software in networks whose structure can overlap and evolve. Paradoxically, these systems may have the most stringent determinism and fault-tolerant needs. In this paper we review how RESTful APIs can potentially be used to design, create, test, and deploy systems rapidly while addressing security and referential integrity even when the nodes of many systems might physically co-mingle. We will also explore ways to take advantage of the RESTful paradigm for fault tolerance and what extensions might be necessary to deal with high-performance and determinism.

An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures.

PubMed

Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico; Moriello, Rosario Schiano Lo; Bonavolontà, Francesco; Fabbrocino, Francesco

2017-11-07

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.

An adaptive cryptographic accelerator for network storage security on dynamically reconfigurable platform

NASA Astrophysics Data System (ADS)

Tang, Li; Liu, Jing-Ning; Feng, Dan; Tong, Wei

2008-12-01

Existing security solutions in network storage environment perform poorly because cryptographic operations (encryption and decryption) implemented in software can dramatically reduce system performance. In this paper we propose a cryptographic hardware accelerator on dynamically reconfigurable platform for the security of high performance network storage system. We employ a dynamic reconfigurable platform based on a FPGA to implement a PowerPCbased embedded system, which executes cryptographic algorithms. To reduce the reconfiguration latency, we apply prefetch scheduling. Moreover, the processing elements could be dynamically configured to support different cryptographic algorithms according to the request received by the accelerator. In the experiment, we have implemented AES (Rijndael) and 3DES cryptographic algorithms in the reconfigurable accelerator. Our proposed reconfigurable cryptographic accelerator could dramatically increase the performance comparing with the traditional software-based network storage systems.

Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease

PubMed Central

Nunez, Paul L.; Srinivasan, Ramesh

2013-01-01

The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628

Managing a Real-Time Embedded Linux Platform with Buildroot

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

Diamond, J.; Martin, K.

2015-01-01

Developers of real-time embedded software often need to build the operating system, kernel, tools and supporting applications from source to work with the differences in their hardware configuration. The first attempts to introduce Linux-based real-time embedded systems into the Fermilab accelerator controls system used this approach but it was found to be time-consuming, difficult to maintain and difficult to adapt to different hardware configurations. Buildroot is an open source build system with a menu-driven configuration tool (similar to the Linux kernel build system) that automates this process. A customized Buildroot [1] system has been developed for use in the Fermilabmore » accelerator controls system that includes several hardware configuration profiles (including Intel, ARM and PowerPC) and packages for Fermilab support software. A bootable image file is produced containing the Linux kernel, shell and supporting software suite that varies from 3 to 20 megabytes large – ideal for network booting. The result is a platform that is easier to maintain and deploy in diverse hardware configurations« less

Embedding speech into virtual realities

NASA Technical Reports Server (NTRS)

Bohn, Christian-Arved; Krueger, Wolfgang

1993-01-01

In this work a speaker-independent speech recognition system is presented, which is suitable for implementation in Virtual Reality applications. The use of an artificial neural network in connection with a special compression of the acoustic input leads to a system, which is robust, fast, easy to use and needs no additional hardware, beside a common VR-equipment.

Credits, Curriculum, and Control in Higher Education: Cross-National Perspectives.

ERIC Educational Resources Information Center

Mason, Terrence C.; Arnove, Robert F.; Sutton, Margaret

2001-01-01

Examines higher education in Indonesia, Nicaragua, and Vietnam to illustrate how use of a credit system is linked to policies and institutions associated with capitalist, market-based economies, and how the credit system, embedded within a network of other educational practices, has transformed the university into an institution focused more on…

The adaptive safety analysis and monitoring system

NASA Astrophysics Data System (ADS)

Tu, Haiying; Allanach, Jeffrey; Singh, Satnam; Pattipati, Krishna R.; Willett, Peter

2004-09-01

The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.

Regenerable Photovoltaic Devices with a Hydrogel-Embedded Microvascular Network

PubMed Central

Koo, Hyung-Jun; Velev, Orlin D.

2013-01-01

Light-driven degradation of photoactive molecules could be one of the major obstacles to stable long term operation of organic dye-based solar light harvesting devices. One solution to this problem may be mimicking the regeneration functionality of a plant leaf. We report an organic dye photovoltaic system that has been endowed with such microfluidic regeneration functionality. A hydrogel medium with embedded channels allows rapid and uniform supply of photoactive reagents by a convection-diffusion mechanism. A washing-activation cycle enables reliable replacement of the organic component in a dye-sensitized photovoltaic system. Repetitive restoration of photovoltaic performance after intensive device degradation is demonstrated. PMID:23912814

An analog silicon retina with multichip configuration.

PubMed

Kameda, Seiji; Yagi, Tetsuya

2006-01-01

The neuromorphic silicon retina is a novel analog very large scale integrated circuit that emulates the structure and the function of the retinal neuronal circuit. We fabricated a neuromorphic silicon retina, in which sample/hold circuits were embedded to generate fluctuation-suppressed outputs in the previous study [1]. The applications of this silicon retina, however, are limited because of a low spatial resolution and computational variability. In this paper, we have fabricated a multichip silicon retina in which the functional network circuits are divided into two chips: the photoreceptor network chip (P chip) and the horizontal cell network chip (H chip). The output images of the P chip are transferred to the H chip with analog voltages through the line-parallel transfer bus. The sample/hold circuits embedded in the P and H chips compensate for the pattern noise generated on the circuits, including the analog communication pathway. Using the multichip silicon retina together with an off-chip differential amplifier, spatial filtering of the image with an odd- and an even-symmetric orientation selective receptive fields was carried out in real time. The analog data transfer method in the present multichip silicon retina is useful to design analog neuromorphic multichip systems that mimic the hierarchical structure of neuronal networks in the visual system.

2015 Marine Corps Security Environment Forecast: Futures 2030-2045

DTIC Science & Technology

2015-01-01

The technologies that make the iPhone “smart” were publically funded—the Internet, wireless networks, the global positioning system, microelectronics...Energy Revolution (63 percent);  Internet of Things (ubiquitous sensors embedded in interconnected computing devices) (50 percent);  “Sci-Fi...Neuroscience & artificial intelligence - Sensors /control systems -Power & energy -Human-robot interaction Robots/autonomous systems will become part of the

Embedded controller for GEM detector readout system

NASA Astrophysics Data System (ADS)

Zabołotny, Wojciech M.; Byszuk, Adrian; Chernyshova, Maryna; Cieszewski, Radosław; Czarski, Tomasz; Dominik, Wojciech; Jakubowska, Katarzyna L.; Kasprowicz, Grzegorz; Poźniak, Krzysztof; Rzadkiewicz, Jacek; Scholz, Marek

2013-10-01

This paper describes the embedded controller used for the multichannel readout system for the GEM detector. The controller is based on the embedded Mini ITX mainboard, running the GNU/Linux operating system. The controller offers two interfaces to communicate with the FPGA based readout system. FPGA configuration and diagnostics is controlled via low speed USB based interface, while high-speed setup of the readout parameters and reception of the measured data is handled by the PCI Express (PCIe) interface. Hardware access is synchronized by the dedicated server written in C. Multiple clients may connect to this server via TCP/IP network, and different priority is assigned to individual clients. Specialized protocols have been implemented both for low level access on register level and for high level access with transfer of structured data with "msgpack" protocol. High level functionalities have been split between multiple TCP/IP servers for parallel operation. Status of the system may be checked, and basic maintenance may be performed via web interface, while the expert access is possible via SSH server. System was designed with reliability and flexibility in mind.

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.

The Portals 4.0 network programming interface.

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

Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin

2012-11-01

This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandias Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generationmore » of machines employing advanced network interface architectures that support enhanced offload capabilities.« less

Microsystems Technology Symposium: Enabling Future Capability (BRIEFING CHARTS)

DTIC Science & Technology

2007-03-07

Microsystems I t r t i r t Wireless and Networked Systems Embedded Computation Signal Processing Communications 4 Microsystems Technology Office: Enabling...Regency Ballroom) (Regency Ballroom) 1330 1400 Communciation Actuation 1430 (Imperial Ballroom) (Imperial Ballroom) 1500 1530 1600 1630 1700 1730 1800

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

Sensor network based vehicle classification and license plate identification system

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

Frigo, Janette Rose; Brennan, Sean M; Rosten, Edward J

Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform.more » Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.« less

Simple debugging techniques for embedded subsystems

NASA Astrophysics Data System (ADS)

MacPherson, Matthew S.; Martin, Kevin S.

1990-08-01

This paper describes some of the tools and methods used for developing and debugging embedded subsystems at Fermilab. Specifically, these tools have been used for the Flying Wire project and are currently being employed for the New TECAR upgrade. The Flying Wire is a subsystem that swings a wire through the beam in order to measure luminosity and beam density distribution, and TECAR (Tevatron excitation controller and regulator) controls the power-supply ramp generation for the superconducting Tevatron accelerator at Fermilab. In both instances the subsystem hardware consists of a VME crate with one or more processors, shared memory and a network connection to the accelerator control system. Two real-time-operating systems are currently being used: VRTX for the Flying Wire system, and MTOS for New TECAR. The code which runs in these subsystems is a combination of C and assembler and is developed using the Microtec cross-development tools on a VAX 8650 running VMS. This paper explains how multiple debuggers are used to give the greatest possible flexibility from assembly to high-level debugging. Also discussed is how network debugging and network downloading can make a very effective and efficient means of finding bugs in the subsystem environment. The debuggers used are PROBE1, TRACER and the MTOS debugger.

Intelligence Control System for Landfills Based on Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Zhang, Qian; Huang, Chuan; Gong, Jian

2018-06-01

This paper put forward an intelligence system for controlling the landfill gas in landfills to make the landfill gas (LFG) exhaust controllably and actively. The system, which is assigned by the wireless sensor network, were developed and supervised by remote applications in workshop instead of manual work. An automatic valve control depending on the sensor units embedded is installed in tube, the air pressure and concentration of LFG are detected to decide the level of the valve switch. The paper also proposed a modified algorithm to solve transmission problem, so that the system can keep a high efficiency and long service life.

DEEP ATTRACTOR NETWORK FOR SINGLE-MICROPHONE SPEAKER SEPARATION.

PubMed

Chen, Zhuo; Luo, Yi; Mesgarani, Nima

2017-03-01

Despite the overwhelming success of deep learning in various speech processing tasks, the problem of separating simultaneous speakers in a mixture remains challenging. Two major difficulties in such systems are the arbitrary source permutation and unknown number of sources in the mixture. We propose a novel deep learning framework for single channel speech separation by creating attractor points in high dimensional embedding space of the acoustic signals which pull together the time-frequency bins corresponding to each source. Attractor points in this study are created by finding the centroids of the sources in the embedding space, which are subsequently used to determine the similarity of each bin in the mixture to each source. The network is then trained to minimize the reconstruction error of each source by optimizing the embeddings. The proposed model is different from prior works in that it implements an end-to-end training, and it does not depend on the number of sources in the mixture. Two strategies are explored in the test time, K-means and fixed attractor points, where the latter requires no post-processing and can be implemented in real-time. We evaluated our system on Wall Street Journal dataset and show 5.49% improvement over the previous state-of-the-art methods.

Automotive Airbag Safety Enhancement Final Report CRADA No. TSB-1165-95

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

Cutting, Jack; Durrell, Robert

The Vehicle Safety systems (VSS) Division of Quantic Industries, Inc. (QII) manufactured automotive airbag components. When both the driver and the passenger side airbags inflated in a tightly sealed passenger compartment, the compression of the surrounding air could and, in some instances, would cause damage to the eardrums of the occupants. The Aerospace and Division (ADD) of QII had partially developed the technology to fracture the canopy of a jet aircraft at the time of pilot ejection. The technical problem was how to adapt the canopy fracturing technology to the rear window of a motor vehicle in a safe andmore » cost effective manner. The existing approach was to replace the embedded rear window defroster with a series-parallel network of exploding bridge wires (EBWs). This would still provide the defrost function at low voltage/ current, but would cause fracturing of the window when a high current/voltage pulse was applied without pyrotechnics or explosives. The elements of this system were the embedded EBW network and a trunk-mounted fireset. The fireset would store the required energy to fire the network upon the receipt of a trigger signal from the existing air bag crash sensor.« less

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.

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.

Accelerating a MPEG-4 video decoder through custom software/hardware co-design

NASA Astrophysics Data System (ADS)

Díaz, Jorge L.; Barreto, Dacil; García, Luz; Marrero, Gustavo; Carballo, Pedro P.; Núñez, Antonio

2007-05-01

In this paper we present a novel methodology to accelerate an MPEG-4 video decoder using software/hardware co-design for wireless DAB/DMB networks. Software support includes the services provided by the embedded kernel μC/OS-II, and the application tasks mapped to software. Hardware support includes several custom co-processors and a communication architecture with bridges to the main system bus and with a dual port SRAM. Synchronization among tasks is achieved at two levels, by a hardware protocol and by kernel level scheduling services. Our reference application is an MPEG-4 video decoder composed of several software functions and written using a special C++ library named CASSE. Profiling and space exploration techniques were used previously over the Advanced Simple Profile (ASP) MPEG-4 decoder to determinate the best HW/SW partition developed here. This research is part of the ARTEMI project and its main goal is the establishment of methodologies for the design of real-time complex digital systems using Programmable Logic Devices with embedded microprocessors as target technology and the design of multimedia systems for broadcasting networks as reference application.

Improving RF Transmit Power and Received Signal Strength in 2.4 GHz ZigBee Based Active RFID System with Embedded Method

NASA Astrophysics Data System (ADS)

Po'ad, F. A.; Ismail, W.; Jusoh, J. F.

2017-08-01

This paper describes the experiments and analysis conducted on 2.4 GHz embedded active Radio Frequency Identification (RFID) - Wireless Sensor Network (WSN) based system that has been developed for the purposes of location tracking and monitoring in indoor and outdoor environments. Several experiments are conducted to test the effectiveness and performance of the developed system and two of them is by measuring the Radio Frequency (RF) transmitting power and Received Signal Strength (RSS) to prove that the embedded active RFID tag is capable to generate higher transmit power during data transmission and able to provide better RSS reading compared to standalone RFID tag. Experiments are carried out on two RFID tags which are active RFID tag embedded with GPS and GSM (ER2G); and standalone RFID tag communicating with the same active RFID reader. The developed ER2G contributes 12.26 % transmit power and 6.47 % RSS reading higher than standalone RFID tag. The results conclude that the ER2G gives better performance compared to standalone RFID tag and can be used as guidelines for future design improvements.

An Approach to V&V of Embedded Adaptive Systems

NASA Technical Reports Server (NTRS)

Liu, Yan; Yerramalla, Sampath; Fuller, Edgar; Cukic, Bojan; Gururajan, Srikaruth

2004-01-01

Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

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 dynamical networks into distributed models

NASA Astrophysics Data System (ADS)

Innocenti, Giacomo; Paoletti, Paolo

2015-07-01

Large networks of interacting dynamical systems are well-known for the complex behaviours they are able to display, even when each node features a quite simple dynamics. Despite examples of such networks being widespread both in nature and in technological applications, the interplay between the local and the macroscopic behaviour, through the interconnection topology, is still not completely understood. Moreover, traditional analytical methods for dynamical response analysis fail because of the intrinsically large dimension of the phase space of the network which makes the general problem intractable. Therefore, in this paper we develop an approach aiming to condense all the information in a compact description based on partial differential equations. By focusing on propagative phenomena, rigorous conditions under which the original network dynamical properties can be successfully analysed within the proposed framework are derived as well. A network of Fitzhugh-Nagumo systems is finally used to illustrate the effectiveness of the proposed method.

Synchronization of Switched Neural Networks With Communication Delays via the Event-Triggered Control.

PubMed

Wen, Shiping; Zeng, Zhigang; Chen, Michael Z Q; Huang, Tingwen

2017-10-01

This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results.

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.

An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures

PubMed Central

Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico

2017-01-01

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions. PMID:29112128

EOS: A project to investigate the design and construction of real-time distributed embedded operating systems

NASA Technical Reports Server (NTRS)

Campbell, R. H.; Essick, R. B.; Grass, J.; Johnston, G.; Kenny, K.; Russo, V.

1986-01-01

The EOS project is investigating the design and construction of a family of real-time distributed embedded operating systems for reliable, distributed aerospace applications. Using the real-time programming techniques developed in co-operation with NASA in earlier research, the project staff is building a kernel for a multiple processor networked system. The first six months of the grant included a study of scheduling in an object-oriented system, the design philosophy of the kernel, and the architectural overview of the operating system. In this report, the operating system and kernel concepts are described. An environment for the experiments has been built and several of the key concepts of the system have been prototyped. The kernel and operating system is intended to support future experimental studies in multiprocessing, load-balancing, routing, software fault-tolerance, distributed data base design, and real-time processing.

Optimizing the switching time for 400 kV SF6 circuit breakers

NASA Astrophysics Data System (ADS)

Ciulica, D.

2018-01-01

This paper presents real-time voltage and current analysis for optimizing the wave switching point of the circuit breaker SF6. Circuit Breaker plays an important role in power systems. It provides protection for equipment in embedded stations in transport networks. SF6 Circuit Breaker is very important equipment in Power Systems, which is used for up to 400 kV due to its excellent performance. The controlled switching is used to eliminate transient modes and electrodynamic and dielectric charges in the network at manual switching of capacitor, shunt reactors and power transformers. These effects reduce the reliability and lifetime of the equipment installed on the network, or may lead to erroneous protection.

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.

Hidden Markov models and neural networks for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic

1994-01-01

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.

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

The portals 4.0.1 network programming interface.

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

Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin

2013-04-01

This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandias Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generationmore » of machines employing advanced network interface architectures that support enhanced offload capabilities. 3« less

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.

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.

Framework and Method for Controlling a Robotic System Using a Distributed Computer Network

NASA Technical Reports Server (NTRS)

Sanders, Adam M. (Inventor); Strawser, Philip A. (Inventor); Barajas, Leandro G. (Inventor); Permenter, Frank Noble (Inventor)

2015-01-01

A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.

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

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.

Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

PubMed

Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S

2016-01-01

Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.

Transition in Gas Turbine Control System Architecture: Modular, Distributed, and Embedded

NASA Technical Reports Server (NTRS)

Culley, Dennis

2010-01-01

Controls systems are an increasingly important component of turbine-engine system technology. However, as engines become more capable, the control system itself becomes ever more constrained by the inherent environmental conditions of the engine; a relationship forced by the continued reliance on commercial electronics technology. A revolutionary change in the architecture of turbine-engine control systems will change this paradigm and result in fully distributed engine control systems. Initially, the revolution will begin with the physical decoupling of the control law processor from the hostile engine environment using a digital communications network and engine-mounted high temperature electronics requiring little or no thermal control. The vision for the evolution of distributed control capability from this initial implementation to fully distributed and embedded control is described in a roadmap and implementation plan. The development of this plan is the result of discussions with government and industry stakeholders

The CAN Microcluster: Parallel Processing over the Controller Area Network

ERIC Educational Resources Information Center

Kuban, Paul A.; Ragade, Rammohan K.

2005-01-01

Most electrical engineering and computer science undergraduate programs include at least one course on microcontrollers and assembly language programming. Some departments offer legacy courses in C programming, but few include C programming from an embedded systems perspective, where it is still regularly used. Distributed computing and parallel…

Large Scale IR Evaluation

ERIC Educational Resources Information Center

Pavlu, Virgil

2008-01-01

Today, search engines are embedded into all aspects of digital world: in addition to Internet search, all operating systems have integrated search engines that respond even as you type, even over the network, even on cell phones; therefore the importance of their efficacy and efficiency cannot be overstated. There are many open possibilities for…

Data and Time Transfer Using SONET Radio

NASA Technical Reports Server (NTRS)

Graceffo, Gary M.

1996-01-01

The need for precise knowledge of time and frequency has become ubiquitous throughout our society. The areas of astronomy, navigation, and high speed wide-area networks are among a few of the many consumers of this type of information. The Global Positioning System (GPS) has the potential to be the most comprehensive source of precise timing information developed to date; however, the introduction of selective availability has made it difficult for many users to recover this information from the GPS system with the precision required for today's systems. The system described in this paper is a 'Synchronous Optical NetWORK (SONET) Radio Data and Time Transfer System'. The objective of this system is to provide precise time and frequency information to a variety of end-users using a two-way data and time-transfer system. Although time and frequency transfers have been done for many years, this system is unique in that time and frequency information are embedded into existing communications traffic. This eliminates the need to make the transfer of time and frequency informatio a dedicated function of the communications system. For this system SONET has been selected as the transport format from which precise time is derived. SONET has been selected because of its high data rates and its increasing acceptance throughout the industry. This paper details a proof-of-concept initiative to perform embedded time and frequency transfers using SONET Radio.

Systems biology-embedded target validation: improving efficacy in drug discovery.

PubMed

Vandamme, Drieke; Minke, Benedikt A; Fitzmaurice, William; Kholodenko, Boris N; Kolch, Walter

2014-01-01

The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment. © 2013 Wiley Periodicals, Inc.

Design of UAV-Embedded Microphone Array System for Sound Source Localization in Outdoor Environments †

PubMed Central

Hoshiba, Kotaro; Washizaki, Kai; Wakabayashi, Mizuho; Ishiki, Takahiro; Bando, Yoshiaki; Gabriel, Daniel; Nakadai, Kazuhiro; Okuno, Hiroshi G.

2017-01-01

In search and rescue activities, unmanned aerial vehicles (UAV) should exploit sound information to compensate for poor visual information. This paper describes the design and implementation of a UAV-embedded microphone array system for sound source localization in outdoor environments. Four critical development problems included water-resistance of the microphone array, efficiency in assembling, reliability of wireless communication, and sufficiency of visualization tools for operators. To solve these problems, we developed a spherical microphone array system (SMAS) consisting of a microphone array, a stable wireless network communication system, and intuitive visualization tools. The performance of SMAS was evaluated with simulated data and a demonstration in the field. Results confirmed that the SMAS provides highly accurate localization, water resistance, prompt assembly, stable wireless communication, and intuitive information for observers and operators. PMID:29099790

Design of UAV-Embedded Microphone Array System for Sound Source Localization in Outdoor Environments.

PubMed

Hoshiba, Kotaro; Washizaki, Kai; Wakabayashi, Mizuho; Ishiki, Takahiro; Kumon, Makoto; Bando, Yoshiaki; Gabriel, Daniel; Nakadai, Kazuhiro; Okuno, Hiroshi G

2017-11-03

In search and rescue activities, unmanned aerial vehicles (UAV) should exploit sound information to compensate for poor visual information. This paper describes the design and implementation of a UAV-embedded microphone array system for sound source localization in outdoor environments. Four critical development problems included water-resistance of the microphone array, efficiency in assembling, reliability of wireless communication, and sufficiency of visualization tools for operators. To solve these problems, we developed a spherical microphone array system (SMAS) consisting of a microphone array, a stable wireless network communication system, and intuitive visualization tools. The performance of SMAS was evaluated with simulated data and a demonstration in the field. Results confirmed that the SMAS provides highly accurate localization, water resistance, prompt assembly, stable wireless communication, and intuitive information for observers and operators.

Reframing coalitions as systems interventions: a network study exploring the contribution of a youth violence prevention coalition to broader system capacity.

PubMed

Bess, Kimberly D

2015-06-01

This longitudinal research conceptualizes community coalitions as events in local intervention systems (Hawe et al. in Am J Commun Psychol 43(3-4):267-276, 2009). It explores the potential contribution coalitions make, through the collaborative activities of their members, to the broader intervention systems in which they are embedded. Using social network analysis, it examines patterns of structural change in a network of 99 organizations focused on youth violence prevention (YVP) over a 5-year period in which 30 of the 99 organizations were involved in a local YVP Coalition. Both longitudinal modeling and cross sectional analyses are used to examine change in system capacity-strong interorganizational networks-related to patterns of network density, centralization, and hierarchy. Somewhat surprisingly, the study found that capacity in the broader YVP Intervention System actually diminished during the 5-year period of the coalition's operation, though part of the system-the sub-network that made up the YVP Coalition-was marginally strengthened. In this case, therefore, the evidence suggests that power and relational resources in the broader YVP Intervention System were redistributed. The article explores how the definition of capacity related to density and hierarchy may be contextually dependent. Implications for the role of coalitions in building system capacity are discussed.

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.

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.

[Advances in sensor node and wireless communication technology of body sensor network].

PubMed

Lin, Weibing; Lei, Sheng; Wei, Caihong; Li, Chunxiang; Wang, Cang

2012-06-01

With the development of the wireless communication technology, implantable biosensor technology, and embedded system technology, Body Sensor Network (BSN) as one branch of wireless sensor networks and important part of the Internet of things has caught more attention of researchers and enterprises. This paper offers the basic concept of the BSN and analyses the related research. We focus on sensor node and wireless communication technology from perspectives of technology challenges, research advance and development trend in the paper. Besides, we also present a relative overview of domestic and overseas projects for the BSN.

Investigating System Dependability Modeling Using AADL

NASA Technical Reports Server (NTRS)

Hall, Brendan; Driscoll, Kevin R.; Madl, Gabor

2013-01-01

This report describes Architecture Analysis & Design Language (AADL) models for a diverse set of fault-tolerant, embedded data networks and describes the methods and tools used to created these models. It also includes error models per the AADL Error Annex. Some networks were modeled using Error Detection Isolation Containment Types (EDICT). This report gives a brief description for each of the networks, a description of its modeling, the model itself, and evaluations of the tools used for creating the models. The methodology includes a naming convention that supports a systematic way to enumerate all of the potential failure modes.

NSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner spheres

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

Ortiz-Rodriguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.

In this work a neutron spectrum unfolding code, based on artificial intelligence technology is presented. The code called ''Neutron Spectrometry and Dosimetry with Artificial Neural Networks and two Bonner spheres'', (NSDann2BS), was designed in a graphical user interface under the LabVIEW programming environment. The main features of this code are to use an embedded artificial neural network architecture optimized with the ''Robust design of artificial neural networks methodology'' and to use two Bonner spheres as the only piece of information. In order to build the code here presented, once the net topology was optimized and properly trained, knowledge stored atmore » synaptic weights was extracted and using a graphical framework build on the LabVIEW programming environment, the NSDann2BS code was designed. This code is friendly, intuitive and easy to use for the end user. The code is freely available upon request to authors. To demonstrate the use of the neural net embedded in the NSDann2BS code, the rate counts of {sup 252}Cf, {sup 241}AmBe and {sup 239}PuBe neutron sources measured with a Bonner spheres system.« less

NSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner spheres

NASA Astrophysics Data System (ADS)

Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

2013-07-01

In this work a neutron spectrum unfolding code, based on artificial intelligence technology is presented. The code called "Neutron Spectrometry and Dosimetry with Artificial Neural Networks and two Bonner spheres", (NSDann2BS), was designed in a graphical user interface under the LabVIEW programming environment. The main features of this code are to use an embedded artificial neural network architecture optimized with the "Robust design of artificial neural networks methodology" and to use two Bonner spheres as the only piece of information. In order to build the code here presented, once the net topology was optimized and properly trained, knowledge stored at synaptic weights was extracted and using a graphical framework build on the LabVIEW programming environment, the NSDann2BS code was designed. This code is friendly, intuitive and easy to use for the end user. The code is freely available upon request to authors. To demonstrate the use of the neural net embedded in the NSDann2BS code, the rate counts of 252Cf, 241AmBe and 239PuBe neutron sources measured with a Bonner spheres system.

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.

Research on a Banknote Printing Wastewater Monitoring System based on Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Li, B. B.; Yuan, Z. F.

2006-10-01

In this paper, a banknote printing wastewater monitoring system based on WSN is presented in line with the system demands and actual condition of the worksite for a banknote printing factory. In Physical Layer, the network node is a nRF9e5-centric embedded instrument, which can realize the multi-function such as data collecting, status monitoring, wireless data transmission and so on. Limited by the computing capability, memory capability, communicating energy and others factors, it is impossible for the node to get every detail information of the network, so the communication protocol on WSN couldn't be very complicated. The competitive-based MACA (Multiple Access with Collision Avoidance) Protocol is introduced in MAC, which can decide the communication process and working mode of the nodes, avoid the collision of data transmission, hidden and exposed station problem of nodes. On networks layer, the routing protocol in charge of the transmitting path of the data, the networks topology structure is arranged based on address assignation. Accompanied with some redundant nodes, the network performances stabile and expandable. The wastewater monitoring system is a tentative practice of WSN theory in engineering. Now, the system has passed test and proved efficiently.

Packetized Video On MAGNET

NASA Astrophysics Data System (ADS)

Lazar, Aurel A.; White, John S.

1987-07-01

Theoretical analysis of integrated local area network model of MAGNET, an integrated network testbed developed at Columbia University, shows that the bandwidth freed up during video and voice calls during periods of little movement in the images and periods of silence in the speech signals could be utilized efficiently for graphics and data transmission. Based on these investigations, an architecture supporting adaptive protocols that are dynamicaly controlled by the requirements of a fluctuating load and changing user environment has been advanced. To further analyze the behavior of the network, a real-time packetized video system has been implemented. This system is embedded in the real-time multimedia workstation EDDY, which integrates video, voice, and data traffic flows. Protocols supporting variable-bandwidth, fixed-quality packetized video transport are described in detail.

Implementation of remote monitoring and managing switches

NASA Astrophysics Data System (ADS)

Leng, Junmin; Fu, Guo

2010-12-01

In order to strengthen the safety performance of the network and provide the big convenience and efficiency for the operator and the manager, the system of remote monitoring and managing switches has been designed and achieved using the advanced network technology and present network resources. The fast speed Internet Protocol Cameras (FS IP Camera) is selected, which has 32-bit RSIC embedded processor and can support a number of protocols. An Optimal image compress algorithm Motion-JPEG is adopted so that high resolution images can be transmitted by narrow network bandwidth. The architecture of the whole monitoring and managing system is designed and implemented according to the current infrastructure of the network and switches. The control and administrative software is projected. The dynamical webpage Java Server Pages (JSP) development platform is utilized in the system. SQL (Structured Query Language) Server database is applied to save and access images information, network messages and users' data. The reliability and security of the system is further strengthened by the access control. The software in the system is made to be cross-platform so that multiple operating systems (UNIX, Linux and Windows operating systems) are supported. The application of the system can greatly reduce manpower cost, and can quickly find and solve problems.

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.

The Blurring of Lines Between Combatants and Civilians in Twenty-First Century Armed Conflict

DTIC Science & Technology

2013-03-28

concern for retirement, pensions , placement, or medical care. Speed, technical expertise, continuity, and flexibility are advantages gained by using...including the Internet, telecommunications networks, computer systems , and embedded processors and controllers.”42 Cyberspace and the technologies that... systems . Additionally, the Department of Defense relies heavily on its National Security Agency to defend the United States from attacks against its

Gamma motes for detection of radioactive materials in shipping containers

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

Harold McHugh; William Quam; Stephan Weeks

Shipping containers can be effectively monitored for radiological materials using gamma (and neutron) motes in distributed mesh networks. The mote platform is ideal for collecting data for integration into operational management systems required for efficiently and transparently monitoring international trade. Significant reductions in size and power requirements have been achieved for room-temperature cadmium zinc telluride (CZT) gamma detectors. Miniaturization of radio modules and microcontroller units are paving the way for low-power, deeply-embedded, wireless sensor distributed mesh networks.

Overlapping community detection in weighted networks via a Bayesian approach

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Xiang, Xin; Tang, Buzhou; Chen, Qingcai; Fan, Shixi; Bu, Junzhao

2017-02-01

Complex networks as a powerful way to represent complex systems have been widely studied during the past several years. One of the most important tasks of complex network analysis is to detect communities embedded in networks. In the real world, weighted networks are very common and may contain overlapping communities where a node is allowed to belong to multiple communities. In this paper, we propose a novel Bayesian approach, called the Bayesian mixture network (BMN) model, to detect overlapping communities in weighted networks. The advantages of our method are (i) providing soft-partition solutions in weighted networks; (ii) providing soft memberships, which quantify 'how strongly' a node belongs to a community. Experiments on a large number of real and synthetic networks show that our model has the ability in detecting overlapping communities in weighted networks and is competitive with other state-of-the-art models at shedding light on community partition.

Implementation of medical monitor system based on networks

NASA Astrophysics Data System (ADS)

Yu, Hui; Cao, Yuzhen; Zhang, Lixin; Ding, Mingshi

2006-11-01

In this paper, the development trend of medical monitor system is analyzed and portable trend and network function become more and more popular among all kinds of medical monitor devices. The architecture of medical network monitor system solution is provided and design and implementation details of medical monitor terminal, monitor center software, distributed medical database and two kind of medical information terminal are especially discussed. Rabbit3000 system is used in medical monitor terminal to implement security administration of data transfer on network, human-machine interface, power management and DSP interface while DSP chip TMS5402 is used in signal analysis and data compression. Distributed medical database is designed for hospital center according to DICOM information model and HL7 standard. Pocket medical information terminal based on ARM9 embedded platform is also developed to interactive with center database on networks. Two kernels based on WINCE are customized and corresponding terminal software are developed for nurse's routine care and doctor's auxiliary diagnosis. Now invention patent of the monitor terminal is approved and manufacture and clinic test plans are scheduled. Applications for invention patent are also arranged for two medical information terminals.

Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera

NASA Astrophysics Data System (ADS)

Dziri, Aziz; Duranton, Marc; Chapuis, Roland

2016-07-01

Multiple-object tracking constitutes a major step in several computer vision applications, such as surveillance, advanced driver assistance systems, and automatic traffic monitoring. Because of the number of cameras used to cover a large area, these applications are constrained by the cost of each node, the power consumption, the robustness of the tracking, the processing time, and the ease of deployment of the system. To meet these challenges, the use of low-power and low-cost embedded vision platforms to achieve reliable tracking becomes essential in networks of cameras. We propose a tracking pipeline that is designed for fixed smart cameras and which can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on a low-cost embedded smart camera composed of a Raspberry-Pi board and a RaspiCam camera. The tracking quality and the processing speed obtained with the proposed pipeline are evaluated on publicly available datasets and compared to the state-of-the-art methods.

Long-range wireless mesh network for weather monitoring in unfriendly geographic conditions.

PubMed

Toledano-Ayala, Manuel; Herrera-Ruiz, Gilberto; Soto-Zarazúa, Genaro M; Rivas-Araiza, Edgar A; Bazán Trujillo, Rey D; Porrás-Trejo, Rafael E

2011-01-01

In this paper a long-range wireless mesh network system is presented. It consists of three main parts: Remote Terminal Units (RTUs), Base Terminal Units (BTUs) and a Central Server (CS). The RTUs share a wireless network transmitting in the industrial, scientific and medical applications ISM band, which reaches up to 64 Km in a single point-to-point communication. A BTU controls the traffic within the network and has as its main task interconnecting it to a Ku-band satellite link using an embedded microcontroller-based gateway. Collected data is stored in a CS and presented to the final user in a numerical and a graphical form in a web portal.

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Embedded Streaming Deep Neural Networks Accelerator With Applications.

PubMed

Dundar, Aysegul; Jin, Jonghoon; Martini, Berin; Culurciello, Eugenio

2017-07-01

Deep convolutional neural networks (DCNNs) have become a very powerful tool in visual perception. DCNNs have applications in autonomous robots, security systems, mobile phones, and automobiles, where high throughput of the feedforward evaluation phase and power efficiency are important. Because of this increased usage, many field-programmable gate array (FPGA)-based accelerators have been proposed. In this paper, we present an optimized streaming method for DCNNs' hardware accelerator on an embedded platform. The streaming method acts as a compiler, transforming a high-level representation of DCNNs into operation codes to execute applications in a hardware accelerator. The proposed method utilizes maximum computational resources available based on a novel-scheduled routing topology that combines data reuse and data concatenation. It is tested with a hardware accelerator implemented on the Xilinx Kintex-7 XC7K325T FPGA. The system fully explores weight-level and node-level parallelizations of DCNNs and achieves a peak performance of 247 G-ops while consuming less than 4 W of power. We test our system with applications on object classification and object detection in real-world scenarios. Our results indicate high-performance efficiency, outperforming all other presented platforms while running these applications.

Complex networks as an emerging property of hierarchical preferential attachment.

PubMed

Hébert-Dufresne, Laurent; Laurence, Edward; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J

2015-12-01

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

Complex networks as an emerging property of hierarchical preferential attachment

NASA Astrophysics Data System (ADS)

Hébert-Dufresne, Laurent; Laurence, Edward; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

2015-12-01

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

Toward an embedded training tool for Deep Space Network operations

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.; Sturdevant, Kathryn F.; Johnson, W. L.

1993-01-01

There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor. The cognitive model was developed in Soar for the DSN's Link Monitor and Control (LMC) system; it led to several insights about learning in the task domain that were used to design an intelligent tutor called REACT that implements a method called 'impasse-driven tutoring'. REACT is one component of the LMC training system, which also includes a communications link simulator and a graphical user interface. A pilot study of the LMC training system indicates that REACT shows promise as an effective way for helping operators to quickly acquire expert skills.

Using Neural Networks in Decision Making for a Reconfigurable Electro Mechanical Actuator (EMA)

NASA Technical Reports Server (NTRS)

Latino, Carl D.

2001-01-01

The objectives of this project were to demonstrate applicability and advantages of a neural network approach for evaluating the performance of an electro-mechanical actuator (EMA). The EMA in question was intended for the X-37 Advanced Technology Vehicle. It will have redundant components for safety and reliability. The neural networks for this application are to monitor the operation of the redundant electronics that control the actuator in real time and decide on the operating configuration. The system we proposed consists of the actuator, sensors, control circuitry and dedicated (embedded) processors. The main purpose of the study was to develop suitable hardware and neural network capable of allowing real time reconfiguration decisions to be made. This approach was to be compared to other methods such as fuzzy logic and knowledge based systems considered for the same application. Over the course of the project a more general objective was the identification of the other neural network applications and the education of interested NASA personnel on the topic of Neural Networks.

Development of an embedded thin-film strain-gauge-based SHM network into 3D-woven composite structure for wind turbine blades

NASA Astrophysics Data System (ADS)

Zhao, Dongning; Rasool, Shafqat; Forde, Micheal; Weafer, Bryan; Archer, Edward; McIlhagger, Alistair; McLaughlin, James

2017-04-01

Recently, there has been increasing demand in developing low-cost, effective structure health monitoring system to be embedded into 3D-woven composite wind turbine blades to determine structural integrity and presence of defects. With measuring the strain and temperature inside composites at both in-situ blade resin curing and in-service stages, we are developing a novel scheme to embed a resistive-strain-based thin-metal-film sensory into the blade spar-cap that is made of composite laminates to determine structural integrity and presence of defects. Thus, with fiberglass, epoxy, and a thinmetal- film sensing element, a three-part, low-cost, smart composite laminate is developed. Embedded strain sensory inside composite laminate prototype survived after laminate curing process. The internal strain reading from embedded strain sensor under three-point-bending test standard is comparable. It proves that our proposed method will provide another SHM alternative to reduce sensing costs during the renewable green energy generation.

In vivo wireless biodiagnosis system for long-term bioactivity monitoring network

NASA Astrophysics Data System (ADS)

Chen, Chun-Kuang; Wu, Wen-Jong; Yu, Shih-An; Huang, Jhen-Gang; Lin, Yun-Han; Chen, Yih-Fan; Jin, Ming-Hui; Wen, Chih-Min; Kao, Cheng-Yan; Lin, Shi-Ming; Lu, Shey-Shi; Lin, Chii-Wann; Yen, Jia-Yush; Jaw, Fu-Shan; Chen, Chi-An; Liao, Fang-Jen; Chiu, Nan-Fu; Chien, Chia-Nan; Lee, Chih-Kung

2004-07-01

Attempts to develop a Wireless Health Advanced Mobile Bio-diagnostic System (abbreviated as WHAM-BioS) have arisen from the need to monitor the health status of patients under long-term care programs. The proposed WHAM-BioS as presented here was developed by integrating various technologies: nano/MEMS technology, biotechnology, network/communication technology, and information technology. The biochips proposed not only detect certain diseases but will also report any abnormal status readings on the patient to the medical personnel immediately through the network system. Since long-term home care is typically involved, the parameters monitored must be analyzed and traced continuously over a long period of time. To minimize the intrusion to the patients, a wireless sensor embedded within a wireless network is highly recommended. To facilitate the widest possible use of various biochips, a smart sensor node concept was implemented. More specifically, various technologies and components such as built-in micro power generators, energy storage devices, initialization processes, no-waste bio-detection methodologies, embedded controllers, wireless warning signal transmissions, and power/data management were merged and integrated to create this novel technology. The design methodologies and the implementation schemes are detailed. Potential expansions of this newly developed technology to other applications regimes will be presented as well.

Analysis and logical modeling of biological signaling transduction networks

NASA Astrophysics Data System (ADS)

Sun, Zhongyao

The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

Enhancing Research in Networking & System Security, and Forensics, in Puerto Rico

DTIC Science & Technology

2015-03-03

Researcher and her research revolves around using Cognitive Systems, which are machines that can think, listen and see in order to help the disabled ...Subsequence. The implementation is been conducted using R- Language because of its statistical and analysis abilities. Because it works using a command line...Technology. 14-AUG-13, . : , Eduardo Melendez. FROM RANDOM EMBEDDING TECHNIQUES TO ENTROPY USING IMAGEPOINT ADJACENT SHADE VALUES, 12th Annual

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,"…

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.

Development and Implementation of Production Area of Agricultural Product Data Collection System Based on Embedded System

NASA Astrophysics Data System (ADS)

Xi, Lei; Guo, Wei; Che, Yinchao; Zhang, Hao; Wang, Qiang; Ma, Xinming

To solve problems in detecting the origin of agricultural products, this paper brings about an embedded data-based terminal, applies middleware thinking, and provides reusable long-range two-way data exchange module between business equipment and data acquisition systems. The system is constructed by data collection node and data center nodes. Data collection nodes taking embedded data terminal NetBoxII as the core, consisting of data acquisition interface layer, controlling information layer and data exchange layer, completing the data reading of different front-end acquisition equipments, and packing the data TCP to realize the data exchange between data center nodes according to the physical link (GPRS / CDMA / Ethernet). Data center node consists of the data exchange layer, the data persistence layer, and the business interface layer, which make the data collecting durable, and provide standardized data for business systems based on mapping relationship of collected data and business data. Relying on public communications networks, application of the system could establish the road of flow of information between the scene of origin certification and management center, and could realize the real-time collection, storage and processing between data of origin certification scene and databases of certification organization, and could achieve needs of long-range detection of agricultural origin.

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

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.

ISLE: Intelligent Selection of Loop Electronics. A CLIPS/C++/INGRES integrated application

NASA Technical Reports Server (NTRS)

Fischer, Lynn; Cary, Judson; Currie, Andrew

1990-01-01

The Intelligent Selection of Loop Electronics (ISLE) system is an integrated knowledge-based system that is used to configure, evaluate, and rank possible network carrier equipment known as Digital Loop Carrier (DLC), which will be used to meet the demands of forecasted telephone services. Determining the best carrier systems and carrier architectures, while minimizing the cost, meeting corporate policies and addressing area service demands, has become a formidable task. Network planners and engineers use the ISLE system to assist them in this task of selecting and configuring the appropriate loop electronics equipment for future telephone services. The ISLE application is an integrated system consisting of a knowledge base, implemented in CLIPS (a planner application), C++, and an object database created from existing INGRES database information. The embedibility, performance, and portability of CLIPS provided us with a tool with which to capture, clarify, and refine corporate knowledge and distribute this knowledge within a larger functional system to network planners and engineers throughout U S WEST.

A complex systems analysis of stick-slip dynamics of a laboratory fault

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

Walker, David M.; Tordesillas, Antoinette, E-mail: atordesi@unimelb.edu.au; Small, Michael

2014-03-15

We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructedmore » by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.« less

Network structure exploration in networks with node attributes

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Bu, Junzhao; Tang, Buzhou; Xiang, Xin

2016-05-01

Complex networks provide a powerful way to represent complex systems and have been widely studied during the past several years. One of the most important tasks of network analysis is to detect structures (also called structural regularities) embedded in networks by determining group number and group partition. Most of network structure exploration models only consider network links. However, in real world networks, nodes may have attributes that are useful for network structure exploration. In this paper, we propose a novel Bayesian nonparametric (BNP) model to explore structural regularities in networks with node attributes, called Bayesian nonparametric attribute (BNPA) model. This model does not only take full advantage of both links between nodes and node attributes for group partition via shared hidden variables, but also determine group number automatically via the Bayesian nonparametric theory. Experiments conducted on a number of real and synthetic networks show that our BNPA model is able to automatically explore structural regularities in networks with node attributes and is competitive with other state-of-the-art models.

Spatial networks

NASA Astrophysics Data System (ADS)

Barthélemy, Marc

2011-02-01

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

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.

On the origins of hierarchy in complex networks

PubMed Central

Corominas-Murtra, Bernat; Goñi, Joaquín; Solé, Ricard V.; Rodríguez-Caso, Carlos

2013-01-01

Hierarchy seems to pervade complexity in both living and artificial systems. Despite its relevance, no general theory that captures all features of hierarchy and its origins has been proposed yet. Here we present a formal approach resulting from the convergence of theoretical morphology and network theory that allows constructing a 3D morphospace of hierarchies and hence comparing the hierarchical organization of ecological, cellular, technological, and social networks. Embedded within large voids in the morphospace of all possible hierarchies, four major groups are identified. Two of them match the expected from random networks with similar connectivity, thus suggesting that nonadaptive factors are at work. Ecological and gene networks define the other two, indicating that their topological order is the result of functional constraints. These results are consistent with an exploration of the morphospace, using in silico evolved networks. PMID:23898177

Identifying and tracking dynamic processes in social networks

NASA Astrophysics Data System (ADS)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

Fiber-Optic Network Architectures for Onboard Avionics Applications Investigated

NASA Technical Reports Server (NTRS)

Nguyen, Hung D.; Ngo, Duc H.

2003-01-01

This project is part of a study within the Advanced Air Transportation Technologies program undertaken at the NASA Glenn Research Center. The main focus of the program is the improvement of air transportation, with particular emphasis on air transportation safety. Current and future advances in digital data communications between an aircraft and the outside world will require high-bandwidth onboard communication networks. Radiofrequency (RF) systems, with their interconnection network based on coaxial cables and waveguides, increase the complexity of communication systems onboard modern civil and military aircraft with respect to weight, power consumption, and safety. In addition, safety and reliability concerns from electromagnetic interference between the RF components embedded in these communication systems exist. A simple, reliable, and lightweight network that is free from the effects of electromagnetic interference and capable of supporting the broadband communications needs of future onboard digital avionics systems cannot be easily implemented using existing coaxial cable-based systems. Fiber-optical communication systems can meet all these challenges of modern avionics applications in an efficient, cost-effective manner. The objective of this project is to present a number of optical network architectures for onboard RF signal distribution. Because of the emergence of a number of digital avionics devices requiring high-bandwidth connectivity, fiber-optic RF networks onboard modern aircraft will play a vital role in ensuring a low-noise, highly reliable RF communication system. Two approaches are being used for network architectures for aircraft onboard fiber-optic distribution systems: a hybrid RF-optical network and an all-optical wavelength division multiplexing (WDM) network.

Service oriented network architecture for control and management of home appliances

NASA Astrophysics Data System (ADS)

Hayakawa, Hiroshi; Koita, Takahiro; Sato, Kenya

2005-12-01

Recent advances in multimedia network systems and mechatronics have led to the development of a new generation of applications that associate the use of various multimedia objects with the behavior of multiple robotic actors. The connection of audio and video devices through high speed multimedia networks is expected to make the system more convenient to use. For example, many home appliances, such as a video camera, a display monitor, a video recorder, an audio system and so on, are being equipped with a communication interface in the near future. Recently some platforms (i.e. UPnP1, HAVi2 and so on) are proposed for constructing home networks; however, there are some issues to be solved to realize various services by connecting different equipment via the pervasive peer-to-peer network. UPnP offers network connectivity of PCs of intelligent home appliances, practically, which means to require a PC in the network to control other devices. Meanwhile, HAVi has been developed for intelligent AV equipments with sophisticated functions using high CPU power and large memory. Considering the targets of home alliances are embedded systems, this situation raises issues of software and hardware complexity, cost, power consumption and so on. In this study, we have proposed and developed the service oriented network architecture for control and management of home appliances, named SONICA (Service Oriented Network Interoperability for Component Adaptation), to address these issues described before.

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.

Two-layer wireless distributed sensor/control network based on RF

NASA Astrophysics Data System (ADS)

Feng, Li; Lin, Yuchi; Zhou, Jingjing; Dong, Guimei; Xia, Guisuo

2006-11-01

A project of embedded Wireless Distributed Sensor/Control Network (WDSCN) based on RF is presented after analyzing the disadvantages of traditional measure and control system. Because of high-cost and complexity, such wireless techniques as Bluetooth and WiFi can't meet the needs of WDSCN. The two-layer WDSCN is designed based on RF technique, which operates in the ISM free frequency channel with low power and high transmission speed. Also the network is low cost, portable and moveable, integrated with the technologies of computer network, sensor, microprocessor and wireless communications. The two-layer network topology is selected in the system; a simple but efficient self-organization net protocol is designed to fit the periodic data collection, event-driven and store-and-forward. Furthermore, adaptive frequency hopping technique is adopted for anti-jamming apparently. The problems about power reduction and synchronization of data in wireless system are solved efficiently. Based on the discussion above, a measure and control network is set up to control such typical instruments and sensors as temperature sensor and signal converter, collect data, and monitor environmental parameters around. This system works well in different rooms. Experiment results show that the system provides an efficient solution to WDSCN through wireless links, with high efficiency, low power, high stability, flexibility and wide working range.

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.

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.

Localizing Tortoise Nests by Neural Networks.

PubMed

Barbuti, Roberto; Chessa, Stefano; Micheli, Alessio; Pucci, Rita

2016-01-01

The goal of this research is to recognize the nest digging activity of tortoises using a device mounted atop the tortoise carapace. The device classifies tortoise movements in order to discriminate between nest digging, and non-digging activity (specifically walking and eating). Accelerometer data was collected from devices attached to the carapace of a number of tortoises during their two-month nesting period. Our system uses an accelerometer and an activity recognition system (ARS) which is modularly structured using an artificial neural network and an output filter. For the purpose of experiment and comparison, and with the aim of minimizing the computational cost, the artificial neural network has been modelled according to three different architectures based on the input delay neural network (IDNN). We show that the ARS can achieve very high accuracy on segments of data sequences, with an extremely small neural network that can be embedded in programmable low power devices. Given that digging is typically a long activity (up to two hours), the application of ARS on data segments can be repeated over time to set up a reliable and efficient system, called Tortoise@, for digging activity recognition.

A flow-control mechanism for distributed systems

NASA Technical Reports Server (NTRS)

Maitan, J.

1991-01-01

A new approach to the rate-based flow control in store-and-forward networks is evaluated. Existing methods display oscillations in the presence of transport delays. The proposed scheme is based on the explicit use of an embedded dynamic model of a store-and-forward buffer in a controller's feedback loop. It is shown that the use of the model eliminates the oscillations caused by the transport delays. The paper presents simulation examples and assesses the applicability of the scheme in the new generation of high-speed photonic networks where transport delays must be considered.

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.

Long-term optical stimulation of channelrhodopsin-expressing neurons to study network plasticity

PubMed Central

Lignani, Gabriele; Ferrea, Enrico; Difato, Francesco; Amarù, Jessica; Ferroni, Eleonora; Lugarà, Eleonora; Espinoza, Stefano; Gainetdinov, Raul R.; Baldelli, Pietro; Benfenati, Fabio

2013-01-01

Neuronal plasticity produces changes in excitability, synaptic transmission, and network architecture in response to external stimuli. Network adaptation to environmental conditions takes place in time scales ranging from few seconds to days, and modulates the entire network dynamics. To study the network response to defined long-term experimental protocols, we setup a system that combines optical and electrophysiological tools embedded in a cell incubator. Primary hippocampal neurons transduced with lentiviruses expressing channelrhodopsin-2/H134R were subjected to various photostimulation protocols in a time window in the order of days. To monitor the effects of light-induced gating of network activity, stimulated transduced neurons were simultaneously recorded using multi-electrode arrays (MEAs). The developed experimental model allows discerning short-term, long-lasting, and adaptive plasticity responses of the same neuronal network to distinct stimulation frequencies applied over different temporal windows. PMID:23970852

Method and apparatus for eliminating unsuccessful tries in a search tree

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Chow, Edward (Inventor); Madan, Herb S. (Inventor)

1991-01-01

A circuit switching system in an M-ary, n-cube connected network completes a best-first path from an originating node to a destination node by latching valid legs of the path as the path is being sought out. Each network node is provided with a routing hyperswitch sub-network, (HSN) connected between that node and bidirectional high capacity communication channels of the n-cube network. The sub-networks are all controlled by routing algorithms which respond to message identification headings (headers) on messages to be routed along one or more routing legs. The header includes information embedded therein which is interpreted by each sub-network to route and historically update the header. A logic circuit, available at every node, implements the algorithm and automatically forwards or back-tracks the header in the network legs of various paths until a completed path is latched.

Long-term optical stimulation of channelrhodopsin-expressing neurons to study network plasticity.

PubMed

Lignani, Gabriele; Ferrea, Enrico; Difato, Francesco; Amarù, Jessica; Ferroni, Eleonora; Lugarà, Eleonora; Espinoza, Stefano; Gainetdinov, Raul R; Baldelli, Pietro; Benfenati, Fabio

2013-01-01

Neuronal plasticity produces changes in excitability, synaptic transmission, and network architecture in response to external stimuli. Network adaptation to environmental conditions takes place in time scales ranging from few seconds to days, and modulates the entire network dynamics. To study the network response to defined long-term experimental protocols, we setup a system that combines optical and electrophysiological tools embedded in a cell incubator. Primary hippocampal neurons transduced with lentiviruses expressing channelrhodopsin-2/H134R were subjected to various photostimulation protocols in a time window in the order of days. To monitor the effects of light-induced gating of network activity, stimulated transduced neurons were simultaneously recorded using multi-electrode arrays (MEAs). The developed experimental model allows discerning short-term, long-lasting, and adaptive plasticity responses of the same neuronal network to distinct stimulation frequencies applied over different temporal windows.

Development of network-based multichannel neuromuscular electrical stimulation system for stroke rehabilitation.

PubMed

Qu, Hongen; Xie, Yongji; Liu, Xiaoxuan; He, Xin; Hao, Manzhao; Bao, Yong; Xie, Qing; Lan, Ning

2016-01-01

Neuromuscular electrical stimulation (NMES) is a promising assistive technology for stroke rehabilitation. Here we present the design and development of a multimuscle stimulation system as an emerging therapy for people with paretic stroke. A network-based multichannel NMES system was integrated based on dual bus architecture of communication and an H-bridge current regulator with a power booster. The structure of the system was a body area network embedded with multiple stimulators and a communication protocol of controlled area network to transmit muscle stimulation parameter information to individual stimulators. A graphical user interface was designed to allow clinicians to specify temporal patterns and muscle stimulation parameters. We completed and tested a prototype of the hardware and communication software modules of the multichannel NMES system. The prototype system was first verified in nondisabled subjects for safety, and then tested in subjects with stroke for feasibility with assisting multijoint movements. Results showed that synergistic stimulation of multiple muscles in subjects with stroke improved performance of multijoint movements with more natural velocity profiles at elbow and shoulder and reduced acromion excursion due to compensatory trunk rotation. The network-based NMES system may provide an innovative solution that allows more physiological activation of multiple muscles in multijoint task training for patients with stroke.

Integration of communications and tracking data processing simulation for space station

NASA Technical Reports Server (NTRS)

Lacovara, Robert C.

1987-01-01

A simplified model of the communications network for the Communications and Tracking Data Processing System (CTDP) was developed. It was simulated by use of programs running on several on-site computers. These programs communicate with one another by means of both local area networks and direct serial connections. The domain of the model and its simulation is from Orbital Replaceable Unit (ORU) interface to Data Management Systems (DMS). The simulation was designed to allow status queries from remote entities across the DMS networks to be propagated through the model to several simulated ORU's. The ORU response is then propagated back to the remote entity which originated the request. Response times at the various levels were investigated in a multi-tasking, multi-user operating system environment. Results indicate that the effective bandwidth of the system may be too low to support expected data volume requirements under conventional operating systems. Instead, some form of embedded process control program may be required on the node computers.

Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks.

PubMed

Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

2016-01-04

Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks' activities in an uninterrupted and efficient manner.

Preprogramming Complex Hydrogel Responses using Enzymatic Reaction Networks.

PubMed

Postma, Sjoerd G J; Vialshin, Ilia N; Gerritsen, Casper Y; Bao, Min; Huck, Wilhelm T S

2017-02-06

The creation of adaptive matter is heavily inspired by biological systems. However, it remains challenging to design complex material responses that are governed by reaction networks, which lie at the heart of cellular complexity. The main reason for this slow progress is the lack of a general strategy to integrate reaction networks with materials. Herein we use a systematic approach to preprogram the response of a hydrogel to a trigger, in this case the enzyme trypsin, which activates a reaction network embedded within the hydrogel. A full characterization of all the kinetic rate constants in the system enabled the construction of a computational model, which predicted different hydrogel responses depending on the input concentration of the trigger. The results of the simulation are in good agreement with experimental findings. Our methodology can be used to design new, adaptive materials of which the properties are governed by reaction networks of arbitrary complexity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic effective connectivity in cortically embedded systems of recurrently coupled synfire chains.

PubMed

Trengove, Chris; Diesmann, Markus; van Leeuwen, Cees

2016-02-01

As a candidate mechanism of neural representation, large numbers of synfire chains can efficiently be embedded in a balanced recurrent cortical network model. Here we study a model in which multiple synfire chains of variable strength are randomly coupled together to form a recurrent system. The system can be implemented both as a large-scale network of integrate-and-fire neurons and as a reduced model. The latter has binary-state pools as basic units but is otherwise isomorphic to the large-scale model, and provides an efficient tool for studying its behavior. Both the large-scale system and its reduced counterpart are able to sustain ongoing endogenous activity in the form of synfire waves, the proliferation of which is regulated by negative feedback caused by collateral noise. Within this equilibrium, diverse repertoires of ongoing activity are observed, including meta-stability and multiple steady states. These states arise in concert with an effective connectivity structure (ECS). The ECS admits a family of effective connectivity graphs (ECGs), parametrized by the mean global activity level. Of these graphs, the strongly connected components and their associated out-components account to a large extent for the observed steady states of the system. These results imply a notion of dynamic effective connectivity as governing neural computation with synfire chains, and related forms of cortical circuitry with complex topologies.

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.

Efficient Data Transfer Rate and Speed of Secured Ethernet Interface System.

PubMed

Ghanti, Shaila; Naik, G M

2016-01-01

Embedded systems are extensively used in home automation systems, small office systems, vehicle communication systems, and health service systems. The services provided by these systems are available on the Internet and these services need to be protected. Security features like IP filtering, UDP protection, or TCP protection need to be implemented depending on the specific application used by the device. Every device on the Internet must have network interface. This paper proposes the design of the embedded Secured Ethernet Interface System to protect the service available on the Internet against the SYN flood attack. In this experimental study, Secured Ethernet Interface System is customized to protect the web service against the SYN flood attack. Secured Ethernet Interface System is implemented on ALTERA Stratix IV FPGA as a system on chip and uses the modified SYN flood attack protection method. The experimental results using Secured Ethernet Interface System indicate increase in number of genuine clients getting service from the server, considerable improvement in the data transfer rate, and better response time during the SYN flood attack.

Efficient Data Transfer Rate and Speed of Secured Ethernet Interface System

PubMed Central

Ghanti, Shaila

2016-01-01

Embedded systems are extensively used in home automation systems, small office systems, vehicle communication systems, and health service systems. The services provided by these systems are available on the Internet and these services need to be protected. Security features like IP filtering, UDP protection, or TCP protection need to be implemented depending on the specific application used by the device. Every device on the Internet must have network interface. This paper proposes the design of the embedded Secured Ethernet Interface System to protect the service available on the Internet against the SYN flood attack. In this experimental study, Secured Ethernet Interface System is customized to protect the web service against the SYN flood attack. Secured Ethernet Interface System is implemented on ALTERA Stratix IV FPGA as a system on chip and uses the modified SYN flood attack protection method. The experimental results using Secured Ethernet Interface System indicate increase in number of genuine clients getting service from the server, considerable improvement in the data transfer rate, and better response time during the SYN flood attack. PMID:28116350

Center for Advanced Sensors Year Two Funding (FY2006)

DTIC Science & Technology

2008-02-26

Cheong, and F. Zhao (2005) "Semantics-Based Optimization Across Uncoordinated Tasks in Networked Embedded Systems," Proceedings of the 5th ACM Conference...analysis," Optical Engineering, vol. 46, 116401, 2007. R.L. Espinola, E.L. Jacobs, C.E. Halford, D.H. Tofsted and R. Vollmerhausen, "Modeling...the target acquisition performance of active imaging systems," Optics Express, vol. 15, March, 2007. C.E. Halford, A.L. Robinson, E.L. Jacobs and

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.

Design of fuzzy system by NNs and realization of adaptability

NASA Technical Reports Server (NTRS)

Takagi, Hideyuki

1993-01-01

The issue of designing and tuning fuzzy membership functions by neural networks (NN's) was started by NN-driven Fuzzy Reasoning in 1988. NN-driven fuzzy reasoning involves a NN embedded in the fuzzy system which generates membership values. In conventional fuzzy system design, the membership functions are hand-crafted by trial and error for each input variable. In contrast, NN-driven fuzzy reasoning considers several variables simultaneously and can design a multidimensional, nonlinear membership function for the entire subspace.

A Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies.

PubMed

Geminiani, Alice; Casellato, Claudia; Antonietti, Alberto; D'Angelo, Egidio; Pedrocchi, Alessandra

2018-06-01

The cerebellum plays a crucial role in sensorimotor control and cerebellar disorders compromise adaptation and learning of motor responses. However, the link between alterations at network level and cerebellar dysfunction is still unclear. In principle, this understanding would benefit of the development of an artificial system embedding the salient neuronal and plastic properties of the cerebellum and operating in closed-loop. To this aim, we have exploited a realistic spiking computational model of the cerebellum to analyze the network correlates of cerebellar impairment. The model was modified to reproduce three different damages of the cerebellar cortex: (i) a loss of the main output neurons (Purkinje Cells), (ii) a lesion to the main cerebellar afferents (Mossy Fibers), and (iii) a damage to a major mechanism of synaptic plasticity (Long Term Depression). The modified network models were challenged with an Eye-Blink Classical Conditioning test, a standard learning paradigm used to evaluate cerebellar impairment, in which the outcome was compared to reference results obtained in human or animal experiments. In all cases, the model reproduced the partial and delayed conditioning typical of the pathologies, indicating that an intact cerebellar cortex functionality is required to accelerate learning by transferring acquired information to the cerebellar nuclei. Interestingly, depending on the type of lesion, the redistribution of synaptic plasticity and response timing varied greatly generating specific adaptation patterns. Thus, not only the present work extends the generalization capabilities of the cerebellar spiking model to pathological cases, but also predicts how changes at the neuronal level are distributed across the network, making it usable to infer cerebellar circuit alterations occurring in cerebellar pathologies.

Integrated software health management for aerospace guidance, navigation, and control systems: A probabilistic reasoning approach

NASA Astrophysics Data System (ADS)

Mbaya, Timmy

Embedded Aerospace Systems have to perform safety and mission critical operations in a real-time environment where timing and functional correctness are extremely important. Guidance, Navigation, and Control (GN&C) systems substantially rely on complex software interfacing with hardware in real-time; any faults in software or hardware, or their interaction could result in fatal consequences. Integrated Software Health Management (ISWHM) provides an approach for detection and diagnosis of software failures while the software is in operation. The ISWHM approach is based on probabilistic modeling of software and hardware sensors using a Bayesian network. To meet memory and timing constraints of real-time embedded execution, the Bayesian network is compiled into an Arithmetic Circuit, which is used for on-line monitoring. This type of system monitoring, using an ISWHM, provides automated reasoning capabilities that compute diagnoses in a timely manner when failures occur. This reasoning capability enables time-critical mitigating decisions and relieves the human agent from the time-consuming and arduous task of foraging through a multitude of isolated---and often contradictory---diagnosis data. For the purpose of demonstrating the relevance of ISWHM, modeling and reasoning is performed on a simple simulated aerospace system running on a real-time operating system emulator, the OSEK/Trampoline platform. Models for a small satellite and an F-16 fighter jet GN&C (Guidance, Navigation, and Control) system have been implemented. Analysis of the ISWHM is then performed by injecting faults and analyzing the ISWHM's diagnoses.

Gravity Cues Embedded in the Kinematics of Human Motion Are Detected in Form-from-Motion Areas of the Visual System and in Motor-Related Areas

PubMed Central

Cignetti, Fabien; Chabeauti, Pierre-Yves; Menant, Jasmine; Anton, Jean-Luc J. J.; Schmitz, Christina; Vaugoyeau, Marianne; Assaiante, Christine

2017-01-01

The present study investigated the cortical areas engaged in the perception of graviceptive information embedded in biological motion (BM). To this end, functional magnetic resonance imaging was used to assess the cortical areas active during the observation of human movements performed under normogravity and microgravity (parabolic flight). Movements were defined by motion cues alone using point-light displays. We found that gravity modulated the activation of a restricted set of regions of the network subtending BM perception, including form-from-motion areas of the visual system (kinetic occipital region, lingual gyrus, cuneus) and motor-related areas (primary motor and somatosensory cortices). These findings suggest that compliance of observed movements with normal gravity was carried out by mapping them onto the observer’s motor system and by extracting their overall form from local motion of the moving light points. We propose that judgment on graviceptive information embedded in BM can be established based on motor resonance and visual familiarity mechanisms and not necessarily by accessing the internal model of gravitational motion stored in the vestibular cortex. PMID:28861024

Embedded Volttron specification - benchmarking small footprint compute device for Volttron

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

Sanyal, Jibonananda; Fugate, David L.; Woodworth, Ken

An embedded system is a small footprint computing unit that typically serves a specific purpose closely associated with measurements and control of hardware devices. These units are designed for reasonable durability and operations in a wide range of operating conditions. Some embedded systems support real-time operations and can demonstrate high levels of reliability. Many have failsafe mechanisms built to handle graceful shutdown of the device in exception conditions. The available memory, processing power, and network connectivity of these devices are limited due to the nature of their specific-purpose design and intended application. Industry practice is to carefully design the softwaremore » for the available hardware capability to suit desired deployment needs. Volttron is an open source agent development and deployment platform designed to enable researchers to interact with devices and appliances without having to write drivers themselves. Hosting Volttron on small footprint embeddable devices enables its demonstration for embedded use. This report details the steps required and the experience in setting up and running Volttron applications on three small footprint devices: the Intel Next Unit of Computing (NUC), the Raspberry Pi 2, and the BeagleBone Black. In addition, the report also details preliminary investigation of the execution performance of Volttron on these devices.« less

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

PubMed

Markert, H; Kaufmann, U; Kara Kayikci, Z; Palm, G

2009-03-01

Language understanding is a long-standing problem in computer science. However, the human brain is capable of processing complex languages with seemingly no difficulties. This paper shows a model for language understanding using biologically plausible neural networks composed of associative memories. The model is able to deal with ambiguities on the single word and grammatical level. The language system is embedded into a robot in order to demonstrate the correct semantical understanding of the input sentences by letting the robot perform corresponding actions. For that purpose, a simple neural action planning system has been combined with neural networks for visual object recognition and visual attention control mechanisms.

uFarm: a smart farm management system based on RFID

NASA Astrophysics Data System (ADS)

Kim, Hyoungsuk; Lee, Moonsup; Jung, Jonghyuk; Lee, Hyunwook; Kim, Taehyoun

2007-12-01

Recently, the livestock industry in Korea has been threatened by many challenges such as low productivity due to labor intensiveness, global competition compelled by the Free Trade Agreement (FTA), and emerging animal disease issues such as BSE or foot-and-mouth. In this paper, we propose a smart farm management system, called uFarm, which would come up with such challenges by automating farm management. First, we automate labor-intensive jobs using equipments based on sensors and actuators. The automation subsystem can be controlled by remote user through wireless network. Second, we provide real-time traceability of information on farm animals using the radio-frequency identification (RFID) method and embedded data server with network connectivity.

Image processing for navigation on a mobile embedded platform

NASA Astrophysics Data System (ADS)

Preuss, Thomas; Gentsch, Lars; Rambow, Mark

2006-02-01

Mobile computing devices such as PDAs or cellular phones may act as "Personal Multimedia Exchanges", but they are limited in their processing power as well as in their connectivity. Sensors as well as cellular phones and PDAs are able to gather multimedia data, e. g. images, but leak computing power to process that data on their own. Therefore, it is necessary, that these devices connect to devices with more performance, which provide e.g. image processing services. In this paper, a generic approach is presented that connects different kinds of clients with each other and allows them to interact with more powerful devices. This architecture, called BOSPORUS, represents a communication framework for dynamic peer-to-peer computing. Each peer offers and uses services in this network and communicates loosely coupled and asynchronously with the others. These features make BOSPORUS a service oriented network architecture (SONA). A mobile embedded system, which uses external services for image processing based on the BOSPORUS Framework is shown as an application of the BOSPORUS framework.

Ethernet-based smart networked elements (sensors and actuators)

NASA Astrophysics Data System (ADS)

Mata, Carlos T.; Perotti, José M.; Oostdyk, Rebecca L.; Lucena, Angel

2006-05-01

This paper outlines the present design approach for the Ethernet-Based Smart Networked Elements (SNE) being developed by NASA's Instrumentation Branch and the Advanced Electronics and Technology Development Laboratory of ASRC Aerospace Corporation at Kennedy Space Center (KSC). The SNEs are being developed as part of the Integrated Intelligent Health Management System (IIHMS), jointly developed by Stennis Space Center (SSC), KSC, and Marshall Space Flight Center (MSFC). SNEs are sensors/actuators with embedded intelligence, capable of networking among themselves and with higher-level systems (external processors and controllers) to provide not only instrumentation data but also associated data validity qualifiers. NASA KSC has successfully developed and preliminarily demonstrated this new generation of SNEs. SNEs that collect pressure, strain, and temperature measurements (including cryogenic temperature ranges) have been developed and tested in the laboratory and are ready for demonstration in the field.

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

Face Patch Resting State Networks Link Face Processing to Social Cognition

PubMed Central

Schwiedrzik, Caspar M.; Zarco, Wilbert; Everling, Stefan; Freiwald, Winrich A.

2015-01-01

Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills. PMID:26348613

Adaptive Multi-Sensor Interrogation of Targets Embedded in Complex Environments

DTIC Science & Technology

2010-06-09

to efficient refinement of data from distributed networked sensor systems for interpretation by both machines and humans in a low latency and...of a DP draw: Tk^HIltiU-^). Vk*& Beta{l,a), d’k ~ d" H. (19) where 5g - is a point measure concentrated at 9*k (each 9*k is termed an atom

Organisational Structure and Information Technology (IT): Exploring the Implications of IT for Future Military Structures

DTIC Science & Technology

2006-07-01

4 Abbreviations AI Artificial Intelligence AM Artificial Memory CAD Computer Aided...memory (AM), artificial intelligence (AI), and embedded knowledge systems it is possible to expand the “effective span of competence” of...Technology J Joint J2 Joint Intelligence J3 Joint Operations NATO North Atlantic Treaty Organisation NCW Network Centric Warfare NHS National Health

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.

Simulator of Space Communication Networks

NASA Technical Reports Server (NTRS)

Clare, Loren; Jennings, Esther; Gao, Jay; Segui, John; Kwong, Winston

2005-01-01

Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) is a suite of software tools that simulates the behaviors of communication networks to be used in space exploration, and predict the performance of established and emerging space communication protocols and services. MACHETE consists of four general software systems: (1) a system for kinematic modeling of planetary and spacecraft motions; (2) a system for characterizing the engineering impact on the bandwidth and reliability of deep-space and in-situ communication links; (3) a system for generating traffic loads and modeling of protocol behaviors and state machines; and (4) a system of user-interface for performance metric visualizations. The kinematic-modeling system makes it possible to characterize space link connectivity effects, including occultations and signal losses arising from dynamic slant-range changes and antenna radiation patterns. The link-engineering system also accounts for antenna radiation patterns and other phenomena, including modulations, data rates, coding, noise, and multipath fading. The protocol system utilizes information from the kinematic-modeling and link-engineering systems to simulate operational scenarios of space missions and evaluate overall network performance. In addition, a Communications Effect Server (CES) interface for MACHETE has been developed to facilitate hybrid simulation of space communication networks with actual flight/ground software/hardware embedded in the overall system.

Measurement and Control System Based on Wireless Senor Network for Granary

NASA Astrophysics Data System (ADS)

Song, Jian

A wireless measurement and control system for granary is developed for the sake of overcoming the shortcoming of the wired measurement and control system such as complex wiring and low anti-interference capacity. In this system, Zigbee technology is applied with Zigbee protocol stack development platform by TI, and wireless senor network is used to collect and control the temperature and the humidity. It is composed of the upper PC, central control node based on CC2530, sensor nodes, sensor modules and the executive device. The wireless sensor node is programmed by C language in IAR Embedded Workbench for MCS-51 Evaluation environment. The upper PC control system software is developed based on Visual C++ 6.0 platform. It is shown by experiments that data transmission in the system is accurate and reliable and the error of the temperature and humidity is below 2%, meeting the functional requirements for the granary measurement and control system.

Character-level neural network for biomedical named entity recognition.

PubMed

Gridach, Mourad

2017-06-01

Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance. In this paper, we introduce a novel neural network architecture that benefits from both word- and character-level representations automatically, by using a combination of bidirectional long short-term memory (LSTM) and conditional random field (CRF) eliminating the need for most feature engineering tasks. We evaluate our system on two datasets: JNLPBA corpus and the BioCreAtIvE II Gene Mention (GM) corpus. We obtained state-of-the-art performance by outperforming the previous systems. To the best of our knowledge, we are the first to investigate the combination of deep neural networks, CRF, word embeddings and character-level representation in recognizing biomedical named entities. Copyright © 2017 Elsevier Inc. All rights reserved.

Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

PubMed

Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose

2018-02-22

Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

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

Enabling Dynamic Security Management of Networked Systems via Device-Embedded Security (Self-Securing Devices)

DTIC Science & Technology

2007-01-15

it can detect specifically proscribed content changes to critical files (e.g., illegal shells inserted into /etc/ passwd ). Fourth, it can detect the...UNIX password management involves a pair of inter-related files (/etc/ passwd and /etc/shadow). The corresponding access patterns seen at the storage...content integrity verification is utilized. As a concrete example, consider a UNIX system password file (/etc/ passwd ), which consists of a set of well

Formal System Verification for Trustworthy Embedded Systems

DTIC Science & Technology

2011-04-19

microkernel basis. We had previously achieved code- level formal verification of the seL4 microkernel [3]. In the present project, over 12 months with 0.6 FTE...project, we designed and implemented a secure network access device (SAC) on top of the verified seL4 microkernel. The device allows a trusted front...Engelhardt, Rafal Kolan- ski, Michael Norrish, Thomas Sewell, Harvey Tuch, and Simon Winwood. seL4 : Formal verification of an OS kernel. CACM, 53(6):107

Non-invasive system for monitoring of the manufacturing equipment

NASA Astrophysics Data System (ADS)

Mazăre, A. G.; Belu, N.; Ionescu, L. M.; Rachieru, N.; Misztal, A.

2017-08-01

The automotive industry is one of the most important industries in the world that concerns the economy and the world culture. High demand has resulted in increasing of the pressure on the production lines. In conclusion, it is required more careful in monitoring of the production equipment not only for maintenance but also for staff safety and to increase the quality of production. In this paper, we propose a solution for non-invasive monitoring of the industrial equipment operation by measuring the current consumption on energy supply lines. Thus, it is determined the utilization schedule of the equipment and operation mode. Based on these measurements, it’s built an activity report for that equipment, available to the quality management and maintenance team. The solution consists of the current measuring equipment, with self-harvesting capabilities and radio transceiver, and an embedded system which run a server. The current measuring equipment will transmit data about consumption of each energy supply network line where is placed the industrial equipment. So, we have an internal measuring radio network. The embedded system will collect data for the equipment and put in a local data base and it will provide via an intranet application. The entire system not requires any supplementary energy supply and interventions in the factory infrastructure. It is experimented in a company from the automotive industries.

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

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

Topological networks for quantum communication between distant qubits

NASA Astrophysics Data System (ADS)

Lang, Nicolai; Büchler, Hans Peter

2017-11-01

Efficient communication between qubits relies on robust networks, which allow for fast and coherent transfer of quantum information. It seems natural to harvest the remarkable properties of systems characterized by topological invariants to perform this task. Here, we show that a linear network of coupled bosonic degrees of freedom, characterized by topological bands, can be employed for the efficient exchange of quantum information over large distances. Important features of our setup are that it is robust against quenched disorder, all relevant operations can be performed by global variations of parameters, and the time required for communication between distant qubits approaches linear scaling with their distance. We demonstrate that our concept can be extended to an ensemble of qubits embedded in a two-dimensional network to allow for communication between all of them.

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

A low-power data acquisition system for geomagnetic observatories and variometer stations

NASA Astrophysics Data System (ADS)

Morschhauser, Achim; Haseloff, Jürgen; Bronkalla, Oliver; Müller-Brettschneider, Carsten; Matzka, Jürgen

2017-09-01

A modern geomagnetic observatory must provide data of high stability, continuity, and resolution. The INTERMAGNET network has therefore specified quantitative criteria to ensure a high quality standard of geomagnetic observatories. Here, we present a new data acquisition system which was designed to meet these criteria, in particular with respect to 1 Hz data. This system is based on a Raspberry Pi embedded PC and runs a C+ + data acquisition software. As a result, the data acquisition system is modular, cheap, and flexible, and it can be operated in remote areas with limited power supply. In addition, the system is capable of near-real-time data transmission, using a reverse SSH tunnel to work with any network available. The system hardware was successfully tested at the Niemegk observatory for a period of 1 year and subsequently installed at the Tatuoca observatory in Brazil.

Software for embedded processors: Problems and solutions

NASA Astrophysics Data System (ADS)

Bogaerts, J. A. C.

1990-08-01

Data Acquistion systems in HEP experiments use a wide spectrum of computers to cope with two major problems: high event rates and a large data volume. They do this by using special fast trigger processors at the source to reduce the event rate by several orders of magnitude. The next stage of a data acquisition system consists of a network of fast but conventional microprocessors which are embedded in high speed bus systems where data is still further reduced, filtered and merged. In the final stage complete events are farmed out to a another collection of processors, which reconstruct the events and perhaps achieve a further event rejection by a small factor, prior to recording onto magnetic tape. Detectors are monitored by analyzing a fraction of the data. This may be done for individual detectors at an early state of the data acquisition or it may be delayed till the complete events are available. A network of workstations is used for monitoring, displays and run control. Software for trigger processors must have a simple structure. Rejection algorithms are carefully optimized, and overheads introduced by system software cannot be tolerated. The embedded microprocessors have to co-operate, and need to be synchronized with the preceding and following stages. Real time kernels are typically used to solve synchronization and communication problems. Applications are usually coded in C, which is reasonably efficient and allows direct control over low level hardware functions. Event reconstruction software is very similar or even identical to offline software, predominantly written in FORTRAN. With the advent of powerful RISC processors, and with manufacturers tending to adopt open bus architectures, there is a move towards commercial processors and hence the introduction of the UNIX operating system. Building and controlling such a heterogeneous data acquisition system puts a heavy strain on the software. Communications is now as important as CPU capacity and I/O bandwidth, the traditional key parameters of a HEP data acquisition system. Software engineering and real time system simulation tools are becoming indispensible for the design of future data acquisition systems.

The architecture of the management system of complex steganographic information

NASA Astrophysics Data System (ADS)

Evsutin, O. O.; Meshcheryakov, R. V.; Kozlova, A. S.; Solovyev, T. M.

2017-01-01

The aim of the study is to create a wide area information system that allows one to control processes of generation, embedding, extraction, and detection of steganographic information. In this paper, the following problems are considered: the definition of the system scope and the development of its architecture. For creation of algorithmic maintenance of the system, classic methods of steganography are used to embed information. Methods of mathematical statistics and computational intelligence are used to identify the embedded information. The main result of the paper is the development of the architecture of the management system of complex steganographic information. The suggested architecture utilizes cloud technology in order to provide service using the web-service via the Internet. It is meant to provide streams of multimedia data processing that are streams with many sources of different types. The information system, built in accordance with the proposed architecture, will be used in the following areas: hidden transfer of documents protected by medical secrecy in telemedicine systems; copyright protection of online content in public networks; prevention of information leakage caused by insiders.

Structure and Evolution of Scientific Collaboration Networks in a Modern Research Collaboratory

ERIC Educational Resources Information Center

Pepe, Alberto

2010-01-01

This dissertation is a study of scientific collaboration at the Center for Embedded Networked Sensing (CENS), a modern, multi-disciplinary, distributed laboratory involved in sensor network research. By use of survey research and network analysis, this dissertation examines the collaborative ecology of CENS in terms of three networks of…

Feature-based component model for design of embedded systems

NASA Astrophysics Data System (ADS)

Zha, Xuan Fang; Sriram, Ram D.

2004-11-01

An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

("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…

IEEE 1451.2 based Smart sensor system using ADuc847

NASA Astrophysics Data System (ADS)

Sreejithlal, A.; Ajith, Jose

IEEE 1451 standard defines a standard interface for connecting transducers to microprocessor based data acquisition systems, instrumentation systems, control and field networks. Smart transducer interface module (STIM) acts as a unit which provides signal conditioning, digitization and data packet generation functions to the transducers connected to it. This paper describes the implementation of a microcontroller based smart transducer interface module based on IEEE 1451.2 standard. The module, implemented using ADuc847 microcontroller has 2 transducer channels and is programmed using Embedded C language. The Sensor system consists of a Network Controlled Application Processor (NCAP) module which controls the Smart transducer interface module (STIM) over an IEEE1451.2-RS232 bus. The NCAP module is implemented as a software module in C# language. The hardware details, control principles involved and the software implementation for the STIM are described in detail.

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.

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.

Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks

PubMed Central

Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

2016-01-01

Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks’ activities in an uninterrupted and efficient manner. PMID:26742042

Analysis of structure-function network decoupling in the brain systems of spastic diplegic cerebral palsy.

PubMed

Lee, Dongha; Pae, Chongwon; Lee, Jong Doo; Park, Eun Sook; Cho, Sung-Rae; Um, Min-Hee; Lee, Seung-Koo; Oh, Maeng-Keun; Park, Hae-Jeong

2017-10-01

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The Shale Hills Sensorium for Embedded Sensors, Simulation, & Visualization: A Prototype for Land-Vegetation-Atmosphere Interactions

NASA Astrophysics Data System (ADS)

Duffy, C.

2008-12-01

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, and state-of-the-art visualization deployed and coordinated at a testbed within the Penn State Experimental Forest. The Shale Hills Hydro_Sensorium prototype proposed here is designed to observe land-atmosphere interactions in four-dimensional (space and time). The term Hydro_Sensorium implies the totality of physical sensors, models and visualization tools that allow us to perceive the detailed space and time complexities of the water and energy cycle for a watershed or river basin for all physical states and fluxes (groundwater, soil moisture, temperature, streamflow, latent heat, snowmelt, chemistry, isotopes etc.). This research will ultimately catalyze the study of complex interactions between the land surface, subsurface, biological and atmospheric systems over a broad range of scales. The sensor array would be real-time and fully controllable by remote users for "computational steering" and data fusion. 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. The sensor and simulation system has the following elements: 1) extensive, spatially-distributed, non- invasive, smart sensor networks to gather massive geologic, hydrologic, and geochemical data; 2) stochastic information fusion methods; 3) spatially-explicit multiphysics models/solutions of the land-vegetation- atmosphere system; and 4) asynchronous, parallel/distributed, adaptive algorithms for rapidly simulating the states of a basin at high resolution, 5) signal processing tools for data mining and parameter estimation, and 6) visualization tools. The prototype proposed sensor array and simulation system proposed here will offer a coherent new approach to environmental predictions with a fully integrated observing system design. We expect that the Shale Hills Hydro_Sensorium may provide the needed synthesis of information and conceptualization necessary to advance predictive understanding in complex hydrologic systems.

X-Graphs: Language and Algorithms for Heterogeneous Graph Streams

DTIC Science & Technology

2017-09-01

INTRODUCTION 1 3 METHODS , ASUMPTIONS, AND PROCEDURES 2 Software Abstractions for Graph Analytic Applications 2 High performance Platforms for Graph Processing...data is stored in a distributed file system. 3 METHODS , ASUMPTIONS, AND PROCEDURES Software Abstractions for Graph Analytic Applications To...implementations of novel methods for networks analysis: several methods for detection of overlapping communities, personalized PageRank, node embeddings into a d

Cyberspace and Posse Comitatus: Legal Implications of a Borderless Domain

DTIC Science & Technology

2010-03-01

technology infrastructures, including the Internet , telecommunications networks, computer systems, and embedded processors and controllers.” 9 This...the people, and stopped just short of shutting down economic markets . 2 Though never admitted, all indications point to a coordinated attack from...control orders transit many of the same, generally commercially-owned, routers, switches, computers, and wires, each with the goal of passing information

Real-Time Configuration of Networked Embedded Systems

DTIC Science & Technology

2005-05-01

and inside buildings. Such information is also useful to civilians, as it can be used for personal navigation by campers and hikers, firemen and...traveled, and use direction of movement and distance traveled to generate trajectory points, which are then appropriately displayed. There were...the waist belt is used to detect acceleration of body movement . From the filtered signal, we can approximate the step length by [1] (reference

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

PubMed Central

Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

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.

Analysis and Visualization of Relations in eLearning

NASA Astrophysics Data System (ADS)

Dráždilová, Pavla; Obadi, Gamila; Slaninová, Kateřina; Martinovič, Jan; Snášel, Václav

The popularity of eLearning systems is growing rapidly; this growth is enabled by the consecutive development in Internet and multimedia technologies. Web-based education became wide spread in the past few years. Various types of learning management systems facilitate development of Web-based courses. Users of these courses form social networks through the different activities performed by them. This chapter focuses on searching the latent social networks in eLearning systems data. These data consist of students activity records wherein latent ties among actors are embedded. The social network studied in this chapter is represented by groups of students who have similar contacts and interact in similar social circles. Different methods of data clustering analysis can be applied to these groups, and the findings show the existence of latent ties among the group members. The second part of this chapter focuses on social network visualization. Graphical representation of social network can describe its structure very efficiently. It can enable social network analysts to determine the network degree of connectivity. Analysts can easily determine individuals with a small or large amount of relationships as well as the amount of independent groups in a given network. When applied to the field of eLearning, data visualization simplifies the process of monitoring the study activities of individuals or groups, as well as the planning of educational curriculum, the evaluation of study processes, etc.

Evaluation of the traffic parameters in a metropolitan area by fusing visual perceptions and CNN processing of webcam images.

PubMed

Faro, Alberto; Giordano, Daniela; Spampinato, Concetto

2008-06-01

This paper proposes a traffic monitoring architecture based on a high-speed communication network whose nodes are equipped with fuzzy processors and cellular neural network (CNN) embedded systems. It implements a real-time mobility information system where visual human perceptions sent by people working on the territory and video-sequences of traffic taken from webcams are jointly processed to evaluate the fundamental traffic parameters for every street of a metropolitan area. This paper presents the whole methodology for data collection and analysis and compares the accuracy and the processing time of the proposed soft computing techniques with other existing algorithms. Moreover, this paper discusses when and why it is recommended to fuse the visual perceptions of the traffic with the automated measurements taken from the webcams to compute the maximum traveling time that is likely needed to reach any destination in the traffic network.

Advanced information processing system: Authentication protocols for network communication

NASA Technical Reports Server (NTRS)

Harper, Richard E.; Adams, Stuart J.; Babikyan, Carol A.; Butler, Bryan P.; Clark, Anne L.; Lala, Jaynarayan H.

1994-01-01

In safety critical I/O and intercomputer communication networks, reliable message transmission is an important concern. Difficulties of communication and fault identification in networks arise primarily because the sender of a transmission cannot be identified with certainty, an intermediate node can corrupt a message without certainty of detection, and a babbling node cannot be identified and silenced without lengthy diagnosis and reconfiguration . Authentication protocols use digital signature techniques to verify the authenticity of messages with high probability. Such protocols appear to provide an efficient solution to many of these problems. The objective of this program is to develop, demonstrate, and evaluate intercomputer communication architectures which employ authentication. As a context for the evaluation, the authentication protocol-based communication concept was demonstrated under this program by hosting a real-time flight critical guidance, navigation and control algorithm on a distributed, heterogeneous, mixed redundancy system of workstations and embedded fault-tolerant computers.

Tune the topology to create or destroy patterns

NASA Astrophysics Data System (ADS)

Asllani, Malbor; Carletti, Timoteo; Fanelli, Duccio

2016-12-01

We consider the dynamics of a reaction-diffusion system on a multigraph. The species share the same set of nodes but can access different links to explore the embedding spatial support. By acting on the topology of the networks we can control the ability of the system to self-organise in macroscopic patterns, emerging as a symmetry breaking instability of an homogeneous fixed point. Two different cases study are considered: on the one side, we produce a global modification of the networks, starting from the limiting setting where species are hosted on the same graph. On the other, we consider the effect of inserting just one additional single link to differentiate the two graphs. In both cases, patterns can be generated or destroyed, as follows the imposed, small, topological perturbation. Approximate analytical formulae allow to grasp the essence of the phenomenon and can potentially inspire innovative control strategies to shape the macroscopic dynamics on multigraph networks.

Packetized video on MAGNET

NASA Astrophysics Data System (ADS)

Lazar, Aurel A.; White, John S.

1986-11-01

Theoretical analysis of an ILAN model of MAGNET, an integrated network testbed developed at Columbia University, shows that the bandwidth freed up by video and voice calls during periods of little movement in the images and silence periods in the speech signals could be utilized efficiently for graphics and data transmission. Based on these investigations, an architecture supporting adaptive protocols that are dynamically controlled by the requirements of a fluctuating load and changing user environment has been advanced. To further analyze the behavior of the network, a real-time packetized video system has been implemented. This system is embedded in the real time multimedia workstation EDDY that integrates video, voice and data traffic flows. Protocols supporting variable bandwidth, constant quality packetized video transport are descibed in detail.

Realistic modeling of neurons and networks: towards brain simulation.

PubMed

D'Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

2013-01-01

Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.

Realistic modeling of neurons and networks: towards brain simulation

PubMed Central

D’Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

Summary Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field. PMID:24139652

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.

Loss surface of XOR artificial neural networks

NASA Astrophysics Data System (ADS)

Mehta, Dhagash; Zhao, Xiaojun; Bernal, Edgar A.; Wales, David J.

2018-05-01

Training an artificial neural network involves an optimization process over the landscape defined by the cost (loss) as a function of the network parameters. We explore these landscapes using optimization tools developed for potential energy landscapes in molecular science. The number of local minima and transition states (saddle points of index one), as well as the ratio of transition states to minima, grow rapidly with the number of nodes in the network. There is also a strong dependence on the regularization parameter, with the landscape becoming more convex (fewer minima) as the regularization term increases. We demonstrate that in our formulation, stationary points for networks with Nh hidden nodes, including the minimal network required to fit the XOR data, are also stationary points for networks with Nh+1 hidden nodes when all the weights involving the additional node are zero. Hence, smaller networks trained on XOR data are embedded in the landscapes of larger networks. Our results clarify certain aspects of the classification and sensitivity (to perturbations in the input data) of minima and saddle points for this system, and may provide insight into dropout and network compression.

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

Happenny, Sean F.

The United States’ power infrastructure is aging, underfunded, and vulnerable to cyber attack. Emerging smart grid technologies may take some of the burden off of existing systems and make the grid as a whole more efficient, reliable, and secure. The Pacific Northwest National Laboratory (PNNL) is funding research into several aspects of smart grid technology and grid security, creating a software simulation tool that will allow researchers to test power distribution networks utilizing different smart grid technologies to determine how the grid and these technologies react under different circumstances. Demonstrating security in embedded systems is another research area PNNL ismore » tackling. Many of the systems controlling the U.S. critical infrastructure, such as the power grid, lack integrated security and the networks protecting them are becoming easier to breach. Providing a virtual power substation network to each student team at the National Collegiate Cyber Defense Competition, thereby supporting the education of future cyber security professionals, is another way PNNL is helping to strengthen the security of the nation’s power infrastructure.« less

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.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Multi-physics optimization of three-dimensional microvascular polymeric components

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.; Saksena, Rajat; Kozola, Brian D.; Geubelle, Philippe H.; Christensen, Kenneth T.; White, Scott R.

2013-01-01

This work discusses the computational design of microvascular polymeric materials, which aim at mimicking the behavior found in some living organisms that contain a vascular system. The optimization of the topology of the embedded three-dimensional microvascular network is carried out by coupling a multi-objective constrained genetic algorithm with a finite-element based physics solver, the latter validated through experiments. The optimization is carried out on multiple conflicting objective functions, namely the void volume fraction left by the network, the energy required to drive the fluid through the network and the maximum temperature when the material is subjected to thermal loads. The methodology presented in this work results in a viable alternative for the multi-physics optimization of these materials for active-cooling applications.

Pervasive surveillance-agent system based on wireless sensor networks: design and deployment

NASA Astrophysics Data System (ADS)

Martínez, José F.; Bravo, Sury; García, Ana B.; Corredor, Iván; Familiar, Miguel S.; López, Lourdes; Hernández, Vicente; Da Silva, Antonio

2010-12-01

Nowadays, proliferation of embedded systems is enhancing the possibilities of gathering information by using wireless sensor networks (WSNs). Flexibility and ease of installation make these kinds of pervasive networks suitable for security and surveillance environments. Moreover, the risk for humans to be exposed to these functions is minimized when using these networks. In this paper, a virtual perimeter surveillance agent, which has been designed to detect any person crossing an invisible barrier around a marked perimeter and send an alarm notification to the security staff, is presented. This agent works in a state of 'low power consumption' until there is a crossing on the perimeter. In our approach, the 'intelligence' of the agent has been distributed by using mobile nodes in order to discern the cause of the event of presence. This feature contributes to saving both processing resources and power consumption since the required code that detects presence is the only system installed. The research work described in this paper illustrates our experience in the development of a surveillance system using WNSs for a practical application as well as its evaluation in real-world deployments. This mechanism plays an important role in providing confidence in ensuring safety to our environment.

Polymer-based platform for microfluidic systems

DOEpatents

Benett, William [Livermore, CA; Krulevitch, Peter [Pleasanton, CA; Maghribi, Mariam [Livermore, CA; Hamilton, Julie [Tracy, CA; Rose, Klint [Boston, MA; Wang, Amy W [Oakland, CA

2009-10-13

A method of forming a polymer-based microfluidic system platform using network building blocks selected from a set of interconnectable network building blocks, such as wire, pins, blocks, and interconnects. The selected building blocks are interconnectably assembled and fixedly positioned in precise positions in a mold cavity of a mold frame to construct a three-dimensional model construction of a microfluidic flow path network preferably having meso-scale dimensions. A hardenable liquid, such as poly (dimethylsiloxane) is then introduced into the mold cavity and hardened to form a platform structure as well as to mold the microfluidic flow path network having channels, reservoirs and ports. Pre-fabricated elbows, T's and other joints are used to interconnect various building block elements together. After hardening the liquid the building blocks are removed from the platform structure to make available the channels, cavities and ports within the platform structure. Microdevices may be embedded within the cast polymer-based platform, or bonded to the platform structure subsequent to molding, to create an integrated microfluidic system. In this manner, the new microfluidic platform is versatile and capable of quickly generating prototype systems, and could easily be adapted to a manufacturing setting.

Fields and coupling between coils embedded in conductive environments

NASA Astrophysics Data System (ADS)

Chu, Son; Vallecchi, Andrea; Stevens, Christopher J.; Shamonina, Ekaterina

2018-02-01

An approximate solution is developed for the mutual inductance of two circular coils enclosed by insulating cavities in a conducting medium. This solution is used to investigate the variation of the mutual inductance upon the conductivity of the background (e.g., soil, seawater or human body), as well as upon other parameters such as the vertical of the coils and the displacement of one of the coils in the horizontal plane. Our theoretical results are compared with full wave simulations and a previous solution valid when a conductive slab is inserted between two coupled resonant coils. The proposed approach can have direct impact on the design and optimisation of magnetoinductive waveguides and wireless power transfer for underground/underwater networks and embedded biomedical systems.

Analysis and Application of Microgrids

NASA Astrophysics Data System (ADS)

Yue, Lu

New trends of generating electricity locally and utilizing non-conventional or renewable energy sources have attracted increasing interests due to the gradual depletion of conventional fossil fuel energy sources. The new type of power generation is called Distributed Generation (DG) and the energy sources utilized by Distributed Generation are termed Distributed Energy Sources (DERs). With DGs embedded in the distribution networks, they evolve from passive distribution networks to active distribution networks enabling bidirectional power flows in the networks. Further incorporating flexible and intelligent controllers and employing future technologies, active distribution networks will turn to a Microgrid. A Microgrid is a small-scale, low voltage Combined with Heat and Power (CHP) supply network designed to supply electrical and heat loads for a small community. To further implement Microgrids, a sophisticated Microgrid Management System must be integrated. However, due to the fact that a Microgrid has multiple DERs integrated and is likely to be deregulated, the ability to perform real-time OPF and economic dispatch with fast speed advanced communication network is necessary. In this thesis, first, problems such as, power system modelling, power flow solving and power system optimization, are studied. Then, Distributed Generation and Microgrid are studied and reviewed, including a comprehensive review over current distributed generation technologies and Microgrid Management Systems, etc. Finally, a computer-based AC optimization method which minimizes the total transmission loss and generation cost of a Microgrid is proposed and a wireless communication scheme based on synchronized Code Division Multiple Access (sCDMA) is proposed. The algorithm is tested with a 6-bus power system and a 9-bus power system.

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.

Application of neural based estimation algorithm for gait phases of above knee prosthesis.

PubMed

Tileylioğlu, E; Yilmaz, A

2015-01-01

In this study, two gait phase estimation methods which utilize a rule based quantization and an artificial neural network model respectively are developed and applied for the microcontroller based semi-active knee prosthesis in order to respond user demands and adapt environmental conditions. In this context, an experimental environment in which gait data collected synchronously from both inertial and image based measurement systems has been set up. The inertial measurement system that incorporates MEM accelerometers and gyroscopes is used to perform direct motion measurement through the microcontroller, while the image based measurement system is employed for producing the verification data and assessing the success of the prosthesis. Embedded algorithms dynamically normalize the input data prior to gait phase estimation. The real time analyses of two methods revealed that embedded ANN based approach performs slightly better in comparison with the rule based algorithm and has advantage of being easily-scalable, thus able to accommodate additional input parameters considering the microcontroller constraints.

Institutions, interest groups, and ideology: an agenda for the sociology of health care reform.

PubMed

Quadagno, Jill

2010-06-01

A central sociological premise is that health care systems are organizations that are embedded within larger institutions, which have been shaped by historical precedents and operate within a specific cultural context. Although bound by policy legacies, embedded constituencies, and path dependent processes, health care systems are not rigid, static, and impervious to change. The success of health care reform in 2010 has shown that existing regimes do have the capacity to respond to new needs in ways that transcend their institutional and ideological limits. For the United States the question is how health care reform will reconfigure the existing network of public and private benefits and the power relationships between the numerous constituencies surrounding them. This article considers how institutions, interest groups, and ideology have affected the organization of the health care system in the United States as well as in other nations. It then discusses issues for future research in the aftermath of the 2009-10 health care reform debate.

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.

Analysis and characterization of structurally embedded vascular antennas using liquid metals

NASA Astrophysics Data System (ADS)

Hartl, Darren J.; Huff, Gregory H.; Pan, Hong; Smith, Lisa; Bradford, Robyn L.; Frank, Geoffrey J.; Baur, Jeffrey W.

2016-04-01

Over the past decade, a large body of research associated with the addition of microvascular networks to structural composites has been generated. The engineering goal is most often the extension of structural utility to include extended functionalities such as self-healing or improved thermal management and resilience. More recently, efforts to design reconfigurable embedded electronics via the incorporation of non-toxic liquid metals have been initiated. A wide range of planar antenna configurations are possible, and the trade-offs between structural effects, other system costs, and increased flexibility in transmitting and receiving frequencies are being explored via the structurally embedded vascular antenna (SEVA) concept. This work describes for the first time the design of a bowtie-like tunable liquid metal-based antenna for integration into a structural composite for electromagnetic use. The design of both the solid/fluid feed structure and fluid transmission lines are described and analysis results regarding the RF performance of the antenna are provided. Fabrication methods for the SEVA are explained in detail and as-fabricated components are described. Challenges associated with both fabrication and system implementation and testing are elucidated. Results from preliminary RF testing indicate that in situ response tuning is feasible in these novel multifunctional composites.

Pressurized vascular systems for self-healing materials

PubMed Central

Hamilton, A. R.; Sottos, N. R.; White, S. R.

2012-01-01

An emerging strategy for creating self-healing materials relies on embedded vascular networks of microchannels to transport reactive fluids to regions of damage. Here we investigate the use of active pumping for the pressurized delivery of a two-part healing system, allowing a small vascular system to deliver large volumes of healing agent. Different pumping strategies are explored to improve the mixing and subsequent polymerization of healing agents in the damage zone. Significant improvements in the number of healing cycles and in the overall healing efficiency are achieved compared with prior passive schemes that use only capillary forces for the delivery of healing agents. At the same time, the volume of the vascular system required to achieve this superior healing performance is significantly reduced. In the best case, nearly full recovery of fracture toughness is attained throughout 15 cycles of damage and healing, with a vascular network constituting just 0.1 vol% of the specimen. PMID:21957119

Knowledge-based operation and management of communications systems

NASA Technical Reports Server (NTRS)

Heggestad, Harold M.

1988-01-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Knowledge-based operation and management of communications systems

NASA Astrophysics Data System (ADS)

Heggestad, Harold M.

1988-11-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Design of embedded endoscopic ultrasonic imaging system

NASA Astrophysics Data System (ADS)

Li, Ming; Zhou, Hao; Wen, Shijie; Chen, Xiodong; Yu, Daoyin

2008-12-01

Endoscopic ultrasonic imaging system is an important component in the endoscopic ultrasonography system (EUS). Through the ultrasonic probe, the characteristics of the fault histology features of digestive organs is detected by EUS, and then received by the reception circuit which making up of amplifying, gain compensation, filtering and A/D converter circuit, in the form of ultrasonic echo. Endoscopic ultrasonic imaging system is the back-end processing system of the EUS, with the function of receiving digital ultrasonic echo modulated by the digestive tract wall from the reception circuit, acquiring and showing the fault histology features in the form of image and characteristic data after digital signal processing, such as demodulation, etc. Traditional endoscopic ultrasonic imaging systems are mainly based on image acquisition and processing chips, which connecting to personal computer with USB2.0 circuit, with the faults of expensive, complicated structure, poor portability, and difficult to popularize. To against the shortcomings above, this paper presents the methods of digital signal acquisition and processing specially based on embedded technology with the core hardware structure of ARM and FPGA for substituting the traditional design with USB2.0 and personal computer. With built-in FIFO and dual-buffer, FPGA implement the ping-pong operation of data storage, simultaneously transferring the image data into ARM through the EBI bus by DMA function, which is controlled by ARM to carry out the purpose of high-speed transmission. The ARM system is being chosen to implement the responsibility of image display every time DMA transmission over and actualizing system control with the drivers and applications running on the embedded operating system Windows CE, which could provide a stable, safe and reliable running platform for the embedded device software. Profiting from the excellent graphical user interface (GUI) and good performance of Windows CE, we can not only clearly show 511×511 pixels ultrasonic echo images through application program, but also provide a simple and friendly operating interface with mouse and touch screen which is more convenient than the traditional endoscopic ultrasonic imaging system. Including core and peripheral circuits of FPGA and ARM, power network circuit and LCD display circuit, we designed the whole embedded system, achieving the desired purpose by implementing ultrasonic image display properly after the experimental verification, solving the problem of hugeness and complexity of the traditional endoscopic ultrasonic imaging system.

Citizen ’Cyber’ Airmen: Maintaining Ready and Proficient Cyberspace Operators in the Reserve Components

DTIC Science & Technology

2016-02-01

Internet service providers and global supply chains, over which DOD has no direct authority to mitigate risk effectively. The global technology supply...cyberspace. CO are composed of the military, intelligence, and ordinary business operations of DOD in and through cyberspace. Cyberspace, while a global ...infrastructures, including the Internet , telecommunications networks, computer systems, and embedded processors and controllers, and the content that flows across

Theoretical Perspectives of Terrorist Enemies as Networks

DTIC Science & Technology

2005-10-01

applied to human systems, meaningful and repeatable measurements are extremely difficult (humans and societies are each unique and much that is...defined as- pects. Families can have patriarchs (or matriarchs for that matter) who serve as head of the family. As one individual dies another will...strengthen it. This type of construct does not illustrate how completely terrorist organi- zations are embedded within a larger society , and the importance

A Deep Learning-Based Method for Similar Patient Question Retrieval in Chinese.

PubMed

Tang, Guo Yu; Ni, Yuan; Xie, Guo Tong; Fan, Xin Li; Shi, Yan Ling

2017-01-01

The online patient question and answering (Q&A) system, either as a website or a mobile application, attracts an increasing number of users in China. Patients will post their questions and the registered doctors then provide the corresponding answers. A large amount of questions with answers from doctors are accumulated. Instead of awaiting the response from a doctor, the newly posted question could be quickly answered by finding a semantically equivalent question from the Q&A achive. In this study, we investigated a novel deep learning based method to retrieve the similar patient question in Chinese. An unsupervised learning algorithm using deep neural network is performed on the corpus to generate the word embedding. The word embedding was then used as the input to a supervised learning algorithm using a designed deep neural network, i.e. the supervised neural attention model (SNA), to predict the similarity between two questions. The experimental results showed that our SNA method achieved P@1 = 77% and P@5 = 84%, which outperformed all other compared methods.

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.

Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.

PubMed

Cocos, Anne; Fiks, Alexander G; Masino, Aaron J

2017-07-01

Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Social media includes informal vocabulary and irregular grammar, which challenge natural language processing methods. Our objective is to develop a scalable, deep-learning approach that exceeds state-of-the-art ADR detection performance in social media. We developed a recurrent neural network (RNN) model that labels words in an input sequence with ADR membership tags. The only input features are word-embedding vectors, which can be formed through task-independent pretraining or during ADR detection training. Our best-performing RNN model used pretrained word embeddings created from a large, non-domain-specific Twitter dataset. It achieved an approximate match F-measure of 0.755 for ADR identification on the dataset, compared to 0.631 for a baseline lexicon system and 0.65 for the state-of-the-art conditional random field model. Feature analysis indicated that semantic information in pretrained word embeddings boosted sensitivity and, combined with contextual awareness captured in the RNN, precision. Our model required no task-specific feature engineering, suggesting generalizability to additional sequence-labeling tasks. Learning curve analysis showed that our model reached optimal performance with fewer training examples than the other models. ADR detection performance in social media is significantly improved by using a contextually aware model and word embeddings formed from large, unlabeled datasets. The approach reduces manual data-labeling requirements and is scalable to large social media datasets. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A monitoring system for vegetable greenhouses based on a wireless sensor network.

PubMed

Li, Xiu-hong; Cheng, Xiao; Yan, Ke; Gong, Peng

2010-01-01

A wireless sensor network-based automatic monitoring system is designed for monitoring the life conditions of greenhouse vegetables. The complete system architecture includes a group of sensor nodes, a base station, and an internet data center. For the design of wireless sensor node, the JN5139 micro-processor is adopted as the core component and the Zigbee protocol is used for wireless communication between nodes. With an ARM7 microprocessor and embedded ZKOS operating system, a proprietary gateway node is developed to achieve data influx, screen display, system configuration and GPRS based remote data forwarding. Through a Client/Server mode the management software for remote data center achieves real-time data distribution and time-series analysis. Besides, a GSM-short-message-based interface is developed for sending real-time environmental measurements, and for alarming when a measurement is beyond some pre-defined threshold. The whole system has been tested for over one year and satisfactory results have been observed, which indicate that this system is very useful for greenhouse environment monitoring.

Entropy of network ensembles

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

2009-03-01

In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

Embedding health policy and systems research into decision-making processes in low- and middle-income countries

PubMed Central

2013-01-01

Attention is increasingly directed to bridging the gap between the production of knowledge and its use for health decision-making in low- and middle-income countries (LMICs). An important and underdeveloped area of health policy and systems research (HPSR) is the organization of this process. Drawing from an interdisciplinary conception of embeddedness, a literature review was conducted to identify examples of embedded HPSR used to inform decision-making in LMICs. The results of the literature review were organized according to the World Health Organization’s Building Blocks Framework. Next, a conceptual model was created to illustrate the arrangement of organizations that produce embedded HPSR and the characteristics that facilitate its uptake into the arena of decision-making. We found that multiple forces converge to create context-specific pathways through which evidence enters into decision-making. Depending on the decision under consideration, the literature indicates that decision-makers may call upon an intricate combination of actors for sourcing HPSR. While proximity to decision-making does have advantages, it is not the position of the organization within the network, but rather the qualities the organization possesses, that enable it to be embedded. Our findings suggest that four qualities influence embeddedness: reputation, capacity, quality of connections to decision-makers, and quantity of connections to decision-makers and others. In addition to this, the policy environment (e.g. the presence of legislation governing the use of HPSR, presence of strong civil society, etc.) strongly influences uptake. Through this conceptual model, we can understand which conditions are likely to enhance uptake of HPSR in LMIC health systems. This raises several important considerations for decision-makers and researchers about the arrangement and interaction of evidence-generating organizations in health systems. PMID:23924162

Embedding health policy and systems research into decision-making processes in low- and middle-income countries.

PubMed

Koon, Adam D; Rao, Krishna D; Tran, Nhan T; Ghaffar, Abdul

2013-08-08

Attention is increasingly directed to bridging the gap between the production of knowledge and its use for health decision-making in low- and middle-income countries (LMICs). An important and underdeveloped area of health policy and systems research (HPSR) is the organization of this process. Drawing from an interdisciplinary conception of embeddedness, a literature review was conducted to identify examples of embedded HPSR used to inform decision-making in LMICs. The results of the literature review were organized according to the World Health Organization's Building Blocks Framework. Next, a conceptual model was created to illustrate the arrangement of organizations that produce embedded HPSR and the characteristics that facilitate its uptake into the arena of decision-making. We found that multiple forces converge to create context-specific pathways through which evidence enters into decision-making. Depending on the decision under consideration, the literature indicates that decision-makers may call upon an intricate combination of actors for sourcing HPSR. While proximity to decision-making does have advantages, it is not the position of the organization within the network, but rather the qualities the organization possesses, that enable it to be embedded. Our findings suggest that four qualities influence embeddedness: reputation, capacity, quality of connections to decision-makers, and quantity of connections to decision-makers and others. In addition to this, the policy environment (e.g. the presence of legislation governing the use of HPSR, presence of strong civil society, etc.) strongly influences uptake. Through this conceptual model, we can understand which conditions are likely to enhance uptake of HPSR in LMIC health systems. This raises several important considerations for decision-makers and researchers about the arrangement and interaction of evidence-generating organizations in health systems.

Assuring image authenticity within a data grid using lossless digital signature embedding and a HIPAA-compliant auditing system

NASA Astrophysics Data System (ADS)

Lee, Jasper C.; Ma, Kevin C.; Liu, Brent J.

2008-03-01

A Data Grid for medical images has been developed at the Image Processing and Informatics Laboratory, USC to provide distribution and fault-tolerant storage of medical imaging studies across Internet2 and public domain. Although back-up policies and grid certificates guarantee privacy and authenticity of grid-access-points, there still lacks a method to guarantee the sensitive DICOM images have not been altered or corrupted during transmission across a public domain. This paper takes steps toward achieving full image transfer security within the Data Grid by utilizing DICOM image authentication and a HIPAA-compliant auditing system. The 3-D lossless digital signature embedding procedure involves a private 64 byte signature that is embedded into each original DICOM image volume, whereby on the receiving end the signature can to be extracted and verified following the DICOM transmission. This digital signature method has also been developed at the IPILab. The HIPAA-Compliant Auditing System (H-CAS) is required to monitor embedding and verification events, and allows monitoring of other grid activity as well. The H-CAS system federates the logs of transmission and authentication events at each grid-access-point and stores it into a HIPAA-compliant database. The auditing toolkit is installed at the local grid-access-point and utilizes Syslog [1], a client-server standard for log messaging over an IP network, to send messages to the H-CAS centralized database. By integrating digital image signatures and centralized logging capabilities, DICOM image integrity within the Medical Imaging and Informatics Data Grid can be monitored and guaranteed without loss to any image quality.

Unfree markets: socially embedded informal health providers in northern Karnataka, India.

PubMed

George, Asha; Iyer, Aditi

2013-11-01

The dynamics of informal health markets in marginalised regions are relevant to policy discourse in India, but are poorly understood. We examine how informal health markets operate from the viewpoint of informal providers (those without any government-recognised medical degrees, otherwise known as RMPs) by drawing upon data from a household survey in 2002, a provider census in 2004 and ongoing field observations from a research site in Koppal district, Karnataka, India. We find that despite their illegality, RMPs depend on government and private providers for their training and referral networks. Buffeted by unregulated market pressures, RMPs are driven to provide allopathic commodities regardless of need, but can also be circumspect in their practice. Though motivated by profit, their socially embedded practice at community level at times undermines their ability to ensure payment of fees for their services. In addition, RMPs feel that communities can threaten them via violence or malicious rumours, leading them to seek political favour and social protection from village elites and elected representatives. RMPs operate within negotiated quid pro quo bargains that lead to tenuous reciprocity or fragile trust between them and the communities in which they practise. In the context of this 'unfree' market, some RMPs reported being more embedded in health systems, more responsive to communities and more vulnerable to unregulated market pressures than others. Understanding the heterogeneity, nuanced motivations and the embedded social relations that mark informal providers in the health systems, markets and communities they work in, is critical for health system reforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

The design of multiplayer online video game systems

NASA Astrophysics Data System (ADS)

Hsu, Chia-chun A.; Ling, Jim; Li, Qing; Kuo, C.-C. J.

2003-11-01

The distributed Multiplayer Online Game (MOG) system is complex since it involves technologies in computer graphics, multimedia, artificial intelligence, computer networking, embedded systems, etc. Due to the large scope of this problem, the design of MOG systems has not yet been widely addressed in the literatures. In this paper, we review and analyze the current MOG system architecture followed by evaluation. Furthermore, we propose a clustered-server architecture to provide a scalable solution together with the region oriented allocation strategy. Two key issues, i.e. interesting management and synchronization, are discussed in depth. Some preliminary ideas to deal with the identified problems are described.

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.

Scalable Asset Discovery, Vulnerability Scanning, and Penetration Testing for Remote Sites and Wireless Spectrums Utilizing an Embedded Linux Plug - PwniPlug and the Raspberry Pi B+ as a Sample Pen Test

NASA Technical Reports Server (NTRS)

Ganzy, Ethan G.

2014-01-01

All devices attached to the NASA KSC network are subject to security vulnerability scanning and/or penetration testing. In today's changing environment, vulnerable and/or unprotected systems can easily be overlooked. Systems that are not properly managed can become a potential threat to the operational integrity of our systems and networks. This includes all NASA (internal and external) information systems within NASA KSC Internet Protocol (IP) address space, and NASA KSC facilities. The Office of the Chief Information Officer (OCIO) recommends that all NASA Centers and information systems be subject to penetration testing on a regular interval in accordance with the guidelines identified by the National Institute of Standards and Technology (NIST). (ITS-HBK-2810.04-02A) Protecting information and equipment at NASA is an area of increasing concern. In addition to the CPU's on the network; Supervisory, Control and Data Acquisition (SCADA) systems are especially vulnerable because these systems have lacked standards, use embedded controllers with little computational power and informal software, are connected to physical processes, have few operators, and are increasingly also being connected to corporate networks. The scope of work is comprised of several individual components which together build upon previous work by Drew Branch, NASA KSC Intern. The Pwn Plug is the selected COTS (Commercial-Off-The-Shelf) device chosen to test simplification of mandatory IT Security tasks. The device will be utilized to provide services to NASA KSC and enable an assessment of infrastructure soundness and regulatory compliance in an efficient, economical, and business responsive manner. The Pwn Plug is designed as a pen testing appliance which provides a hardware platform that can support commercial penetration testing efforts at significantly reduced costs. The expected outcomes are: 1) External Penetration Testing, 2) Social Engineering, 3) Procedural Documentation, 4) Recommended Remediation Action Plan, 5) System Retest & Remediation Attestation and 6) Final Reports, out briefing and Presentation. Due to physical and material constraints beyond intern and mentor control, the project was redefined as a working pen-test scenario. Limitations of lab availability and tools dictated an academic exercise. This report was developed within the scenario guidelines suggested by the project mentor. The guidelines were to be creative in developing a Pen Test program for a client.

Assessing the influence of knowledge translation platforms on health system policy processes to achieve the health millennium development goals in Cameroon and Uganda: a comparative case study.

PubMed

Ongolo-Zogo, Pierre; Lavis, John N; Tomson, Goran; Sewankambo, Nelson K

2018-05-01

There is a scarcity of empirical data on the influence of initiatives supporting evidence-informed health system policy-making (EIHSP), such as the knowledge translation platforms (KTPs) operating in Africa. To assess whether and how two KTPs housed in government-affiliated institutions in Cameroon and Uganda have influenced: (1) health system policy-making processes and decisions aiming at supporting achievement of the health millennium development goals (MDGs); and (2) the general climate for EIHSP. We conducted an embedded comparative case study of four policy processes in which Evidence Informed Policy Network (EVIPNet) Cameroon and Regional East African Community Health Policy Initiative (REACH-PI) Uganda were involved between 2009 and 2011. We combined a documentary review and semi structured interviews of 54 stakeholders. A framework-guided thematic analysis, inspired by scholarship in health policy analysis and knowledge utilization was used. EVIPNet Cameroon and REACH-PI Uganda have had direct influence on health system policy decisions. The coproduction of evidence briefs combined with tacit knowledge gathered during inclusive evidence-informed stakeholder dialogues helped to reframe health system problems, unveil sources of conflicts, open grounds for consensus and align viable and affordable options for achieving the health MDGs thus leading to decisions. New policy issue networks have emerged. The KTPs indirectly influenced health policy processes by changing how interests interact with one another and by introducing safe-harbour deliberations and intersected with contextual ideational factors by improving access to policy-relevant evidence. KTPs were perceived as change agents with positive impact on the understanding, acceptance and adoption of EIHSP because of their complementary work in relation to capacity building, rapid evidence syntheses and clearinghouse of policy-relevant evidence. This embedded case study illustrates how two KTPs influenced policy decisions through pathways involving policy issue networks, interest groups interaction and evidence-supported ideas and how they influenced the general climate for EIHSP.

Assessing the influence of knowledge translation platforms on health system policy processes to achieve the health millennium development goals in Cameroon and Uganda: a comparative case study

PubMed Central

Lavis, John N; Tomson, Goran; Sewankambo, Nelson K

2018-01-01

Abstract There is a scarcity of empirical data on the influence of initiatives supporting evidence-informed health system policy-making (EIHSP), such as the knowledge translation platforms (KTPs) operating in Africa. To assess whether and how two KTPs housed in government-affiliated institutions in Cameroon and Uganda have influenced: (1) health system policy-making processes and decisions aiming at supporting achievement of the health millennium development goals (MDGs); and (2) the general climate for EIHSP. We conducted an embedded comparative case study of four policy processes in which Evidence Informed Policy Network (EVIPNet) Cameroon and Regional East African Community Health Policy Initiative (REACH-PI) Uganda were involved between 2009 and 2011. We combined a documentary review and semi structured interviews of 54 stakeholders. A framework-guided thematic analysis, inspired by scholarship in health policy analysis and knowledge utilization was used. EVIPNet Cameroon and REACH-PI Uganda have had direct influence on health system policy decisions. The coproduction of evidence briefs combined with tacit knowledge gathered during inclusive evidence-informed stakeholder dialogues helped to reframe health system problems, unveil sources of conflicts, open grounds for consensus and align viable and affordable options for achieving the health MDGs thus leading to decisions. New policy issue networks have emerged. The KTPs indirectly influenced health policy processes by changing how interests interact with one another and by introducing safe-harbour deliberations and intersected with contextual ideational factors by improving access to policy-relevant evidence. KTPs were perceived as change agents with positive impact on the understanding, acceptance and adoption of EIHSP because of their complementary work in relation to capacity building, rapid evidence syntheses and clearinghouse of policy-relevant evidence. This embedded case study illustrates how two KTPs influenced policy decisions through pathways involving policy issue networks, interest groups interaction and evidence-supported ideas and how they influenced the general climate for EIHSP. PMID:29506146

An Earthquake Shake Map Routine with Low Cost Accelerometers: Preliminary Results

NASA Astrophysics Data System (ADS)

Alcik, H. A.; Tanircan, G.; Kaya, Y.

2015-12-01

Vast amounts of high quality strong motion data are indispensable inputs of the analyses in the field of geotechnical and earthquake engineering however, high cost of installation of the strong motion systems constitutes the biggest obstacle for worldwide dissemination. In recent years, MEMS based (micro-electro-mechanical systems) accelerometers have been used in seismological research-oriented studies as well as earthquake engineering oriented projects basically due to precision obtained in downsized instruments. In this research our primary goal is to ensure the usage of these low-cost instruments in the creation of shake-maps immediately after a strong earthquake. Second goal is to develop software that will automatically process the real-time data coming from the rapid response network and create shake-map. For those purposes, four MEMS sensors have been set up to deliver real-time data. Data transmission is done through 3G modems. A subroutine was coded in assembler language and embedded into the operating system of each instrument to create MiniSEED files with packages of 1-second instead of 512-byte packages.The Matlab-based software calculates the strong motion (SM) parameters at every second, and they are compared with the user-defined thresholds. A voting system embedded in the software captures the event if the total vote exceeds the threshold. The user interface of the software enables users to monitor the calculated SM parameters either in a table or in a graph (Figure 1). A small scale and affordable rapid response network is created using four MEMS sensors, and the functionality of the software has been tested and validated using shake table tests. The entire system is tested together with a reference sensor under real strong ground motion recordings as well as series of sine waves with varying amplitude and frequency. The successful realization of this software allowed us to set up a test network at Tekirdağ Province, the closest coastal point to the moderate size earthquake activities in the Marmara Sea, Turkey.

Ship electric propulsion simulator based on networking technology

NASA Astrophysics Data System (ADS)

Zheng, Huayao; Huang, Xuewu; Chen, Jutao; Lu, Binquan

2006-11-01

According the new ship building tense, a novel electric propulsion simulator (EPS) had been developed in Marine Simulation Center of SMU. The architecture, software function and FCS network technology of EPS and integrated power system (IPS) were described. In allusion to the POD propeller in ship, a special physical model was built. The POD power was supplied from the simulative 6.6 kV Medium Voltage Main Switchboard, its control could be realized in local or remote mode. Through LAN, the simulated feature information of EPS will pass to the physical POD model, which would reflect the real thruster working status in different sea conditions. The software includes vessel-propeller math module, thruster control system, distribution and emergency integrated management, double closed loop control system, vessel static water resistance and dynamic software; instructor main control software. The monitor and control system is realized by real time data collection system and CAN bus technology. During the construction, most devices such as monitor panels and intelligent meters, are developed in lab which were based on embedded microcomputer system with CAN interface to link the network. They had also successfully used in practice and would be suitable for the future demands of digitalization ship.

Research on ARM Numerical Control System

NASA Astrophysics Data System (ADS)

Wei, Xu; JiHong, Chen

Computerized Numerical Control (CNC) machine tools is the foundation of modern manufacturing systems, whose advanced digital technology is the key to solve the problem of sustainable development of machine tool manufacturing industry. The paper is to design CNC system embedded on ARM and indicates the hardware design and the software systems supported. On the hardware side: the driving chip of the motor control unit, as the core of components, is MCX314AL of DSP motion control which is developed by NOVA Electronics Co., Ltd. of Japan. It make convenient to control machine because of its excellent performance, simple interface, easy programming. On the Software side, the uC/OS-2 is selected as the embedded operating system of the open source, which makes a detailed breakdown of the modules of the CNC system. Those priorities are designed according to their actual requirements. The ways of communication between the module and the interrupt response are so different that it guarantees real-time property and reliability of the numerical control system. Therefore, it not only meets the requirements of the current social precision machining, but has good man-machine interface and network support to facilitate a variety of craftsmen use.

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…

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.

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.

Energy efficiency of task allocation for embedded JPEG systems.

PubMed

Fan, Yang-Hsin; Wu, Jan-Ou; Wang, San-Fu

2014-01-01

Embedded system works everywhere for repeatedly performing a few particular functionalities. Well-known products include consumer electronics, smart home applications, and telematics device, and so forth. Recently, developing methodology of embedded systems is applied to conduct the design of cloud embedded system resulting in the applications of embedded system being more diverse. However, the more energy consumes result from the more embedded system works. This study presents hyperrectangle technology (HT) to embedded system for obtaining energy saving. The HT adopts drift effect to construct embedded systems with more hardware circuits than software components or vice versa. It can fast construct embedded system with a set of hardware circuits and software components. Moreover, it has a great benefit to fast explore energy consumption for various embedded systems. The effects are presented by assessing a JPEG benchmarks. Experimental results demonstrate that the HT, respectively, achieves the energy saving by 29.84%, 2.07%, and 68.80% on average to GA, GHO, and Lin.

Energy Efficiency of Task Allocation for Embedded JPEG Systems

PubMed Central

2014-01-01

Embedded system works everywhere for repeatedly performing a few particular functionalities. Well-known products include consumer electronics, smart home applications, and telematics device, and so forth. Recently, developing methodology of embedded systems is applied to conduct the design of cloud embedded system resulting in the applications of embedded system being more diverse. However, the more energy consumes result from the more embedded system works. This study presents hyperrectangle technology (HT) to embedded system for obtaining energy saving. The HT adopts drift effect to construct embedded systems with more hardware circuits than software components or vice versa. It can fast construct embedded system with a set of hardware circuits and software components. Moreover, it has a great benefit to fast explore energy consumption for various embedded systems. The effects are presented by assessing a JPEG benchmarks. Experimental results demonstrate that the HT, respectively, achieves the energy saving by 29.84%, 2.07%, and 68.80% on average to GA, GHO, and Lin. PMID:24982983

An Ada implementation of the network manager for the advanced information processing system

NASA Technical Reports Server (NTRS)

Nagle, Gail A.

1986-01-01

From an implementation standpoint, the Ada language provided many features which facilitated the data and procedure abstraction process. The language supported a design which was dynamically flexible (despite strong typing), modular, and self-documenting. Adequate training of programmers requires access to an efficient compiler which supports full Ada. When the performance issues for real time processing are finally addressed by more stringent requirements for tasking features and the development of efficient run-time environments for embedded systems, the full power of the language will be realized.

Optical-nanofiber-based interface for single molecules

NASA Astrophysics Data System (ADS)

Skoff, Sarah M.; Papencordt, David; Schauffert, Hardy; Bayer, Bernhard C.; Rauschenbeutel, Arno

2018-04-01

Optical interfaces for quantum emitters are a prerequisite for implementing quantum networks. Here, we couple single molecules to the guided modes of an optical nanofiber. The molecules are embedded within a crystal that provides photostability and, due to the inhomogeneous broadening, a means to spectrally address single molecules. Single molecules are excited and detected solely via the nanofiber interface without the requirement of additional optical access. In this way, we realize a fully fiber-integrated system that is scalable and may become a versatile constituent for quantum hybrid systems.

Autonomous telemetry system by using mobile networks for a long-term seismic observation

NASA Astrophysics Data System (ADS)

Hirahara, S.; Uchida, N.; Nakajima, J.

2012-04-01

When a large earthquake occurs, it is important to know the detailed distribution of aftershocks immediately after the main shock for the estimation of the fault plane. The large amount of seismic data is also required to determine the three-dimensional seismic velocity structure around the focal area. We have developed an autonomous telemetry system using mobile networks, which is specialized for aftershock observations. Because the newly developed system enables a quick installation and real-time data transmission by using mobile networks, we can construct a dense online seismic network even in mountain areas where conventional wired networks are not available. This system is equipped with solar panels that charge lead-acid battery, and enables a long-term seismic observation without maintenance. Furthermore, this system enables a continuous observation at low costs with flat-rate or prepaid Internet access. We have tried to expand coverage areas of mobile communication and back up Internet access by configuring plural mobile carriers. A micro server embedded with Linux consists of automatic control programs of the Internet connection and data transmission. A status monitoring and remote maintenance are available via the Internet. In case of a communication failure, an internal storage can back up data for two years. The power consumption of communication device ranges from 2.5 to 4.0 W. With a 50 Ah lead-acid battery, this system continues to record data for four days if the battery charging by solar panels is temporarily unavailable.

Development and Demonstration of a Networked Telepathology 3-D Imaging, Databasing, and Communication System

DTIC Science & Technology

1996-10-01

aligned using an octree search algorithm combined with cross correlation analysis . Successive 4x downsampling with optional and specifiable neighborhood...desired and the search engine embedded in the OODBMS will find the requested imagery and que it to the user for further analysis . This application was...obtained during Hoftmann-LaRoche production pathology imaging performed at UMICH. Versant works well and is easy to use; 3) Pathology Image Analysis

The role of human-automation consensus in multiple unmanned vehicle scheduling.

PubMed

Cummings, M L; Clare, Andrew; Hart, Christin

2010-02-01

This study examined the impact of increasing automation replanning rates on operator performance and workload when supervising a decentralized network of heterogeneous unmanned vehicles. Futuristic unmanned vehicles systems will invert the operator-to-vehicle ratio so that one operator can control multiple dissimilar vehicles connected through a decentralized network. Significant human-automation collaboration will be needed because of automation brittleness, but such collaboration could cause high workload. Three increasing levels of replanning were tested on an existing multiple unmanned vehicle simulation environment that leverages decentralized algorithms for vehicle routing and task allocation in conjunction with human supervision. Rapid replanning can cause high operator workload, ultimately resulting in poorer overall system performance. Poor performance was associated with a lack of operator consensus for when to accept the automation's suggested prompts for new plan consideration as well as negative attitudes toward unmanned aerial vehicles in general. Participants with video game experience tended to collaborate more with the automation, which resulted in better performance. In decentralized unmanned vehicle networks, operators who ignore the automation's requests for new plan consideration and impose rapid replans both increase their own workload and reduce the ability of the vehicle network to operate at its maximum capacity. These findings have implications for personnel selection and training for futuristic systems involving human collaboration with decentralized algorithms embedded in networks of autonomous systems.

Embedded ARM system for volcano monitoring in remote areas: application to the active volcano on Deception Island (Antarctica).

PubMed

Peci, Luis Miguel; Berrocoso, Manuel; Fernández-Ros, Alberto; García, Alicia; Marrero, José Manuel; Ortiz, Ramón

2014-01-02

This paper describes the development of a multi-parameter system for monitoring volcanic activity. The system permits the remote access and the connection of several modules in a network. An embedded ARM™ processor has been used, allowing a great flexibility in hardware configuration. The use of a complete Linux solution (Debian™) as Operating System permits a quick, easy application development to control sensors and communications. This provides all the capabilities required and great stability with relatively low energy consumption. The cost of the components and applications development is low since they are widely used in different fields. Sensors and commercial modules have been combined with other self-developed modules. The Modular Volcano Monitoring System (MVMS) described has been deployed on the active Deception Island (Antarctica) volcano, within the Spanish Antarctic Program, and has proved successful for monitoring the volcano, with proven reliability and efficient operation under extreme conditions. In another context, i.e., the recent volcanic activity on El Hierro Island (Canary Islands) in 2011, this technology has been used for the seismic equipment and GPS systems deployed, thus showing its efficiency in the monitoring of a volcanic crisis.

Embedded ARM System for Volcano Monitoring in Remote Areas: Application to the Active Volcano on Deception Island (Antarctica)

PubMed Central

Peci, Luis Miguel; Berrocoso, Manuel; Fernández-Ros, Alberto; García, Alicia; Marrero, José Manuel; Ortiz, Ramón

2014-01-01

This paper describes the development of a multi-parameter system for monitoring volcanic activity. The system permits the remote access and the connection of several modules in a network. An embedded ARM™™ processor has been used, allowing a great flexibility in hardware configuration. The use of a complete Linux solution (Debian™) as Operating System permits a quick, easy application development to control sensors and communications. This provides all the capabilities required and great stability with relatively low energy consumption. The cost of the components and applications development is low since they are widely used in different fields. Sensors and commercial modules have been combined with other self-developed modules. The Modular Volcano Monitoring System (MVMS) described has been deployed on the active Deception Island (Antarctica) volcano, within the Spanish Antarctic Program, and has proved successful for monitoring the volcano, with proven reliability and efficient operation under extreme conditions. In another context, i.e., the recent volcanic activity on El Hierro Island (Canary Islands) in 2011, this technology has been used for the seismic equipment and GPS systems deployed, thus showing its efficiency in the monitoring of a volcanic crisis. PMID:24451461

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.

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…

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

Implementation of envelope detection based Wake-Up Receiver for IEEE 802.15.4 WPAN from off-the-shelf components

NASA Astrophysics Data System (ADS)

Arndt, Josua; Krystofiak, Lukas; Bonehi, Vahid; Wunderlich, Ralf; Heinen, Stefan

2017-09-01

Power consumption in wireless networks is crucial. In most scenarios the transmission time is short compared to the idle listening time for data transmission, the most power is consumed by the receiver. In low latency systems there is a need for low power wake-up receivers (WuRx) that reduce the power consumption when the node is idle, but keep it responsive. This work presents a WuRx designed out of commercial components to investigate the needs of a WuRx when it is embedded in a Wireless Personal Area Network (WPAN) system in a real environment setup including WLAN and LTE communication and considering interferer rejection. The calculation necessary for the attenuation of those interferers is explained in detail. Furthermore, a system design is presented that fulfills the requirements for this environment and is build from off-the-shelf components.

A Taxonomy on Accountability and Privacy Issues in Smart Grids

NASA Astrophysics Data System (ADS)

Naik, Ameya; Shahnasser, Hamid

2017-07-01

Cyber-Physical Systems (CPS) are combinations of computation, networking, and physical processes. Embedded computers and networks monitor control the physical processes, which affect computations and vice versa. Two applications of cyber physical systems include health-care and smart grid. In this paper, we have considered privacy aspects of cyber-physical system applicable to smart grid. Smart grid in collaboration with different stockholders can help in the improvement of power generation, communication, circulation and consumption. The proper management with monitoring feature by customers and utility of energy usage can be done through proper transmission and electricity flow; however cyber vulnerability could be increased due to an increased assimilation and linkage. This paper discusses various frameworks and architectures proposed for achieving accountability in smart grids by addressing privacy issues in Advance Metering Infrastructure (AMI). This paper also highlights additional work needed for accountability in more precise specifications such as uncertainty or ambiguity, indistinct, unmanageability, and undetectably.

Microcapillary imaging of lamina cribrosa in porcine eyes using photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Moothanchery, Mohesh; Chuangsuwanich, Thanadet; Yan, Alvan Tsz Chung; Schmetterer, Leopold; Girard, Michael J. A.; Pramanik, Manojit

2018-02-01

In order to understand the pathophysiology of glaucoma, Lamina cribrosa (LC) perfusion needs to be the subject of thorough investigation. It is currently difficult to obtain high resolution images of the embedded microcapillary network of the LC using conventional imaging techniques. In this study, an optical resolution photoacoustic microscopy (OR-PAM) system was used for imaging lamina cribrosa of an ex vivo porcine eye. Extrinsic contrast agent was used to perfuse the eye via its ciliary arteries. The OR-PAM system have a lateral resolution of 4 μm and an axial resolution of 30 μm. The high resolution system could able resolve a perfused LC microcapillary network to show vascular structure within the LC thickness. OR-PAM could be a promising imaging modality to study the LC perfusion and hence could be used to elucidate the hemodynamic aspect of glaucoma.

Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations

NASA Technical Reports Server (NTRS)

Shapiro, Bruce E.; Levchenko, Andre; Meyerowitz, Elliot M.; Wold, Barbara J.; Mjolsness, Eric D.

2003-01-01

Cellerator describes single and multi-cellular signal transduction networks (STN) with a compact, optionally palette-driven, arrow-based notation to represent biochemical reactions and transcriptional activation. Multi-compartment systems are represented as graphs with STNs embedded in each node. Interactions include mass-action, enzymatic, allosteric and connectionist models. Reactions are translated into differential equations and can be solved numerically to generate predictive time courses or output as systems of equations that can be read by other programs. Cellerator simulations are fully extensible and portable to any operating system that supports Mathematica, and can be indefinitely nested within larger data structures to produce highly scaleable models.

Platelet lysate embedded scaffolds for skin regeneration.

PubMed

Sandri, Giuseppina; Bonferoni, Maria Cristina; Rossi, Silvia; Ferrari, Franca; Mori, Michela; Cervio, Marila; Riva, Federica; Liakos, Ioannis; Athanassiou, Athanassia; Saporito, Francesca; Marini, Lara; Caramella, Carla

2015-04-01

The work presents the development of acellular scaffolds extemporaneously embedded with platelet lysate (PL), as an innovative approach in the field of tissue regeneration/reparation. PL embedded scaffolds should have a tridimensional architecture to support cell migration and growth, in order to restore skin integrity. For this reason, chondroitin sulfate (CS) was associated with sodium alginate (SA) to prepare highly porous systems. The developed scaffolds were characterized for chemical stability to γ-radiation, morphology, hydration and mechanical properties. Moreover, the capability of fibroblasts and endothelial cells to populate the scaffold was evaluated by means of proliferation test 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and confocal laser scanning microscopy study. The scaffolds, not altered by sterilization, were characterized by limited swelling and high flexibility, by foam-like structure with bubbles that formed a high surface area and irregular texture suitable for cell adhesion. Cell growth and scaffold population were evident on the bubble surface, where the cells appeared anchored to the scaffold structure. Scaffold network based on CS and SA demonstrated to be an effective support to enhance and to allow fibroblasts and endothelial cells (human umbilical vein endothelial cells, HUVEC) adhesion and proliferation. In particular, it could be hypothesized that cell adhesion was facilitated by the synergic effect of PL and CS. Although further in vivo evaluation is needed, on the basis of in vitro results, PL embedded scaffolds seem promising systems for skin wound healing.

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.

To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets

NASA Astrophysics Data System (ADS)

Borondo, J.; Borondo, F.; Rodriguez-Sickert, C.; Hidalgo, C. A.

2014-01-01

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

To each according to its degree: the meritocracy and topocracy of embedded markets.

PubMed

Borondo, J; Borondo, F; Rodriguez-Sickert, C; Hidalgo, C A

2014-01-21

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Solving data-at-rest for the storage and retrieval of files in ad hoc networks

NASA Astrophysics Data System (ADS)

Knobler, Ron; Scheffel, Peter; Williams, Jonathan; Gaj, Kris; Kaps, Jens-Peter

2013-05-01

Based on current trends for both military and commercial applications, the use of mobile devices (e.g. smartphones and tablets) is greatly increasing. Several military applications consist of secure peer to peer file sharing without a centralized authority. For these military applications, if one or more of these mobile devices are lost or compromised, sensitive files can be compromised by adversaries, since COTS devices and operating systems are used. Complete system files cannot be stored on a device, since after compromising a device, an adversary can attack the data at rest, and eventually obtain the original file. Also after a device is compromised, the existing peer to peer system devices must still be able to access all system files. McQ has teamed with the Cryptographic Engineering Research Group at George Mason University to develop a custom distributed file sharing system to provide a complete solution to the data at rest problem for resource constrained embedded systems and mobile devices. This innovative approach scales very well to a large number of network devices, without a single point of failure. We have implemented the approach on representative mobile devices as well as developed an extensive system simulator to benchmark expected system performance based on detailed modeling of the network/radio characteristics, CONOPS, and secure distributed file system functionality. The simulator is highly customizable for the purpose of determining expected system performance for other network topologies and CONOPS.

Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation.

PubMed

Jimeno Yepes, Antonio

2017-09-01

Word sense disambiguation helps identifying the proper sense of ambiguous words in text. With large terminologies such as the UMLS Metathesaurus ambiguities appear and highly effective disambiguation methods are required. Supervised learning algorithm methods are used as one of the approaches to perform disambiguation. Features extracted from the context of an ambiguous word are used to identify the proper sense of such a word. The type of features have an impact on machine learning methods, thus affect disambiguation performance. In this work, we have evaluated several types of features derived from the context of the ambiguous word and we have explored as well more global features derived from MEDLINE using word embeddings. Results show that word embeddings improve the performance of more traditional features and allow as well using recurrent neural network classifiers based on Long-Short Term Memory (LSTM) nodes. The combination of unigrams and word embeddings with an SVM sets a new state of the art performance with a macro accuracy of 95.97 in the MSH WSD data set. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Wireless patient monitoring system for a moving-actuator type artificial heart.

PubMed

Nam, K W; Chung, J; Choi, S W; Sun, K; Min, B G

2006-10-01

In this study, we developed a wireless monitoring system for outpatients equipped with a moving-actuator type pulsatile bi-ventricular assist device, AnyHeart. The developed monitoring system consists of two parts; a Bluetooth-based short-distance self-monitoring system that can monitor and control the operating status of a VAD using a Bluetooth-embedded personal digital assistant or a personal computer within a distance of 10 meters, and a cellular network-based remote monitoring system that can continuously monitor and control the operating status of AnyHeart at any location. Results of in vitro experiments demonstrate the developed system's ability to monitor the operational status of an implanted AnyHeart.

Accounting for heterogeneity of nutrient dynamics in riverscapes through spatially distributed models

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Stewart, R. J.

2011-12-01

Numerous types of heterogeneity exist within river systems, leading to hotspots of nutrient sources, sinks, and impacts embedded within an underlying gradient defined by river size. This heterogeneity influences the downstream propagation of anthropogenic impacts across flow conditions. We applied a river network model to explore how nitrogen saturation at river network scales is influenced by the abundance and distribution of potential nutrient processing hotspots (lakes, beaver ponds, tributary junctions, hyporheic zones) under different flow conditions. We determined that under low flow conditions, whole network nutrient removal is relatively insensitive to the number of hotspots because the underlying river network structure has sufficient nutrient processing capacity. However, hotspots become more important at higher flows and greatly influence the spatial distribution of removal within the network at all flows, suggesting that identification of heterogeneity is critical to develop predictive understanding of nutrient removal processes under changing loading and climate conditions. New temporally intensive data from in situ sensors can potentially help to better understand and constrain these dynamics.

A disassembly-driven mechanism explains F-actin-mediated chromosome transport in starfish oocytes

PubMed Central

Bun, Philippe; Dmitrieff, Serge; Belmonte, Julio M

2018-01-01

While contraction of sarcomeric actomyosin assemblies is well understood, this is not the case for disordered networks of actin filaments (F-actin) driving diverse essential processes in animal cells. For example, at the onset of meiosis in starfish oocytes a contractile F-actin network forms in the nuclear region transporting embedded chromosomes to the assembling microtubule spindle. Here, we addressed the mechanism driving contraction of this 3D disordered F-actin network by comparing quantitative observations to computational models. We analyzed 3D chromosome trajectories and imaged filament dynamics to monitor network behavior under various physical and chemical perturbations. We found no evidence of myosin activity driving network contractility. Instead, our observations are well explained by models based on a disassembly-driven contractile mechanism. We reconstitute this disassembly-based contractile system in silico revealing a simple architecture that robustly drives chromosome transport to prevent aneuploidy in the large oocyte, a prerequisite for normal embryonic development. PMID:29350616

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.

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.

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

Network motif frequency vectors reveal evolving metabolic network organisation.

PubMed

Pearcy, Nicole; Crofts, Jonathan J; Chuzhanova, Nadia

2015-01-01

At the systems level many organisms of interest may be described by their patterns of interaction, and as such, are perhaps best characterised via network or graph models. Metabolic networks, in particular, are fundamental to the proper functioning of many important biological processes, and thus, have been widely studied over the past decade or so. Such investigations have revealed a number of shared topological features, such as a short characteristic path-length, large clustering coefficient and hierarchical modular structure. However, the extent to which evolutionary and functional properties of metabolism manifest via this underlying network architecture remains unclear. In this paper, we employ a novel graph embedding technique, based upon low-order network motifs, to compare metabolic network structure for 383 bacterial species categorised according to a number of biological features. In particular, we introduce a new global significance score which enables us to quantify important evolutionary relationships that exist between organisms and their physical environments. Using this new approach, we demonstrate a number of significant correlations between environmental factors, such as growth conditions and habitat variability, and network motif structure, providing evidence that organism adaptability leads to increased complexities in the resultant metabolic networks.

Structural Health Monitoring of a Composite Panel Based on PZT Sensors and a Transfer Impedance Framework.

PubMed

Dziendzikowski, Michal; Niedbala, Patryk; Kurnyta, Artur; Kowalczyk, Kamil; Dragan, Krzysztof

2018-05-11

One of the ideas for development of Structural Health Monitoring (SHM) systems is based on excitation of elastic waves by a network of PZT piezoelectric transducers integrated with the structure. In the paper, a variant of the so-called Transfer Impedance (TI) approach to SHM is followed. Signal characteristics, called the Damage Indices (DIs), were proposed for data presentation and analysis. The idea underlying the definition of DIs was to maintain most of the information carried by the voltage induced on PZT sensors by elastic waves. In particular, the DIs proposed in the paper should be sensitive to all types of damage which can influence the amplitude or the phase of the voltage induced on the sensor. Properties of the proposed DIs were investigated experimentally using a GFRP composite panel equipped with PZT networks attached to its surface and embedded into its internal structure. Repeatability and stability of DI indications under controlled conditions were verified in tests. Also, some performance indicators for surface-attached and structure-embedded sensors were obtained. The DIs' behavior was dependent mostly on the presence of a simulated damage in the structure. Anisotropy of mechanical properties of the specimen, geometrical properties of PZT network as well as, to some extent, the technology of sensor integration with the structure were irrelevant for damage indication. This property enables the method to be used for damage detection and classification.

Inferring topologies via driving-based generalized synchronization of two-layer networks

NASA Astrophysics Data System (ADS)

Wang, Yingfei; Wu, Xiaoqun; Feng, Hui; Lu, Jun-an; Xu, Yuhua

2016-05-01

The interaction topology among the constituents of a complex network plays a crucial role in the network’s evolutionary mechanisms and functional behaviors. However, some network topologies are usually unknown or uncertain. Meanwhile, coupling delays are ubiquitous in various man-made and natural networks. Hence, it is necessary to gain knowledge of the whole or partial topology of a complex dynamical network by taking into consideration communication delay. In this paper, topology identification of complex dynamical networks is investigated via generalized synchronization of a two-layer network. Particularly, based on the LaSalle-type invariance principle of stochastic differential delay equations, an adaptive control technique is proposed by constructing an auxiliary layer and designing proper control input and updating laws so that the unknown topology can be recovered upon successful generalized synchronization. Numerical simulations are provided to illustrate the effectiveness of the proposed method. The technique provides a certain theoretical basis for topology inference of complex networks. In particular, when the considered network is composed of systems with high-dimension or complicated dynamics, a simpler response layer can be constructed, which is conducive to circuit design. Moreover, it is practical to take into consideration perturbations caused by control input. Finally, the method is applicable to infer topology of a subnetwork embedded within a complex system and locate hidden sources. We hope the results can provide basic insight into further research endeavors on understanding practical and economical topology inference of networks.

Integrated Design and Implementation of Embedded Control Systems with Scilab

PubMed Central

Ma, Longhua; Xia, Feng; Peng, Zhe

2008-01-01

Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly time-consuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost. PMID:27873827

Integrated Design and Implementation of Embedded Control Systems with Scilab.

PubMed

Ma, Longhua; Xia, Feng; Peng, Zhe

2008-09-05

Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly timeconsuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost.

Integration science and distributed networks

NASA Astrophysics Data System (ADS)

Landauer, Christopher; Bellman, Kirstie L.

2002-07-01

Our work on integration of data and knowledge sources is based in a common theoretical treatment of 'Integration Science', which leads to systematic processes for combining formal logical and mathematical systems, computational and physical systems, and human systems and organizations. The theory is based on the processing of explicit meta-knowledge about the roles played by the different knowledge sources and the methods of analysis and semantic implications of the different data values, together with information about the context in which and the purpose for which they are being combined. The research treatment is primarily mathematical, and though this kind of integration mathematics is still under development, there are some applicable common threads that have emerged already. Instead of describing the current state of the mathematical investigations, since they are not yet crystallized enough for formalisms, we describe our applications of the approach in several different areas, including our focus area of 'Constructed Complex Systems', which are complex heterogeneous systems managed or mediated by computing systems. In this context, it is important to remember that all systems are embedded, all systems are autonomous, and that all systems are distributed networks.

Intelligent control system based on ARM for lithography tool

NASA Astrophysics Data System (ADS)

Chen, Changlong; Tang, Xiaoping; Hu, Song; Wang, Nan

2014-08-01

The control system of traditional lithography tool is based on PC and MCU. The PC handles the complex algorithm, human-computer interaction, and communicates with MCU via serial port; The MCU controls motors and electromagnetic valves, etc. This mode has shortcomings like big volume, high power consumption, and wasting of PC resource. In this paper, an embedded intelligent control system of lithography tool, based on ARM, is provided. The control system used S5PV210 as processor, completing the functions of PC in traditional lithography tool, and provided a good human-computer interaction by using LCD and capacitive touch screen. Using Android4.0.3 as operating system, the equipment provided a cool and easy UI which made the control more user-friendly, and implemented remote control and debug, pushing video information of product by network programming. As a result, it's convenient for equipment vendor to provide technical support for users. Finally, compared with traditional lithography tool, this design reduced the PC part, making the hardware resources efficiently used and reducing the cost and volume. Introducing embedded OS and the concepts in "The Internet of things" into the design of lithography tool can be a development trend.

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…

Simulation of uniaxial deformation of hexagonal crystals (Mg, Be)

NASA Astrophysics Data System (ADS)

Vlasova, A. M.; Kesarev, A. G.

2017-12-01

Molecular dynamics (MD) simulations were performed for the nanocompression loading of nanocrystalline magnesium and beryllium modeled by an interatomic potential of the embedded atom method (EAM). It is shown that the main deformation modes are prismatic slip and twinning for magnesium, and only prismatic slip for beryllium. The formation of stable configurations of dislocation grids in magnesium and beryllium was observed. Dislocation networks are formed in the habit plane of the twin in a magnesium nanocrystall. Some dislocation reactions are suggested to explain the appearance of such networks. Shockley partial dislocations in a beryllium nanocrystall form grids in the slip plane. A strong anisotropy between slip systems was observed, which is in agreement with experimental data.

Towards Guided Underwater Survey Using Light Visual Odometry

NASA Astrophysics Data System (ADS)

Nawaf, M. M.; Drap, P.; Royer, J. P.; Merad, D.; Saccone, M.

2017-02-01

A light distributed visual odometry method adapted to embedded hardware platform is proposed. The aim is to guide underwater surveys in real time. We rely on image stream captured using portable stereo rig attached to the embedded system. Taken images are analyzed on the fly to assess image quality in terms of sharpness and lightness, so that immediate actions can be taken accordingly. Images are then transferred over the network to another processing unit to compute the odometry. Relying on a standard ego-motion estimation approach, we speed up points matching between image quadruplets using a low level points matching scheme relying on fast Harris operator and template matching that is invariant to illumination changes. We benefit from having the light source attached to the hardware platform to estimate a priori rough depth belief following light divergence over distance low. The rough depth is used to limit points correspondence search zone as it linearly depends on disparity. A stochastic relative bundle adjustment is applied to minimize re-projection errors. The evaluation of the proposed method demonstrates the gain in terms of computation time w.r.t. other approaches that use more sophisticated feature descriptors. The built system opens promising areas for further development and integration of embedded computer vision techniques.

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

Implementing Internet of Things in a military command and control environment

NASA Astrophysics Data System (ADS)

Raglin, Adrienne; Metu, Somiya; Russell, Stephen; Budulas, Peter

2017-05-01

While the term Internet of Things (IoT) has been coined relatively recently, it has deep roots in multiple other areas of research including cyber-physical systems, pervasive and ubiquitous computing, embedded systems, mobile ad-hoc networks, wireless sensor networks, cellular networks, wearable computing, cloud computing, big data analytics, and intelligent agents. As the Internet of Things, these technologies have created a landscape of diverse heterogeneous capabilities and protocols that will require adaptive controls to effect linkages and changes that are useful to end users. In the context of military applications, it will be necessary to integrate disparate IoT devices into a common platform that necessarily must interoperate with proprietary military protocols, data structures, and systems. In this environment, IoT devices and data will not be homogeneous and provenance-controlled (i.e. single vendor/source/supplier owned). This paper presents a discussion of the challenges of integrating varied IoT devices and related software in a military environment. A review of contemporary commercial IoT protocols is given and as a practical example, a middleware implementation is proffered that provides transparent interoperability through a proactive message dissemination system. The implementation is described as a framework through which military applications can integrate and utilize commercial IoT in conjunction with existing military sensor networks and command and control (C2) systems.

A quantum annealing approach for fault detection and diagnosis of graph-based systems

NASA Astrophysics Data System (ADS)

Perdomo-Ortiz, A.; Fluegemann, J.; Narasimhan, S.; Biswas, R.; Smelyanskiy, V. N.

2015-02-01

Diagnosing the minimal set of faults capable of explaining a set of given observations, e.g., from sensor readouts, is a hard combinatorial optimization problem usually tackled with artificial intelligence techniques. We present the mapping of this combinatorial problem to quadratic unconstrained binary optimization (QUBO), and the experimental results of instances embedded onto a quantum annealing device with 509 quantum bits. Besides being the first time a quantum approach has been proposed for problems in the advanced diagnostics community, to the best of our knowledge this work is also the first research utilizing the route Problem → QUBO → Direct embedding into quantum hardware, where we are able to implement and tackle problem instances with sizes that go beyond previously reported toy-model proof-of-principle quantum annealing implementations; this is a significant leap in the solution of problems via direct-embedding adiabatic quantum optimization. We discuss some of the programmability challenges in the current generation of the quantum device as well as a few possible ways to extend this work to more complex arbitrary network graphs.

Network communities within and across borders

PubMed Central

Cerina, Federica; Chessa, Alessandro; Pammolli, Fabio; Riccaboni, Massimo

2014-01-01

We investigate the impact of borders on the topology of spatially embedded networks. Indeed territorial subdivisions and geographical borders significantly hamper the geographical span of networks thus playing a key role in the formation of network communities. This is especially important in scientific and technological policy-making, highlighting the interplay between pressure for the internationalization to lead towards a global innovation system and the administrative borders imposed by the national and regional institutions. In this study we introduce an outreach index to quantify the impact of borders on the community structure and apply it to the case of the European and US patent co-inventors networks. We find that (a) the US connectivity decays as a power of distance, whereas we observe a faster exponential decay for Europe; (b) European network communities essentially correspond to nations and contiguous regions while US communities span multiple states across the whole country without any characteristic geographic scale. We confirm our findings by means of a set of simulations aimed at exploring the relationship between different patterns of cross-border community structures and the outreach index. PMID:24686380

Network communities within and across borders.

PubMed

Cerina, Federica; Chessa, Alessandro; Pammolli, Fabio; Riccaboni, Massimo

2014-04-01

We investigate the impact of borders on the topology of spatially embedded networks. Indeed territorial subdivisions and geographical borders significantly hamper the geographical span of networks thus playing a key role in the formation of network communities. This is especially important in scientific and technological policy-making, highlighting the interplay between pressure for the internationalization to lead towards a global innovation system and the administrative borders imposed by the national and regional institutions. In this study we introduce an outreach index to quantify the impact of borders on the community structure and apply it to the case of the European and US patent co-inventors networks. We find that (a) the US connectivity decays as a power of distance, whereas we observe a faster exponential decay for Europe; (b) European network communities essentially correspond to nations and contiguous regions while US communities span multiple states across the whole country without any characteristic geographic scale. We confirm our findings by means of a set of simulations aimed at exploring the relationship between different patterns of cross-border community structures and the outreach index.

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

Study of Composite Plate Damages Using Embedded PZT Sensors with Various Center Frequency

NASA Astrophysics Data System (ADS)

Kang, Kyoung-Tak; Chun, Heoung-Jae; Son, Ju-Hyun; Byun, Joon-Hyung; Um, Moon-Kwang; Lee, Sang-Kwan

This study presents part of an experimental and analytical survey of candidate methods for damage detection of composite structural. Embedded piezoceramic (PZT) sensors were excited with the high power ultrasonic wave generator generating a propagation of stress wave along the composite plate. The same embedded piezoceramic (PZT) sensors are used as receivers for acquiring stress signals. The effects of center frequency of embedded sensor were evaluated for the damage identification capability with known localized defects. The study was carried out to assess damage in composite plate by fusing information from multiple sensing paths of the embedded network. It was based on the Hilbert transform, signal correlation and probabilistic searching. The obtained results show that satisfactory detection of defects could be achieved by proposed method.

Hybrid Piezoelectric/Fiber-Optic Sensor Sheets

NASA Technical Reports Server (NTRS)

Lin, Mark; Qing, Xinlin

2004-01-01

Hybrid piezoelectric/fiber-optic (HyPFO) sensor sheets are undergoing development. They are intended for use in nondestructive evaluation and long-term monitoring of the integrity of diverse structures, including aerospace, aeronautical, automotive, and large stationary ones. It is anticipated that the further development and subsequent commercialization of the HyPFO sensor systems will lead to economic benefits in the form of increased safety, reduction of life-cycle costs through real-time structural monitoring, increased structural reliability, reduction of maintenance costs, and increased readiness for service. The concept of a HyPFO sensor sheet is a generalization of the concept of a SMART Layer(TradeMark), which is a patented device that comprises a thin dielectric film containing an embedded network of distributed piezoelectric actuator/sensors. Such a device can be mounted on the surface of a metallic structure or embedded inside a composite-material structure during fabrication of the structure. There is has been substantial interest in incorporating sensors other than piezoelectric ones into SMART Layer(TradeMark) networks: in particular, because of the popularity of the use of fiber-optic sensors for monitoring the "health" of structures in recent years, it was decided to incorporate fiber-optic sensors, giving rise to the concept of HyPFO devices.

Enhanced Communication Network Solution for Positive Train Control Implementation

NASA Technical Reports Server (NTRS)

Fatehi, M. T.; Simon, J.; Chang, W.; Chow, E. T.; Burleigh, S. C.

2011-01-01

The commuter and freight railroad industry is required to implement Positive Train Control (PTC) by 2015 (2012 for Metrolink), a challenging network communications problem. This paper will discuss present technologies developed by the National Aeronautics and Space Administration (NASA) to overcome comparable communication challenges encountered in deep space mission operations. PTC will be based on a new cellular wireless packet Internet Protocol (IP) network. However, ensuring reliability in such a network is difficult due to the "dead zones" and transient disruptions we commonly experience when we lose calls in commercial cellular networks. These disruptions make it difficult to meet PTC s stringent reliability (99.999%) and safety requirements, deployment deadlines, and budget. This paper proposes innovative solutions based on space-proven technologies that would help meet these challenges: (1) Delay Tolerant Networking (DTN) technology, designed for use in resource-constrained, embedded systems and currently in use on the International Space Station, enables reliable communication over networks in which timely data acknowledgments might not be possible due to transient link outages. (2) Policy-Based Management (PBM) provides dynamic management capabilities, allowing vital data to be exchanged selectively (with priority) by utilizing alternative communication resources. The resulting network may help railroads implement PTC faster, cheaper, and more reliably.

Field programmable chemistry: integrated chemical and electronic processing of informational molecules towards electronic chemical cells.

PubMed

Wagler, Patrick F; Tangen, Uwe; Maeke, Thomas; McCaskill, John S

2012-07-01

The topic addressed is that of combining self-constructing chemical systems with electronic computation to form unconventional embedded computation systems performing complex nano-scale chemical tasks autonomously. The hybrid route to complex programmable chemistry, and ultimately to artificial cells based on novel chemistry, requires a solution of the two-way massively parallel coupling problem between digital electronics and chemical systems. We present a chemical microprocessor technology and show how it can provide a generic programmable platform for complex molecular processing tasks in Field Programmable Chemistry, including steps towards the grand challenge of constructing the first electronic chemical cells. Field programmable chemistry employs a massively parallel field of electrodes, under the control of latched voltages, which are used to modulate chemical activity. We implement such a field programmable chemistry which links to chemistry in rather generic, two-phase microfluidic channel networks that are separated into weakly coupled domains. Electric fields, produced by the high-density array of electrodes embedded in the channel floors, are used to control the transport of chemicals across the hydrodynamic barriers separating domains. In the absence of electric fields, separate microfluidic domains are essentially independent with only slow diffusional interchange of chemicals. Electronic chemical cells, based on chemical microprocessors, exploit a spatially resolved sandwich structure in which the electronic and chemical systems are locally coupled through homogeneous fine-grained actuation and sensor networks and play symmetric and complementary roles. We describe how these systems are fabricated, experimentally test their basic functionality, simulate their potential (e.g. for feed forward digital electrophoretic (FFDE) separation) and outline the application to building electronic chemical cells. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Arc-welding quality assurance by means of embedded fiber sensor and spectral processing combining feature selection and neural networks

NASA Astrophysics Data System (ADS)

Mirapeix, J.; García-Allende, P. B.; Cobo, A.; Conde, O.; López-Higuera, J. M.

2007-07-01

A new spectral processing technique designed for its application in the on-line detection and classification of arc-welding defects is presented in this paper. A non-invasive fiber sensor embedded within a TIG torch collects the plasma radiation originated during the welding process. The spectral information is then processed by means of two consecutive stages. A compression algorithm is first applied to the data allowing real-time analysis. The selected spectral bands are then used to feed a classification algorithm, which will be demonstrated to provide an efficient weld defect detection and classification. The results obtained with the proposed technique are compared to a similar processing scheme presented in a previous paper, giving rise to an improvement in the performance of the monitoring system.

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.

Time-domain fiber loop ringdown sensor and sensor network

NASA Astrophysics Data System (ADS)

Kaya, Malik

Optical fibers have been mostly used in fiber optic communications, imaging optics, sensing technology, etc. Fiber optic sensors have gained increasing attention for scientific and structural health monitoring (SHM) applications. In this study, fiber loop ringdown (FLRD) sensors were fabricated for scientific, SHM, and sensor networking applications. FLRD biosensors were fabricated for both bulk refractive index (RI)- and surface RI-based DNA sensing and one type of bacteria sensing. Furthermore, the effect of glucose oxidase (GOD) immobilization at the sensor head on sensor performance was evaluated for both glucose and synthetic urine solutions with glucose concentration between 0.1% and 10%. Detection sensitivities of the glucose sensors were achieved as low as 0.05%. For chemical sensing, heavy water, ranging from 97% to 10%, and several elemental solutions were monitored by using the FLRD chemical sensors. Bulk index-based FLRD sensing showed that trace elements can be detected in deionized water. For physical sensing, water and cracking sensors were fabricated and embedded into concrete. A partially-etched single-mode fiber (SMF) was embedded into a concrete bar for water monitoring while a bare SMF without any treatment was directly embedded into another concrete bar for monitoring cracks. Furthermore, detection sensitivities of water and crack sensors were investigated as 10 ml water and 0.5 mm surface crack width, respectively. Additionally fiber loop ringdown-fiber Bragg grating temperature sensors were developed in the laboratory; two sensor units for water, crack, and temperature sensing were deployed into a concrete cube in a US Department of Energy test bed (Miami, FL). Multi-sensor applications in a real concrete structure were accomplished by testing the six FLRD sensors. As a final stage, a sensor network was assembled by multiplexing two or three FLRD sensors in series and parallel. Additionally, two FLRD sensors were combined in series and parallel by using a 2x1 micro-electromechanical system optical switch to control sensors individually. For both configurations, contributions of each sensor to two or three coupled signals were simulated theoretically. Results show that numerous FLRD sensors can be connected in different configurations, and a sensor network can be built up for multi-function sensing applications.

A Monitoring System for Vegetable Greenhouses based on a Wireless Sensor Network

PubMed Central

Li, Xiu-hong; Cheng, Xiao; Yan, Ke; Gong, Peng

2010-01-01

A wireless sensor network-based automatic monitoring system is designed for monitoring the life conditions of greenhouse vegetatables. The complete system architecture includes a group of sensor nodes, a base station, and an internet data center. For the design of wireless sensor node, the JN5139 micro-processor is adopted as the core component and the Zigbee protocol is used for wireless communication between nodes. With an ARM7 microprocessor and embedded ZKOS operating system, a proprietary gateway node is developed to achieve data influx, screen display, system configuration and GPRS based remote data forwarding. Through a Client/Server mode the management software for remote data center achieves real-time data distribution and time-series analysis. Besides, a GSM-short-message-based interface is developed for sending real-time environmental measurements, and for alarming when a measurement is beyond some pre-defined threshold. The whole system has been tested for over one year and satisfactory results have been observed, which indicate that this system is very useful for greenhouse environment monitoring. PMID:22163391

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

Development of intelligent instruments with embedded HTTP servers for control and data acquisition in a cryogenic setup--The hardware, firmware, and software implementation.

PubMed

Antony, Joby; Mathuria, D S; Datta, T S; Maity, Tanmoy

2015-12-01

The power of Ethernet for control and automation technology is being largely understood by the automation industry in recent times. Ethernet with HTTP (Hypertext Transfer Protocol) is one of the most widely accepted communication standards today. Ethernet is best known for being able to control through internet from anywhere in the globe. The Ethernet interface with built-in on-chip embedded servers ensures global connections for crate-less model of control and data acquisition systems which have several advantages over traditional crate-based control architectures for slow applications. This architecture will completely eliminate the use of any extra PLC (Programmable Logic Controller) or similar control hardware in any automation network as the control functions are firmware coded inside intelligent meters itself. Here, we describe the indigenously built project of a cryogenic control system built for linear accelerator at Inter University Accelerator Centre, known as "CADS," which stands for "Complete Automation of Distribution System." CADS deals with complete hardware, firmware, and software implementation of the automated linac cryogenic distribution system using many Ethernet based embedded cryogenic instruments developed in-house. Each instrument works as an intelligent meter called device-server which has the control functions and control loops built inside the firmware itself. Dedicated meters with built-in servers were designed out of ARM (Acorn RISC (Reduced Instruction Set Computer) Machine) and ATMEL processors and COTS (Commercially Off-the-Shelf) SMD (Surface Mount Devices) components, with analog sensor front-end and a digital back-end web server implementing remote procedure call over HTTP for digital control and readout functions. At present, 24 instruments which run 58 embedded servers inside, each specific to a particular type of sensor-actuator combination for closed loop operations, are now deployed and distributed across control LAN (Local Area Network). A group of six categories of such instruments have been identified for all cryogenic applications required for linac operation which were designed to build this medium-scale cryogenic automation setup. These devices have special features like remote rebooters, daughter boards for PIDs (Proportional Integral Derivative), etc., to operate them remotely in radiation areas and also have emergency switches by which each device can be taken to emergency mode temporarily. Finally, all the data are monitored, logged, controlled, and analyzed online at a central control room which has a user-friendly control interface developed using LabVIEW(®). This paper discusses the overall hardware, firmware, software design, and implementation for the cryogenics setup.

Development of intelligent instruments with embedded HTTP servers for control and data acquisition in a cryogenic setup—The hardware, firmware, and software implementation

NASA Astrophysics Data System (ADS)

Antony, Joby; Mathuria, D. S.; Datta, T. S.; Maity, Tanmoy

2015-12-01

The power of Ethernet for control and automation technology is being largely understood by the automation industry in recent times. Ethernet with HTTP (Hypertext Transfer Protocol) is one of the most widely accepted communication standards today. Ethernet is best known for being able to control through internet from anywhere in the globe. The Ethernet interface with built-in on-chip embedded servers ensures global connections for crate-less model of control and data acquisition systems which have several advantages over traditional crate-based control architectures for slow applications. This architecture will completely eliminate the use of any extra PLC (Programmable Logic Controller) or similar control hardware in any automation network as the control functions are firmware coded inside intelligent meters itself. Here, we describe the indigenously built project of a cryogenic control system built for linear accelerator at Inter University Accelerator Centre, known as "CADS," which stands for "Complete Automation of Distribution System." CADS deals with complete hardware, firmware, and software implementation of the automated linac cryogenic distribution system using many Ethernet based embedded cryogenic instruments developed in-house. Each instrument works as an intelligent meter called device-server which has the control functions and control loops built inside the firmware itself. Dedicated meters with built-in servers were designed out of ARM (Acorn RISC (Reduced Instruction Set Computer) Machine) and ATMEL processors and COTS (Commercially Off-the-Shelf) SMD (Surface Mount Devices) components, with analog sensor front-end and a digital back-end web server implementing remote procedure call over HTTP for digital control and readout functions. At present, 24 instruments which run 58 embedded servers inside, each specific to a particular type of sensor-actuator combination for closed loop operations, are now deployed and distributed across control LAN (Local Area Network). A group of six categories of such instruments have been identified for all cryogenic applications required for linac operation which were designed to build this medium-scale cryogenic automation setup. These devices have special features like remote rebooters, daughter boards for PIDs (Proportional Integral Derivative), etc., to operate them remotely in radiation areas and also have emergency switches by which each device can be taken to emergency mode temporarily. Finally, all the data are monitored, logged, controlled, and analyzed online at a central control room which has a user-friendly control interface developed using LabVIEW®. This paper discusses the overall hardware, firmware, software design, and implementation for the cryogenics setup.

Development of intelligent instruments with embedded HTTP servers for control and data acquisition in a cryogenic setup—The hardware, firmware, and software implementation

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

Antony, Joby; Mathuria, D. S.; Datta, T. S.

The power of Ethernet for control and automation technology is being largely understood by the automation industry in recent times. Ethernet with HTTP (Hypertext Transfer Protocol) is one of the most widely accepted communication standards today. Ethernet is best known for being able to control through internet from anywhere in the globe. The Ethernet interface with built-in on-chip embedded servers ensures global connections for crate-less model of control and data acquisition systems which have several advantages over traditional crate-based control architectures for slow applications. This architecture will completely eliminate the use of any extra PLC (Programmable Logic Controller) or similarmore » control hardware in any automation network as the control functions are firmware coded inside intelligent meters itself. Here, we describe the indigenously built project of a cryogenic control system built for linear accelerator at Inter University Accelerator Centre, known as “CADS,” which stands for “Complete Automation of Distribution System.” CADS deals with complete hardware, firmware, and software implementation of the automated linac cryogenic distribution system using many Ethernet based embedded cryogenic instruments developed in-house. Each instrument works as an intelligent meter called device-server which has the control functions and control loops built inside the firmware itself. Dedicated meters with built-in servers were designed out of ARM (Acorn RISC (Reduced Instruction Set Computer) Machine) and ATMEL processors and COTS (Commercially Off-the-Shelf) SMD (Surface Mount Devices) components, with analog sensor front-end and a digital back-end web server implementing remote procedure call over HTTP for digital control and readout functions. At present, 24 instruments which run 58 embedded servers inside, each specific to a particular type of sensor-actuator combination for closed loop operations, are now deployed and distributed across control LAN (Local Area Network). A group of six categories of such instruments have been identified for all cryogenic applications required for linac operation which were designed to build this medium-scale cryogenic automation setup. These devices have special features like remote rebooters, daughter boards for PIDs (Proportional Integral Derivative), etc., to operate them remotely in radiation areas and also have emergency switches by which each device can be taken to emergency mode temporarily. Finally, all the data are monitored, logged, controlled, and analyzed online at a central control room which has a user-friendly control interface developed using LabVIEW{sup ®}. This paper discusses the overall hardware, firmware, software design, and implementation for the cryogenics setup.« less

Facilitating and securing offline e-medicine service through image steganography.

PubMed

Kamal, A H M; Islam, M Mahfuzul

2014-06-01

E-medicine is a process to provide health care services to people using the Internet or any networking technology. In this Letter, a new idea is proposed to model the physical structure of the e-medicine system to better provide offline health care services. Smart cards are used to authenticate the user singly. A very unique technique is also suggested to verify the card owner's identity and to embed secret data to the card while providing patients' reports either at booths or at the e-medicine server system. The simulation results of card authentication and embedding procedure justify the proposed implementation.

Automatic Implementation of Ttethernet-Based Time-Triggered Avionics Applications

NASA Astrophysics Data System (ADS)

Gorcitz, Raul Adrian; Carle, Thomas; Lesens, David; Monchaux, David; Potop-Butucaruy, Dumitru; Sorel, Yves

2015-09-01

The design of safety-critical embedded systems such as those used in avionics still involves largely manual phases. But in avionics the definition of standard interfaces embodied in standards such as ARINC 653 or TTEthernet should allow the definition of fully automatic code generation flows that reduce the costs while improving the quality of the generated code, much like compilers have done when replacing manual assembly coding. In this paper, we briefly present such a fully automatic implementation tool, called Lopht, for ARINC653-based time-triggered systems, and then explain how it is currently extended to include support for TTEthernet networks.

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.

Light scattering optimization of chitin random network in ultrawhite beetle scales

NASA Astrophysics Data System (ADS)

Utel, Francesco; Cortese, Lorenzo; Pattelli, Lorenzo; Burresi, Matteo; Vignolini, Silvia; Wiersma, Diederik

2017-09-01

Among the natural white colored photonics structures, a bio-system has become of great interest in the field of disordered optical media: the scale of the white beetle Chyphochilus. Despite its low thickness, on average 7 μm, and low refractive index, this beetle exhibits extreme high brightness and unique whiteness. These properties arise from the interaction of light with a complex network of chitin nano filaments embedded in the interior of the scales. As it's been recently claimed, this could be a consequence of the peculiar morphology of the filaments network that, by means of high filling fraction (0.61) and structural anisotropy, optimizes the multiple scattering of light. We therefore performed a numerical analysis on the structural properties of the chitin network in order to understand their role in the enhancement of the scale scattering intensity. Modeling the filaments as interconnected rod shaped scattering centers, we numerically generated the spatial coordinates of the network components. Controlling the quantities that are claimed to play a fundamental role in the brightness and whiteness properties of the investigated system (filling fraction and average rods orientation, i.e. the anisotropy of the ensemble of scattering centers), we obtained a set of customized random networks. FDTD simulations of light transport have been performed on these systems, observing high reflectance for all the visible frequencies and proving the implemented algorithm to numerically generate the structures is suitable to investigate the dependence of reflectance by anisotropy.

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.

Clinical Named Entity Recognition Using Deep Learning Models.

PubMed

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER.

Patient centredness in integrated care: results of a qualitative study based on a systems theoretical framework

PubMed Central

Lüdecke, Daniel

2014-01-01

Introduction Health care providers seek to improve patient-centred care. Due to fragmentation of services, this can only be achieved by establishing integrated care partnerships. The challenge is both to control costs while enhancing the quality of care and to coordinate this process in a setting with many organisations involved. The problem is to establish control mechanisms, which ensure sufficiently consideration of patient centredness. Theory and methods Seventeen qualitative interviews have been conducted in hospitals of metropolitan areas in northern Germany. The documentary method, embedded into a systems theoretical framework, was used to describe and analyse the data and to provide an insight into the specific perception of organisational behaviour in integrated care. Results The findings suggest that integrated care partnerships rely on networks based on professional autonomy in the context of reliability. The relationships of network partners are heavily based on informality. This correlates with a systems theoretical conception of organisations, which are assumed autonomous in their decision-making. Conclusion and discussion Networks based on formal contracts may restrict professional autonomy and competition. Contractual bindings that suppress the competitive environment have negative consequences for patient-centred care. Drawbacks remain due to missing self-regulation of the network. To conclude, less regimentation of integrated care partnerships is recommended. PMID:25411573

Patient centredness in integrated care: results of a qualitative study based on a systems theoretical framework.

PubMed

Lüdecke, Daniel

2014-10-01

Health care providers seek to improve patient-centred care. Due to fragmentation of services, this can only be achieved by establishing integrated care partnerships. The challenge is both to control costs while enhancing the quality of care and to coordinate this process in a setting with many organisations involved. The problem is to establish control mechanisms, which ensure sufficiently consideration of patient centredness. Seventeen qualitative interviews have been conducted in hospitals of metropolitan areas in northern Germany. The documentary method, embedded into a systems theoretical framework, was used to describe and analyse the data and to provide an insight into the specific perception of organisational behaviour in integrated care. The findings suggest that integrated care partnerships rely on networks based on professional autonomy in the context of reliability. The relationships of network partners are heavily based on informality. This correlates with a systems theoretical conception of organisations, which are assumed autonomous in their decision-making. Networks based on formal contracts may restrict professional autonomy and competition. Contractual bindings that suppress the competitive environment have negative consequences for patient-centred care. Drawbacks remain due to missing self-regulation of the network. To conclude, less regimentation of integrated care partnerships is recommended.

A Distributed Data Acquisition System for the Sensor Network of the TAWARA_RTM Project

NASA Astrophysics Data System (ADS)

Fontana, Cristiano Lino; Donati, Massimiliano; Cester, Davide; Fanucci, Luca; Iovene, Alessandro; Swiderski, Lukasz; Moretto, Sandra; Moszynski, Marek; Olejnik, Anna; Ruiu, Alessio; Stevanato, Luca; Batsch, Tadeusz; Tintori, Carlo; Lunardon, Marcello

This paper describes a distributed Data Acquisition System (DAQ) developed for the TAWARA_RTM project (TAp WAter RAdioactivity Real Time Monitor). The aim is detecting the presence of radioactive contaminants in drinking water; in order to prevent deliberate or accidental threats. Employing a set of detectors, it is possible to detect alpha, beta and gamma radiations, from emitters dissolved in water. The Sensor Network (SN) consists of several heterogeneous nodes controlled by a centralized server. The SN cyber-security is guaranteed in order to protect it from external intrusions and malicious acts. The nodes were installed in different locations, along the water treatment processes, in the waterworks plant supplying the aqueduct of Warsaw, Poland. Embedded computers control the simpler nodes, and are directly connected to the SN. Local-PCs (LPCs) control the more complex nodes that consist signal digitizers acquiring data from several detectors. The DAQ in the LPC is split in several processes communicating with sockets in a local sub-network. Each process is dedicated to a very simple task (e.g. data acquisition, data analysis, hydraulics management) in order to have a flexible and fault-tolerant system. The main SN and the local DAQ networks are separated by data routers to ensure the cyber-security.

Clinical Named Entity Recognition Using Deep Learning Models

PubMed Central

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER. PMID:29854252

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

Use of artificial intelligence in analytical systems for the clinical laboratory

PubMed Central

Truchaud, Alain; Ozawa, Kyoichi; Pardue, Harry; Schnipelsky, Paul

1995-01-01

The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks. This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system. In the second part of the paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories. It is concluded that AI constitutes a collective form of intellectual propery, and that there is a need for better documentation, evaluation and regulation of the systems already being used in clinical laboratories. PMID:18924784

Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

PubMed Central

Pandey, Gaurav; Arora, Sonali; Manocha, Sahil; Whalen, Sean

2014-01-01

Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks. PMID:25275489

Dissecting psychiatric spectrum disorders by generative embedding☆☆☆

PubMed Central

Brodersen, Kay H.; Deserno, Lorenz; Schlagenhauf, Florian; Lin, Zhihao; Penny, Will D.; Buhmann, Joachim M.; Stephan, Klaas E.

2013-01-01

This proof-of-concept study examines the feasibility of defining subgroups in psychiatric spectrum disorders by generative embedding, using dynamical system models which infer neuronal circuit mechanisms from neuroimaging data. To this end, we re-analysed an fMRI dataset of 41 patients diagnosed with schizophrenia and 42 healthy controls performing a numerical n-back working-memory task. In our generative-embedding approach, we used parameter estimates from a dynamic causal model (DCM) of a visual–parietal–prefrontal network to define a model-based feature space for the subsequent application of supervised and unsupervised learning techniques. First, using a linear support vector machine for classification, we were able to predict individual diagnostic labels significantly more accurately (78%) from DCM-based effective connectivity estimates than from functional connectivity between (62%) or local activity within the same regions (55%). Second, an unsupervised approach based on variational Bayesian Gaussian mixture modelling provided evidence for two clusters which mapped onto patients and controls with nearly the same accuracy (71%) as the supervised approach. Finally, when restricting the analysis only to the patients, Gaussian mixture modelling suggested the existence of three patient subgroups, each of which was characterised by a different architecture of the visual–parietal–prefrontal working-memory network. Critically, even though this analysis did not have access to information about the patients' clinical symptoms, the three neurophysiologically defined subgroups mapped onto three clinically distinct subgroups, distinguished by significant differences in negative symptom severity, as assessed on the Positive and Negative Syndrome Scale (PANSS). In summary, this study provides a concrete example of how psychiatric spectrum diseases may be split into subgroups that are defined in terms of neurophysiological mechanisms specified by a generative model of network dynamics such as DCM. The results corroborate our previous findings in stroke patients that generative embedding, compared to analyses of more conventional measures such as functional connectivity or regional activity, can significantly enhance both the interpretability and performance of computational approaches to clinical classification. PMID:24363992

Software Development Technologies for Reactive, Real-Time, and Hybrid Systems: Summary of Research

NASA Technical Reports Server (NTRS)

Manna, Zohar

1998-01-01

This research is directed towards the implementation of a comprehensive deductive-algorithmic environment (toolkit) for the development and verification of high assurance reactive systems, especially concurrent, real-time, and hybrid systems. For this, we have designed and implemented the STCP (Stanford Temporal Prover) verification system. Reactive systems have an ongoing interaction with their environment, and their computations are infinite sequences of states. A large number of systems can be seen as reactive systems, including hardware, concurrent programs, network protocols, and embedded systems. Temporal logic provides a convenient language for expressing properties of reactive systems. A temporal verification methodology provides procedures for proving that a given system satisfies a given temporal property. The research covered necessary theoretical foundations as well as implementation and application issues.

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…

Travelling within the fetal gut: simple rules for an arduous journey

PubMed Central

2014-01-01

The complex physiology of the gastrointestinal tract is regulated by intricate neural networks embedded within the gut wall. How neural crest cells colonize the intestine to form the enteric nervous system is of great interest to developmental biologists, but also highly relevant for understanding gastrointestinal disorders. A recent paper in BMC Biology addresses this issue with live imaging of gut explants from mouse embryos. See research article: http://www.biomedcentral.com/1741-7007/12/23. PMID:25184534

Private Yet Abuse Resistant Open Publishing

NASA Astrophysics Data System (ADS)

Danezis, George; Laurie, Ben

We present the problem of abusive, off-topic or repetitive postings on open publishing websites, and the difficulties associated with filtering them out. We propose a scheme that extracts enough information to allow for filtering, based on users being embedded in a social network. Our system maintains the privacy of the poster, and does not require full identification to work well. We present a concrete realization using constructions based on discrete logarithms, and a sketch of how our scheme could be implemented in a centralized fashion.

Convolutional Neural Network on Embedded Linux(trademark) System-on-Chip: A Methodology and Performance Benchmark

DTIC Science & Technology

2016-05-01

A9 CPU and 15 W for the i7 CPU. A method of accelerating this computation is by using a customized hardware unit called a field- programmable gate...implementation of custom logic to accelerate com- putational workloads. This FPGA fabric, in addition to the standard programmable logic, contains 220...chip; field- programmable gate array Daniel Gebhardt U U U U 18 (619) 553-2786 INITIAL DISTRIBUTION 84300 Library (2) 85300 Archive/Stock (1

Convolutional Neural Network on Embedded Linux System-on-Chip: A Methodology and Performance Benchmark

DTIC Science & Technology

2016-05-01

A9 CPU and 15 W for the i7 CPU. A method of accelerating this computation is by using a customized hardware unit called a field- programmable gate...implementation of custom logic to accelerate com- putational workloads. This FPGA fabric, in addition to the standard programmable logic, contains 220...chip; field- programmable gate array Daniel Gebhardt U U U U 18 (619) 553-2786 INITIAL DISTRIBUTION 84300 Library (2) 85300 Archive/Stock (1

Banknote recognition: investigating processing and cognition framework using competitive neural network.

PubMed

Oyedotun, Oyebade K; Khashman, Adnan

2017-02-01

Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded. In a similar analogy, the robustness of intelligent systems to perform the task of banknote recognition should not collapse under some minimum level of partial occlusion. Artificial neural networks are intelligent systems which from inception have taken many important cues related to structure and learning rules from the human nervous/cognition processing system. Likewise, it has been shown that advances in artificial neural network simulations can help us understand the human nervous/cognition system even furthermore. In this paper, we investigate three cognition hypothetical frameworks to vision-based recognition of banknote denominations using competitive neural networks. In order to make the task more challenging and stress-test the investigated hypotheses, we also consider the recognition of occluded banknotes. The implemented hypothetical systems are tasked to perform fast recognition of banknotes with up to 75 % occlusion. The investigated hypothetical systems are trained on Nigeria's Naira banknotes and several experiments are performed to demonstrate the findings presented within this work.

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…

Indoor communications networks realized through hybrid free-space optical and Wi-Fi links

NASA Astrophysics Data System (ADS)

Liverman, Spencer; Wang, Qiwei; Chu, Yu-Chung; Borah, Anindita; Wang, Songtao; Natarajan, Arun; Nguyen, Thinh; Wang, Alan X.

2018-01-01

Recently, free-space optical (FSO) networks have been investigated as a potential replacement for traditional WiFi networks due to their large bandwidth potentials. However, FSO networks often suffer from a lack of mobility. We present a hybrid free-space optical and radio frequency (RF) system that we have named WiFO, which seamlessly integrates free-space optical links with pre-existing WiFi networks. The free-space optical link in this system utilizes infrared LEDs operating at a wavelength of 850nm and is capable of transmitting 50Mbps over a three-meter distance. In this hybrid system, optical transmitters are embedded periodically throughout the ceiling of a workspace. Each transmitter directs an optical signal downward in a diffuse light cone, establishing a line of sight optical link. Line of sight communications links have an intrinsic physical layer of security due to the fact that a user must be directly in the path of transmission to access the link; however, this feature also poses a challenge for mobility. In our system, if the free-space optical link is interrupted, a control algorithm redirects traffic over a pre-existing WiFi link ensuring uninterrupted transmissions. After data packets are received, acknowledgments are sent back to a central access point via a WiFi link. As the demand for wireless bandwidth continues to increase exponentially, utilizing the unregulated bandwidth contained within optical spectrum will become necessary. Our fully functional hybrid free-space optical and WiFi prototype system takes full advantage of the untapped bandwidth potential in the optical spectrum, while also maintaining the mobility inherent in WiFi networks.

Scotland's Knowledge Network: translating knowledge into action to improve quality of care.

PubMed

Wales, A; Graham, S; Rooney, K; Crawford, A

2012-11-01

The Knowledge Network (www.knowledge.scot.nhs.uk) is Scotland's online knowledge service for health and social care. It is designed to support practitioners to apply knowledge in frontline delivery of care, helping to translate knowledge into better health-care outcomes through safe, effective, person-centred care. The Knowledge Network helps to combine the worlds of evidence-based practice and quality improvement by providing access to knowledge about the effectiveness of clinical interventions ('know-what') and knowledge about how to implement this knowledge to support individual patients in working health-care environments ('know-how'). An 'evidence and guidance' search enables clinicians to quickly access quality-assured evidence and best practice, while point of care and mobile solutions provide knowledge in actionable formats to embed in clinical workflow. This research-based knowledge is complemented by social networking services and improvement tools which support the capture and exchange of knowledge from experience, facilitating practice change and systems improvement. In these cases, the Knowledge Network supports key components of the knowledge-to-action cycle--acquiring, creating, sharing and disseminating knowledge to improve performance and innovate. It provides a vehicle for implementing the recommendations of the national Knowledge into Action review, which outlines a new national approach to embedding knowledge in frontline practice and systems improvement.

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

Data fusion for target tracking and classification with wireless sensor network

NASA Astrophysics Data System (ADS)

Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

2016-10-01

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Microscale Mechanics of Actin Networks During Dynamic Assembly and Dissociation

NASA Astrophysics Data System (ADS)

Gurmessa, Bekele; Robertson-Anderson, Rae; Ross, Jennifer; Nguyen, Dan; Saleh, Omar

Actin is one of the key components of the cytoskeleton, enabling cells to move and divide while maintaining shape by dynamic polymerization, dissociation and crosslinking. Actin polymerization and network formation is driven by ATP hydrolysis and varies depending on the concentrations of actin monomers and crosslinking proteins. The viscoelastic properties of steady-state actin networks have been well-characterized, yet the mechanical properties of these non-equilibrium systems during dynamic assembly and disassembly remain to be understood. We use semipermeable microfluidic devices to induce in situ dissolution and re-polymerization of entangled and crosslinked actin networks, by varying ATP concentrations in real-time, while measuring the mechanical properties during disassembly and re-assembly. We use optical tweezers to sinusoidally oscillate embedded microspheres and measure the resulting force at set time-intervals and in different regions of the network during cyclic assembly/disassembly. We determine the time-dependent viscoelastic properties of non-equilibrium network intermediates and the reproducibility and homogeneity of network formation and dissolution. Results inform the role that cytoskeleton reorganization plays in the dynamic multifunctional mechanics of cells. NSF CAREER Award (DMR-1255446) and a Scialog Collaborative Innovation Award funded by Research Corporation for Scientific Advancement (Grant No. 24192).

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

Mapping the online communication patterns of political conversations

NASA Astrophysics Data System (ADS)

Borondo, J.; Morales, A. J.; Benito, R. M.; Losada, J. C.

2014-11-01

The structure of the social networks in which individuals are embedded influences their political choices and therefore their voting behavior. Nowadays, social media represent a new channel for individuals to communicate, what together with the availability of the data, makes it possible to analyze the online social network resulting from political conversations. Here, by taking advantage of the recently developed techniques to analyze complex systems, we map the communication patterns resulting from Spanish political conversations. We identify the different existing communities, building networks of communities, and finding that users cluster themselves in politically homogeneous networks. We found that while most of the collective attention was monopolized by politicians, traditional media accounts were still the preferred sources from which to propagate information. Finally, we propose methods to analyze the use of different languages, finding a clear trend from sympathizers of several political parties to overuse or infra-use each language. We conclude that, on the light of a social media analysis perspective, the political conversation is constrained by both ideology and language.

A Feasibility Study on Crash Avoidance at Four-Way Stop-Sign-Controlled Intersections Using Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Do Hyun; Choi, Kyoung Ho; Kim, Kyeong Tae; Li, Ki Joune

In this letter, we propose a novel approach using wireless sensor networks (WSNs) to enhance the safety and efficiency of four-way stop-sign-controlled (FWSC) intersections. The proposed algorithm provides right of way (RoW) and crash avoidance information by means of an intelligent WSN system. The system is composed of magnetic sensors, embedded in the center of a lane, with relay nodes and a base station placed on the side of the road. The experimental results show that the vehicle detection accuracy is over 99% and the sensor node battery life expectancy is over 3 years for traffic of 5, 800 vehicles per day. For the traffic application we consider, a strong effect is observed as the projected conflict rate was reduced by 72% compared to an FWSC intersection operated with only driver perception.

Quantum-enabled temporal and spectral mode conversion of microwave signals

PubMed Central

Andrews, R. W.; Reed, A. P.; Cicak, K.; Teufel, J. D.; Lehnert, K. W.

2015-01-01

Electromagnetic waves are ideal candidates for transmitting information in a quantum network as they can be routed rapidly and efficiently between locations using optical fibres or microwave cables. Yet linking quantum-enabled devices with cables has proved difficult because most cavity or circuit quantum electrodynamics systems used in quantum information processing can only absorb and emit signals with a specific frequency and temporal envelope. Here we show that the temporal and spectral content of microwave-frequency electromagnetic signals can be arbitrarily manipulated with a flexible aluminium drumhead embedded in a microwave circuit. The aluminium drumhead simultaneously forms a mechanical oscillator and a tunable capacitor. This device offers a way to build quantum microwave networks using separate and otherwise mismatched components. Furthermore, it will enable the preparation of non-classical states of motion by capturing non-classical microwave signals prepared by the most coherent circuit quantum electrodynamics systems. PMID:26617386

Applications of software-defined radio (SDR) technology in hospital environments.

PubMed

Chávez-Santiago, Raúl; Mateska, Aleksandra; Chomu, Konstantin; Gavrilovska, Liljana; Balasingham, Ilangko

2013-01-01

A software-defined radio (SDR) is a radio communication system where the major part of its functionality is implemented by means of software in a personal computer or embedded system. Such a design paradigm has the major advantage of producing devices that can receive and transmit widely different radio protocols based solely on the software used. This flexibility opens several application opportunities in hospital environments, where a large number of wired and wireless electronic devices must coexist in confined areas like operating rooms and intensive care units. This paper outlines some possible applications in the 2360-2500 MHz frequency band. These applications include the integration of wireless medical devices in a common communication platform for seamless interoperability, and cognitive radio (CR) for body area networks (BANs) and wireless sensor networks (WSNs) for medical environmental surveillance. The description of a proof-of-concept CR prototype is also presented.

Using OPC technology to support the study of advanced process control.

PubMed

Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

2015-03-01

OPC, originally the Object Linking and Embedding (OLE) for Process Control, brings a broad communication opportunity between different kinds of control systems. This paper investigates the use of OPC technology for the study of distributed control systems (DCS) as a cost effective and flexible research tool for the development and testing of advanced process control (APC) techniques in university research centers. Co-Simulation environment based on Matlab, LabVIEW and TCP/IP network is presented here. Several implementation issues and OPC based client/server control application have been addressed for TCP/IP network. A nonlinear boiler model is simulated as OPC server and OPC client is used for closed loop model identification, and to design a Model Predictive Controller. The MPC is able to control the NOx emissions in addition to drum water level and steam pressure. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Adaptive control of the packet transmission period with solar energy harvesting prediction in wireless sensor networks.

PubMed

Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

2015-04-24

A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%.

Agreement dynamics on interaction networks with diverse topologies

NASA Astrophysics Data System (ADS)

Barrat, Alain; Baronchelli, Andrea; Dall'Asta, Luca; Loreto, Vittorio

2007-06-01

We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence.

Evaluation of the applicability of the dual‐domain mass transfer model in porous media containing connected high‐conductivity channels

USGS Publications Warehouse

Liu, Gaisheng; Zheng, Chunmiao; Gorelick, Steven M.

2007-01-01

This paper evaluates the dual‐domain mass transfer (DDMT) model to represent transport processes when small‐scale high‐conductivity (K) preferential flow paths (PFPs) are present in a homogenous porous media matrix. The effects of PFPs upon solute transport were examined through detailed numerical experiments involving different realizations of PFP networks, PFP/matrix conductivity contrasts varying from 10:1 to 200:1, different magnitudes of effective conductivities, and a range of molecular diffusion coefficients. Results suggest that the DDMT model can reproduce both the near‐source peak and the downstream low‐concentration spreading observed in the embedded dendritic network when there are large conductivity contrasts between high‐K PFPs and the low‐K matrix. The accuracy of the DDMT model is also affected by the geometry of PFP networks and by the relative significance of the diffusion process in the network‐matrix system.

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

Barrett, Brian; Brightwell, Ronald B.; Grant, Ryan

This report presents a specification for the Portals 4 networ k programming interface. Portals 4 is intended to allow scalable, high-performance network communication betwee n nodes of a parallel computing system. Portals 4 is well suited to massively parallel processing and embedded syste ms. Portals 4 represents an adaption of the data movement layer developed for massively parallel processing platfor ms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4 is tarmore » geted to the next generation of machines employing advanced network interface architectures that support enh anced offload capabilities.« less

HTTM - Design and Implementation of a Type-2 Hypervisor for MIPS64 Based Systems

NASA Astrophysics Data System (ADS)

Ain, Qurrat ul; Anwar, Usama; Mehmood, Muhammad Amir; Waheed, Abdul

2017-01-01

Virtualization has emerged as an attractive software solution for many problems in server domain. Recently, it has started to enrich embedded systems domain by offering features such as hardware consolidation, security, and isolation. Our objective is to bring virtualization to high-end MIPS64 based systems, such as network routers, switches, wireless base station, etc. For this purpose a Type-2 hypervisor is a viable software solution which is easy to deploy and requires no changes in host system. In this paper we present the internal design HTTM -A Type-2 hypervisor for MIPS64 based systems and demonstrate its functional correctness by using Linux Testing Project (LTP) tests. Finally, we performed LMbench tests for performance evaluation.

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.

Weapon system simulation in flight (WaSiF)

NASA Astrophysics Data System (ADS)

Bartoldus, Klaus H.

2005-05-01

The research and technology demonstration program was co-funded by the Ministries of Defence of five European countries under the framework of the "EUropean Cooperation for the Long term in Defence" (EUCLID) MoU to include Germany, Italy, The Netherlands, Portugal and Turkey with considerable financial contribution from the industrial entities. EADS Military Aircraft Munich has led a team of seven industries and research centers, including Aermacchi of Italy, DutchSpace and NLR of The Netherlands, OGMA and INETI of Portugal and Marmara Research Center of Turkey. The purpose of the project was the design, realization and demonstration of an embedded real time simulation system allowing the combat training of operational aircrew in a virtual air defence scenario and threat environment against computer generated forces in the air and on the ground while flying on a real aircraft. The simulated scenario is focused on air-to-air beyond visual range engagements of fighter aircraft. WaSiF represents one of the first demonstrations of an advanced embedded real time training system onboard a fighter/training aircraft. The system is integrated onboard the MB339CX aircraft. The overall flight test activity covered a wide variety of test conditions for a total of 21 test flights; the operational airborne time of the WaSiF amounted to nearly 18 hours. The demonstration and evaluation were quite positive; the five-nation aircrew was very fond of their first encounter with the virtual world in the military flight training. A common view and approach towards Network Centric Warfare is but emerging. WaSiF in a future networked configuration holds lots of promise to serve the needs of Integrated Air Defence: Common training in a virtual environment.

Towards a new Mercator Observatory Control System

NASA Astrophysics Data System (ADS)

Pessemier, W.; Raskin, G.; Prins, S.; Saey, P.; Merges, F.; Padilla, J. P.; Van Winckel, H.; Waelkens, C.

2010-07-01

A new control system is currently being developed for the 1.2-meter Mercator Telescope at the Roque de Los Muchachos Observatory (La Palma, Spain). Formerly based on transputers, the new Mercator Observatory Control System (MOCS) consists of a small network of Linux computers complemented by a central industrial controller and an industrial real-time data communication network. Python is chosen as the high-level language to develop flexible yet powerful supervisory control and data acquisition (SCADA) software for the Linux computers. Specialized applications such as detector control, auto-guiding and middleware management are also integrated in the same Python software package. The industrial controller, on the other hand, is connected to the majority of the field devices and is targeted to run various control loops, some of which are real-time critical. Independently of the Linux distributed control system (DCS), this controller makes sure that high priority tasks such as the telescope motion, mirror support and hydrostatic bearing control are carried out in a reliable and safe way. A comparison is made between different controller technologies including a LabVIEW embedded system, a PROFINET Programmable Logic Controller (PLC) and motion controller, and an EtherCAT embedded PC (soft-PLC). As the latter is chosen as the primary platform for the lower level control, a substantial part of the software is being ported to the IEC 61131-3 standard programming languages. Additionally, obsolete hardware is gradually being replaced by standard industrial alternatives with fast EtherCAT communication. The use of Python as a scripting language allows a smooth migration to the final MOCS: finished parts of the new control system can readily be commissioned to replace the corresponding transputer units of the old control system with minimal downtime. In this contribution, we give an overview of the systems design, implementation details and the current status of the project.

Spaceport Processing System Development Lab

NASA Technical Reports Server (NTRS)

Dorsey, Michael

2013-01-01

The Spaceport Processing System Development Lab (SPSDL), developed and maintained by the Systems Hardware and Engineering Branch (NE-C4), is a development lab with its own private/restricted networks. A private/restricted network is a network with restricted or no communication with other networks. This allows users from different groups to work on their own projects in their own configured environment without interfering with others utilizing their resources in the lab. The different networks being used in the lab have no way to talk with each other due to the way they are configured, so how a user configures his software, operating system, or the equipment doesn't interfere or carry over on any of the other networks in the lab. The SPSDL is available for any project in KSC that is in need of a lab environment. My job in the SPSDL was to assist in maintaining the lab to make sure it's accessible for users. This includes, but is not limited to, making sure the computers in the lab are properly running and patched with updated hardware/software. In addition to this, I also was to assist users who had issues in utilizing the resources in the lab, which may include helping to configure a restricted network for their own environment. All of this was to ensure workers were able to use the SPSDL to work on their projects without difficulty which would in turn, benefit the work done throughout KSC. When I wasn't working in the SPSDL, I would instead help other coworkers with smaller tasks which included, but wasn't limited to, the proper disposal, moving of, or search for essential equipment. I also, during the free time I had, used NASA's resources to increase my knowledge and skills in a variety of subjects related to my major as a computer engineer, particularly in UNIX, Networking, and Embedded Systems.

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

Structural Health Monitoring of a Composite Panel Based on PZT Sensors and a Transfer Impedance Framework

PubMed Central

Dziendzikowski, Michal; Niedbala, Patryk; Kurnyta, Artur; Kowalczyk, Kamil; Dragan, Krzysztof

2018-01-01

One of the ideas for development of Structural Health Monitoring (SHM) systems is based on excitation of elastic waves by a network of PZT piezoelectric transducers integrated with the structure. In the paper, a variant of the so-called Transfer Impedance (TI) approach to SHM is followed. Signal characteristics, called the Damage Indices (DIs), were proposed for data presentation and analysis. The idea underlying the definition of DIs was to maintain most of the information carried by the voltage induced on PZT sensors by elastic waves. In particular, the DIs proposed in the paper should be sensitive to all types of damage which can influence the amplitude or the phase of the voltage induced on the sensor. Properties of the proposed DIs were investigated experimentally using a GFRP composite panel equipped with PZT networks attached to its surface and embedded into its internal structure. Repeatability and stability of DI indications under controlled conditions were verified in tests. Also, some performance indicators for surface-attached and structure-embedded sensors were obtained. The DIs’ behavior was dependent mostly on the presence of a simulated damage in the structure. Anisotropy of mechanical properties of the specimen, geometrical properties of PZT network as well as, to some extent, the technology of sensor integration with the structure were irrelevant for damage indication. This property enables the method to be used for damage detection and classification. PMID:29751664

Geometry in Biomimetic Network: Double Gyroid to Pseudo-Single Gyroid in Nanohybrid Materials

NASA Astrophysics Data System (ADS)

Hsueh, Han-Yu; Ho, Rong-Ming; Hung, Yu-Chueh; Ling, Yi-Chun; Hasegawa, Hirokazu

2013-03-01

Biological systems have developed delicately arranged micro- and architectures to produce striking optical effects since millions of years ago. Inspired by the textures of butterfly wings with single gyroid (SG) structure, herein, we aim to fabricate biocompatible and robust materials with SG-like structure in nanometer size so as to give new materials with unprecedented optical properties for applications. Biommicking from the biological photonic structures of butterfly wings, a double gyroid (DG) structure in nanometer size is obtained from the self-assembly of polystyrene-b-poly(L-lactide) (PS-PLLA). To acquire robust backbone networks, inorganic networks in polymer matrix are fabricated by using the hydrolyzed PS-PLLA with DG structure as a template for sol-gel reaction. Owing to the soft polymer matrix, two co-continuous inorganic networks embedded in the polymer matrix can be rearranged by thermal annealing at temperature above the glass transition of the polymer. Consequently, the rearrangement of these inorganic networks leads the formation of SG-like structure possessing unique nanohybrids with ordered texture. This unique nanomaterials with SG-like structure is referred as a pseudo-SG (p-SG) nanohybrids.

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.

Conceptual Design of a Communication-Based Deep Space Navigation Network

NASA Technical Reports Server (NTRS)

Anzalone, Evan J.; Chuang, C. H.

2012-01-01

As the need grows for increased autonomy and position knowledge accuracy to support missions beyond Earth orbit, engineers must push and develop more advanced navigation sensors and systems that operate independent of Earth-based analysis and processing. Several spacecraft are approaching this problem using inter-spacecraft radiometric tracking and onboard autonomous optical navigation methods. This paper proposes an alternative implementation to aid in spacecraft position fixing. The proposed method Network-Based Navigation technique takes advantage of the communication data being sent between spacecraft and between spacecraft and ground control to embed navigation information. The navigation system uses these packets to provide navigation estimates to an onboard navigation filter to augment traditional ground-based radiometric tracking techniques. As opposed to using digital signal measurements to capture inherent information of the transmitted signal itself, this method relies on the embedded navigation packet headers to calculate a navigation estimate. This method is heavily dependent on clock accuracy and the initial results show the promising performance of a notional system.

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

Review of battery powered embedded systems design for mission-critical low-power applications

NASA Astrophysics Data System (ADS)

Malewski, Matthew; Cowell, David M. J.; Freear, Steven

2018-06-01

The applications and uses of embedded systems is increasingly pervasive. Mission and safety critical systems relying on embedded systems pose specific challenges. Embedded systems is a multi-disciplinary domain, involving both hardware and software. Systems need to be designed in a holistic manner so that they are able to provide the desired reliability and minimise unnecessary complexity. The large problem landscape means that there is no one solution that fits all applications of embedded systems. With the primary focus of these mission and safety critical systems being functionality and reliability, there can be conflicts with business needs, and this can introduce pressures to reduce cost at the expense of reliability and functionality. This paper examines the challenges faced by battery powered systems, and then explores at more general problems, and several real-world embedded systems.

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

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.

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,…

Advanced Pedestrian Positioning System to Smartphones and Smartwatches.

PubMed

Correa, Alejandro; Munoz Diaz, Estefania; Bousdar Ahmed, Dina; Morell, Antoni; Lopez Vicario, Jose

2016-11-11

In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user's position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m 2 .

Robonaut 2 and Watson: Cognitive Dexterity for Future Exploration

NASA Technical Reports Server (NTRS)

Badger, Julia M.; Strawser, Philip; Farrell, Logan; Goza, S. Michael; Claunch, Charles A.; Chancey, Raphael; Potapinski, Russell

2018-01-01

Future exploration missions will dictate a level of autonomy never before experienced in human spaceflight. Mission plans involving the uncrewed phases of complex human spacecraft in deep space will require a coordinated autonomous capability to be able to maintain the spacecraft when ground control is not available. One promising direction involves embedding intelligence into the system design both through the employment of state-of-the-art system engineering principles as well as through the creation of a cognitive network between a smart spacecraft or habitat and embodiments of cognitive agents. The work described here details efforts to integrate IBM's Watson and other cognitive computing services into NASA Johnson Space Center (JSC)'s Robonaut 2 (R2) anthropomorphic robot. This paper also discusses future directions this work will take. A cognitive spacecraft management system that is able to seamlessly collect data from subsystems, determine corrective actions, and provide commands to enable those actions is the end goal. These commands could be to embedded spacecraft systems or to a set of robotic assets that are tied into the cognitive system. An exciting collaboration with Woodside provides a promising Earth-bound testing analog, as controlling and maintaining not normally manned off-shore platforms have similar constraints to the space missions described.

Research on numerical control system based on S3C2410 and MCX314AL

NASA Astrophysics Data System (ADS)

Ren, Qiang; Jiang, Tingbiao

2008-10-01

With the rapid development of micro-computer technology, embedded system, CNC technology and integrated circuits, numerical control system with powerful functions can be realized by several high-speed CPU chips and RISC (Reduced Instruction Set Computing) chips which have small size and strong stability. In addition, the real-time operating system also makes the attainment of embedded system possible. Developing the NC system based on embedded technology can overcome some shortcomings of common PC-based CNC system, such as the waste of resources, low control precision, low frequency and low integration. This paper discusses a hardware platform of ENC (Embedded Numerical Control) system based on embedded processor chip ARM (Advanced RISC Machines)-S3C2410 and DSP (Digital Signal Processor)-MCX314AL and introduces the process of developing ENC system software. Finally write the MCX314AL's driver under the embedded Linux operating system. The embedded Linux operating system can deal with multitask well moreover satisfy the real-time and reliability of movement control. NC system has the advantages of best using resources and compact system with embedded technology. It provides a wealth of functions and superior performance with a lower cost. It can be sure that ENC is the direction of the future development.

Advancing interconnect density for spiking neural network hardware implementations using traffic-aware adaptive network-on-chip routers.

PubMed

Carrillo, Snaider; Harkin, Jim; McDaid, Liam; Pande, Sandeep; Cawley, Seamus; McGinley, Brian; Morgan, Fearghal

2012-09-01

The brain is highly efficient in how it processes information and tolerates faults. Arguably, the basic processing units are neurons and synapses that are interconnected in a complex pattern. Computer scientists and engineers aim to harness this efficiency and build artificial neural systems that can emulate the key information processing principles of the brain. However, existing approaches cannot provide the dense interconnect for the billions of neurons and synapses that are required. Recently a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an efficient, robust computing platform. However, the use of the NoC as an interconnection fabric for large-scale SNNs demands a good trade-off between scalability, throughput, neuron/synapse ratio and power consumption. This paper presents a novel traffic-aware, adaptive NoC router, which forms part of a proposed embedded mixed-signal SNN architecture called EMBRACE (EMulating Biologically-inspiRed ArChitectures in hardwarE). The proposed adaptive NoC router provides the inter-neuron connectivity for EMBRACE, maintaining router communication and avoiding dropped router packets by adapting to router traffic congestion. Results are presented on throughput, power and area performance analysis of the adaptive router using a 90 nm CMOS technology which outperforms existing NoCs in this domain. The adaptive behaviour of the router is also verified on a Stratix II FPGA implementation of a 4 × 2 router array with real-time traffic congestion. The presented results demonstrate the feasibility of using the proposed adaptive NoC router within the EMBRACE architecture to realise large-scale SNNs on embedded hardware. Copyright © 2012 Elsevier Ltd. All rights reserved.

Public health preparedness in Alberta: a systems-level study.

PubMed

Moore, Douglas; Shiell, Alan; Noseworthy, Tom; Russell, Margaret; Predy, Gerald

2006-12-28

Recent international and national events have brought critical attention to the Canadian public health system and how prepared the system is to respond to various types of contemporary public health threats. This article describes the study design and methods being used to conduct a systems-level analysis of public health preparedness in the province of Alberta, Canada. The project is being funded under the Health Research Fund, Alberta Heritage Foundation for Medical Research. We use an embedded, multiple-case study design, integrating qualitative and quantitative methods to measure empirically the degree of inter-organizational coordination existing among public health agencies in Alberta, Canada. We situate our measures of inter-organizational network ties within a systems-level framework to assess the relative influence of inter-organizational ties, individual organizational attributes, and institutional environmental features on public health preparedness. The relative contribution of each component is examined for two potential public health threats: pandemic influenza and West Nile virus. The organizational dimensions of public health preparedness depend on a complex mix of individual organizational characteristics, inter-agency relationships, and institutional environmental factors. Our study is designed to discriminate among these different system components and assess the independent influence of each on the other, as well as the overall level of public health preparedness in Alberta. While all agree that competent organizations and functioning networks are important components of public health preparedness, this study is one of the first to use formal network analysis to study the role of inter-agency networks in the development of prepared public health systems.

'Multimorbidity' as the manifestation of network disturbances.

PubMed

Sturmberg, Joachim P; Bennett, Jeanette M; Martin, Carmel M; Picard, Martin

2017-02-01

We argue that 'multimorbidity' is the manifestation of interconnected physiological network processes within an individual in his or her socio-cultural environment. Networks include genomic, metabolomic, proteomic, neuroendocrine, immune and mitochondrial bioenergetic elements, as well as social, environmental and health care networks. Stress systems and other physiological mechanisms create feedback loops that integrate and regulate internal networks within the individual. Minor (e.g. daily hassles) and major (e.g. trauma) stressful life experiences perturb internal and social networks resulting in physiological instability with changes ranging from improved resilience to unhealthy adaptation and 'clinical disease'. Understanding 'multimorbidity' as a complex adaptive systems response to biobehavioural and socio-environmental networks is essential. Thus, designing integrative care delivery approaches that more adequately address the underlying disease processes as the manifestation of a state of physiological dysregulation is essential. This framework can shape care delivery approaches to meet the individual's care needs in the context of his or her underlying illness experience. It recognizes 'multimorbidity' and its symptoms as the end product of complex physiological processes, namely, stress activation and mitochondrial energetics, and suggests new opportunities for treatment and prevention. The future of 'multimorbidity' management might become much more discerning by combining the balancing of physiological dysregulation with targeted personalized biotechnology interventions such as small molecule therapeutics targeting specific cellular components of the stress response, with community-embedded interventions that involve addressing psycho-socio-cultural impediments that would aim to strengthen personal/social resilience and enhance social capital. © 2016 John Wiley & Sons, Ltd.

The Use of Video-Gaming Devices as a Motivation for Learning Embedded Systems Programming

ERIC Educational Resources Information Center

Gonzalez, J.; Pomares, H.; Damas, M.; Garcia-Sanchez,P.; Rodriguez-Alvarez, M.; Palomares, J. M.

2013-01-01

As embedded systems are becoming prevalent in everyday life, many universities are incorporating embedded systems-related courses in their undergraduate curricula. However, it is not easy to motivate students in such courses since they conceive of embedded systems as bizarre computing elements, different from the personal computers with which they…

Biologically Inspired Electronic, Photovoltaic and Microfluidic Devices Based on Aqueous Soft Matter

NASA Astrophysics Data System (ADS)

Koo, Hyung Jun

Hydrogels are a water-based soft material where three dimensional networks of hydrophilic polymer retain large amounts of water. We developed hydrogel based devices with new functionalities inspired by materials, structures and processes in nature. The advantages, such as softness, biocompatibility and high ionic conductivity, could enable hydrogels to be novel materials for biomimetic devices operated by ionic current. Moreover, microfluidic patterns are easily embedded in moldable hydrogels and allow for unique convective/diffusive transport mechanism in porous gel to be used for uniform delivery of reagent solution. We first developed and characterized a device with unidirectional ionic current flow across a SiO2/Gel junction, which showed highly efficient rectification of the ionic current by non-linear conductivity of SiO2 films. Addition of polyelectrolytes and salt to the gel layer significantly improved the performance of the new diode device because of the enhanced gel conductance. A soft matter based diode composed of hydrogel and liquid metal (eutectic gallium indium, EGaIn) was also presented. The ability to control the thickness, and thus resistivity, of an insulating oxide skin on the metal enables the current rectification. The effect of ionic conductivity and pH on the formation of the insulating oxide was investigated in a simple model system with liquid metal/electrolyte solution or hydrogel/Pt interfaces. Finally, we present a diode composed entirely of soft materials by replacing the platinum electrode with a second liquid metal electrode. A new type of hydrogel-based photovoltaic systems (HGPVs) was constructed. Two photosensitive ionized molecules embedded in aqueous gel served as photoactive species. The HGPVs showed performance comparable with or higher than those of some other biomimetic or ionic photovoltaic systems reported recently. We suggest a provisional mechanism of the device operation, based on a synergetic effect of the two dye molecules. To reduce the fabrication cost without efficiency loss, we found an inexpensive replacement of the expensive Pt counter-electrode with copper coated with carbon materials. Biologically derived photoactive molecules, such as Chlorophyll and Photosystem II, were successfully operated in the aqueous gel of such HGPVs. As a proof of demonstration of biomimetic structures, a light driven biomimetic reactor was developed by using hydrogel media with embedded photocatalytic TiO2 nanoparticles. Uniform supply of the reactants and extraction of the products was accomplished via a microfluidic channel network, broadly similar to the vein structure of live leaves. The dyes were transported in the gel between the microchannels and degraded by photocatalytic oxidation by the illuminated TiO2 particles. Quantitative analysis of the photocatalytic degradation rate of the injected dyes revealed that the microvascular reactor has high quantum efficiency per catalyst mass. Numerical modeling was performed to explore how a soluble reagent could be supplied rapidly and efficiently through microfluidic channel networks embedded in hydrogels. The computational model takes into account the fluid transport in porous media and the solute convection and diffusion, to simulate the solute distribution and outflux with time in microfluidic hydrogel media. The effect of the channel dimensions and shapes on mass transport rapidity and efficiency was quantitatively evaluated. Experimental data proved the validity of the time dependent concentration profile calculated by the simulation. Lastly, a microfluidic hydrogel solar cell with biomimetic regeneration functionality was demonstrated as a result of the above experimental and modeling studies. A new concept of open and replenishable photovoltaics was constructed on the basis of dye-sensitized solar cells. Photovoltaic reagents, dyes and redox electrolytes, were uniformly delivered via microfluidic networks embedded in a hydrogel, resulting in increase of photocurrent generation. The regeneration process was established, based on the pH dependence of adsorption/desorption kinetics of the dye molecules on a TiO2 photoanode. Complete and reliable recovery of the photocurrent after an accelerated photodegradation in the biomimetic photovoltaics was demonstrated.

Implementation of the Web-based laboratory

NASA Astrophysics Data System (ADS)

Ying, Liu; Li, Xunbo

2005-12-01

With the rapid developments of Internet technologies, remote access and control via Internet is becoming a reality. A realization of the web-based laboratory (the W-LAB) was presented. The main target of the W-LAB was to allow users to easily access and conduct experiments via the Internet. While realizing the remote communication, a system, which adopted the double client-server architecture, was introduced. It ensures the system better security and higher functionality. The experimental environment implemented in the W-Lab was integrated by both virtual lab and remote lab. The embedded technology in the W-LAB system as an economical and efficient way to build the distributed infrastructural network was introduced. Furthermore, by introducing the user authentication mechanism in the system, it effectively secures the remote communication.

OWL reasoning framework over big biological knowledge network.

PubMed

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

OWL Reasoning Framework over Big Biological Knowledge Network

PubMed Central

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

Design and implementation of a 3-lead ECG wireless remote monitoring system

NASA Astrophysics Data System (ADS)

Zhang, Shi; Jia, Xiaonan; Shang, Shuai

2006-11-01

Cardiovascular disease is one of the main diseases that menaces human health. It is necessary to monitor the patient's real-time electrocardiograph (ECG) for a long time to realize diagnosis and salvage. Remote ECG monitoring system is the solution. This paper introduces the design and implement of a 3-lead ECG wireless remote monitoring system. It collects, stores and transmits user's ECG which can be received by hospital and diagnosed by doctors. The development of the whole system contains three parts, the hardware and embedded software implementation of MONITOR, software of the MONITORING CENTER, and the routing software of NETWORK CENTER. According to the clinic experimentation, this system has high reliability and utility. There will be great social and economic benefit if this system is put into use.

A scaleable integrated sensing and control system for NDE, monitoring, and control of medium to very large composite smart structures

NASA Astrophysics Data System (ADS)

Jones, Jerry; Rhoades, Valerie; Arner, Radford; Clem, Timothy; Cuneo, Adam

2007-04-01

NDE measurements, monitoring, and control of smart and adaptive composite structures requires that the central knowledge system have an awareness of the entire structure. Achieving this goal necessitates the implementation of an integrated network of significant numbers of sensors. Additionally, in order to temporally coordinate the data from specially distributed sensors, the data must be time relevant. Early adoption precludes development of sensor technology specifically for this application, instead it will depend on the ability to utilize legacy systems. Partially supported by the U.S. Department of Commerce, National Institute of Standards and Technology, Advanced Technology Development Program (NIST-ATP), a scalable integrated system has been developed to implement monitoring of structural integrity and the control of adaptive/intelligent structures. The project, called SHIELD (Structural Health Identification and Electronic Life Determination), was jointly undertaken by: Caterpillar, N.A. Tech., Motorola, and Microstrain. SHIELD is capable of operation with composite structures, metallic structures, or hybrid structures. SHIELD consists of a real-time processing core on a Motorola MPC5200 using a C language based real-time operating system (RTOS). The RTOS kernel was customized to include a virtual backplane which makes the system completely scalable. This architecture provides for multiple processes to be operating simultaneously. They may be embedded as multiple threads on the core hardware or as separate independent processors connected to the core using a software driver called a NAT-Network Integrator (NATNI). NATNI's can be created for any communications application. In it's current embodiment, NATNI's have been created for CAN bus, TCP/IP (Ethernet) - both wired and 802.11 b and g, and serial communications using RS485 and RS232. Since SHIELD uses standard C language, it is easy to port any monitoring or control algorithm, thus providing for legacy technology which may use other hardware processors and various communications means. For example, two demonstrations of SHIELD have been completed, in January and May 2005 respectively. One demonstration used algorithms in C running in multiple threads in the SHIELD core and utilizing two different sensor networks, one CAN bus and one wireless. The second had algorithms operating in C on the SHIELD core and other algorithms running on multiple Texas Instruments DSP processors using a NATNI that communicated via wired TCP/IP. A key feature of SHIELD is the implementation of a wireless ZIGBEE (802.15.4) network for implementing large numbers of small, low cost, low power sensors communication via a meshstar wireless network. While SHIELD was designed to integrate with a wide variety of existing communications protocols, a ZIGBEE network capability was implemented specifically for SHIELD. This will facilitate the monitoring of medium to very large structures including marine applications, utility scale multi-megawatt wind energy systems, and aircraft/spacecraft. The SHIELD wireless network will facilitate large numbers of sensors (up to 32000), accommodate sensors embedded into the composite material, can communicate to both sensors and actuators, and prevents obsolescence by providing for re-programming of the nodes via remote RF communications. The wireless network provides for ultra-low energy use, spatial location, and accurate timestamping, utilizing the beaconing feature of ZIGBEE.

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.

Persistent topological features of dynamical systems

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

Maletić, Slobodan, E-mail: slobodan@hitsz.edu.cn; Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade; Zhao, Yi, E-mail: zhao.yi@hitsz.edu.cn

Inspired by an early work of Muldoon et al., Physica D 65, 1–16 (1993), we present a general method for constructing simplicial complex from observed time series of dynamical systems based on the delay coordinate reconstruction procedure. The obtained simplicial complex preserves all pertinent topological features of the reconstructed phase space, and it may be analyzed from topological, combinatorial, and algebraic aspects. In focus of this study is the computation of homology of the invariant set of some well known dynamical systems that display chaotic behavior. Persistent homology of simplicial complex and its relationship with the embedding dimensions are examinedmore » by studying the lifetime of topological features and topological noise. The consistency of topological properties for different dynamic regimes and embedding dimensions is examined. The obtained results shed new light on the topological properties of the reconstructed phase space and open up new possibilities for application of advanced topological methods. The method presented here may be used as a generic method for constructing simplicial complex from a scalar time series that has a number of advantages compared to the mapping of the same time series to a complex network.« less