Science.gov

Sample records for advanced intelligent network

  1. Macromolecular networks and intelligence in microorganisms

    PubMed Central

    Westerhoff, Hans V.; Brooks, Aaron N.; Simeonidis, Evangelos; García-Contreras, Rodolfo; He, Fei; Boogerd, Fred C.; Jackson, Victoria J.; Goncharuk, Valeri; Kolodkin, Alexey

    2014-01-01

    Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity – particularly activity of the human brain – with a phenomenon we call “intelligence.” Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as “human” and “brain” out of the defining features of “intelligence,” all forms of life – from microbes to humans – exhibit some or all characteristics consistent with “intelligence.” We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo. PMID:25101076

  2. Macromolecular networks and intelligence in microorganisms.

    PubMed

    Westerhoff, Hans V; Brooks, Aaron N; Simeonidis, Evangelos; García-Contreras, Rodolfo; He, Fei; Boogerd, Fred C; Jackson, Victoria J; Goncharuk, Valeri; Kolodkin, Alexey

    2014-01-01

    Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity - particularly activity of the human brain - with a phenomenon we call "intelligence." Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as "human" and "brain" out of the defining features of "intelligence," all forms of life - from microbes to humans - exhibit some or all characteristics consistent with "intelligence." We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo.

  3. Advances in intelligent sootblowing

    SciTech Connect

    Carter, H.R.

    2005-10-01

    Smart software now can decide whether a boiler section is sufficiently free of ash or slag, or needs to be cleaned by sootblowing. Such software constitutes the brains of integrated control systems capable of optimizing the order and frequency of sootblower operations and determining achievable cleanliness levels. Some of these systems can even perform adaptive set point control by basing cleanliness levels on real-time boiler operating parameters. The article describes the various modules of an intelligent sootblowing system (ISB) and gives results of the implementation of the system on PRB coal-burning boilers. 5 figs.

  4. Intelligent Control via Wireless Sensor Networks for Advanced Coal Combustion Systems

    SciTech Connect

    Aman Behal; Sunil Kumar; Goodarz Ahmadi

    2007-08-05

    Numerical Modeling of Solid Gas Flow, System Identification for purposes of modeling and control, and Wireless Sensor and Actor Network design were pursued as part of this project. Time series input-output data was obtained from NETL's Morgantown CFB facility courtesy of Dr. Lawrence Shadle. It was run through a nonlinear kernel estimator and nonparametric models were obtained for the system. Linear and first-order nonlinear kernels were then utilized to obtain a state-space description of the system. Neural networks were trained that performed better at capturing the plant dynamics. It is possible to use these networks to find a plant model and the inversion of this model can be used to control the system. These models allow one to compare with physics based models whose parameters can then be determined by comparing them against the available data based model. On a parallel track, Dr. Kumar designed an energy-efficient and reliable transport protocol for wireless sensor and actor networks, where the sensors could be different types of wireless sensors used in CFB based coal combustion systems and actors are more powerful wireless nodes to set up a communication network while avoiding the data congestion. Dr. Ahmadi's group studied gas solid flow in a duct. It was seen that particle concentration clearly shows a preferential distribution. The particles strongly interact with the turbulence eddies and are concentrated in narrow bands that are evolving with time. It is believed that observed preferential concentration is due to the fact that these particles are flung out of eddies by centrifugal force.

  5. Brain anatomical network and intelligence.

    PubMed

    Li, Yonghui; Liu, Yong; Li, Jun; Qin, Wen; Li, Kuncheng; Yu, Chunshui; Jiang, Tianzi

    2009-05-01

    Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. PMID:19492086

  6. Human intelligence and brain networks.

    PubMed

    Colom, Roberto; Karama, Sherif; Jung, Rex E; Haier, Richard J

    2010-01-01

    Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other.

  7. Advanced Artificial Intelligence Technology Testbed

    NASA Technical Reports Server (NTRS)

    Anken, Craig S.

    1993-01-01

    The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

  8. Wireless intelligent network: infrastructure before services?

    NASA Astrophysics Data System (ADS)

    Chu, Narisa N.

    1996-01-01

    The Wireless Intelligent Network (WIN) intends to take advantage of the Advanced Intelligent Network (AIN) concepts and products developed from wireline communications. However, progress of the AIN deployment has been slow due to the many barriers that exist in the traditional wireline carriers' deployment procedures and infrastructure. The success of AIN has not been truly demonstrated. The AIN objectives and directions are applicable to the wireless industry although the plans and implementations could be significantly different. This paper points out WIN characteristics in architecture, flexibility, deployment, and value to customers. In order to succeed, the technology driven AIN concept has to be reinforced by the market driven WIN services. An infrastructure suitable for the WIN will contain elements that are foreign to the wireline network. The deployment process is expected to seed with the revenue generated services. Standardization will be achieved by simplifying and incorporating the IS-41C, AIN, and Intelligent Network CS-1 recommendations. Integration of the existing and future systems impose the biggest challenge of all. Service creation has to be complemented with service deployment process which heavily impact the carriers' infrastructure. WIN deployment will likely start from an Intelligent Peripheral, a Service Control Point and migrate to a Service Node when sufficient triggers are implemented in the mobile switch for distributed call control. The struggle to move forward will not be based on technology, but rather on the impact to existing infrastructure.

  9. Advances in neural networks research: an introduction.

    PubMed

    Kozma, Robert; Bressler, Steven; Perlovsky, Leonid; Venayagamoorthy, Ganesh Kumar

    2009-01-01

    The present Special Issue "Advances in Neural Networks Research: IJCNN2009" provides a state-of-art overview of the field of neural networks. It includes 39 papers from selected areas of the 2009 International Joint Conference on Neural Networks (IJCNN2009). IJCNN2009 took place on June 14-19, 2009 in Atlanta, Georgia, USA, and it represents an exemplary collaboration between the International Neural Networks Society and the IEEE Computational Intelligence Society. Topics in this issue include neuroscience and cognitive science, computational intelligence and machine learning, hybrid techniques, nonlinear dynamics and chaos, various soft computing technologies, intelligent signal processing and pattern recognition, bioinformatics and biomedicine, and engineering applications. PMID:19632811

  10. Advances in neural networks research: an introduction.

    PubMed

    Kozma, Robert; Bressler, Steven; Perlovsky, Leonid; Venayagamoorthy, Ganesh Kumar

    2009-01-01

    The present Special Issue "Advances in Neural Networks Research: IJCNN2009" provides a state-of-art overview of the field of neural networks. It includes 39 papers from selected areas of the 2009 International Joint Conference on Neural Networks (IJCNN2009). IJCNN2009 took place on June 14-19, 2009 in Atlanta, Georgia, USA, and it represents an exemplary collaboration between the International Neural Networks Society and the IEEE Computational Intelligence Society. Topics in this issue include neuroscience and cognitive science, computational intelligence and machine learning, hybrid techniques, nonlinear dynamics and chaos, various soft computing technologies, intelligent signal processing and pattern recognition, bioinformatics and biomedicine, and engineering applications.

  11. Advancements in metro optical network architectures

    NASA Astrophysics Data System (ADS)

    Paraschis, Loukas

    2005-02-01

    This paper discusses the innovation in network architectures, and optical transport, that enables metropolitan networks to cost-effectively scale to hundreds Gb/s of capacity, and to hundreds km of reach, and to also meet the diverse service needs of enterprise and residential applications. A converged metro network, where Ethernet/IP services, and traditional TDM traffic operate over an intelligent WDM transport layer is increasingly becoming the most attractive architecture addressing the primary need of network operators for significantly improved capital and operational network cost. At the same time, this converged network has to leverage advanced technology, and introduce intelligence in order to significantly improve the deployment and manageability of WDM transport. The most important system advancements and the associated technology innovations that enhance the cost-effectiveness of metropolitan optical networks are being reviewed.

  12. Soft optics in intelligent optical networks

    NASA Astrophysics Data System (ADS)

    Shue, Chikong; Cao, Yang

    2001-10-01

    In addition to the recent advances in Hard-optics that pushes the optical transmission speed, distance, wave density and optical switching capacity, Soft-optics provides the necessary intelligence and control software that reduces operational costs, increase efficiency, and enhances revenue generating services by automating optimal optical circuit placement and restoration, and enabling value-added new services like Optical VPN. This paper describes the advances in 1) Overall Hard-optics and Soft-optics 2) Layered hierarchy of Soft-optics 3) Component of Soft-optics, including hard-optics drivers, Management Soft-optics, Routing Soft-optics and System Soft-optics 4) Key component of Routing and System Soft-optics, namely optical routing and signaling (including UNI/NNI and GMPLS signaling). In summary, the soft-optics on a new generation of OXC's enables Intelligent Optical Networks to provide just-in-time service delivery and fast restoration, and real-time capacity management that eliminates stranded bandwidth. It reduces operational costs and provides new revenue opportunities.

  13. Advanced Optical Network

    NASA Astrophysics Data System (ADS)

    Braun, Steve; Michael, Xuejun

    The following article describes an advanced dense wavelength division multiplexing (DWDM) Optical Network developed by L-3 Photonics. The network, configured as an amplified optical bus, carries traffic simultaneously in both directions, using multiple wavelengths. As a result, data distribution is of the form peer-to-multi-peer, it is protocol independent, and it is scalable. The network leverages the rapid growth in commercial optical technologies, including wavelength division multiplexing (WDM), and when applied to military and commercial platforms such as aircraft, ships, unmanned and other vehicles, provides a cost-effective, low-weight, high-speed, and high noise-immune data distribution system.

  14. Multidimensional neural growing networks and computer intelligence

    SciTech Connect

    Yashchenko, V.A.

    1995-03-01

    This paper examines information-computation processes in time and in space and some aspects of computer intelligence using multidimensional matrix neural growing networks. In particular, issues of object-oriented {open_quotes}thinking{close_quotes} of computers are considered.

  15. Intelligence Constraints on Terrorist Network Plots

    NASA Astrophysics Data System (ADS)

    Woo, Gordon

    Since 9/11, the western intelligence and law enforcement services have managed to interdict the great majority of planned attacks against their home countries. Network analysis shows that there are important intelligence constraints on the number and complexity of terrorist plots. If two many terrorists are involved in plots at a given time, a tipping point is reached whereby it becomes progressively easier for the dots to be joined and for the conspirators to be arrested, and for the aggregate evidence to secure convictions. Implications of this analysis are presented for the campaign to win hearts and minds.

  16. Distributed intelligent control and status networking

    NASA Technical Reports Server (NTRS)

    Fortin, Andre; Patel, Manoj

    1993-01-01

    Over the past two years, the Network Control Systems Branch (Code 532) has been investigating control and status networking technologies. These emerging technologies use distributed processing over a network to accomplish a particular custom task. These networks consist of small intelligent 'nodes' that perform simple tasks. Containing simple, inexpensive hardware and software, these nodes can be easily developed and maintained. Once networked, the nodes can perform a complex operation without a central host. This type of system provides an alternative to more complex control and status systems which require a central computer. This paper will provide some background and discuss some applications of this technology. It will also demonstrate the suitability of one particular technology for the Space Network (SN) and discuss the prototyping activities of Code 532 utilizing this technology.

  17. The intelligent user interface for NASA's advanced information management systems

    NASA Technical Reports Server (NTRS)

    Campbell, William J.; Short, Nicholas, Jr.; Rolofs, Larry H.; Wattawa, Scott L.

    1987-01-01

    NASA has initiated the Intelligent Data Management Project to design and develop advanced information management systems. The project's primary goal is to formulate, design and develop advanced information systems that are capable of supporting the agency's future space research and operational information management needs. The first effort of the project was the development of a prototype Intelligent User Interface to an operational scientific database, using expert systems and natural language processing technologies. An overview of Intelligent User Interface formulation and development is given.

  18. Application of CAN-bus Network in Intelligent parking

    NASA Astrophysics Data System (ADS)

    Jianjun, WU; Juan, Hu

    Convenient life makes intelligent parking every- where. This paper describes how to connect the various separate modern terminal of intelligent parking with CAN-bus network, and the competitive advantage of the system by using the CAN-bus network. From a technical point of view, this paper describes the development trend of intelligent parking in next few years.

  19. Association of structural global brain network properties with intelligence in normal aging.

    PubMed

    Fischer, Florian U; Wolf, Dominik; Scheurich, Armin; Fellgiebel, Andreas

    2014-01-01

    Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60-85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R) and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient) were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience.

  20. Intelligent Classification and Visualization of Network Scans

    SciTech Connect

    Chen, L; Muelder, C; Ma, K; Bartoletti, A

    2007-03-01

    Network scans are a common first step in a network intrusion attempt. In order to gain information about a potential network intrusion, it is beneficial to analyze these network scans. Statistical methods such as wavelet scalogram analysis have been used along with visualization techniques in previous methods. However, applying these statistical methods to reduce the data causes a substantial amount of data loss. This paper presents a study of using associative memory learning techniques to directly compare network scans in order to create a classification which can be used by itself or in conjunction with existing visualization techniques to better characterize the sources of these scans. This produces an integrated system of visual and intelligent analysis which is applicable to real world data.

  1. Transition from intelligence cycle to intelligence process: the network-centric intelligence in narrow seas

    NASA Astrophysics Data System (ADS)

    Büker, Engin

    2015-05-01

    The defence technologies which have been developing and changing rapidly, today make it difficult to be able to foresee the next environment and spectrum of warfare. When said change and development is looked in specific to the naval operations, it can be said that the possible battlefield and scenarios to be developed in the near and middle terms (5-20 years) are more clarified with compare to other force components. Network Centric Naval Warfare Concept that was developed for the floating, diving and flying fleet platforms which serves away from its own mainland for miles, will keep its significance in the future. Accordingly, Network Centric Intelligence structure completely integrating with the command and control systems will have relatively more importance. This study will firstly try to figure out the transition from the traditional intelligence cycle that is still used in conventional war to Network Centric Intelligence Production Process. In the last part, the use of this new approach on the base of UAV that is alternative to satellite based command control and data transfer systems in the joint operations in narrow seas will be examined, a model suggestion for the use of operative and strategic UAVs which are assured within the scope of the NATO AGS2 for this aim will be brought.

  2. Intelligent optical networking with photonic cross connections

    NASA Astrophysics Data System (ADS)

    Ceuppens, L.; Jerphagnon, Olivier L.; Lang, Jonathan; Banerjee, Ayan; Blumenthal, Daniel J.

    2002-09-01

    Optical amplification and dense wavelength division multiplexing (DWDM) have fundamentally changed optical transport networks. Now that these technologies are widely adopted, the bottleneck has moved from the outside line plant to nodal central offices, where electrical switching equipment has not kept pace. While OEO technology was (and still is) necessary for grooming and traffic aggregation, the transport network has dramatically changed, requiring a dramatic rethinking of how networks need to be designed and operated. While todays transport networks carry remarkable amounts of bandwidth, their optical layer is fundamentally static and provides for only simple point-to-point transport. Efficiently managing the growing number of wavelengths can only be achieved through a new breed of networking element. Photonic switching systems (PSS) can efficiently execute these functions because they are bit rate, wavelength, and protocol transparent. With their all-optical switch cores and interfaces, PSS can switch optical signals at various levels of granularity wavelength, sub band, and composite DWDM fiber levels. Though cross-connect systems with electrical switch cores are available, they perform these functions at very high capital costs and operational inefficiencies. This paper examines enabling technologies for deployment of intelligent optical transport networks (OTN), and takes a practical perspective on survivability architecture migration and implementation issues.

  3. Adaptive routing in wireless communication networks using swarm intelligence

    NASA Technical Reports Server (NTRS)

    Arabshahi, P.; Gray, A.; Kassabalidis, I.; Das, A.; Narayanan, S.; Sharkawi, M. El; Marks, R. J.

    2001-01-01

    In this paper we focus on the network routing problem, and survey swarm intelligent approaches for its efficient solution, after a brief overview of power-aware routing schemes, which are important in the network examples outlined above.

  4. The Design and Development of Intelligent Multimedia Network CAI Courseware

    ERIC Educational Resources Information Center

    Liu, Guangran; Yin, Hong

    2005-01-01

    Currently, the intelligence and individuality of multimedia network courseware is not enough, which limits the universal development of modern long-distance education. It is the best way to develop network courseware with intelligence. The paper basing on "College English" introduces the idea of design, system structure and development of process.

  5. "TIS": An Intelligent Gateway Computer for Information and Modeling Networks. Overview.

    ERIC Educational Resources Information Center

    Hampel, Viktor E.; And Others

    TIS (Technology Information System) is being used at the Lawrence Livermore National Laboratory (LLNL) to develop software for Intelligent Gateway Computers (IGC) suitable for the prototyping of advanced, integrated information networks. Dedicated to information management, TIS leads the user to available information resources, on TIS or…

  6. Development of a Real-Time Intelligent Network Environment.

    ERIC Educational Resources Information Center

    Gordonov, Anatoliy; Kress, Michael; Klibaner, Roberta

    This paper presents a model of an intelligent computer network that provides real-time evaluation of students' performance by incorporating intelligence into the application layer protocol. Specially designed drills allow students to independently solve a number of problems based on current lecture material; students are switched to the most…

  7. An advanced intelligent control system framework

    NASA Technical Reports Server (NTRS)

    Nemeth, ED; Anderson, Ronald R.; Maram, Jon; Norman, Arnie; Merrill, Walt

    1992-01-01

    A reusable rocket-engine intelligent control system (RREICS) framework was developed to a define a control framework for rocket-engine systems that reduces the required engine maintenance, extends the useful operating life, and maximizes the probability of mission success. The RREICS framework defines a controller that handles a rocket engine cluster as a single system rather than as a collection of individual engines. This enables the controller to alter individual engine operations in response to engine performance or integrity degradations while maintaining the propulsion subsystem external parameters at the levels required for mission success. A simplified model of a three engine cluster and the associated propulsion subsystem controller is also described.

  8. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    NASA Astrophysics Data System (ADS)

    Wali, W. A.; Hassan, K. H.; Cullen, J. D.; Al-Shamma'a, A. I.; Shaw, A.; Wylie, S. R.

    2011-08-01

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  9. The Role of Intelligent Agents in Advanced Information Systems

    NASA Technical Reports Server (NTRS)

    Kerschberg, Larry

    1999-01-01

    In this presentation we review the current ongoing research within George Mason University's (GMU) Center for Information Systems Integration and Evolution (CISE). We define characteristics of advanced information systems, discuss a family of agents for such systems, and show how GMU's Domain modeling tools and techniques can be used to define a product line Architecture for configuring NASA missions. These concepts can be used to define Advanced Engineering Environments such as those envisioned for NASA's new initiative for intelligent design and synthesis environments.

  10. Distributed intelligence in an astronomical Distributed Sensor Network

    NASA Astrophysics Data System (ADS)

    White, R. R.; Davis, H.; Vestrand, W. T.; Wozniak, P. R.

    2008-03-01

    The Telescope Alert Operations Network System (TALONS) was designed and developed in the year 2000, around the architectural principles of a distributed sensor network. This network supported the original Rapid Telescopes for Optical Response (RAPTOR) project goals; however, only with further development could TALONS meet the goals of the larger Thinking Telescope Project. The complex objectives of the Thinking Telescope project required a paradigm shift in the software architecture - the centralised intelligence merged into the TALONS network operations could no longer meet all of the new requirements. The intelligence needed to be divorced from the network operations and developed as a series of peripheral intelligent agents, distributing the decision making and analytical processes based on the temporal volatility of the data. This paper is presented as only one part of the poster from the workshop and in it we will explore the details of this architecture and how that merges with the current Thinking Telescope system to meet our project goals.

  11. Emotional intelligence skills for maintaining social networks in healthcare organizations.

    PubMed

    Freshman, Brenda; Rubino, Louis

    2004-01-01

    For healthcare organizations to survive in these increasingly challenging times, leadership and management must face mounting interpersonal concerns. The authors present the boundaries of internal and external social networks with respect to leadership and managerial functions: Social networks within the organization are stretched by reductions in available resources and structural ambiguity, whereas external social networks are stressed by interorganizational competitive pressures. The authors present the development of emotional intelligence skills in employees as a strategic training objective that can strengthen the internal and external social networks of healthcare organizations. The authors delineate the unique functions of leadership and management with respect to the application of emotional intelligence skills and discuss training and future research implications for emotional intelligence skill sets and social networks.

  12. Supporting tactical intelligence using collaborative environments and social networking

    NASA Astrophysics Data System (ADS)

    Wollocko, Arthur B.; Farry, Michael P.; Stark, Robert F.

    2013-05-01

    Modern military environments place an increased emphasis on the collection and analysis of intelligence at the tactical level. The deployment of analytical tools at the tactical level helps support the Warfighter's need for rapid collection, analysis, and dissemination of intelligence. However, given the lack of experience and staffing at the tactical level, most of the available intelligence is not exploited. Tactical environments are staffed by a new generation of intelligence analysts who are well-versed in modern collaboration environments and social networking. An opportunity exists to enhance tactical intelligence analysis by exploiting these personnel strengths, but is dependent on appropriately designed information sharing technologies. Existing social information sharing technologies enable users to publish information quickly, but do not unite or organize information in a manner that effectively supports intelligence analysis. In this paper, we present an alternative approach to structuring and supporting tactical intelligence analysis that combines the benefits of existing concepts, and provide detail on a prototype system embodying that approach. Since this approach employs familiar collaboration support concepts from social media, it enables new-generation analysts to identify the decision-relevant data scattered among databases and the mental models of other personnel, increasing the timeliness of collaborative analysis. Also, the approach enables analysts to collaborate visually to associate heterogeneous and uncertain data within the intelligence analysis process, increasing the robustness of collaborative analyses. Utilizing this familiar dynamic collaboration environment, we hope to achieve a significant reduction of time and skill required to glean actionable intelligence in these challenging operational environments.

  13. Neural Network Based Intelligent Sootblowing System

    SciTech Connect

    Mark Rhode

    2005-04-01

    , particulate matter is also a by-product of coal combustion. Modern day utility boilers are usually fitted with electrostatic precipitators to aid in the collection of particulate matter. Although extremely efficient, these devices are sensitive to rapid changes in inlet mass concentration as well as total mass loading. Traditionally, utility boilers are equipped with devices known as sootblowers, which use, steam, water or air to dislodge and clean the surfaces within the boiler and are operated based upon established rule or operator's judgment. Poor sootblowing regimes can influence particulate mass loading to the electrostatic precipitators. The project applied a neural network intelligent sootblowing system in conjunction with state-of-the-art controls and instruments to optimize the operation of a utility boiler and systematically control boiler slagging/fouling. This optimization process targeted reduction of NOx of 30%, improved efficiency of 2% and a reduction in opacity of 5%. The neural network system proved to be a non-invasive system which can readily be adapted to virtually any utility boiler. Specific conclusions from this neural network application are listed below. These conclusions should be used in conjunction with the specific details provided in the technical discussions of this report to develop a thorough understanding of the process.

  14. Intelligent Microscopes: Recent And Near-Future Advances

    NASA Astrophysics Data System (ADS)

    Prewitt, Judith M. S.

    1980-02-01

    Robert Hooke conjectured about fluid circulation in plants as well as in animals in Micrographia in a passage that is equally important as a commentary on the dependence, not of technology on science, but of science on technology: It seems very probable that Nature has ... very many appropriated instruments and contrivances, whereby to bring her designs and end to pass, which 'tis not improbable but that some diligent observer, if helped with better Microscopes, may in time detect.This paper, written in the form of a scientific poem, reviews the current and near- future state-of-the-art of automated intelligent microscopes based on computer science and technology. The basic concepts of computer intelligence for cytology and histology are presented and elaborated. Limitations of commercial devices and research proto- types are examined (Dx), and remedies are suggested (Rx). The course of action pro- posed and being undertaken constitutes an original contribution toward advancing the state-of-the-science, in the hope of advancing the state-of-the-art of medicine.With rapid, contemporary advances in both science and technology, it may now be appropriate to modify Hooke's passage:It seems very probable that Nature has ... very many appropriated instruments and contrivances, whereby to bring her designs and end to pass, which 'tis not improbable but that some diligent observer, if helped with Intelligent Microscopes, may in time detect.

  15. Recent Advances in the Theory and Measurement of Intelligence.

    ERIC Educational Resources Information Center

    Eysenck, Hans

    1984-01-01

    Illustrates kinds of intelligence tests, discussing factors indicating intelligence: genetics, reaction time, latency and amplitude, and variability. Lists the advantages and disadvantages of the intelligence tests mentioned. (CI)

  16. Behavioral networks as a model for intelligent agents

    NASA Technical Reports Server (NTRS)

    Sliwa, Nancy E.

    1990-01-01

    On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs.

  17. Intelligence and the Tuning-In of Brain Networks

    ERIC Educational Resources Information Center

    Stankov, Lazar; Danthiir, Vanessa; Williams, Leanne M.; Pallier, Gerry; Roberts, Richard D.; Gordon, Evian

    2006-01-01

    The phase-synchronization of Gamma-band oscillations has been postulated as a mechanism of "network binding" and implicated in various aspects of perception, memory, and cognition. The current study investigates a possible link between Gamma synchrony and individual differences in intelligence within the theory of fluid and crystallized…

  18. Intelligent Engine Systems: Thermal Management and Advanced Cooling

    NASA Technical Reports Server (NTRS)

    Bergholz, Robert

    2008-01-01

    The objective of the Advanced Turbine Cooling and Thermal Management program is to develop intelligent control and distribution methods for turbine cooling, while achieving a reduction in total cooling flow and assuring acceptable turbine component safety and reliability. The program also will develop embedded sensor technologies and cooling system models for real-time engine diagnostics and health management. Both active and passive control strategies will be investigated that include the capability of intelligent modulation of flow quantities, pressures, and temperatures both within the supply system and at the turbine component level. Thermal management system concepts were studied, with a goal of reducing HPT blade cooling air supply temperature. An assessment will be made of the use of this air by the active clearance control system as well. Turbine component cooling designs incorporating advanced, high-effectiveness cooling features, will be evaluated. Turbine cooling flow control concepts will be studied at the cooling system level and the component level. Specific cooling features or sub-elements of an advanced HPT blade cooling design will be downselected for core fabrication and casting demonstrations.

  19. An intelligent service-based network architecture for wearable robots.

    PubMed

    Lee, Ka Keung; Zhang, Ping; Xu, Yangsheng; Liang, Bin

    2004-08-01

    We are developing a novel robot concept called the wearable robot. Wearable robots are mobile information devices capable of supporting remote communication and intelligent interaction between networked entities. In this paper, we explore the possible functions of such a robotic network and will present a distributed network architecture based on service components. In order to support the interaction and communication between the components in the wearable robot system, we have developed an intelligent network architecture. This service-based architecture involves three major mechanisms. The first mechanism involves the use of a task coordinator service such that the execution of the services can be managed using a priority queue. The second mechanism enables the system to automatically push the required service proxy to the client intelligently based on certain system-related conditions. In the third mechanism, we allow the system to automatically deliver services based on contextual information. Using a fuzzy-logic-based decision making system, the matching service can determine whether the service should be automatically delivered utilizing the information provided by the service, client, lookup service, and context sensors. An application scenario has been implemented to demonstrate the feasibility of this distributed service-based robot architecture. The architecture is implemented as extensions to the Jini network model.

  20. An artificial neural network controller for intelligent transportation systems applications

    SciTech Connect

    Vitela, J.E.; Hanebutte, U.R.; Reifman, J.

    1996-04-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems applications. The AICC is based on a simple nonlinear model of the vehicle dynamics. A Neural Network Controller (NNC) code developed at Argonne National Laboratory to control discrete dynamical systems was used for this purpose. In order to test the NNC, an AICC-simulator containing graphical displays was developed for a system of two vehicles driving in a single lane. Two simulation cases are shown, one involving a lead vehicle with constant velocity and the other a lead vehicle with varying acceleration. More realistic vehicle dynamic models will be considered in future work.

  1. Advanced aerospace composite material structural design using artificial intelligent technology

    SciTech Connect

    Sun, S.H.; Chen, J.L.; Hwang, W.C.

    1993-12-31

    Due to the complexity in the prediction of property and behavior, composite material has not substituted for metal widely yet, though it has high specific-strength and high specific-modulus that are more important in the aerospace industry. In this paper two artificial intelligent techniques, the expert systems and neural network technology, were introduced to the structural design of composite material. Expert System which has good ability in symbolic processing can helps us to solve problem by saving experience and knowledge. It is, therefore, a reasonable way to combine expert system technology to tile composite structural design. The development of a prototype expert system to help designer during the process of composite structural design is presented. Neural network is a network similar to people`s brain that can simulate the thinking way of people and has the ability of learning from the training data by adapting the weights of network. Because of the bottleneck in knowledge acquisition processes, the application of neural network and its learning ability to strength design of composite structures are presented. Some examples are in this paper to demonstrate the idea.

  2. Evolution of the Intelligent Telecommunications Network.

    ERIC Educational Resources Information Center

    Mayo, John S.

    1982-01-01

    Discusses the evolution of the nationwide telecommunications network, including key technologies (transistors, communications satellites, and lasers), putting these technologies together, current and future services, and challenges for the future. (JN)

  3. Vehicle routing, traveler adis, network modeling, and advanced control systems. Transportation research record

    SciTech Connect

    Not Available

    1992-01-01

    Partial Contents: Efficient Search Algorithms for Route Information Services of Direct and Connecting Transit Trips; Influence of Urban Network Features on Quality of Traffic Service; Advanced Traffic Management System: Real-Time Network Traffic Simulation Methodology with a Massively Parallel Computing Architecture; Standards for Intelligent Vehicle-Highway System Technologies; Concept of Super Smart Vehicle Systems and Their Relation to Advanced Vehicle Control Systems; Intelligent Vehicle-Highway System Safety: A Demonstration Specification and Hazard Analysis; California INRAD Project: Demonstration of Low-Power Inductive Loop Radio Technology for Use in Traffic Operations; Development of Prototype Knowledge-Based Expert System for Managing Congestion on Massachusetts Turnpike; Artificial Intelligence-Based System Representation and Search Procedures for Transit Route Network Design; Evaluation of Artificial Neural Network Applications in Transportation Engineering; Validation of an Expert System: A Case Study; Model for Optimum Deployment of Emergency Repair Trucks: Application in Electric Utility Industry.

  4. Intelligent Network Management and Functional Cerebellum Synthesis

    NASA Technical Reports Server (NTRS)

    Loebner, Egon E.

    1989-01-01

    Transdisciplinary modeling of the cerebellum across histology, physiology, and network engineering provides preliminary results at three organization levels: input/output links to central nervous system networks; links between the six neuron populations in the cerebellum; and computation among the neurons of the populations. Older models probably underestimated the importance and role of climbing fiber input which seems to supply write as well as read signals, not just to Purkinje but also to basket and stellate neurons. The well-known mossy fiber-granule cell-Golgi cell system should also respond to inputs originating from climbing fibers. Corticonuclear microcomplexing might be aided by stellate and basket computation and associate processing. Technological and scientific implications of the proposed cerebellum model are discussed.

  5. Evaluating neural networks and artificial intelligence systems

    NASA Astrophysics Data System (ADS)

    Alberts, David S.

    1994-02-01

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

  6. Distributed intelligence in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Shirgur, Vikram L.; Rao, Vittal S.

    2003-07-01

    With the advent of new wireless standards, faster microprocessors and smart sensors, it has become possible to construct wireless sensor networks with ample processing and communication capability. Our thrust in this paper is toward implementing a collaborative processing system for wireless sensor networks. A number of research groups have developed algorithms for applications such as target tracking and location, environment monitoring, and health monitoring of structures. What has been missing is a distributed sensor processing system which provides a framework for these algorithms to function. The system described here borrows heavily from the parallel processing sphere especially the Parallel Virtual Machine (PVM) system developed by ORNL. To facilitate distribution of computational resources, a new algorithm has been proposed for efficient distribution with the use of minimum system resources, in other words, determining an optimal set of nodes which can handle the distributed computation. For this purpose, we assign costs to the various parameters of interest in the network such as the node energy level, the communication energy cost/complexity and resource availability. We then arrive at a cost function by assigning suitable weights to these costs and choose only those nodes whose cost function evaluates to above a particular threshold value. Implementation of typical feature extraction algorithms such as the Discrete Fourier Transform (DFT) and the Discrete Wavelet Transform (DWT) are discussed.

  7. Intelligent Nanoparticles for Advanced Drug Delivery in Cancer Treatment

    PubMed Central

    Spencer, David S.; Puranik, Amey S.; Peppas, Nicholas A.

    2015-01-01

    Treatment of cancer using nanoparticle-based approaches relies on the rational design of carriers with respect to size, charge, and surface properties. Polymer-based nanomaterials, inorganic materials such as gold, iron oxide, and silica as well as carbon based materials such as carbon nanotubes and graphene are being explored extensively for cancer therapy. The challenges associated with the delivery of these nanoparticles depend greatly on the type of cancer and stage of development. This review highlights design considerations to develop nanoparticle-based approaches for overcoming physiological hurdles in cancer treatment, as well as emerging research in engineering advanced delivery systems for the treatment of primary, metastatic, and multidrug resistant cancers. A growing understanding of cancer biology will continue to foster development of intelligent nanoparticle-based therapeutics that take into account diverse physiological contexts of changing disease states to improve treatment outcomes. PMID:25621200

  8. Intelligent Wireless Sensor Networks for System Health Monitoring

    NASA Technical Reports Server (NTRS)

    Alena, Rick

    2011-01-01

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

  9. Intelligent Resource Management for Local Area Networks: Approach and Evolution

    NASA Technical Reports Server (NTRS)

    Meike, Roger

    1988-01-01

    The Data Management System network is a complex and important part of manned space platforms. Its efficient operation is vital to crew, subsystems and experiments. AI is being considered to aid in the initial design of the network and to augment the management of its operation. The Intelligent Resource Management for Local Area Networks (IRMA-LAN) project is concerned with the application of AI techniques to network configuration and management. A network simulation was constructed employing real time process scheduling for realistic loads, and utilizing the IEEE 802.4 token passing scheme. This simulation is an integral part of the construction of the IRMA-LAN system. From it, a causal model is being constructed for use in prediction and deep reasoning about the system configuration. An AI network design advisor is being added to help in the design of an efficient network. The AI portion of the system is planned to evolve into a dynamic network management aid. The approach, the integrated simulation, project evolution, and some initial results are described.

  10. Development of an advanced intelligent robot navigation system

    SciTech Connect

    Hai Quan Dai; Dalton, G.R.; Tulenko, J.; Crane, C.C. III )

    1992-01-01

    As part of the US Department of Energy's Robotics for Advanced Reactors Project, the authors are in the process of assembling an advanced intelligent robotic navigation and control system based on previous work performed on this project in the areas of computer control, database access, graphical interfaces, shared data and computations, computer vision for positions determination, and sonar-based computer navigation systems. The system will feature three levels of goals: (1) high-level system for management of lower level functions to achieve specific functional goals; (2) intermediate level of goals such as position determination, obstacle avoidance, and discovering unexpected objects; and (3) other supplementary low-level functions such as reading and recording sonar or video camera data. In its current phase, the Cybermotion K2A mobile robot is not equipped with an onboard computer system, which will be included in the final phase. By that time, the onboard system will play important roles in vision processing and in robotic control communication.

  11. Neural networks: A versatile tool from artificial intelligence

    SciTech Connect

    Yama, B.R.; Lineberry, G.T.

    1996-12-31

    Artificial Intelligence research has produced several tools for commercial application in recent years. Artificial Neural Networks (ANNs), Fuzzy Logic, and Expert Systems are some of the techniques that are widely used today in various fields of engineering and business. Among these techniques, ANNs are gaining popularity due to their learning and other brain-like capabilities. Within the mining industry, ANN technology is being utilized with large payoffs for real-time process control applications. In this paper, a brief introduction to ANNs and the associated terminology is given. The neural network development process is outlined, followed by the back-propagation learning algorithm. Next, the development of two multi-layer, feed-forward neural networks is described and the results axe presented. One network is developed for prediction of strength of intact rock specimens, and another network is developed for prediction of mineral concentrations. Preliminary results indicate a predictive error less than 10% using cross-validation on a limited data set. The performance of the neural network for prediction of mineral concentrations was compared with kriging. It was found that the neural network performed not only satisfactorily, but in some cases performed better than, the kriging model.

  12. The application of artificial intelligence techniques to large distributed networks

    NASA Technical Reports Server (NTRS)

    Dubyah, R.; Smith, T. R.; Star, J. L.

    1985-01-01

    Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

  13. Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network.

    PubMed

    Budiharto, Widodo

    2015-01-01

    For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system. PMID:26089863

  14. Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network

    PubMed Central

    2015-01-01

    For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system. PMID:26089863

  15. Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network.

    PubMed

    Budiharto, Widodo

    2015-01-01

    For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system.

  16. A Review of the Kaufman Adolescent and Adult Intelligence Test: An Advancement in Cognitive Assessment?

    ERIC Educational Resources Information Center

    Flanagan, Dawn P.; Alfonso, Vincent C.; Flanagan, Rosemary

    1994-01-01

    Reviews Kaufman Adolescent and Adult Intelligence Test (KAIT), a new assessment of cognitive function for technical qualities such as reliability, validity, and standardization characters. Concludes that KAIT represents advancements in cognitive assessment but cannot be regarded as superior to existing intelligence measures until data is available…

  17. Building a functional multiple intelligences theory to advance educational neuroscience

    PubMed Central

    Cerruti, Carlo

    2013-01-01

    A key goal of educational neuroscience is to conduct constrained experimental research that is theory-driven and yet also clearly related to educators’ complex set of questions and concerns. However, the fields of education, cognitive psychology, and neuroscience use different levels of description to characterize human ability. An important advance in research in educational neuroscience would be the identification of a cognitive and neurocognitive framework at a level of description relatively intuitive to educators. I argue that the theory of multiple intelligences (MI; Gardner, 1983), a conception of the mind that motivated a past generation of teachers, may provide such an opportunity. I criticize MI for doing little to clarify for teachers a core misunderstanding, specifically that MI was only an anatomical map of the mind but not a functional theory that detailed how the mind actually processes information. In an attempt to build a “functional MI” theory, I integrate into MI basic principles of cognitive and neural functioning, namely interregional neural facilitation and inhibition. In so doing I hope to forge a path toward constrained experimental research that bears upon teachers’ concerns about teaching and learning. PMID:24391613

  18. Building a functional multiple intelligences theory to advance educational neuroscience.

    PubMed

    Cerruti, Carlo

    2013-01-01

    A key goal of educational neuroscience is to conduct constrained experimental research that is theory-driven and yet also clearly related to educators' complex set of questions and concerns. However, the fields of education, cognitive psychology, and neuroscience use different levels of description to characterize human ability. An important advance in research in educational neuroscience would be the identification of a cognitive and neurocognitive framework at a level of description relatively intuitive to educators. I argue that the theory of multiple intelligences (MI; Gardner, 1983), a conception of the mind that motivated a past generation of teachers, may provide such an opportunity. I criticize MI for doing little to clarify for teachers a core misunderstanding, specifically that MI was only an anatomical map of the mind but not a functional theory that detailed how the mind actually processes information. In an attempt to build a "functional MI" theory, I integrate into MI basic principles of cognitive and neural functioning, namely interregional neural facilitation and inhibition. In so doing I hope to forge a path toward constrained experimental research that bears upon teachers' concerns about teaching and learning.

  19. Building a functional multiple intelligences theory to advance educational neuroscience.

    PubMed

    Cerruti, Carlo

    2013-01-01

    A key goal of educational neuroscience is to conduct constrained experimental research that is theory-driven and yet also clearly related to educators' complex set of questions and concerns. However, the fields of education, cognitive psychology, and neuroscience use different levels of description to characterize human ability. An important advance in research in educational neuroscience would be the identification of a cognitive and neurocognitive framework at a level of description relatively intuitive to educators. I argue that the theory of multiple intelligences (MI; Gardner, 1983), a conception of the mind that motivated a past generation of teachers, may provide such an opportunity. I criticize MI for doing little to clarify for teachers a core misunderstanding, specifically that MI was only an anatomical map of the mind but not a functional theory that detailed how the mind actually processes information. In an attempt to build a "functional MI" theory, I integrate into MI basic principles of cognitive and neural functioning, namely interregional neural facilitation and inhibition. In so doing I hope to forge a path toward constrained experimental research that bears upon teachers' concerns about teaching and learning. PMID:24391613

  20. Intelligent Facial Recognition Systems: Technology advancements for security applications

    SciTech Connect

    Beer, C.L.

    1993-07-01

    Insider problems such as theft and sabotage can occur within the security and surveillance realm of operations when unauthorized people obtain access to sensitive areas. A possible solution to these problems is a means to identify individuals (not just credentials or badges) in a given sensitive area and provide full time personnel accountability. One approach desirable at Department of Energy facilities for access control and/or personnel identification is an Intelligent Facial Recognition System (IFRS) that is non-invasive to personnel. Automatic facial recognition does not require the active participation of the enrolled subjects, unlike most other biological measurement (biometric) systems (e.g., fingerprint, hand geometry, or eye retinal scan systems). It is this feature that makes an IFRS attractive for applications other than access control such as emergency evacuation verification, screening, and personnel tracking. This paper discusses current technology that shows promising results for DOE and other security applications. A survey of research and development in facial recognition identified several companies and universities that were interested and/or involved in the area. A few advanced prototype systems were also identified. Sandia National Laboratories is currently evaluating facial recognition systems that are in the advanced prototype stage. The initial application for the evaluation is access control in a controlled environment with a constant background and with cooperative subjects. Further evaluations will be conducted in a less controlled environment, which may include a cluttered background and subjects that are not looking towards the camera. The outcome of the evaluations will help identify areas of facial recognition systems that need further development and will help to determine the effectiveness of the current systems for security applications.

  1. Intrusion-Tolerant Location Information Services in Intelligent Vehicular Networks

    NASA Astrophysics Data System (ADS)

    Yan, Gongjun; Yang, Weiming; Shaner, Earl F.; Rawat, Danda B.

    Intelligent Vehicular Networks, known as Vehicle-to-Vehicle and Vehicle-to-Roadside wireless communications (also called Vehicular Ad hoc Networks), are revolutionizing our daily driving with better safety and more infortainment. Most, if not all, applications will depend on accurate location information. Thus, it is of importance to provide intrusion-tolerant location information services. In this paper, we describe an adaptive algorithm that detects and filters the false location information injected by intruders. Given a noisy environment of mobile vehicles, the algorithm estimates the high resolution location of a vehicle by refining low resolution location input. We also investigate results of simulations and evaluate the quality of the intrusion-tolerant location service.

  2. Sensors-network and its application in the intelligent storage security

    NASA Astrophysics Data System (ADS)

    Zhang, Qingying; Nicolescu, Mihai; Jiang, Xia; Zhang, Ying; Yue, Weihong; Xiao, Weihong

    2004-11-01

    Intelligent storage systems run on different advanced technologies, such as linear layout, business intelligence and data mining. Security, the basic desire of the storage system, has been focused on with the indraught of multimedia communication technology and sensors" network. Along with the developing of science and the social demands, multifarious alarming system has been designed and improved to be intelligentized, modularized and have network connections. It is of great moment to make the storage, and further more, the logistics system more and more efficient and perfect with modern science and technology. Diversified information on the spot should be caught by different kinds of sensors. Those signals are treated and communicated to the control center to give the further actions. For fire-proofing, broad-spectrum gas sensors, fume sensors, flame sensors and temperature sensors are used to catch the information in their own ways. Once the fire is taken somewhere, the sensors work by the fume, temperature, and flame as well as gas immediately. Meanwhile the intelligent control system starts. It passes the tidings to the center unit. At the same time, it sets those movable walls on to work quickly to obstruct the fire"s spreading. While for guarding the warehouse against theft, cut-off sensors, body sensors, photoelectric sensors, microwave sensors and closed-circuit television as well as electronic clocks are available to monitor the warehouse reasonably. All of those sensors work in a net way. The intelligent control system is made with a digital circuit instead of traditional switch one. This system can work in a better way in many cases. Its reliability is high and the cost is low.

  3. Advanced Networks in Motion Mobile Sensorweb

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Stewart, David H.

    2011-01-01

    Advanced mobile networking technology applicable to mobile sensor platforms was developed, deployed and demonstrated. A two-tier sensorweb design was developed. The first tier utilized mobile network technology to provide mobility. The second tier, which sits above the first tier, utilizes 6LowPAN (Internet Protocol version 6 Low Power Wireless Personal Area Networks) sensors. The entire network was IPv6 enabled. Successful mobile sensorweb system field tests took place in late August and early September of 2009. The entire network utilized IPv6 and was monitored and controlled using a remote Web browser via IPv6 technology. This paper describes the mobile networking and 6LowPAN sensorweb design, implementation, deployment and testing as well as wireless systems and network monitoring software developed to support testing and validation.

  4. Functional brain networks related to individual differences in human intelligence at rest.

    PubMed

    Hearne, Luke J; Mattingley, Jason B; Cocchi, Luca

    2016-01-01

    Intelligence is a fundamental ability that sets humans apart from other animal species. Despite its importance in defining human behaviour, the neural networks responsible for intelligence are not well understood. The dominant view from neuroimaging work suggests that intelligent performance on a range of tasks is underpinned by segregated interactions in a fronto-parietal network of brain regions. Here we asked whether fronto-parietal interactions associated with intelligence are ubiquitous, or emerge from more widespread associations in a task-free context. First we undertook an exploratory mapping of the existing literature on functional connectivity associated with intelligence. Next, to empirically test hypotheses derived from the exploratory mapping, we performed network analyses in a cohort of 317 unrelated participants from the Human Connectome Project. Our results revealed a novel contribution of across-network interactions between default-mode and fronto-parietal networks to individual differences in intelligence at rest. Specifically, we found that greater connectivity in the resting state was associated with higher intelligence scores. Our findings highlight the need to broaden the dominant fronto-parietal conceptualisation of intelligence to encompass more complex and context-specific network dynamics. PMID:27561736

  5. Functional brain networks related to individual differences in human intelligence at rest

    PubMed Central

    Hearne, Luke J.; Mattingley, Jason B.; Cocchi, Luca

    2016-01-01

    Intelligence is a fundamental ability that sets humans apart from other animal species. Despite its importance in defining human behaviour, the neural networks responsible for intelligence are not well understood. The dominant view from neuroimaging work suggests that intelligent performance on a range of tasks is underpinned by segregated interactions in a fronto-parietal network of brain regions. Here we asked whether fronto-parietal interactions associated with intelligence are ubiquitous, or emerge from more widespread associations in a task-free context. First we undertook an exploratory mapping of the existing literature on functional connectivity associated with intelligence. Next, to empirically test hypotheses derived from the exploratory mapping, we performed network analyses in a cohort of 317 unrelated participants from the Human Connectome Project. Our results revealed a novel contribution of across-network interactions between default-mode and fronto-parietal networks to individual differences in intelligence at rest. Specifically, we found that greater connectivity in the resting state was associated with higher intelligence scores. Our findings highlight the need to broaden the dominant fronto-parietal conceptualisation of intelligence to encompass more complex and context-specific network dynamics. PMID:27561736

  6. Tracking Vehicle in GSM Network to Support Intelligent Transportation Systems

    NASA Astrophysics Data System (ADS)

    Koppanyi, Z.; Lovas, T.; Barsi, A.; Demeter, H.; Beeharee, A.; Berenyi, A.

    2012-07-01

    The penetration of GSM capable devices is very high, especially in Europe. To exploit the potential of turning these mobile devices into dynamic data acquisition nodes that provides valuable data for Intelligent Transportation Systems (ITS), position information is needed. The paper describes the basic operation principles of the GSM system and provides an overview on the existing methods for deriving location data in the network. A novel positioning solution is presented that rely on handover (HO) zone measurements; the zone geometry properties are also discussed. A new concept of HO zone sequence recognition is introduced that involves application of Probabilistic Deterministic Finite State Automata (PDFA). Both the potential commercial applications and the use of the derived position data in ITS is discussed for tracking vehicles and monitoring traffic flow. As a practical cutting edge example, the integration possibility of the technology in the SafeTRIP platform (developed in an EC FP7 project) is presented.

  7. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    SciTech Connect

    Saini, K. K.; Saini, Sanju

    2008-10-07

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  8. A Workflow-based Intelligent Network Data Movement Advisor with End-to-end Performance Optimization

    SciTech Connect

    Zhu, Michelle M.; Wu, Chase Q.

    2013-11-07

    Next-generation eScience applications often generate large amounts of simulation, experimental, or observational data that must be shared and managed by collaborative organizations. Advanced networking technologies and services have been rapidly developed and deployed to facilitate such massive data transfer. However, these technologies and services have not been fully utilized mainly because their use typically requires significant domain knowledge and in many cases application users are even not aware of their existence. By leveraging the functionalities of an existing Network-Aware Data Movement Advisor (NADMA) utility, we propose a new Workflow-based Intelligent Network Data Movement Advisor (WINDMA) with end-to-end performance optimization for this DOE funded project. This WINDMA system integrates three major components: resource discovery, data movement, and status monitoring, and supports the sharing of common data movement workflows through account and database management. This system provides a web interface and interacts with existing data/space management and discovery services such as Storage Resource Management, transport methods such as GridFTP and GlobusOnline, and network resource provisioning brokers such as ION and OSCARS. We demonstrate the efficacy of the proposed transport-support workflow system in several use cases based on its implementation and deployment in DOE wide-area networks.

  9. Intelligent Middle-Ware Architecture for Mobile Networks

    NASA Astrophysics Data System (ADS)

    Rayana, Rayene Ben; Bonnin, Jean-Marie

    Recent advances in electronic and automotive industries as well as in wireless telecommunication technologies have drawn a new picture where each vehicle became “fully networked”. Multiple stake-holders (network operators, drivers, car manufacturers, service providers, etc.) will participate in this emerging market, which could grow following various models. To free the market from technical constraints, it is important to return to the basics of the Internet, i.e., providing embarked devices with a fully operational Internet connectivity (IPv6).

  10. Hybrid Intelligent Perception System: Intelligent perception through combining Artificial Neural Networks and an Expert System

    SciTech Connect

    Glover, C.W.; Spelt, P.F.

    1990-01-01

    This paper presents a report of work-in-progress on a project to combine Artificial Neural Networks (ANNs) and Expert Systems (ESs) into a hybrid, self-improving pattern recognition system. The purpose of this project is to explore methods of combining multiple classifiers into a Hybrid Intelligent Perception (HIP) System. The central research issue to be addressed for a multiclassifier hybrid system is whether such a system can perform better than the two classifiers taken by themselves. ANNs and ESs have different strengths and weaknesses, which are being exploited in this project in such a way that they are complementary to each other: Strengths in one system make up for weaknesses in the other, and vice versa. There is presently considerable interest in the AI community in ways to exploit the strengths of these methodologies to produce an intelligent system which is more robust and flexible than one using either technology alone. Perception, which involves both data-driven (bottom-up) and concept-driven (top-down) processing, is a process which seems especially well-suited to displaying the capabilities of such a hybrid system. This work has been funded for the past six months by an Oak Ridge National Laboratory seed grant, and most of the system components are operating in both the PC and the hypercube computer environments. Here we report on the efforts to develop the low-level ANNs and a graphic representation of their knowledge, and discuss ways of using an ES to integrate and supervise the entire system. 11 refs., 3 figs.

  11. Advanced Optical Burst Switched Network Concepts

    NASA Astrophysics Data System (ADS)

    Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

    would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.

  12. Worldwide Intelligent Systems: Approaches to Telecommunications and Network Management. Frontiers in Artificial Intelligence and Applications, Volume 24.

    ERIC Educational Resources Information Center

    Liebowitz, Jay, Ed.; Prerau, David S., Ed.

    This is an international collection of 12 papers addressing artificial intelligence (AI) and knowledge technology applications in telecommunications and network management. It covers the latest and emerging AI technologies as applied to the telecommunications field. The papers are: "The Potential for Knowledge Technology in Telecommunications: A…

  13. Advanced networks and computing in healthcare

    PubMed Central

    Ackerman, Michael

    2011-01-01

    As computing and network capabilities continue to rise, it becomes increasingly important to understand the varied applications for using them to provide healthcare. The objective of this review is to identify key characteristics and attributes of healthcare applications involving the use of advanced computing and communication technologies, drawing upon 45 research and development projects in telemedicine and other aspects of healthcare funded by the National Library of Medicine over the past 12 years. Only projects publishing in the professional literature were included in the review. Four projects did not publish beyond their final reports. In addition, the authors drew on their first-hand experience as project officers, reviewers and monitors of the work. Major themes in the corpus of work were identified, characterizing key attributes of advanced computing and network applications in healthcare. Advanced computing and network applications are relevant to a range of healthcare settings and specialties, but they are most appropriate for solving a narrower range of problems in each. Healthcare projects undertaken primarily to explore potential have also demonstrated effectiveness and depend on the quality of network service as much as bandwidth. Many applications are enabling, making it possible to provide service or conduct research that previously was not possible or to achieve outcomes in addition to those for which projects were undertaken. Most notable are advances in imaging and visualization, collaboration and sense of presence, and mobility in communication and information-resource use. PMID:21486877

  14. Intelligent routing protocol for ad hoc wireless network

    NASA Astrophysics Data System (ADS)

    Peng, Chaorong; Chen, Chang Wen

    2006-05-01

    A novel routing scheme for mobile ad hoc networks (MANETs), which combines hybrid and multi-inter-routing path properties with a distributed topology discovery route mechanism using control agents is proposed in this paper. In recent years, a variety of hybrid routing protocols for Mobile Ad hoc wireless networks (MANETs) have been developed. Which is proactively maintains routing information for a local neighborhood, while reactively acquiring routes to destinations beyond the global. The hybrid protocol reduces routing discovery latency and the end-to-end delay by providing high connectivity without requiring much of the scarce network capacity. On the other side the hybrid routing protocols in MANETs likes Zone Routing Protocol still need route "re-discover" time when a route between zones link break. Sine the topology update information needs to be broadcast routing request on local zone. Due to this delay, the routing protocol may not be applicable for real-time data and multimedia communication. We utilize the advantages of a clustering organization and multi-routing path in routing protocol to achieve several goals at the same time. Firstly, IRP efficiently saves network bandwidth and reduces route reconstruction time when a routing path fails. The IRP protocol does not require global periodic routing advertisements, local control agents will automatically monitor and repair broke links. Secondly, it efficiently reduces congestion and traffic "bottlenecks" for ClusterHeads in clustering network. Thirdly, it reduces significant overheads associated with maintaining clusters. Fourthly, it improves clusters stability due to dynamic topology changing frequently. In this paper, we present the Intelligent Routing Protocol. First, we discuss the problem of routing in ad hoc networks and the motivation of IRP. We describe the hierarchical architecture of IRP. We describe the routing process and illustrate it with an example. Further, we describe the control manage

  15. Intercluster Connection in Cognitive Wireless Mesh Networks Based on Intelligent Network Coding

    NASA Astrophysics Data System (ADS)

    Chen, Xianfu; Zhao, Zhifeng; Jiang, Tao; Grace, David; Zhang, Honggang

    2009-12-01

    Cognitive wireless mesh networks have great flexibility to improve spectrum resource utilization, within which secondary users (SUs) can opportunistically access the authorized frequency bands while being complying with the interference constraint as well as the QoS (Quality-of-Service) requirement of primary users (PUs). In this paper, we consider intercluster connection between the neighboring clusters under the framework of cognitive wireless mesh networks. Corresponding to the collocated clusters, data flow which includes the exchanging of control channel messages usually needs four time slots in traditional relaying schemes since all involved nodes operate in half-duplex mode, resulting in significant bandwidth efficiency loss. The situation is even worse at the gateway node connecting the two colocated clusters. A novel scheme based on network coding is proposed in this paper, which needs only two time slots to exchange the same amount of information mentioned above. Our simulation shows that the network coding-based intercluster connection has the advantage of higher bandwidth efficiency compared with the traditional strategy. Furthermore, how to choose an optimal relaying transmission power level at the gateway node in an environment of coexisting primary and secondary users is discussed. We present intelligent approaches based on reinforcement learning to solve the problem. Theoretical analysis and simulation results both show that the intelligent approaches can achieve optimal throughput for the intercluster relaying in the long run.

  16. Advanced Scientific Computing Research Network Requirements

    SciTech Connect

    Bacon, Charles; Bell, Greg; Canon, Shane; Dart, Eli; Dattoria, Vince; Goodwin, Dave; Lee, Jason; Hicks, Susan; Holohan, Ed; Klasky, Scott; Lauzon, Carolyn; Rogers, Jim; Shipman, Galen; Skinner, David; Tierney, Brian

    2013-03-08

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.

  17. Advance Network Reservation and Provisioning for Science

    SciTech Connect

    Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex

    2009-07-10

    We are witnessing a new era that offers new opportunities to conduct scientific research with the help of recent advancements in computational and storage technologies. Computational intensive science spans multiple scientific domains, such as particle physics, climate modeling, and bio-informatics simulations. These large-scale applications necessitate collaborators to access very large data sets resulting from simulations performed in geographically distributed institutions. Furthermore, often scientific experimental facilities generate massive data sets that need to be transferred to validate the simulation data in remote collaborating sites. A major component needed to support these needs is the communication infrastructure which enables high performance visualization, large volume data analysis, and also provides access to computational resources. In order to provide high-speed on-demand data access between collaborating institutions, national governments support next generation research networks such as Internet 2 and ESnet (Energy Sciences Network). Delivering network-as-a-service that provides predictable performance, efficient resource utilization and better coordination between compute and storage resources is highly desirable. In this paper, we study network provisioning and advanced bandwidth reservation in ESnet for on-demand high performance data transfers. We present a novel approach for path finding in time-dependent transport networks with bandwidth guarantees. We plan to improve the current ESnet advance network reservation system, OSCARS [3], by presenting to the clients, the possible reservation options and alternatives for earliest completion time and shortest transfer duration. The Energy Sciences Network (ESnet) provides high bandwidth connections between research laboratories and academic institutions for data sharing and video/voice communication. The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) establishes

  18. Advanced fault diagnosis methods in molecular networks.

    PubMed

    Habibi, Iman; Emamian, Effat S; Abdi, Ali

    2014-01-01

    Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally.

  19. Advance lightpath provisioning in interdomain optical networks

    NASA Astrophysics Data System (ADS)

    Hafid, A.; Maach, A.; Khair, M. G.; Drissi, J.

    2005-11-01

    In interconnected optical networks, users submit lightpath requests at the time they wish to establish the lightpath. The service provider consults the information gathered by the interdomain routing protocols for available resources. For each request, the network must decide immediately whether to accept or reject the request. In this model, there is always the uncertainty of whether the user will be able to establish the desired lightpath at the desired time or not. Furthermore, in the context of a number of applications, e.g., grid applications, users need to set up lightpaths in advance to perform their activities that are planned in advance. We propose a new interdomain routing protocol called Advance Optical Routing Border Gateway Protocol (AORBGP) and a scheme that allows the setup of interdomain lightpaths in advance. AORBGP allows gathering information about interdomain paths and availability of wavelengths in the future. The proposed advance lightpath setup scheme makes use of AORBGP to get information about available resources (i.e., wavelengths) required to process lightpath setup requests. One of the key innovations of the scheme is that it provides the user with alternatives, carefully selected, when his or her request cannot be accommodated because of resource shortages. Indeed, the scheme provides the user with options to set up a lightpath later than the requested start time or with shorter duration than the requested duration. We performed a set of simulations to evaluate the benefits of the proposed scheme and the effect of a number of parameters on the performance of AORBGP.

  20. Communication services for advanced network applications.

    SciTech Connect

    Bresnahan, J.; Foster, I.; Insley, J.; Toonen, B.; Tuecke, S.

    1999-06-10

    Advanced network applications such as remote instrument control, collaborative environments, and remote I/O are distinguished by traditional applications such as videoconferencing by their need to create multiple, heterogeneous flows with different characteristics. For example, a single application may require remote I/O for raw datasets, shared controls for a collaborative analysis system, streaming video for image rendering data, and audio for collaboration. Furthermore, each flow can have different requirements in terms of reliability, network quality of service, security, etc. They argue that new approaches to communication services, protocols, and network architecture are required both to provide high-level abstractions for common flow types and to support user-level management of flow creation and quality. They describe experiences with the development of such applications and communication services.

  1. Recent advances in the assessment of intelligence and cognition.

    PubMed

    Sparrow, S S; Davis, S M

    2000-01-01

    In this paper, we review current issues in cognitive assessment. After addressing important definitional and theoretical issues, we discuss some recently developed cognitive assessment instruments as well as some recently revised instruments. Tests that are scheduled for revision will also be mentioned. As most readers are generally familiar with the widely used and nationally standardized IQ tests, we will summarize these tests according to their general usage. The testing of intelligence has been a major focus and contribution since the early days of Psychology, when the birthplace of the intelligence testing movement began in France with the work of Alfred Binet toward the end of the 19th century. Many of the most widely known and used IQ tests have been developed in the U.S.A. and are used internationally. In addition, other IQ tests have been developed in many other countries outside the U.S.A. The use of IQ tests and selected assessment considerations will be reviewed. Finally, we make some predictions about the future role of cognitive assessment in the coming century.

  2. Brain Networks for Working Memory and Factors of Intelligence Assessed in Males and Females with fMRI and DTI

    ERIC Educational Resources Information Center

    Tang, C. Y.; Eaves, E. L.; Ng, J. C.; Carpenter, D. M.; Mai, X.; Schroeder, D. H.; Condon, C. A.; Colom, R.; Haier, R. J.

    2010-01-01

    Neuro-imaging studies of intelligence implicate the importance of a parietal-frontal network. One unresolved issue is whether this network underlies a general factor of intelligence ("g") or other specific cognitive factors. A second unresolved issue is whether males and females use different parts of this network. Here we obtained intelligence…

  3. Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence

    PubMed Central

    Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

    2016-01-01

    We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case. PMID:27298752

  4. Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

    PubMed

    Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

    2016-01-01

    We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

  5. An Intelligent Agent Approach for Teaching Neural Networks Using LEGO[R] Handy Board Robots

    ERIC Educational Resources Information Center

    Imberman, Susan P.

    2004-01-01

    In this article we describe a project for an undergraduate artificial intelligence class. The project teaches neural networks using LEGO[R] handy board robots. Students construct robots with two motors and two photosensors. Photosensors provide readings that act as inputs for the neural network. Output values power the motors and maintain the…

  6. Intelligence

    PubMed Central

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  7. Intelligence.

    PubMed

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  8. Intelligence.

    PubMed

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  9. The relationship of certified flight instructors' emotional intelligence levels on flight student advancement

    NASA Astrophysics Data System (ADS)

    Hokeness, Mark Merrill

    Aviation researchers estimate airline companies will require nearly 500,000 pilots in the next 20 years. The role of a Certified Flight Instructor (CFI) is to move student pilots to professional pilots with training typically conducted in one-on-one student and instructor sessions. The knowledge of aviation, professionalism as a teacher, and the CFI’s interpersonal skills can directly affect the successes and advancement of a student pilot. A new and emerging assessment of people skills is known as emotional intelligence (EI). The EI of the CFI can and will affect a flight students’ learning experiences. With knowledge of emotional intelligence and its effect on flight training, student pilot dropouts from aviation may be reduced, thus helping to ensure an adequate supply of pilots. Without pilots, the growth of the commercial aviation industry will be restricted. This mixed method research study established the correlation between a CFI’s measured EI levels and the advancement of flight students. The elements contributing to a CFI’s EI level were not found to be teaching or flight-related experiences, suggesting other life factors are drawn upon by the CFI and are reflected in their emotional intelligence levels presented to flight students. Students respond positively to CFIs with higher levels of emotional intelligence. Awareness of EI skills by both the CFI and flight student contribute to flight student successes and advancement.

  10. Intelligent Engine Systems: Thermal Management and Advanced Cooling

    NASA Technical Reports Server (NTRS)

    Bergholz, Robert

    2008-01-01

    The objective is to provide turbine-cooling technologies to meet Propulsion 21 goals related to engine fuel burn, emissions, safety, and reliability. Specifically, the GE Aviation (GEA) Advanced Turbine Cooling and Thermal Management program seeks to develop advanced cooling and flow distribution methods for HP turbines, while achieving a substantial reduction in total cooling flow and assuring acceptable turbine component safety and reliability. Enhanced cooling techniques, such as fluidic devices, controlled-vortex cooling, and directed impingement jets, offer the opportunity to incorporate both active and passive schemes. Coolant heat transfer enhancement also can be achieved from advanced designs that incorporate multi-disciplinary optimization of external film and internal cooling passage geometry.

  11. Underwater acoustic wireless sensor networks: advances and future trends in physical, MAC and routing layers.

    PubMed

    Climent, Salvador; Sanchez, Antonio; Capella, Juan Vicente; Meratnia, Nirvana; Serrano, Juan Jose

    2014-01-01

    This survey aims to provide a comprehensive overview of the current research on underwater wireless sensor networks, focusing on the lower layers of the communication stack, and envisions future trends and challenges. It analyzes the current state-of-the-art on the physical, medium access control and routing layers. It summarizes their security threads and surveys the currently proposed studies. Current envisioned niches for further advances in underwater networks research range from efficient, low-power algorithms and modulations to intelligent, energy-aware routing and medium access control protocols. PMID:24399155

  12. Underwater acoustic wireless sensor networks: advances and future trends in physical, MAC and routing layers.

    PubMed

    Climent, Salvador; Sanchez, Antonio; Capella, Juan Vicente; Meratnia, Nirvana; Serrano, Juan Jose

    2014-01-01

    This survey aims to provide a comprehensive overview of the current research on underwater wireless sensor networks, focusing on the lower layers of the communication stack, and envisions future trends and challenges. It analyzes the current state-of-the-art on the physical, medium access control and routing layers. It summarizes their security threads and surveys the currently proposed studies. Current envisioned niches for further advances in underwater networks research range from efficient, low-power algorithms and modulations to intelligent, energy-aware routing and medium access control protocols.

  13. Underwater Acoustic Wireless Sensor Networks: Advances and Future Trends in Physical, MAC and Routing Layers

    PubMed Central

    Climent, Salvador; Sanchez, Antonio; Capella, Juan Vicente; Meratnia, Nirvana; Serrano, Juan Jose

    2014-01-01

    This survey aims to provide a comprehensive overview of the current research on underwater wireless sensor networks, focusing on the lower layers of the communication stack, and envisions future trends and challenges. It analyzes the current state-of-the-art on the physical, medium access control and routing layers. It summarizes their security threads and surveys the currently proposed studies. Current envisioned niches for further advances in underwater networks research range from efficient, low-power algorithms and modulations to intelligent, energy-aware routing and medium access control protocols. PMID:24399155

  14. Emergency Situation Prediction Mechanism: A Novel Approach for Intelligent Transportation System Using Vehicular Ad Hoc Networks.

    PubMed

    Ganeshkumar, P; Gokulakrishnan, P

    2015-01-01

    In Indian four-lane express highway, millions of vehicles are travelling every day. Accidents are unfortunate and frequently occurring in these highways causing deaths, increase in death toll, and damage to infrastructure. A mechanism is required to avoid such road accidents at the maximum to reduce the death toll. An Emergency Situation Prediction Mechanism, a novel and proactive approach, is proposed in this paper for achieving the best of Intelligent Transportation System using Vehicular Ad Hoc Network. ESPM intends to predict the possibility of occurrence of an accident in an Indian four-lane express highway. In ESPM, the emergency situation prediction is done by the Road Side Unit based on (i) the Status Report sent by the vehicles in the range of RSU and (ii) the road traffic flow analysis done by the RSU. Once the emergency situation or accident is predicted in advance, an Emergency Warning Message is constructed and disseminated to all vehicles in the area of RSU to alert and prevent the vehicles from accidents. ESPM performs well in emergency situation prediction in advance to the occurrence of an accident. ESPM predicts the emergency situation within 0.20 seconds which is comparatively less than the statistical value. The prediction accuracy of ESPM against vehicle density is found better in different traffic scenarios.

  15. Emergency Situation Prediction Mechanism: A Novel Approach for Intelligent Transportation System Using Vehicular Ad Hoc Networks

    PubMed Central

    Gokulakrishnan, P.

    2015-01-01

    In Indian four-lane express highway, millions of vehicles are travelling every day. Accidents are unfortunate and frequently occurring in these highways causing deaths, increase in death toll, and damage to infrastructure. A mechanism is required to avoid such road accidents at the maximum to reduce the death toll. An Emergency Situation Prediction Mechanism, a novel and proactive approach, is proposed in this paper for achieving the best of Intelligent Transportation System using Vehicular Ad Hoc Network. ESPM intends to predict the possibility of occurrence of an accident in an Indian four-lane express highway. In ESPM, the emergency situation prediction is done by the Road Side Unit based on (i) the Status Report sent by the vehicles in the range of RSU and (ii) the road traffic flow analysis done by the RSU. Once the emergency situation or accident is predicted in advance, an Emergency Warning Message is constructed and disseminated to all vehicles in the area of RSU to alert and prevent the vehicles from accidents. ESPM performs well in emergency situation prediction in advance to the occurrence of an accident. ESPM predicts the emergency situation within 0.20 seconds which is comparatively less than the statistical value. The prediction accuracy of ESPM against vehicle density is found better in different traffic scenarios. PMID:26065014

  16. Advances in Games Technology: Software, Models, and Intelligence

    ERIC Educational Resources Information Center

    Prakash, Edmond; Brindle, Geoff; Jones, Kevin; Zhou, Suiping; Chaudhari, Narendra S.; Wong, Kok-Wai

    2009-01-01

    Games technology has undergone tremendous development. In this article, the authors report the rapid advancement that has been observed in the way games software is being developed, as well as in the development of games content using game engines. One area that has gained special attention is modeling the game environment such as terrain and…

  17. Northeast Artificial Intelligence Consortium (NAIC). Volume 4. Distributed artificial intelligence for communications network management. Final report, Sep 84-Dec 89

    SciTech Connect

    Meyer, R.A.; Conry, S.E.

    1990-12-01

    The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and the office of Scientific Research. Its purpose was to conduct pertinent research in artificial intelligence and to perform activities ancillary to this research. This report describes progress during the existence of the NAIC on the technical research tasks undertaken at the member universities. The topics covered in general are: versatile expert system for equipment maintenance, distributed AI for communications system control, automatic photointerpretation, time-oriented problem solving, speech understanding systems, knowledge base maintenance, hardware architectures for very large systems, knowledge based reasoning and planning, and a knowledge acquisition, assistance, and explanation system. The specific topic for this volume is the use of knowledge based systems for communications network management and control via an architecture for a diversely distributed multi-agent system.

  18. Traffic Network Aided Plan and Road Line Optimization in Intelligent Traffic System

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Qin, Guofeng

    2008-11-01

    In ITS(intelligent traffic system), traffic network plan is important. Public traffic network is a basic part in contemporary intelligent traffic and a basis of the municipal infrastructure construction. To construct the public traffic network aided plan, two problems are studied. One is how to plan traffic road line in order to cover the traffic districts; the other is how to choice the best way from the start point to the end. For the first one, a traffic road line aided plan algorithm is taken forward. The other is a road line optimization algorithm. It utilizes the topology theory to analyze the spatial character in public traffic network, and designs the best choice method to meet the user's requirements. The two algorithms are realized, and proved by a case in the graphical interface of GIS(Geographic Information System), including simulation for rationalization of the public traffic network.

  19. Network of Knowledge: Wikipedia as a Sociotechnical System of Intelligence

    ERIC Educational Resources Information Center

    Livingstone, Randall M.

    2012-01-01

    The purpose of this study was to explore the codependencies of the social and technical structures that yield Wikipedia the website and Wikipedia the community. In doing so, the research investigated the implications of such a sociotechnical system for the maintenance of the project and the emergence of collective intelligence. Using a theoretical…

  20. Addressing fundamental architectural challenges of an activity-based intelligence and advanced analytics (ABIAA) system

    NASA Astrophysics Data System (ADS)

    Yager, Kevin; Albert, Thomas; Brower, Bernard V.; Pellechia, Matthew F.

    2015-06-01

    The domain of Geospatial Intelligence Analysis is rapidly shifting toward a new paradigm of Activity Based Intelligence (ABI) and information-based Tipping and Cueing. General requirements for an advanced ABIAA system present significant challenges in architectural design, computing resources, data volumes, workflow efficiency, data mining and analysis algorithms, and database structures. These sophisticated ABI software systems must include advanced algorithms that automatically flag activities of interest in less time and within larger data volumes than can be processed by human analysts. In doing this, they must also maintain the geospatial accuracy necessary for cross-correlation of multi-intelligence data sources. Historically, serial architectural workflows have been employed in ABIAA system design for tasking, collection, processing, exploitation, and dissemination. These simpler architectures may produce implementations that solve short term requirements; however, they have serious limitations that preclude them from being used effectively in an automated ABIAA system with multiple data sources. This paper discusses modern ABIAA architectural considerations providing an overview of an advanced ABIAA system and comparisons to legacy systems. It concludes with a recommended strategy and incremental approach to the research, development, and construction of a fully automated ABIAA system.

  1. Fluid Intelligence Allows Flexible Recruitment of the Parieto-Frontal Network in Analogical Reasoning

    PubMed Central

    Preusse, Franziska; Elke, van der Meer; Deshpande, Gopikrishna; Krueger, Frank; Wartenburger, Isabell

    2011-01-01

    Fluid intelligence is the ability to think flexibly and to understand abstract relations. People with high fluid intelligence (hi-fluIQ) perform better in analogical reasoning tasks than people with average fluid intelligence (ave-fluIQ). Although previous neuroimaging studies reported involvement of parietal and frontal brain regions in geometric analogical reasoning (which is a prototypical task for fluid intelligence), however, neuroimaging findings on geometric analogical reasoning in hi-fluIQ are sparse. Furthermore, evidence on the relation between brain activation and intelligence while solving cognitive tasks is contradictory. The present study was designed to elucidate the cerebral correlates of geometric analogical reasoning in a sample of hi-fluIQ and ave-fluIQ high school students. We employed a geometric analogical reasoning task with graded levels of task difficulty and confirmed the involvement of the parieto-frontal network in solving this task. In addition to characterizing the brain regions involved in geometric analogical reasoning in hi-fluIQ and ave-fluIQ, we found that blood oxygenation level dependency (BOLD) signal changes were greater for hi-fluIQ than for ave-fluIQ in parietal brain regions. However, ave-fluIQ showed greater BOLD signal changes in the anterior cingulate cortex and medial frontal gyrus than hi-fluIQ. Thus, we showed that a similar network of brain regions is involved in geometric analogical reasoning in both groups. Interestingly, the relation between brain activation and intelligence is not mono-directional, but rather, it is specific for each brain region. The negative brain activation–intelligence relationship in frontal brain regions in hi-fluIQ goes along with a better behavioral performance and reflects a lower demand for executive monitoring compared to ave-fluIQ individuals. In conclusion, our data indicate that flexibly modulating the extent of regional cerebral activity is characteristic for fluid intelligence

  2. Advanced systems engineering and network planning support

    NASA Technical Reports Server (NTRS)

    Walters, David H.; Barrett, Larry K.; Boyd, Ronald; Bazaj, Suresh; Mitchell, Lionel; Brosi, Fred

    1990-01-01

    The objective of this task was to take a fresh look at the NASA Space Network Control (SNC) element for the Advanced Tracking and Data Relay Satellite System (ATDRSS) such that it can be made more efficient and responsive to the user by introducing new concepts and technologies appropriate for the 1997 timeframe. In particular, it was desired to investigate the technologies and concepts employed in similar systems that may be applicable to the SNC. The recommendations resulting from this study include resource partitioning, on-line access to subsets of the SN schedule, fluid scheduling, increased use of demand access on the MA service, automating Inter-System Control functions using monitor by exception, increase automation for distributed data management and distributed work management, viewing SN operational control in terms of the OSI Management framework, and the introduction of automated interface management.

  3. An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

    PubMed

    Ranganayaki, V; Deepa, S N

    2016-01-01

    Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

  4. An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

    PubMed

    Ranganayaki, V; Deepa, S N

    2016-01-01

    Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

  5. An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems

    PubMed Central

    Ranganayaki, V.; Deepa, S. N.

    2016-01-01

    Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

  6. Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network.

    PubMed

    Jahidin, A H; Megat Ali, M S A; Taib, M N; Tahir, N Md; Yassin, I M; Lias, S

    2014-04-01

    This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies.

  7. The Use of Artificial Neural Networks to Estimate Speech Intelligibility from Acoustic Variables: A Preliminary Analysis.

    ERIC Educational Resources Information Center

    Metz, Dale Evan; And Others

    1992-01-01

    A preliminary scheme for estimating the speech intelligibility of hearing-impaired speakers from acoustic parameters, using a computerized artificial neural network to process mathematically the acoustic input variables, is outlined. Tests with 60 hearing-impaired speakers found the scheme to be highly accurate in identifying speakers separated by…

  8. A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation

    PubMed Central

    Jovanov, Emil; Milenkovic, Aleksandar; Otto, Chris; de Groen, Piet C

    2005-01-01

    Background Recent technological advances in integrated circuits, wireless communications, and physiological sensing allow miniature, lightweight, ultra-low power, intelligent monitoring devices. A number of these devices can be integrated into a Wireless Body Area Network (WBAN), a new enabling technology for health monitoring. Methods Using off-the-shelf wireless sensors we designed a prototype WBAN which features a standard ZigBee compliant radio and a common set of physiological, kinetic, and environmental sensors. Results We introduce a multi-tier telemedicine system and describe how we optimized our prototype WBAN implementation for computer-assisted physical rehabilitation applications and ambulatory monitoring. The system performs real-time analysis of sensors' data, provides guidance and feedback to the user, and can generate warnings based on the user's state, level of activity, and environmental conditions. In addition, all recorded information can be transferred to medical servers via the Internet and seamlessly integrated into the user's electronic medical record and research databases. Conclusion WBANs promise inexpensive, unobtrusive, and unsupervised ambulatory monitoring during normal daily activities for prolonged periods of time. To make this technology ubiquitous and affordable, a number of challenging issues should be resolved, such as system design, configuration and customization, seamless integration, standardization, further utilization of common off-the-shelf components, security and privacy, and social issues. PMID:15740621

  9. A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation.

    PubMed

    Jovanov, Emil; Milenkovic, Aleksandar; Otto, Chris; de Groen, Piet C

    2005-03-01

    BACKGROUND: Recent technological advances in integrated circuits, wireless communications, and physiological sensing allow miniature, lightweight, ultra-low power, intelligent monitoring devices. A number of these devices can be integrated into a Wireless Body Area Network (WBAN), a new enabling technology for health monitoring. METHODS: Using off-the-shelf wireless sensors we designed a prototype WBAN which features a standard ZigBee compliant radio and a common set of physiological, kinetic, and environmental sensors. RESULTS: We introduce a multi-tier telemedicine system and describe how we optimized our prototype WBAN implementation for computer-assisted physical rehabilitation applications and ambulatory monitoring. The system performs real-time analysis of sensors' data, provides guidance and feedback to the user, and can generate warnings based on the user's state, level of activity, and environmental conditions. In addition, all recorded information can be transferred to medical servers via the Internet and seamlessly integrated into the user's electronic medical record and research databases. CONCLUSION: WBANs promise inexpensive, unobtrusive, and unsupervised ambulatory monitoring during normal daily activities for prolonged periods of time. To make this technology ubiquitous and affordable, a number of challenging issues should be resolved, such as system design, configuration and customization, seamless integration, standardization, further utilization of common off-the-shelf components, security and privacy, and social issues.

  10. Morphodynamics of tidal networks: advances and challenges

    NASA Astrophysics Data System (ADS)

    Coco, G.; Olabarrieta, M.; van Maanen, B.; Zhou, Z.; Tinoco, R.

    2012-12-01

    Tidal embayments are complex environments at the boundary between land and sea. Their evolution, natural or human-induced, feeds back onto ecological, economic and societal functions. Overall, the ability to manage tidal embayments successfully and maintain their value hinges on our knowledge of the system. The morphological behaviour of tidal embayments, however, is very complex because of the variety of feedback mechanisms which lead to morphological change. In recent years, numerical studies have highlighted that the feedback between the hydrodynamics, sediment transport and morphological evolution can lead to the development of tidally-forced morphological networks characterized by slowly-evolving bifurcating channels. Both tidal range and the initial bathymetry appear to have a strong control on the morphological characteristics of the tidal network by affecting final basin hypsometry and channel patterns. Although promising, none of the numerical models presented in the literature and capable of simulating the growth of a tidal network have been scrutinized against field or laboratory data. Here, we show and discuss the performance of one of those numerical models against detailed laboratory data. Preliminary results indicate that numerical simulations can reproduce the general features of pattern development but that a better description of many fast- and small-scale processes is needed to achieve better model-data agreement. Unsurprisingly, the model shows a strong sensitivity to frictional effects and resuspension parameterizations. Numerical models of morphodynamics tend to neglect some physical or biological processes that affect the short- and long-term evolution of tidal networks. In terms of physical processes, wind waves, interacting with the ebb shoal and tidal currents at the mouth of the embayment can significantly affect hydro- and morphodynamics. Under high wave conditions waves can break in the inlet area producing wave induced circulation

  11. SNMP-SI: A Network Management Tool Based on Slow Intelligence System Approach

    NASA Astrophysics Data System (ADS)

    Colace, Francesco; de Santo, Massimo; Ferrandino, Salvatore

    The last decade has witnessed an intense spread of computer networks that has been further accelerated with the introduction of wireless networks. Simultaneously with, this growth has increased significantly the problems of network management. Especially in small companies, where there is no provision of personnel assigned to these tasks, the management of such networks is often complex and malfunctions can have significant impacts on their businesses. A possible solution is the adoption of Simple Network Management Protocol. Simple Network Management Protocol (SNMP) is a standard protocol used to exchange network management information. It is part of the Transmission Control Protocol/Internet Protocol (TCP/IP) protocol suite. SNMP provides a tool for network administrators to manage network performance, find and solve network problems, and plan for network growth. SNMP has a big disadvantage: its simple design means that the information it deals with is neither detailed nor well organized enough to deal with the expanding modern networking requirements. Over the past years much efforts has been given to improve the lack of Simple Network Management Protocol and new frameworks has been developed: A promising approach involves the use of Ontology. This is the starting point of this paper where a novel approach to the network management based on the use of the Slow Intelligence System methodologies and Ontology based techniques is proposed. Slow Intelligence Systems is a general-purpose systems characterized by being able to improve performance over time through a process involving enumeration, propagation, adaptation, elimination and concentration. Therefore, the proposed approach aims to develop a system able to acquire, according to an SNMP standard, information from the various hosts that are in the managed networks and apply solutions in order to solve problems. To check the feasibility of this model first experimental results in a real scenario are showed.

  12. A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

    PubMed

    Kentzoglanakis, Kyriakos; Poole, Matthew

    2012-01-01

    In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures. PMID:21576756

  13. Rapid Intelligent Inspection Process Definition for dimensional measurement in advanced manufacturing

    SciTech Connect

    Brown, C.W.

    1993-03-01

    The Rapid Intelligent Inspection Process Definition (RIIPD) project is an industry-led effort to advance computer integrated manufacturing (CIM) systems for the creation and modification of inspection process definitions. The RIIPD project will define, design, develop, and demonstrate an automated tool (i.e., software) to generate inspection process plans and coordinate measuring machine (CMM) inspection programs, as well as produce support information for the dimensional measurement of piece parts. The goal of this project is to make the inspection and part verification function, specifically CMM measurements, a more effective production support tool by reducing inspection process definition flowtime, creating consistent and standard inspections, increasing confidence of measurement results, and capturing inspection expertise. This objective is accomplished through importing STEP geometry definitions, applying solid modeling, incorporating explicit tolerance representations, establishing dimensional inspection,techniques, embedding artificial intelligence techniques, and adhering to the Dimensional Measuring Interface Standard (DMIS) national standard.

  14. Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

    PubMed

    Vakhtin, Andrei A; Ryman, Sephira G; Flores, Ranee A; Jung, Rex E

    2014-12-01

    The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence.

  15. Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

    PubMed

    Vakhtin, Andrei A; Ryman, Sephira G; Flores, Ranee A; Jung, Rex E

    2014-12-01

    The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence. PMID:25284305

  16. Advanced microprocessor based power protection system using artificial neural network techniques

    SciTech Connect

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

    1995-12-31

    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.

  17. Design on intelligent gateway technique in home network

    NASA Astrophysics Data System (ADS)

    Hu, Zhonggong; Feng, Xiancheng

    2008-12-01

    Based on digitization, multimedia, mobility, wide band, real-time interaction and so on,family networks, because can provide diverse and personalized synthesis service in information, correspondence work, entertainment, education and health care and so on, are more and more paid attention by the market. The family network product development has become the focus of the related industry. In this paper,the concept of the family network and the overall reference model of the family network are introduced firstly.Then the core techniques and the correspondence standard related with the family network are proposed.The key analysis is made for the function of family gateway, the function module of the software,the key technologies to client side software architecture and the trend of development of the family network entertainment seeing and hearing service and so on. Product present situation of the family gateway and the future trend of development, application solution of the digital family service are introduced. The development of the family network product bringing about the digital family network industry is introduced finally.It causes the development of software industries,such as communication industry,electrical appliances industry, computer and game and so on.It also causes the development of estate industry.

  18. Predicting production using a neural network (artificial intelligence beats human intelligence)

    SciTech Connect

    Boomer, R.J.

    1995-12-31

    Petroleum professionals, that is engineers and geoscientist, routinely make recommendations to drill wells. This process requires the generation of a production profile, oil producing rate versus time, which is a key component in the final economic decision of whether or not to drill the well. The success of the drilling program, and possibly the professional`s career, rests, to a high degree, upon the accuracy of this predicted production profile. The more accurate this prediction the more certain the economic value of the recommended drilling location. This paper looks at this predictive process as used in the Vacuum Field of New Mexico. It explores the predictive methods used in the past and reports on their accuracy. A new method, using artificial intelligence, is presented which improves upon the accuracy of this process.

  19. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    PubMed

    Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  20. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    PubMed

    Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

  1. Intelligent detection of impulse noise using multilayer neural network with multi-valued neurons

    NASA Astrophysics Data System (ADS)

    Aizenberg, Igor; Wallace, Glen

    2012-03-01

    In this paper, we solve the impulse noise detection problem using an intelligent approach. We use a multilayer neural network based on multi-valued neurons (MLMVN) as an intelligent impulse noise detector. MLMVN was already used for point spread function identification and intelligent edge enhancement. So it is very attractive to apply it for solving another image processing problem. The main result, which is presented in the paper, is the proven ability of MLMVN to detect impulse noise on different images after a learning session with the data taken just from a single noisy image. Hence MLMVN can be used as a robust impulse detector. It is especially efficient for salt and pepper noise detection and outperforms all competitive techniques. It also shows comparable results in detection of random impulse noise. Moreover, for random impulse noise detection, MLMVN with the output neuron with a periodic activation function is used for the first time.

  2. Autonomic Intelligent Cyber Sensor to Support Industrial Control Network Awareness

    DOE PAGES

    Vollmer, Todd; Manic, Milos; Linda, Ondrej

    2013-06-01

    The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of Autonomic computing and a SOAP based IF-MAP external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, self-managed framework. The contribution of this paper is two-fold: 1) A flexible two level communication layer based on Autonomic computing and Service Oriented Architecture is detailed and 2) Three complementary modules that dynamically reconfiguremore » in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific Operating System and port configurations. Additionally the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.« less

  3. Autonomic Intelligent Cyber Sensor to Support Industrial Control Network Awareness

    SciTech Connect

    Vollmer, Todd; Manic, Milos; Linda, Ondrej

    2013-06-01

    The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of Autonomic computing and a SOAP based IF-MAP external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, self-managed framework. The contribution of this paper is two-fold: 1) A flexible two level communication layer based on Autonomic computing and Service Oriented Architecture is detailed and 2) Three complementary modules that dynamically reconfigure in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific Operating System and port configurations. Additionally the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.

  4. Control for Intelligent Tutoring Systems: A Comparison of Blackboard Architectures and Discourse Management Networks. Report No. R-6267.

    ERIC Educational Resources Information Center

    Murray, William R.

    This paper compares two alternative computer architectures that have been proposed to provide the control mechanism that enables an intelligent tutoring system to decide what instructional action to perform next, i.e., discourse management networks and blackboards. The claim that an intelligent tutoring system controlled by a blackboard…

  5. Advances in the Theory of Complex Networks

    NASA Astrophysics Data System (ADS)

    Peruani, Fernando

    An exhaustive and comprehensive review on the theory of complex networks would imply nowadays a titanic task, and it would result in a lengthy work containing plenty of technical details of arguable relevance. Instead, this chapter addresses very briefly the ABC of complex network theory, visiting only the hallmarks of the theoretical founding, to finally focus on two of the most interesting and promising current research problems: the study of dynamical processes on transportation networks and the identification of communities in complex networks.

  6. Analysis and application of intelligence network based on FTTH

    NASA Astrophysics Data System (ADS)

    Feng, Xiancheng; Yun, Xiang

    2008-12-01

    With the continued rapid growth of Internet, new network service emerges in endless stream, especially the increase of network game, meeting TV, video on demand, etc. The bandwidth requirement increase continuously. Network technique, optical device technical development is swift and violent. FTTH supports all present and future service with enormous bandwidth, including traditional telecommunication service, traditional data service and traditional TV service, and the future digital TV and VOD. With huge bandwidth of FTTH, it wins the final solution of broadband network, becomes the final goal of development of optical access network. Firstly, it introduces the main service which FTTH supports, main analysis key technology such as FTTH system composition way, topological structure, multiplexing, optical cable and device. It focus two kinds of realization methods - PON, P2P technology. Then it proposed that the solution of FTTH can support comprehensive access (service such as broadband data, voice, video and narrowband private line). Finally, it shows the engineering application for FTTH in the district and building. It brings enormous economic benefits and social benefit.

  7. Advanced functional network analysis in the geosciences: The pyunicorn package

    NASA Astrophysics Data System (ADS)

    Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

    2013-04-01

    Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

  8. Optical Multiple Access Network (OMAN) for advanced processing satellite applications

    NASA Technical Reports Server (NTRS)

    Mendez, Antonio J.; Gagliardi, Robert M.; Park, Eugene; Ivancic, William D.; Sherman, Bradley D.

    1991-01-01

    An OMAN breadboard for exploring advanced processing satellite circuit switch applications is introduced. Network architecture, hardware trade offs, and multiple user interference issues are presented. The breadboard test set up and experimental results are discussed.

  9. Hybrid swarm intelligence optimization approach for optimal data storage position identification in wireless sensor networks.

    PubMed

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

  10. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    PubMed Central

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

  11. Advanced medical video services through context-aware medical networks.

    PubMed

    Doukas, Charalampos N; Maglogiannis, Ilias; Pliakas, Thomas

    2007-01-01

    The aim of this paper is to present a framework for advanced medical video delivery services, through network and patient-state awareness. Under this scope a context-aware medical networking platform is described. The developed platform enables proper medical video data coding and transmission according to both a) network availability and/or quality and b) patient status, optimizing thus network performance and telediagnosis. An evaluation platform has been developed based on scalable H.264 coding of medical videos. Corresponding results of video transmission over a WiMax network have proved the effectiveness and efficiency of the platform providing proper video content delivery. PMID:18002643

  12. Advanced medical video services through context-aware medical networks.

    PubMed

    Doukas, Charalampos N; Maglogiannis, Ilias; Pliakas, Thomas

    2007-01-01

    The aim of this paper is to present a framework for advanced medical video delivery services, through network and patient-state awareness. Under this scope a context-aware medical networking platform is described. The developed platform enables proper medical video data coding and transmission according to both a) network availability and/or quality and b) patient status, optimizing thus network performance and telediagnosis. An evaluation platform has been developed based on scalable H.264 coding of medical videos. Corresponding results of video transmission over a WiMax network have proved the effectiveness and efficiency of the platform providing proper video content delivery.

  13. Advanced mobile networking, sensing, and controls.

    SciTech Connect

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

    2005-03-01

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

  14. Practical Intelligence and Tacit Knowledge: Advancements in the Measurement of Developing Expertise

    ERIC Educational Resources Information Center

    Cianciolo, Anna T.; Grigorenko, Elena L.; Jarvin, Linda; Gil, Guillermo; Drebot, Michael E.; Sternberg, Robert J.

    2006-01-01

    Practical intelligence as measured by tacit-knowledge inventories generally has shown a weak relation to other intelligence constructs. However, the use of assessments capturing specialized, job-related knowledge may obscure the generality of practical intelligence and its relation to general intelligence. This article presents three studies in…

  15. Battery-free Wireless Sensor Network For Advanced Fossil-Fuel Based Power Generation

    SciTech Connect

    Yi Jia

    2011-02-28

    This report summarizes technical progress achieved during the project supported by the Department of Energy under Award Number DE-FG26-07NT4306. The aim of the project was to conduct basic research into battery-free wireless sensing mechanism in order to develop novel wireless sensors and sensor network for physical and chemical parameter monitoring in a harsh environment. Passive wireless sensing platform and five wireless sensors including temperature sensor, pressure sensor, humidity sensor, crack sensor and networked sensors developed and demonstrated in our laboratory setup have achieved the objective for the monitoring of various physical and chemical parameters in a harsh environment through remote power and wireless sensor communication, which is critical to intelligent control of advanced power generation system. This report is organized by the sensors developed as detailed in each progress report.

  16. Advanced information processing system: Input/output network management software

    NASA Technical Reports Server (NTRS)

    Nagle, Gail; Alger, Linda; Kemp, Alexander

    1988-01-01

    The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.

  17. Networking Technologies Enable Advances in Earth Science

    NASA Technical Reports Server (NTRS)

    Johnson, Marjory; Freeman, Kenneth; Gilstrap, Raymond; Beck, Richard

    2004-01-01

    This paper describes an experiment to prototype a new way of conducting science by applying networking and distributed computing technologies to an Earth Science application. A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to validate and calibrate remotely sensed geological data in near-real time. This represents a fundamental shift in the way that Earth scientists analyze remotely sensed data. In this paper we describe the experiment and the network infrastructure that enabled it, analyze the data flow during the experiment, and discuss the scientific impact of the results.

  18. SINET3: advanced optical and IP hybrid network

    NASA Astrophysics Data System (ADS)

    Urushidani, Shigeo

    2007-11-01

    This paper introduces the new Japanese academic backbone network called SINET3, which has been in full-scale operation since June 2007. SINET3 provides a wide variety of network services, such as multi-layer transfer, enriched VPN, enhanced QoS, and layer-1 bandwidth on demand (BoD) services to create an innovative and prolific science infrastructure for more than 700 universities and research institutions. The network applies an advanced hybrid network architecture composed of 75 layer-1 switches and 12 high-performance IP routers to accommodate such diversified services in a single network platform, and provides sufficient bandwidth using Japan's first STM256 (40 Gbps) lines. The network adopts lots of the latest networking technologies, such as next-generation SDH (VCAT/GFP/LCAS), GMPLS, advanced MPLS, and logical-router technologies, for high network convergence, flexible resource assignment, and high service availability. This paper covers the network services, network design, and networking technologies of SINET3.

  19. 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

  20. Intelligent transmission of patient sensor data in wireless hospital networks.

    PubMed

    Bragg, Danielle; Yun, Mira; Bragg, Haya; Choi, Hyeong-Ah

    2012-01-01

    Medical data sensors on patients in hospitals produce an increasingly large volume of increasingly diverse real-time data. Because scheduling the transmission of this data through wireless hospital networks becomes a crucial problem, we propose a Reinforcement Learning-based queue management and scheduling scheme. In this scheme, we use a game-theoretical approach where patients compete for transmission resources by assigning different utility values to data packets. These utility functions are largely based on data criticality and deadline, which together determine the data's scheduling priority. Simulation results demonstrate the high performance of this scheme in comparison to a datatype-based scheme, with the drop rate of critical data as a performance measure. We also show how patients can optimize their policies based on the utility functions of competing patients.

  1. Intelligent Transmission of Patient Sensor Data in Wireless Hospital Networks

    PubMed Central

    Bragg, Danielle; Yun, Mira; Bragg, Haya; Choi, Hyeong-Ah

    2012-01-01

    Medical data sensors on patients in hospitals produce an increasingly large volume of increasingly diverse real-time data. Because scheduling the transmission of this data through wireless hospital networks becomes a crucial problem, we propose a Reinforcement Learning-based queue management and scheduling scheme. In this scheme, we use a game-theoretical approach where patients compete for transmission resources by assigning different utility values to data packets. These utility functions are largely based on data criticality and deadline, which together determine the data’s scheduling priority. Simulation results demonstrate the high performance of this scheme in comparison to a datatype-based scheme, with the drop rate of critical data as a performance measure. We also show how patients can optimize their policies based on the utility functions of competing patients. PMID:23304390

  2. Optical protocols for advanced spacecraft networks

    NASA Technical Reports Server (NTRS)

    Bergman, Larry A.

    1991-01-01

    Most present day fiber optic networks are in fact extensions of copper wire networks. As a result, their speed is still limited by electronics even though optics is capable of running three orders of magnitude faster. Also, the fact that photons do not interact with one another (as electrons do) provides optical communication systems with some unique properties or new functionality that is not readily taken advantage of with conventional approaches. Some of the motivation for implementing network protocols in the optical domain, a few possible approaches including optical code-division multiple-access (CDMA), and how this class of networks can extend the technology life cycle of the Space Station Freedom (SSF) with increased performance and functionality are described.

  3. Underwater sensor networks: applications, advances and challenges.

    PubMed

    Heidemann, John; Stojanovic, Milica; Zorzi, Michele

    2012-01-13

    This paper examines the main approaches and challenges in the design and implementation of underwater wireless sensor networks. We summarize key applications and the main phenomena related to acoustic propagation, and discuss how they affect the design and operation of communication systems and networking protocols at various layers. We also provide an overview of communications hardware, testbeds and simulation tools available to the research community.

  4. Modelling intelligent behavior

    NASA Technical Reports Server (NTRS)

    Green, H. S.; Triffet, T.

    1993-01-01

    An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

  5. TALON - The Telescope Alert Operation Network System : intelligent linking of distributed autonomous robotic telescopes

    SciTech Connect

    White, R. R.; Wren, J.; Davis, H. R.; Galassi, M. C.; Starr, D. L.; Vestrand, W. T.; Wozniak, P. R.

    2004-01-01

    The internet has brought about great change in the astronomical community, but this interconnectivity is just starting to be exploited for use in instrumentation. Utilizing the internet for communicating between distributed astronomical systems is still in its infancy, but it already shows great potential. Here we present an example of a distributed network of telescopes that performs more efficienfiy in synchronous operation than as individual instruments. RAPid Telescopes for Optical Response (RAPTOR) is a system of telescopes at LANL that has intelligent intercommunication, combined with wide-field optics, temporal monitoring software, and deep-field follow-up capability all working in closed-loop real-time operation. The Telescope ALert Operations Network (TALON) is a network server that allows intercommunication of alert triggers from external and internal resources and controls the distribution of these to each of the telescopes on the network. TALON is designed to grow, allowing any number of telescopes to be linked together and communicate. Coupled with an intelligent alert client at each telescope, it can analyze and respond to each distributed TALON alert based on the telescopes needs and schedule.

  6. Advances in software development for intelligent interfaces for alarm and emergency management consoles

    SciTech Connect

    Moseley, M.R.; Olson, C.E.

    1986-01-01

    Recent advances in technology allow features like voice synthesis, voice and speech recognition, image understanding, and intelligent data base management to be incorporated in computer driven alarm and emergency management information systems. New software development environments make it possible to do rapid prototyping of custom applications. Three examples using these technologies are discussed. 1) Maximum use is made of high-speed graphics and voice synthesis to implement a state-of-the-art alarm processing and display system with features that make the operator-machine interface efficient and accurate. 2) An application generator which has the capability of ''building'' a specific alarm processing and display application in a matter of a few hours, using the site definition developed in the security planning phase to produce the custom application. 3) A software tool, is described which permits rapid prototyping of human-machine interfaces for a variety of applications including emergency management, alarm display and process information display.

  7. Neural network for intelligent query of an FBI forensic database

    NASA Astrophysics Data System (ADS)

    Uvanni, Lee A.; Rainey, Timothy G.; Balasubramanian, Uma; Brettle, Dean W.; Weingard, Fred; Sibert, Robert W.; Birnbaum, Eric

    1997-02-01

    Examiner is an automated fired cartridge case identification system utilizing a dual-use neural network pattern recognition technology, called the statistical-multiple object detection and location system (S-MODALS) developed by Booz(DOT)Allen & Hamilton, Inc. in conjunction with Rome Laboratory. S-MODALS was originally designed for automatic target recognition (ATR) of tactical and strategic military targets using multisensor fusion [electro-optical (EO), infrared (IR), and synthetic aperture radar (SAR)] sensors. Since S-MODALS is a learning system readily adaptable to problem domains other than automatic target recognition, the pattern matching problem of microscopic marks for firearms evidence was analyzed using S-MODALS. The physics; phenomenology; discrimination and search strategies; robustness requirements; error level and confidence level propagation that apply to the pattern matching problem of military targets were found to be applicable to the ballistic domain as well. The Examiner system uses S-MODALS to rank a set of queried cartridge case images from the most similar to the least similar image in reference to an investigative fired cartridge case image. The paper presents three independent tests and evaluation studies of the Examiner system utilizing the S-MODALS technology for the Federal Bureau of Investigation.

  8. Pervasive community care platform: Ambient Intelligence leveraging sensor networks and mobile agents

    NASA Astrophysics Data System (ADS)

    Su, Chuan-Jun; Chiang, Chang-Yu

    2014-04-01

    Several powerful trends are contributing to an aging of much of the world's population, especially in economically developed countries. To mitigate the negative effects of rapidly ageing populations, societies must act early to plan for the welfare, medical care and residential arrangements of their senior citizens, and for the manpower and associated training needed to execute these plans. This paper describes the development of an Ambient Intelligent Community Care Platform (AICCP), which creates an environment of Ambient Intelligence through the use of sensor network and mobile agent (MA) technologies. The AICCP allows caregivers to quickly and accurately locate their charges; access, update and share critical treatment and wellness data; and automatically archive all records. The AICCP presented in this paper is expected to enable caregivers and communities to offer pervasive, accurate and context-aware care services.

  9. Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques

    NASA Astrophysics Data System (ADS)

    Stottler, D.

    There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.

  10. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    NASA Astrophysics Data System (ADS)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  11. Ambient Intelligence Context-Based Cross-Layer Design in Wireless Sensor Networks

    PubMed Central

    Liu, Yang; Seet, Boon-Chong; Al-Anbuky, Adnan

    2014-01-01

    By exchanging information directly between non-adjacent protocol layers, cross-layer (CL) interaction can significantly improve and optimize network performances such as energy efficiency and delay. This is particularly important for wireless sensor networks (WSNs) where sensor devices are energy-constrained and deployed for real-time monitoring applications. Existing CL schemes mainly exploit information exchange between physical, medium access control (MAC), and routing layers, with only a handful involving application layer. For the first time, we proposed a framework for CL optimization based on user context of ambient intelligence (AmI) application and an ontology-based context modeling and reasoning mechanism. We applied the proposed framework to jointly optimize MAC and network (NET) layer protocols for WSNs. Extensive evaluations show that the resulting optimization through context awareness and CL interaction for both MAC and NET layer protocols can yield substantial improvements in terms of throughput, packet delivery, delay, and energy performances. PMID:25317760

  12. Cooperation and the evolution of intelligence.

    PubMed

    McNally, Luke; Brown, Sam P; Jackson, Andrew L

    2012-08-01

    The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the 'social intelligence hypothesis'), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.

  13. Network-based modeling and intelligent data mining of social media for improving care.

    PubMed

    Akay, Altug; Dragomir, Andrei; Erlandsson, Bjorn-Erik

    2015-01-01

    Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative sentiment, as well as the side effects of treatment, in users' forum posts, and identifies user communities (modules) and influential users for the purpose of ascertaining user opinion of cancer treatment. We used a self-organizing map to analyze word frequency data derived from users' forum posts. We then introduced a novel network-based approach for modeling users' forum interactions and employed a network partitioning method based on optimizing a stability quality measure. This allowed us to determine consumer opinion and identify influential users within the retrieved modules using information derived from both word-frequency data and network-based properties. Our approach can expand research into intelligently mining social media data for consumer opinion of various treatments to provide rapid, up-to-date information for the pharmaceutical industry, hospitals, and medical staff, on the effectiveness (or ineffectiveness) of future treatments.

  14. Recent advances in symmetric and network dynamics.

    PubMed

    Golubitsky, Martin; Stewart, Ian

    2015-09-01

    We summarize some of the main results discovered over the past three decades concerning symmetric dynamical systems and networks of dynamical systems, with a focus on pattern formation. In both of these contexts, extra constraints on the dynamical system are imposed, and the generic phenomena can change. The main areas discussed are time-periodic states, mode interactions, and non-compact symmetry groups such as the Euclidean group. We consider both dynamics and bifurcations. We summarize applications of these ideas to pattern formation in a variety of physical and biological systems, and explain how the methods were motivated by transferring to new contexts René Thom's general viewpoint, one version of which became known as "catastrophe theory." We emphasize the role of symmetry-breaking in the creation of patterns. Topics include equivariant Hopf bifurcation, which gives conditions for a periodic state to bifurcate from an equilibrium, and the H/K theorem, which classifies the pairs of setwise and pointwise symmetries of periodic states in equivariant dynamics. We discuss mode interactions, which organize multiple bifurcations into a single degenerate bifurcation, and systems with non-compact symmetry groups, where new technical issues arise. We transfer many of the ideas to the context of networks of coupled dynamical systems, and interpret synchrony and phase relations in network dynamics as a type of pattern, in which space is discretized into finitely many nodes, while time remains continuous. We also describe a variety of applications including animal locomotion, Couette-Taylor flow, flames, the Belousov-Zhabotinskii reaction, binocular rivalry, and a nonlinear filter based on anomalous growth rates for the amplitude of periodic oscillations in a feed-forward network. PMID:26428565

  15. Recent advances in symmetric and network dynamics

    NASA Astrophysics Data System (ADS)

    Golubitsky, Martin; Stewart, Ian

    2015-09-01

    We summarize some of the main results discovered over the past three decades concerning symmetric dynamical systems and networks of dynamical systems, with a focus on pattern formation. In both of these contexts, extra constraints on the dynamical system are imposed, and the generic phenomena can change. The main areas discussed are time-periodic states, mode interactions, and non-compact symmetry groups such as the Euclidean group. We consider both dynamics and bifurcations. We summarize applications of these ideas to pattern formation in a variety of physical and biological systems, and explain how the methods were motivated by transferring to new contexts René Thom's general viewpoint, one version of which became known as "catastrophe theory." We emphasize the role of symmetry-breaking in the creation of patterns. Topics include equivariant Hopf bifurcation, which gives conditions for a periodic state to bifurcate from an equilibrium, and the H/K theorem, which classifies the pairs of setwise and pointwise symmetries of periodic states in equivariant dynamics. We discuss mode interactions, which organize multiple bifurcations into a single degenerate bifurcation, and systems with non-compact symmetry groups, where new technical issues arise. We transfer many of the ideas to the context of networks of coupled dynamical systems, and interpret synchrony and phase relations in network dynamics as a type of pattern, in which space is discretized into finitely many nodes, while time remains continuous. We also describe a variety of applications including animal locomotion, Couette-Taylor flow, flames, the Belousov-Zhabotinskii reaction, binocular rivalry, and a nonlinear filter based on anomalous growth rates for the amplitude of periodic oscillations in a feed-forward network.

  16. Conceptualizing and Advancing Research Networking Systems.

    PubMed

    Schleyer, Titus; Butler, Brian S; Song, Mei; Spallek, Heiko

    2012-03-01

    Science in general, and biomedical research in particular, is becoming more collaborative. As a result, collaboration with the right individuals, teams, and institutions is increasingly crucial for scientific progress. We propose Research Networking Systems (RNS) as a new type of system designed to help scientists identify and choose collaborators, and suggest a corresponding research agenda. The research agenda covers four areas: foundations, presentation, architecture, and evaluation. Foundations includes project-, institution- and discipline-specific motivational factors; the role of social networks; and impression formation based on information beyond expertise and interests. Presentation addresses representing expertise in a comprehensive and up-to-date manner; the role of controlled vocabularies and folksonomies; the tension between seekers' need for comprehensive information and potential collaborators' desire to control how they are seen by others; and the need to support serendipitous discovery of collaborative opportunities. Architecture considers aggregation and synthesis of information from multiple sources, social system interoperability, and integration with the user's primary work context. Lastly, evaluation focuses on assessment of collaboration decisions, measurement of user-specific costs and benefits, and how the large-scale impact of RNS could be evaluated with longitudinal and naturalistic methods. We hope that this article stimulates the human-computer interaction, computer-supported cooperative work, and related communities to pursue a broad and comprehensive agenda for developing research networking systems.

  17. Conceptualizing and Advancing Research Networking Systems

    PubMed Central

    SCHLEYER, TITUS; BUTLER, BRIAN S.; SONG, MEI; SPALLEK, HEIKO

    2013-01-01

    Science in general, and biomedical research in particular, is becoming more collaborative. As a result, collaboration with the right individuals, teams, and institutions is increasingly crucial for scientific progress. We propose Research Networking Systems (RNS) as a new type of system designed to help scientists identify and choose collaborators, and suggest a corresponding research agenda. The research agenda covers four areas: foundations, presentation, architecture, and evaluation. Foundations includes project-, institution- and discipline-specific motivational factors; the role of social networks; and impression formation based on information beyond expertise and interests. Presentation addresses representing expertise in a comprehensive and up-to-date manner; the role of controlled vocabularies and folksonomies; the tension between seekers’ need for comprehensive information and potential collaborators’ desire to control how they are seen by others; and the need to support serendipitous discovery of collaborative opportunities. Architecture considers aggregation and synthesis of information from multiple sources, social system interoperability, and integration with the user’s primary work context. Lastly, evaluation focuses on assessment of collaboration decisions, measurement of user-specific costs and benefits, and how the large-scale impact of RNS could be evaluated with longitudinal and naturalistic methods. We hope that this article stimulates the human-computer interaction, computer-supported cooperative work, and related communities to pursue a broad and comprehensive agenda for developing research networking systems. PMID:24376309

  18. Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2006-05-01

    A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the

  19. An intelligent computational algorithm based on neural network for spatial data mining in adaptability evaluation

    NASA Astrophysics Data System (ADS)

    Miao, Zuohua; Xu, Hong; Chen, Yong; Zeng, Xiangyang

    2009-10-01

    Back-propagation neural network model (BPNN) is an intelligent computational model based on stylebook learning. This model is different from traditional adaptability symbolic logic reasoning method based on knowledge and rules. At the same time, BPNN model has shortcoming such as: slowly convergence speed and partial minimum. During the process of adaptability evaluation, the factors were diverse, complicated and uncertain, so an effectual model should adopt the technique of data mining method and fuzzy logical technology. In this paper, the author ameliorated the backpropagation of BPNN and applied fuzzy logical theory for dynamic inference of fuzzy rules. Authors also give detail description on training and experiment process of the novel model.

  20. Interference Mitigation Based on Intelligent Location Selection in a Canonical Communication Network

    NASA Astrophysics Data System (ADS)

    Qu, Junyue; Cai, Yueming; Zheng, Jianchao; Yang, Wendong; Yang, Weiwei; Hu, Yajie

    2016-01-01

    In this letter, the interference mitigation in a canonical communication network is discussed from the perspective of intelligent location selection. A potential game model is constructed and a location-selection algorithm is designed combining no-regret procedure. With the proposed algorithm, all nodes can update their strategies with limited information exchange. Specifically, our proposed algorithm can converge to a set of correlated equilibria which are the globally or locally optimal solution to the problem of interference minimization. Moreover, our proposed algorithm can achieve distributed implementation without a central node. Simulation results demonstrate that the total interference can be mitigated efficiently with our proposed algorithm. And the proposed algorithm can converge fast.

  1. Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks

    NASA Technical Reports Server (NTRS)

    Mclauchlan, Robert A.

    1989-01-01

    Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.

  2. Automated sensor networks to advance ocean science

    NASA Astrophysics Data System (ADS)

    Schofield, O.; Orcutt, J. A.; Arrott, M.; Vernon, F. L.; Peach, C. L.; Meisinger, M.; Krueger, I.; Kleinert, J.; Chao, Y.; Chien, S.; Thompson, D. R.; Chave, A. D.; Balasuriya, A.

    2010-12-01

    The National Science Foundation has funded the Ocean Observatories Initiative (OOI), which over the next five years will deploy infrastructure to expand scientist’s ability to remotely study the ocean. The deployed infrastructure will be linked by a robust cyberinfrastructure (CI) that will integrate marine observatories into a coherent system-of-systems. OOI is committed to engaging the ocean sciences community during the construction pahse. For the CI, this is being enabled by using a “spiral design strategy” allowing for input throughout the construction phase. In Fall 2009, the OOI CI development team used an existing ocean observing network in the Mid-Atlantic Bight (MAB) to test OOI CI software. The objective of this CI test was to aggregate data from ships, autonomous underwater vehicles (AUVs), shore-based radars, and satellites and make it available to five different data-assimilating ocean forecast models. Scientists used these multi-model forecasts to automate future glider missions in order to demonstrate the feasibility of two-way interactivity between the sensor web and predictive models. The CI software coordinated and prioritized the shared resources that allowed for the semi-automated reconfiguration of assett-tasking, and thus enabled an autonomous execution of observation plans for the fixed and mobile observation platforms. Efforts were coordinated through a web portal that provided an access point for the observational data and model forecasts. Researchers could use the CI software in tandem with the web data portal to assess the performance of individual numerical model results, or multi-model ensembles, through real-time comparisons with satellite, shore-based radar, and in situ robotic measurements. The resulting sensor net will enable a new means to explore and study the world’s oceans by providing scientists a responsive network in the world’s oceans that can be accessed via any wireless network.

  3. Advanced HF anti-jam network architecture

    NASA Astrophysics Data System (ADS)

    Jackson, E. M.; Horner, Robert W.; Cai, Khiem V.

    The Hughes HF2000 system was developed using a flexible architecture which utilizes a wideband RF front-end and extensive digital signal processing. The HF2000 antijamming (AJ) mode was field tested via an HF skywave path between Fullerton, CA and Carlsbad, CA (about 100 miles), and it was shown that reliable fast frequency-hopping data transmission is feasible at 2400 b/s without adaptive equalization. The necessary requirements of an HF communication network are discussed, and how the HF2000 AJ mode can be used to support those requirements is shown. The Hughes HF2000 AJ mode system architecture is presented.

  4. The ADVANCE network: accelerating data value across a national community health center network

    PubMed Central

    DeVoe, Jennifer E; Gold, Rachel; Cottrell, Erika; Bauer, Vance; Brickman, Andrew; Puro, Jon; Nelson, Christine; Mayer, Kenneth H; Sears, Abigail; Burdick, Tim; Merrell, Jonathan; Matthews, Paul; Fields, Scott

    2014-01-01

    The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network (CDRN) is led by the OCHIN Community Health Information Network in partnership with Health Choice Network and Fenway Health. The ADVANCE CDRN will ‘horizontally’ integrate outpatient electronic health record data for over one million federally qualified health center patients, and ‘vertically’ integrate hospital, health plan, and community data for these patients, often under-represented in research studies. Patient investigators, community investigators, and academic investigators with diverse expertise will work together to meet project goals related to data integration, patient engagement and recruitment, and the development of streamlined regulatory policies. By enhancing the data and research infrastructure of participating organizations, the ADVANCE CDRN will serve as a ‘community laboratory’ for including disadvantaged and vulnerable patients in patient-centered outcomes research that is aligned with the priorities of patients, clinics, and communities in our network. PMID:24821740

  5. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 3: Advanced networks and economics

    NASA Technical Reports Server (NTRS)

    1986-01-01

    This study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  6. Intelligent Surveillance System Design Based on Independent Component Analysis and Wireless Sensor Network

    NASA Astrophysics Data System (ADS)

    Xie, Long; Ogawa, Masatoshi; Kigawa, Youichi; Ogai, Harutoshi

    This paper explores the development of a real time intelligent surveillance system using the technology of pattern recognition based on independent component analysis (ICA) and a novel matching method as a reaction to perceptions of insecurity in sensitive spaces. An array of motion images of people are caught by micro digital cameras on board and transferred through wireless network to FPGA board. The feature points of the shot image and the image in database are extracted out using ICA algorithm in embedded PowerPC. The most similar images are picked up from the image database, which is classified to different clusters, and the potential insecurity level of invaders is detected. Furthermore the respective locations are connected by wireless network. The system of hardware and software co-design is implemented on Xilinx FPGA with the performance of high efficiency, low power consumption and easy integration with other devices.

  7. Advanced logic gates for ultrafast network interchanges

    NASA Astrophysics Data System (ADS)

    Islam, Mohammed N.

    1995-08-01

    By overcoming speed bottlenecks from electronic switching as well as optical/electronic conversions, all-optical logic gates can permit further exploitation of the nearly 40 THz of bandwidth available from optical fibers. We focus on the use of optical solitons and all-optical logic gates to implement ultrafast ``interchanges'' or switching nodes on packet networks with speeds of 100 Gbit/s or greater. For example, all-optical logic gates have been demonstrated with speeds up to 200 Gbit/s, and they may be used to decide whether to add or drop a data packet. The overall goal of our effort is to demonstrate the key enabling technologies and their combination for header processing in 100 Gbit/s, time-division-multiplexed, packed switched networks. Soliton-based fiber logic gates are studied with the goal of combining attractive features of soliton-dragging logic gates, nonlinear loop mirrors, and erbium-doped fiber amplifiers to design logic gates with optimum switching energy, contrast ratio, and timing sensitivity. First, the experimental and numerical work studies low-latency soliton logic gates based on frequency shifts associated with cross-phase modulation. In preliminary experiments, switching in 15 m long low-birefringent fibers has been demonstrated with a contrast ratio of 2.73:1. Using dispersion-shifted fiber in the gate should lower the switching energy and improve the contrast ratio. Next, the low-birefringent fiber can be cross-spliced and wrapped into a nonlinear optical loop mirror to take advantage of mechanisms from both soliton dragging and loop mirrors. The resulting device can have low switching energy and a timing window that results from a combination of soliton dragging and the loop mirror mechanisms.

  8. The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

    NASA Technical Reports Server (NTRS)

    Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris; Holden, Tina; Rudisill, Marianne

    1993-01-01

    One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry.

  9. Compound intelligent control system combining fuzzy control with neural networks in a permanent magnetic synchronous motor

    NASA Astrophysics Data System (ADS)

    Zhang, Zhiyuan; Li, Weili; Li, Taifu

    2005-12-01

    An AC motor belongs to the category of a controlled object that is multi-variable, nonlinear and strong correlation, complex to mathematical model, and whose control performance is affected by a time-changing parameter. Therefore, it is very difficult to obtain the desired static and dynamic characteristic through a general fixed regulator. In this paper, the authors present a compound intelligent control strategy, combined with a neural network and fuzzy control. Considering that a neural network is good at self-learning, and a single fuzzy control algorithm is rapid in its response characteristics, the compound control strategy can compensate for a disadvantage of fuzzy control, which is associated with poor stability and precision and also requires solving a puzzle in the time-changing parameters in the controlled object. On the basis of a dynamic model of the permanent magnetic synchronous motor and its working principle, the authors designed the block diagram of a control system, combined a neural PID control and fuzzy control, and studied the corresponding control algorithm in detail. The simulation results show that the compound intelligent control system is good in dynamic performance and robustness.

  10. Intelligent sensor positioning and orientation through constructive neural network-embedded INS/GPS integration algorithms.

    PubMed

    Chiang, Kai-Wei; Chang, Hsiu-Wen

    2010-01-01

    Mobile mapping systems have been widely applied for acquiring spatial information in applications such as spatial information systems and 3D city models. Nowadays the most common technologies used for positioning and orientation of a mobile mapping system include a Global Positioning System (GPS) as the major positioning sensor and an Inertial Navigation System (INS) as the major orientation sensor. In the classical approach, the limitations of the Kalman Filter (KF) method and the overall price of multi-sensor systems have limited the popularization of most land-based mobile mapping applications. Although intelligent sensor positioning and orientation schemes consisting of Multi-layer Feed-forward Neural Networks (MFNNs), one of the most famous Artificial Neural Networks (ANNs), and KF/smoothers, have been proposed in order to enhance the performance of low cost Micro Electro Mechanical System (MEMS) INS/GPS integrated systems, the automation of the MFNN applied has not proven as easy as initially expected. Therefore, this study not only addresses the problems of insufficient automation in the conventional methodology that has been applied in MFNN-KF/smoother algorithms for INS/GPS integrated systems proposed in previous studies, but also exploits and analyzes the idea of developing alternative intelligent sensor positioning and orientation schemes that integrate various sensors in more automatic ways. The proposed schemes are implemented using one of the most famous constructive neural networks--the Cascade Correlation Neural Network (CCNNs)--to overcome the limitations of conventional techniques based on KF/smoother algorithms as well as previously developed MFNN-smoother schemes. The CCNNs applied also have the advantage of a more flexible topology compared to MFNNs. Based on the experimental data utilized the preliminary results presented in this article illustrate the effectiveness of the proposed schemes compared to smoother algorithms as well as the MFNN

  11. A survey of geosensor networks: advances in dynamic environmental monitoring.

    PubMed

    Nittel, Silvia

    2009-01-01

    In the recent decade, several technology trends have influenced the field of geosciences in significant ways. The first trend is the more readily available technology of ubiquitous wireless communication networks and progress in the development of low-power, short-range radio-based communication networks, the miniaturization of computing and storage platforms as well as the development of novel microsensors and sensor materials. All three trends have changed the type of dynamic environmental phenomena that can be detected, monitored and reacted to. Another important aspect is the real-time data delivery of novel platforms today. In this paper, I will survey the field of geosensor networks, and mainly focus on the technology of small-scale geosensor networks, example applications and their feasibility and lessons learnt as well as the current research questions posed by using this technology today. Furthermore, my objective is to investigate how this technology can be embedded in the current landscape of intelligent sensor platforms in the geosciences and identify its place and purpose. PMID:22346721

  12. Advanced Energy Storage Management in Distribution Network

    SciTech Connect

    Liu, Guodong; Ceylan, Oguzhan; Xiao, Bailu; Starke, Michael R; Ollis, T Ben; King, Daniel J; Irminger, Philip; Tomsovic, Kevin

    2016-01-01

    With increasing penetration of distributed generation (DG) in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative mixed integer quadratic constrained quadratic programming model to optimize the operation of a three phase unbalanced distribution system with high penetration of Photovoltaic (PV) panels, DG and energy storage (ES) is developed. The proposed model minimizes not only the operating cost, including fuel cost and purchasing cost, but also voltage deviations and power loss. The optimization model is based on the linearized sensitivity coefficients between state variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DG and ES). To avoid slow convergence when close to the optimum, a golden search method is introduced to control the step size and accelerate the convergence. The proposed algorithm is demonstrated on modified IEEE 13 nodes test feeders with multiple PV panels, DG and ES. Numerical simulation results validate the proposed algorithm. Various scenarios of system configuration are studied and some critical findings are concluded.

  13. Intelligent neural network and fuzzy logic control of industrial and power systems

    NASA Astrophysics Data System (ADS)

    Kuljaca, Ognjen

    The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of

  14. Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

    PubMed Central

    Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

  15. Advances in software development for intelligent interfaces for alarm and emergency management consoles

    SciTech Connect

    Moseley, M.R.; Olson, C.E.

    1986-01-01

    Recent advances in technology allow features like voice synthesis, voice and speech recognition, image understanding, and intelligent data base management to be incorporated in computer driven alarm and emergency management information systems. New software development environments make it possible to do rapid prototyping of custom applications. Three examples using these technologies are discussed. (1) Maximum use is made of high-speed graphics and voice synthesis to implement a state-of-the-art alarm processing and display system with features that make the operator-machine interface efficient and accurate. Although very functional, this system is not portable or flexible; the software would have to be substantially rewritten for other applications. (2) An application generator which has the capability of ''building'' a specific alarm processing and display application in a matter of a few hours, using the site definition developed in the security planning phase to produce the custom application. This package is based on a standardized choice of hardware, within which it is capable of building a system to order, automatically constructing graphics, data tables, alarm prioritization rules, and interfaces to peripherals. (3) A software tool, the User Interface Management System (UIMS), is described which permits rapid prototyping of human-machine interfaces for a variety of applications including emergency management, alarm display and process information display. The object-oriented software of the UIMS achieves rapid prototyping of a new interface by standardizing to a class library of software objects instead of hardware objects.

  16. Technologies for developing an advanced intelligent ATM with self-defence capabilities

    NASA Astrophysics Data System (ADS)

    Sako, Hiroshi

    2010-01-01

    We have developed several technologies for protecting automated teller machines. These technologies are based mainly on pattern recognition and are used to implement various self-defence functions. They include (i) banknote recognition and information retrieval for preventing machines from accepting counterfeit and damaged banknotes and for retrieving information about detected counterfeits from a relational database, (ii) form processing and character recognition for preventing machines from accepting remittance forms without due dates and/or insufficient payment, (iii) person identification to prevent machines from transacting with non-customers, and (iv) object recognition to guard machines against foreign objects such as spy cams that might be surreptitiously attached to them and to protect users against someone attempting to peek at their user information such as their personal identification number. The person identification technology has been implemented in most ATMs in Japan, and field tests have demonstrated that the banknote recognition technology can recognise more then 200 types of banknote from 30 different countries. We are developing an "advanced intelligent ATM" that incorporates all of these technologies.

  17. Advancing Capabilities for Understanding the Earth System Through Intelligent Systems, the NSF Perspective

    NASA Astrophysics Data System (ADS)

    Gil, Y.; Zanzerkia, E. E.; Munoz-Avila, H.

    2015-12-01

    The National Science Foundation (NSF) Directorate for Geosciences (GEO) and Directorate for Computer and Information Science (CISE) acknowledge the significant scientific challenges required to understand the fundamental processes of the Earth system, within the atmospheric and geospace, Earth, ocean and polar sciences, and across those boundaries. A broad view of the opportunities and directions for GEO are described in the report "Dynamic Earth: GEO imperative and Frontiers 2015-2020." Many of the aspects of geosciences research, highlighted both in this document and other community grand challenges, pose novel problems for researchers in intelligent systems. Geosciences research will require solutions for data-intensive science, advanced computational capabilities, and transformative concepts for visualizing, using, analyzing and understanding geo phenomena and data. Opportunities for the scientific community to engage in addressing these challenges are available and being developed through NSF's portfolio of investments and activities. The NSF-wide initiative, Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21), looks to accelerate research and education through new capabilities in data, computation, software and other aspects of cyberinfrastructure. EarthCube, a joint program between GEO and the Advanced Cyberinfrastructure Division, aims to create a well-connected and facile environment to share data and knowledge in an open, transparent, and inclusive manner, thus accelerating our ability to understand and predict the Earth system. EarthCube's mission opens an opportunity for collaborative research on novel information systems enhancing and supporting geosciences research efforts. NSF encourages true, collaborative partnerships between scientists in computer sciences and the geosciences to meet these challenges.

  18. Developing an Intelligent System for Diagnosis of Asthma Based on Artificial Neural Network

    PubMed Central

    Alizadeh, Behrouz; Safdari, Reza; Zolnoori, Maryam; Bashiri, Azadeh

    2015-01-01

    Introduction: Lack of proper diagnosis and inadequate treatment of asthma, leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson’s coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different modes was made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. So considering the data mining approaches due to the nature of medical data is necessary. PMID:26483595

  19. Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

    PubMed Central

    Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

    2015-01-01

    Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency. PMID:26609303

  20. Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

    PubMed

    Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

    2015-01-01

    Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency. PMID:26609303

  1. Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

    PubMed

    Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

    2015-01-01

    Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.

  2. Intelligent Sensor Positioning and Orientation Through Constructive Neural Network-Embedded INS/GPS Integration Algorithms

    PubMed Central

    Chiang, Kai-Wei; Chang, Hsiu-Wen

    2010-01-01

    Mobile mapping systems have been widely applied for acquiring spatial information in applications such as spatial information systems and 3D city models. Nowadays the most common technologies used for positioning and orientation of a mobile mapping system include a Global Positioning System (GPS) as the major positioning sensor and an Inertial Navigation System (INS) as the major orientation sensor. In the classical approach, the limitations of the Kalman Filter (KF) method and the overall price of multi-sensor systems have limited the popularization of most land-based mobile mapping applications. Although intelligent sensor positioning and orientation schemes consisting of Multi-layer Feed-forward Neural Networks (MFNNs), one of the most famous Artificial Neural Networks (ANNs), and KF/smoothers, have been proposed in order to enhance the performance of low cost Micro Electro Mechanical System (MEMS) INS/GPS integrated systems, the automation of the MFNN applied has not proven as easy as initially expected. Therefore, this study not only addresses the problems of insufficient automation in the conventional methodology that has been applied in MFNN-KF/smoother algorithms for INS/GPS integrated systems proposed in previous studies, but also exploits and analyzes the idea of developing alternative intelligent sensor positioning and orientation schemes that integrate various sensors in more automatic ways. The proposed schemes are implemented using one of the most famous constructive neural networks—the Cascade Correlation Neural Network (CCNNs)—to overcome the limitations of conventional techniques based on KF/smoother algorithms as well as previously developed MFNN-smoother schemes. The CCNNs applied also have the advantage of a more flexible topology compared to MFNNs. Based on the experimental data utilized the preliminary results presented in this article illustrate the effectiveness of the proposed schemes compared to smoother algorithms as well as the MFNN

  3. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  4. [The study on the characters of membrane protein interaction and its network based on integrated intelligence method].

    PubMed

    Shen, Yizhen; Ding, Yongsheng; Hao, Kuangrong

    2011-08-01

    Membrane protein and its interaction network have become a novel research direction in bioinformatics. In this paper, a novel membrane protein interaction network simulator is proposed for system biology studies by integrated intelligence method including spectrum analysis, fuzzy K-Nearest Neighbor(KNN) algorithm and so on. We consider biological system as a set of active computational components interacting with each other and with the external environment. Then we can use the network simulator to construct membrane protein interaction networks. Based on the proposed approach, we found that the membrane protein interaction network almost has some dynamic and collective characteristics, such as small-world network, scale free distributing, and hierarchical module structure. These properties are similar to those of other extensively studied protein interaction networks. The present studies on the characteristics of the membrane protein interaction network will be valuable for its relatively biological and medical studies. PMID:21936357

  5. Adaptive pattern recognition by mini-max neural networks as a part of an intelligent processor

    NASA Technical Reports Server (NTRS)

    Szu, Harold H.

    1990-01-01

    In this decade and progressing into 21st Century, NASA will have missions including Space Station and the Earth related Planet Sciences. To support these missions, a high degree of sophistication in machine automation and an increasing amount of data processing throughput rate are necessary. Meeting these challenges requires intelligent machines, designed to support the necessary automations in a remote space and hazardous environment. There are two approaches to designing these intelligent machines. One of these is the knowledge-based expert system approach, namely AI. The other is a non-rule approach based on parallel and distributed computing for adaptive fault-tolerances, namely Neural or Natural Intelligence (NI). The union of AI and NI is the solution to the problem stated above. The NI segment of this unit extracts features automatically by applying Cauchy simulated annealing to a mini-max cost energy function. The feature discovered by NI can then be passed to the AI system for future processing, and vice versa. This passing increases reliability, for AI can follow the NI formulated algorithm exactly, and can provide the context knowledge base as the constraints of neurocomputing. The mini-max cost function that solves the unknown feature can furthermore give us a top-down architectural design of neural networks by means of Taylor series expansion of the cost function. A typical mini-max cost function consists of the sample variance of each class in the numerator, and separation of the center of each class in the denominator. Thus, when the total cost energy is minimized, the conflicting goals of intraclass clustering and interclass segregation are achieved simultaneously.

  6. FUDAOWANG: A Web-Based Intelligent Tutoring System Implementing Advanced Education Concepts

    ERIC Educational Resources Information Center

    Xu, Wei; Zhao, Ke; Li, Yatao; Yi, Zhenzhen

    2012-01-01

    Determining how to provide good tutoring functions is an important research direction of intelligent tutoring systems. In this study, the authors develop an intelligent tutoring system with good tutoring functions, called "FUDAOWANG." The research domain that FUDAOWANG treats is junior middle school mathematics, which belongs to the objective…

  7. Reflections on the Concept of Intelligence. Advances in Cognition and Educational Practice. Volume 4.

    ERIC Educational Resources Information Center

    Kingma, Johannes, Ed.; Tomic, Welko, Ed.

    This book contains papers that discuss the "g factor" (general intellectual capacity) in discerning intelligence and how to influence the development of intelligence. The g factor relates to the theory that individuals who do well on one mental ability test tend to do well on other mental ability tests due to an innate ability. Chapters include:…

  8. EARLINET: towards an advanced sustainable European aerosol lidar network

    NASA Astrophysics Data System (ADS)

    Pappalardo, G.; Amodeo, A.; Apituley, A.; Comeron, A.; Freudenthaler, V.; Linné, H.; Ansmann, A.; Bösenberg, J.; D'Amico, G.; Mattis, I.; Mona, L.; Wandinger, U.; Amiridis, V.; Alados-Arboledas, L.; Nicolae, D.; Wiegner, M.

    2014-08-01

    The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue, which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 stations in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multiwavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase in the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the

  9. Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

    ERIC Educational Resources Information Center

    Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

    2003-01-01

    Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

  10. Gigabit Satellite Network for NASA's Advanced Communication Technology Satellite (ACTS)

    NASA Technical Reports Server (NTRS)

    Hoder, Douglas; Bergamo, Marcos

    1996-01-01

    The advanced communication technology satellite (ACTS) gigabit satellite network provides long-haul point-to-point and point-to-multipoint full-duplex SONET services over NASA's ACTS. at rates up to 622 Mbit/s (SONET OC-12), with signal quality comparable to that obtained with terrestrial fiber networks. Data multiplexing over the satellite is accomplished using time-division multiple access (TDMA) techniques coordinated with the switching and beam hopping facilities provided by ACTS. Transmissions through the satellite are protected with Reed-Solomon encoding. providing virtually error-free transmission under most weather conditions. Unique to the system are a TDMA frame structure and satellite synchronization mechanism that allow: (a) very efficient utilization of the satellite capacity: (b) over-the-satellite dosed-loop synchronization of the network in configurations with up to 64 ground stations: and (c) ground station initial acquisition without collisions with existing signalling or data traffic. The user interfaces are compatible with SONET standards, performing the function of conventional SONET multiplexers and. as such. can be: readily integrated with standard SONET fiber-based terrestrial networks. Management of the network is based upon the simple network management protocol (SNMP). and includes an over-the-satellite signalling network and backup terrestrial internet (IP-based) connectivity. A description of the ground stations is also included.

  11. Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

    NASA Technical Reports Server (NTRS)

    Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

    1989-01-01

    This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

  12. EDITORIAL: Advances in Measurement Technology and Intelligent Instruments for Production Engineering

    NASA Astrophysics Data System (ADS)

    Gao, Wei; Takaya, Yasuhiro; Gao, Yongsheng; Krystek, Michael

    2008-08-01

    . Neuschaefer-Rube et al, also from PTB, present procedures and standards to test tactile and optical microsensors and micro-computed tomography systems, which are similar to the established tests for classical coordinate measuring machines and assess local and global sensor characteristics. The last three papers are related to micro/nano-metrology and intelligent instrumentation. Jiang et al from Tohoku University describe the fabrication of piezoresistive nanocantilevers for ultra-sensitive force detection by using spin-out diffusion, EB lithography and FAB etching, respectively. Y-C Liu et al from National Taiwan University develop an economical and highly sensitive optical accelerometer using a commercial optical pickup head. Michihata et al from Osaka University experimentally investigate the positioning sensing property and accuracy of a laser trapping probe for a nano-coordinate measuring machine. As guest editors, we believe that this special feature presents the newest information on advances in measurement technology and intelligent instruments from basic research to applied systems for Production Engineering. We would like to thank all the authors for their great contributions to this special feature and the referees for their careful reviews of the papers. We would also like to express our thanks and appreciation to Professor P Hauptmann, Editor-in-Chief of MST, for his kind offer to publish selected ISMTII 2007 papers in MST, and to the publishing staff of MST for their dedicated efforts that have made this special feature possible.

  13. The intelligent operation of an urban drainage system using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Chang, F.; Chiang, Y.; Tsai, M.; Wang, Y.; Chang, L.

    2009-12-01

    The pumping stations are the major hydraulic facilities for the elimination of flood in metropolitan area and therefore play an important role in urban drainage systems. Nevertheless, the time of concentration in such highly developed cities is quite short and usually results in great damage due to the un-functional pumping station that caused by flash flood. Current operation strategy used in Taiwan during typhoon periods depends on the human experience, and thus is necessary for further investigation to increase the operating reliability of pumping station. In view of the characteristic of Adaptive Network-based Fuzzy Inference System (ANFIS), the model was applied in this study for extracting superior operations/rules from torrential rainfall events. Historical records contain information of rainfall amounts, inner water levels, and pump and gate operating records. The results indicate that the ANFIS has an efficient learning ability to construct an intelligent operating strategy and has the potential ability to automatically operate the flood control system.

  14. Analysis of reconfigurable multi-channel wavelength add drop multiplexer for intelligent optical networks

    NASA Astrophysics Data System (ADS)

    Ponmalar, S.; Sundaravadivelu, S.

    2011-07-01

    This paper presents design of an electro-optically tunable polymer multi-channel wavelength add drop multiplexer (WADM). The proposed WADM with trapezoidal waveguide geometry and poled electro-optical polymer material in the waveguide cores enables the wavelength tuning speed of WADM as 7.5 ps at the resonance wavelength of 1550 nm and coupling length of 1.5 mm. The device can be electro-optically tuned to add/drop multiple channels. Transmission spectra of the device with varying device parameters are simulated. The proposed WADM with high speed, small size and varying tuning capability makes this device, an important element in faster provisioning and routing of light paths in intelligent optical network.

  15. Fuzzy Mobile-Robot Positioning in Intelligent Spaces Using Wireless Sensor Networks

    PubMed Central

    Herrero, David; Martínez, Humberto

    2011-01-01

    This work presents the development and experimental evaluation of a method based on fuzzy logic to locate mobile robots in an Intelligent Space using Wireless Sensor Networks (WSNs). The problem consists of locating a mobile node using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. The sensor model of these measurements is very noisy and unreliable. The proposed method makes use of fuzzy logic for modeling and dealing with such uncertain information. Besides, the proposed approach is compared with a probabilistic technique showing that the fuzzy approach is able to handle highly uncertain situations that are difficult to manage by well-known localization methods. PMID:22346673

  16. Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network.

    PubMed

    Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R

    2016-01-01

    Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.

  17. A Geographic Location-Based Security Mechanism for Intelligent Vehicular Networks

    NASA Astrophysics Data System (ADS)

    Yan, Gongjun; Lin, Jingli; Rawat, Danda B.; Yang, Weiming

    In Intelligent Vehicular Networks, featured as car-to-car and car-to-infrastructure wireless communication, most applications need important location information or credential information. We address a location-based encryption method that not only ensures messages confidentiality but also authenticates identity and location of communication peers. The authentication of location means that a message can only decrypted by the receiver which is "physically" present inside a decryption region specified by locations, and is moving at a specific speed, acceleration and at a specific time period. A secret key is generated by converting location, time and mobility information (such as speed and acceleration) into a unique number. The determination of the decryption region is addressed in two steps: predicting and updating. The proposed method evaluated by simulations is efficient and secure.

  18. iSANLA: intelligent sensor and actuator network for life science applications.

    PubMed

    Schloesser, Mario; Schnitzer, Andreas; Ying, Hong; Silex, Carmen; Schiek, Michael

    2008-01-01

    In the fields of neurological rehabilitation and neurophysiological research there is a strong need for miniaturized, multi channel, battery driven, wireless networking DAQ systems enabling real-time digital signal processing and feedback experiments. For the scientific investigation on the passive auditory based 3D-orientation of Barn Owls and the scientific research on vegetative locomotor coordination of Parkinson's disease patients during rehabilitation we developed our 'intelligent Sensor and Actuator Network for Life science Application' (iSANLA) system. Implemented on the ultra low power microcontroller MSP430 sample rates up to 96 kHz have been realised for single channel DAQ. The system includes lossless local data storage up to 4 GB. With its outer dimensions of 20mm per rim and less than 15 g of weight including the Lithium-Ion battery our modular designed sensor node is thoroughly capable of up to eight channel recordings with 8 kHz sample rate each and provides sufficient computational power for digital signal processing ready to start our first mobile experiments. For wireless mobility a compact communication protocol based on the IEEE 802.15.4 wireless standard with net data rates up to 141 kbit/s has been implemented. To merge the lossless acquired data of the distributed iNODEs a time synchronization protocol has been developed preserving causality. Hence the necessary time synchronous start of the data acquisition inside a network of multiple sensors with a precision better than the highest sample rate has been realized. PMID:19163178

  19. The TurboLAN project. Phase 1: Protocol choices for high speed local area networks. Phase 2: TurboLAN Intelligent Network Adapter Card, (TINAC) architecture

    NASA Technical Reports Server (NTRS)

    Alkhatib, Hasan S.

    1991-01-01

    The hardware and the software architecture of the TurboLAN Intelligent Network Adapter Card (TINAC) are described. A high level as well as detailed treatment of the workings of various components of the TINAC are presented. The TINAC is divided into the following four major functional units: (1) the network access unit (NAU); (2) the buffer management unit; (3) the host interface unit; and (4) the node processor unit.

  20. EARLINET: towards an advanced sustainable European aerosol lidar network

    NASA Astrophysics Data System (ADS)

    Pappalardo, G.; Amodeo, A.; Apituley, A.; Comeron, A.; Freudenthaler, V.; Linné, H.; Ansmann, A.; Bösenberg, J.; D'Amico, G.; Mattis, I.; Mona, L.; Wandinger, U.; Amiridis, V.; Alados-Arboledas, L.; Nicolae, D.; Wiegner, M.

    2014-03-01

    The European Aerosol Research Lidar Network, EARLINET was founded in 2000 as a research project for establishing a quantitative, comprehensive and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET is continuing to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last thirteen years. Since 2000, EARLINET has strongly developed in terms of number of stations and spatial distribution, from 17 stations in 10 countries in 2000, to 27 stations in 16 countries in 2013. EARLINET has strongly developed also in terms of technological advances with the spread of advanced multi-wavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing and dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase of the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions and for model evaluation and satellite data validation and integration. Future plans are in the direction of continuous measurements and near real time data delivery in close cooperation with other ground-based networks, as in the ACTRIS research infrastructure, and with the modelling and satellite community, bridging the research community with the

  1. Identifying Gaps in Grid Middleware on Fast Networks with the Advanced Networking Initiative

    NASA Astrophysics Data System (ADS)

    Dykstra, Dave; Garzoglio, Gabriele; Kim, Hyunwoo; Mhashilkar, Parag

    2012-12-01

    As of 2012, a number of US Department of Energy (DOE) National Laboratories have access to a 100 Gb/s wide-area network backbone. The ESnet Advanced Networking Initiative (ANI) project is intended to develop a prototype network, based on emerging 100 Gb/s Ethernet technology. The ANI network will support DOE's science research programs. A 100 Gb/s network test bed is a key component of the ANI project. The test bed offers the opportunity for early evaluation of 100Gb/s network infrastructure for supporting the high impact data movement typical of science collaborations and experiments. In order to make effective use of this advanced infrastructure, the applications and middleware currently used by the distributed computing systems of large-scale science need to be adapted and tested within the new environment, with gaps in functionality identified and corrected. As a user of the ANI test bed, Fermilab aims to study the issues related to end-to-end integration and use of 100 Gb/s networks for the event simulation and analysis applications of physics experiments. In this paper we discuss our findings from evaluating existing HEP Physics middleware and application components, including GridFTP, Globus Online, etc. in the high-speed environment. These will include possible recommendations to the system administrators, application and middleware developers on changes that would make production use of the 100 Gb/s networks, including data storage, caching and wide area access.

  2. An analysis of the structure and evolution of the scientific collaboration network of computer intelligence in games

    NASA Astrophysics Data System (ADS)

    Lara-Cabrera, R.; Cotta, C.; Fernández-Leiva, A. J.

    2014-02-01

    Games constitute a research domain that is attracting the interest of scientists from numerous disciplines. This is particularly true from the perspective of computational intelligence. In order to examine the growing importance of this area in the gaming domain, we present an analysis of the scientific collaboration network of researchers working on computational intelligence in games (CIG). This network has been constructed from bibliographical data obtained from the Digital Bibliography & Library Project (DBLP). We have analyzed from a temporal perspective several properties of the CIG network at the macroscopic, mesoscopic and microscopic levels, studying the large-scale structure, the growth mechanics, and collaboration patterns among other features. Overall, computational intelligence in games exhibits similarities with other collaboration networks such as for example a log-normal degree distribution and sub-linear preferential attachment for new authors. It also has distinctive features, e.g. the number of papers co-authored is exponentially distributed, the internal preferential attachment (new collaborations among existing authors) is linear, and fidelity rates (measured as the relative preference for publishing with previous collaborators) grow super-linearly. The macroscopic and mesoscopic evolution of the network indicates the field is very active and vibrant, but it is still at an early developmental stage. We have also analyzed communities and central nodes and how these are reflected in research topics, thus identifying active research subareas.

  3. Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT.

    PubMed

    Nguyen, Thu L N; Shin, Yoan

    2016-05-18

    Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton's method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach.

  4. Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

    PubMed Central

    Nguyen, Thu L. N.; Shin, Yoan

    2016-01-01

    Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378

  5. Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT.

    PubMed

    Nguyen, Thu L N; Shin, Yoan

    2016-01-01

    Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton's method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378

  6. Advanced Communication and Networking Technologies for Mars Exploration

    NASA Technical Reports Server (NTRS)

    Bhasin, Kul; Hayden, Jeff; Agre, Jonathan R.; Clare, Loren P.; Yan, Tsun-Yee

    2001-01-01

    Next-generation Mars communications networks will provide communications and navigation services to a wide variety of Mars science vehicles including: spacecraft that are arriving at Mars, spacecraft that are entering and descending in the Mars atmosphere, scientific orbiter spacecraft, spacecraft that return Mars samples to Earth, landers, rovers, aerobots, airplanes, and sensing pods. In the current architecture plans, the communication services will be provided using capabilities deployed on the science vehicles as well as dedicated communication satellites that will together make up the Mars network. This network will evolve as additional vehicles arrive, depart or end their useful missions. Cost savings and increased reliability will result from the ability to share communication services between missions. This paper discusses the basic architecture that is needed to support the Mars Communications Network part of NASA's Space Science Enterprise (SSE) communications architecture. The network may use various networking technologies such as those employed in the terrestrial Internet, as well as special purpose deep-space protocols to move data and commands autonomously between vehicles, at disparate Mars vicinity sites (on the surface or in near-Mars space) and between Mars vehicles and earthbound users. The architecture of the spacecraft on-board local communications is being reconsidered in light of these new networking requirements. The trend towards increasingly autonomous operation of the spacecraft is aimed at reducing the dependence on resource scheduling provided by Earth-based operators and increasing system fault tolerance. However, these benefits will result in increased communication and software development requirements. As a result, the envisioned Mars communications infrastructure requires both hardware and protocol technology advancements. This paper will describe a number of the critical technology needs and some of the ongoing research

  7. Developing an Intelligent Reservoir Flood Control Decision Support System through Integrating Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Chang, L. C.; Kao, I. F.; Tsai, F. H.; Hsu, H. C.; Yang, S. N.; Shen, H. Y.; Chang, F. J.

    2015-12-01

    Typhoons and storms hit Taiwan several times every year and cause serious flood disasters. Because the mountainous terrain and steep landform rapidly accelerate the speed of flood flow, rivers cannot be a stable source of water supply. Reservoirs become one of the most important and effective floodwater storage facilities. However, real-time operation for reservoir flood control is a continuous and instant decision-making process based on rules, laws, meteorological nowcast, in addition to the immediate rainfall and hydrological data. The achievement of reservoir flood control can effectively mitigate flood disasters and store floodwaters for future uses. In this study, we construct an intelligent decision support system for reservoir flood control through integrating different types of neural networks and the above information to solve this problem. This intelligent reservoir flood control decision support system includes three parts: typhoon track classification, flood forecast and adaptive water release models. This study used the self-organizing map (SOM) for typhoon track clustering, nonlinear autoregressive with exogenous inputs (NARX) for multi-step-ahead reservoir inflow prediction, and adaptive neuro-fuzzy inference system (ANFIS) for reservoir flood control. Before typhoons landfall, we can estimate the entire flood hydrogragh of reservoir inflow by using SOM and make a pre-release strategy and real-time reservoir flood operating by using ANFIS. In the meanwhile, NARX can be constantly used real-time five-hour-ahead inflow prediction for providing the newest flood information. The system has been successfully implemented Typhoons Trami (2013), Fitow (2013) and Matmo (2014) in Shihmen Reservoir.

  8. The "Wireless Sensor Networks for City-Wide Ambient Intelligence (WISE-WAI)" Project.

    PubMed

    Casari, Paolo; Castellani, Angelo P; Cenedese, Angelo; Lora, Claudio; Rossi, Michele; Schenato, Luca; Zorzi, Michele

    2009-01-01

    This paper gives a detailed technical overview of some of the activities carried out in the context of the "Wireless Sensor networks for city-Wide Ambient Intelligence (WISE-WAI)" project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide. These applications include long-term environmental monitoring, alarm event detection and propagation, single-sensor interrogation, localization and tracking of objects, assisted navigation, as well as fast data dissemination services to be used, e.g., to rapidly re-program all sensors over-the-air. The organization of such a large testbed requires notable efforts in terms of communication protocols and strategies, whose design must pursue scalability, energy efficiency (while sensors are connected through USB cables for logging and debugging purposes, most of them will be battery-operated), as well as the capability to support applications with diverse requirements. These efforts, the description of a subset of the results obtained so far, and of the final objectives to be met are the scope of the present paper. PMID:22408513

  9. Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial.

    PubMed

    Kulin, Merima; Fortuna, Carolina; De Poorter, Eli; Deschrijver, Dirk; Moerman, Ingrid

    2016-06-01

    Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves.

  10. Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial.

    PubMed

    Kulin, Merima; Fortuna, Carolina; De Poorter, Eli; Deschrijver, Dirk; Moerman, Ingrid

    2016-01-01

    Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves. PMID:27258286

  11. Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial

    PubMed Central

    Kulin, Merima; Fortuna, Carolina; De Poorter, Eli; Deschrijver, Dirk; Moerman, Ingrid

    2016-01-01

    Data science or “data-driven research” is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves. PMID:27258286

  12. Advanced mobility handover for mobile IPv6 based wireless networks.

    PubMed

    Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

    2014-01-01

    We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches.

  13. Advanced mobility handover for mobile IPv6 based wireless networks.

    PubMed

    Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

    2014-01-01

    We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches. PMID:25614890

  14. Advanced Mobility Handover for Mobile IPv6 Based Wireless Networks

    PubMed Central

    Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

    2014-01-01

    We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches. PMID:25614890

  15. Advancing Systems Biology in the International Conference on Intelligent Biology and Medicine (ICIBM) 2015.

    PubMed

    Zhao, Zhongming; Liu, Yunlong; Huang, Yufei; Huang, Kun; Ruan, Jianhua

    2016-08-26

    The 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) was held on November 13-15, 2015 in Indianapolis, Indiana, USA. ICIBM 2015 included eight scientific sessions, three tutorial sessions, one poster session, and four keynote presentations that covered the frontier research in broad areas related to bioinformatics, systems biology, big data science, biomedical informatics, pharmacogenomics, and intelligent computing. Here, we present a summary of the 10 research articles that were selected from ICIBM 2015 and included in the supplement to BMC Systems Biology.

  16. Advancing Systems Biology in the International Conference on Intelligent Biology and Medicine (ICIBM) 2015.

    PubMed

    Zhao, Zhongming; Liu, Yunlong; Huang, Yufei; Huang, Kun; Ruan, Jianhua

    2016-01-01

    The 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) was held on November 13-15, 2015 in Indianapolis, Indiana, USA. ICIBM 2015 included eight scientific sessions, three tutorial sessions, one poster session, and four keynote presentations that covered the frontier research in broad areas related to bioinformatics, systems biology, big data science, biomedical informatics, pharmacogenomics, and intelligent computing. Here, we present a summary of the 10 research articles that were selected from ICIBM 2015 and included in the supplement to BMC Systems Biology. PMID:27587087

  17. Web Intelligence and Artificial Intelligence in Education

    ERIC Educational Resources Information Center

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  18. HIDEN: A hybrid intelligent system for synthesizing highly controllable exchanger networks -- Implementation of a distributed strategy for integrating process design and control. [Hybrid Intelligent Design system for Exchanger Networks

    SciTech Connect

    Huang, Y.L. . Dept. of Chemical Engineering); Fan, L.T. . Dept. of Chemical Engineering)

    1994-05-01

    The development of computer-aided-design systems is the key step toward process design automation. The most difficult phase of this development is to endow the system with the capability to perform conceptual design, i.e., process synthesis. This is especially true when a synthesized process is expected to satisfy simultaneously economic and operational criteria. To meet these criteria, it is highly desirable that the first-principles and heuristic knowledge, which can be numerical or symbolic, structured or unstructured, be fully exploited and that the information and data, which can be precise or imprecise, certain or uncertain, be appropriately manipulated. In the present work, a hybrid intelligent design system for synthesizing exchanger networks (HIDEN) is developed by means of a knowledge-based approach, fuzzy logic, and neural networks. This system, built on an artificial intelligence workstation, fully implements the distributed strategy for integrating process design and control. It is capable of synthesizing heat exchanger networks (HEN's) and mass exchanger networks (MEN's) for the recovery of energy and material, respectively. The resulting exchanger networks are cost-effective as well as highly controllable.

  19. Turtle Escapes the Plane: Some Advanced Turtle Geometry. Artificial Intelligence Memo Number 348.

    ERIC Educational Resources Information Center

    diSessa, Andy

    The LOGO Turtles, originally developed at the Massachusetts Institute of Technology Artificial Intelligence Laboratory for teaching concepts in elementary geometry to primary-age children, can also be used in teaching higher-level mathematics. In the exercises described here, the turtle was programed to traverse curved surfaces. Both geometric and…

  20. Recent Advances in Magnetoseismology Using Network Observations by Ground Magnetometers

    NASA Astrophysics Data System (ADS)

    Chi, P. J.; Russell, C. T.

    2011-12-01

    The rise of modern, synchronized networks of ground magnetometers in recent years has inspired and advanced research and development in magnetoseismology. Like the practice in other geophysical disciplines, magnetoseismology can infer the structure of the magnetosphere from the observations of normal-mode frequencies of the magnetic field. It can also time and locate impulsive events by measuring the signal arrival time at multiple ground stations. We highlight recent advances in using network observations by ground magnetometers for both types of magnetoseismic research. In the area of normal-mode magnetoseismology the increase in ground magnetometers has enabled ever more station pairs suitable for the gradient analysis. We demonstrate progress in automatic detection of field line resonance frequencies and the results that reveal longitudinal structure of the plasmasphere. As a relatively young research topic, travel-time magnetoseismology has shown its capability to time and locate sudden impulses and substorm onsets by using ground-based magnetometer observations. These initial successes in turn motivated detailed examination of MHD wave propagation in the magnetosphere. In the end we discuss how these magnetoseismic studies shed light on the regions in the world where future establishment of ground magnetometers is desirable.

  1. Domain decomposition in multidisciplinary design: Role of artificial neural networks and intelligent agents

    NASA Astrophysics Data System (ADS)

    Arslan, Mehmet Ali

    This thesis examines decomposition based procedures in the optimal design of large-scale multidisciplinary systems. The use of formal optimization methods in such systems is complicated by the presence of a large number of design variables and constraints. Decomposition reduces a large-scale system into a sequence of smaller, more tractable subsystems, each with a smaller set of design variables and constraints. The decomposed subsystems, however, are not totally decoupled, and design changes in one subsystem may have a profound influence on changes in other subsystems. The present work examines the effectiveness of counterpropagation (CP) neural networks as a tool to account for this coupling. This capability derives from a pattern completion capability of such networks. The proposed approach is implemented for a class of structural design problems where the decomposed subsystems exhibit hierarchy, i.e., there is a distinct chain of command in the nature of couplings between the subsystems. The role of artificial neural networks is also explored in the context of concurrent subspace optimization (CSSO) where this decomposition based approach is applicable to problems where no distinct hierarchy of influences can be identified. Essential components of decomposition based design methods are strategies to identify a topology for problem decomposition, and to develop coordination strategies which account for couplings among the decomposed problems. The present thesis examines the effectiveness of artificial neural networks as a tool to both account for the coupling, and to develop methods to coordinate the solution in the different subproblems. The solution process for decomposition based design is further enhanced by a novel approach of using Intelligent Agents (IA's). This agent-based paradigm provides the necessary support structure for representing salient characteristics of the design, and for coordinating the solutions in different subproblems. The CSSO method

  2. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

    NASA Astrophysics Data System (ADS)

    Jia, Feng; Lei, Yaguo; Lin, Jing; Zhou, Xin; Lu, Na

    2016-05-01

    Aiming to promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rotating machinery. Among these studies, the methods based on artificial neural networks (ANNs) are commonly used, which employ signal processing techniques for extracting features and further input the features to ANNs for classifying faults. Though these methods did work in intelligent fault diagnosis of rotating machinery, they still have two deficiencies. (1) The features are manually extracted depending on much prior knowledge about signal processing techniques and diagnostic expertise. In addition, these manual features are extracted according to a specific diagnosis issue and probably unsuitable for other issues. (2) The ANNs adopted in these methods have shallow architectures, which limits the capacity of ANNs to learn the complex non-linear relationships in fault diagnosis issues. As a breakthrough in artificial intelligence, deep learning holds the potential to overcome the aforementioned deficiencies. Through deep learning, deep neural networks (DNNs) with deep architectures, instead of shallow ones, could be established to mine the useful information from raw data and approximate complex non-linear functions. Based on DNNs, a novel intelligent method is proposed in this paper to overcome the deficiencies of the aforementioned intelligent diagnosis methods. The effectiveness of the proposed method is validated using datasets from rolling element bearings and planetary gearboxes. These datasets contain massive measured signals involving different health conditions under various operating conditions. The diagnosis results show that the proposed method is able to not only adaptively mine available fault characteristics from the measured signals, but also obtain superior diagnosis accuracy compared with the existing methods.

  3. Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

    PubMed Central

    Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R.

    2016-01-01

    Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors. PMID:27537878

  4. Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network.

    PubMed

    Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R

    2016-01-01

    Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors. PMID:27537878

  5. The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil

    PubMed Central

    Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

    2015-01-01

    Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters. PMID:26569243

  6. The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil.

    PubMed

    Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

    2015-01-01

    Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters. PMID:26569243

  7. A neural network based intelligent predictive sensor for cloudiness, solar radiation and air temperature.

    PubMed

    Ferreira, Pedro M; Gomes, João M; Martins, Igor A C; Ruano, António E

    2012-11-12

    Accurate measurements of global solar radiation and atmospheric temperature,as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature.

  8. A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

    PubMed Central

    Ferreira, Pedro M.; Gomes, João M.; Martins, Igor A. C.; Ruano, António E.

    2012-01-01

    Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature. PMID:23202230

  9. Advanced optical network architecture for integrated digital avionics

    NASA Astrophysics Data System (ADS)

    Morgan, D. Reed

    1996-12-01

    For the first time in the history of avionics, the network designer now has a choice in selecting the media that interconnects the sources and sinks of digital data on aircraft. Electrical designs are already giving way to photonics in application areas where the data rate times distance product is large or where special design requirements such as low weight or EMI considerations are critical. Future digital avionic architectures will increasingly favor the use of photonic interconnects as network data rates of one gigabit/second and higher are needed to support real-time operation of high-speed integrated digital processing. As the cost of optical network building blocks is reduced and as temperature-rugged laser sources are matured, metal interconnects will be forced to retreat to applications spanning shorter and shorter distances. Although the trend is already underway, the widespread use of digital optics will first occur at the system level, where gigabit/second, real-time interconnects between sensors, processors, mass memories and displays separated by a least of few meters will be required. The application of photonic interconnects for inter-printed wiring board signalling across the backplane will eventually find application for gigabit/second applications since signal degradation over copper traces occurs before one gigabit/second and 0.5 meters are reached. For the foreseeable future however, metal interconnects will continue to be used to interconnect devices on printed wiring boards since 5 gigabit/second signals can be sent over metal up to around 15 centimeters. Current-day applications of optical interconnects at the system level are described and a projection of how advanced optical interconnect technology will be driven by the use of high speed integrated digital processing on future aircraft is presented. The recommended advanced network for application in the 2010 time frame is a fiber-based system with a signalling speed of around 2

  10. PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

    PubMed

    Rizvi, Sanam Shahla; Chung, Tae-Sun

    2010-01-01

    Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

  11. PIYAS-Proceeding to Intelligent Service Oriented Memory Allocation for Flash Based Data Centric Sensor Devices in Wireless Sensor Networks

    PubMed Central

    Rizvi, Sanam Shahla; Chung, Tae-Sun

    2010-01-01

    Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks. PMID:22315541

  12. PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

    PubMed

    Rizvi, Sanam Shahla; Chung, Tae-Sun

    2010-01-01

    Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks. PMID:22315541

  13. F-15 IFCS: Intelligent Flight Control System

    NASA Technical Reports Server (NTRS)

    Bosworth, John

    2007-01-01

    This viewgraph presentation describes the F-15 Intelligent Flight Control System (IFCS). The goals of this project include: 1) Demonstrate revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions; and 2) Demonstrate advance neural network-based flight control technology for new aerospace systems designs.

  14. Innovative Networking Concepts Tested on the Advanced Communications Technology Satellite

    NASA Technical Reports Server (NTRS)

    Friedman, Daniel; Gupta, Sonjai; Zhang, Chuanguo; Ephremides, Anthony

    1996-01-01

    This paper describes a program of experiments conducted over the advanced communications technology satellite (ACTS) and the associated TI-VSAT (very small aperture terminal). The experiments were motivated by the commercial potential of low-cost receive only satellite terminals that can operate in a hybrid network environment, and by the desire to demonstrate frame relay technology over satellite networks. The first experiment tested highly adaptive methods of satellite bandwidth allocation in an integrated voice-data service environment. The second involved comparison of forward error correction (FEC) and automatic repeat request (ARQ) methods of error control for satellite communication with emphasis on the advantage that a hybrid architecture provides, especially in the case of multicasts. Finally, the third experiment demonstrated hybrid access to databases and compared the performance of internetworking protocols for interconnecting local area networks (LANs) via satellite. A custom unit termed frame relay access switch (FRACS) was developed by COMSAT Laboratories for these experiments; the preparation and conduct of these experiments involved a total of 20 people from the University of Maryland, the University of Colorado and COMSAT Laboratories, from late 1992 until 1995.

  15. Intelligent biology and medicine in 2015: advancing interdisciplinary education, collaboration, and data science.

    PubMed

    Huang, Kun; Liu, Yunlong; Huang, Yufei; Li, Lang; Cooper, Lee; Ruan, Jianhua; Zhao, Zhongming

    2016-08-22

    We summarize the 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) and the editorial report of the supplement to BMC Genomics. The supplement includes 20 research articles selected from the manuscripts submitted to ICIBM 2015. The conference was held on November 13-15, 2015 at Indianapolis, Indiana, USA. It included eight scientific sessions, three tutorials, four keynote presentations, three highlight talks, and a poster session that covered current research in bioinformatics, systems biology, computational biology, biotechnologies, and computational medicine.

  16. Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

    NASA Astrophysics Data System (ADS)

    Kanevski, Mikhail; Volpi, Michele; Copa, Loris

    2010-05-01

    The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of

  17. An intelligent traffic controller

    SciTech Connect

    Kagolanu, K.; Fink, R.; Smartt, H.; Powell, R.; Larsen, E.

    1995-12-01

    A controller with advanced control logic can significantly improve traffic flows at intersections. In this vein, this paper explores fuzzy rules and algorithms to improve the intersection operation by rationalizing phase changes and green times. The fuzzy logic for control is enhanced by the exploration of neural networks for families of membership functions and for ideal cost functions. The concepts of fuzzy logic control are carried forth into the controller architecture. Finally, the architecture and the modules are discussed. In essence, the control logic and architecture of an intelligent controller are explored.

  18. Intelligent Systems and Advanced User Interfaces for Design, Operation, and Maintenance of Command Management Systems

    NASA Technical Reports Server (NTRS)

    Mitchell, Christine M.

    1998-01-01

    Historically Command Management Systems (CMS) have been large, expensive, spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as a to develop a more generic or a set of core components for CMS systems. Current MOC (mission operations center) hardware and software include Unix workstations, the C/C++ and Java programming languages, and X and Java window interfaces representations. This configuration provides the power and flexibility to support sophisticated systems and intelligent user interfaces that exploit state-of-the-art technologies in human-machine systems engineering, decision making, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of the issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, design and analysis tools from a human-machine systems engineering point of view (e.g., operator and designer models) and human-computer interaction tools, (e.g., graphics, visualization, and animation), may provide significant savings in the design, operation, and maintenance of a spacecraft-specific CMS as well as continuity for CMS design and development across spacecraft with varying needs. The savings in this case is in software reuse at all stages of the software engineering process.

  19. Intelligent systems and advanced user interfaces for design, operation, and maintenance of command management systems

    NASA Technical Reports Server (NTRS)

    Potter, William J.; Mitchell, Christine M.

    1993-01-01

    Historically, command management systems (CMS) have been large and expensive spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as to develop a more generic CMS system. New technologies, in addition to a core CMS common to a range of spacecraft, may facilitate the training and enhance the efficiency of CMS operations. Current mission operations center (MOC) hardware and software include Unix workstations, the C/C++ programming languages, and an X window interface. This configuration provides the power and flexibility to support sophisticated and intelligent user interfaces that exploit state-of-the-art technologies in human-machine interaction, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of these issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, human-machine systems design and analysis tools (e.g., operator and designer models), and human-computer interaction tools (e.g., graphics, visualization, and animation) may provide significant savings in the design, operation, and maintenance of the CMS for a specific spacecraft as well as continuity for CMS design and development across spacecraft. The first six months of this research saw a broad investigation by Georgia Tech researchers into the function, design, and operation of current and planned command management systems at Goddard Space Flight Center. As the first step, the researchers attempted to understand the current and anticipated horizons of command management systems at Goddard

  20. Proceedings of the Workshop on Advanced Network and Technology Concepts for Mobile, Micro, and Personal Communications

    NASA Technical Reports Server (NTRS)

    Paul, Lori (Editor)

    1991-01-01

    The Workshop on Advanced Network and Technology Concepts for Mobile, Micro, and Personal Communications was held at NASA's JPL Laboratory on 30-31 May 1991. It provided a forum for reviewing the development of advanced network and technology concepts for turn-of-the-century telecommunications. The workshop was organized into three main categories: (1) Satellite-Based Networks (L-band, C-band, Ku-band, and Ka-band); (2) Terrestrial-Based Networks (cellular, CT2, PCN, GSM, and other networks); and (3) Hybrid Satellite/Terrestrial Networks. The proceedings contain presentation papers from each of the above categories.

  1. Advanced course for doctors as Departmental IT Network Administrators in anesthesia and intensive care units.

    PubMed

    Lanza, Vincenzo; Huang, Chun-Hsi

    2006-10-01

    The design and administration of a departmental computer network (Local Area Network) in anesthesiology and intensive care offer the opportunity to manage clinical information and control the work-flow. To improve the local network, after basic design, intelligence is necessary to maintain its efficiency. For this reason the role of a medical administrator of the network is fundamental because he is a qualified figure who recognizes the most important characteristics that a network must have, knows the users of the system, represents a valid consultant for the technician that has to build the network, and is able to face possible breakdowns. This paper illustrates the structure of a course to train a medical network administrator in anesthesiology and critical care.

  2. Intelligent biology and medicine in 2015: advancing interdisciplinary education, collaboration, and data science.

    PubMed

    Huang, Kun; Liu, Yunlong; Huang, Yufei; Li, Lang; Cooper, Lee; Ruan, Jianhua; Zhao, Zhongming

    2016-01-01

    We summarize the 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) and the editorial report of the supplement to BMC Genomics. The supplement includes 20 research articles selected from the manuscripts submitted to ICIBM 2015. The conference was held on November 13-15, 2015 at Indianapolis, Indiana, USA. It included eight scientific sessions, three tutorials, four keynote presentations, three highlight talks, and a poster session that covered current research in bioinformatics, systems biology, computational biology, biotechnologies, and computational medicine. PMID:27556295

  3. Interim Service ISDN Satellite (ISIS) network model for advanced satellite designs and experiments

    NASA Technical Reports Server (NTRS)

    Pepin, Gerard R.; Hager, E. Paul

    1991-01-01

    The Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) Network Model for Advanced Satellite Designs and Experiments describes a model suitable for discrete event simulations. A top-down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ISDN modeling abstractions are added to permit the determination and performance for the NASA Satellite Communications Research (SCAR) Program.

  4. Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

    PubMed

    Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

    2006-04-01

    This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control

  5. Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

    PubMed

    Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

    2006-04-01

    This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control

  6. Teaching Advanced Concepts in Computer Networks: VNUML-UM Virtualization Tool

    ERIC Educational Resources Information Center

    Ruiz-Martinez, A.; Pereniguez-Garcia, F.; Marin-Lopez, R.; Ruiz-Martinez, P. M.; Skarmeta-Gomez, A. F.

    2013-01-01

    In the teaching of computer networks the main problem that arises is the high price and limited number of network devices the students can work with in the laboratories. Nowadays, with virtualization we can overcome this limitation. In this paper, we present a methodology that allows students to learn advanced computer network concepts through…

  7. 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…

  8. Data communication requirements for the advanced NAS network

    NASA Technical Reports Server (NTRS)

    Levin, Eugene; Eaton, C. K.; Young, Bruce

    1986-01-01

    The goal of the Numerical Aerodynamic Simulation (NAS) Program is to provide a powerful computational environment for advanced research and development in aeronautics and related disciplines. The present NAS system consists of a Cray 2 supercomputer connected by a data network to a large mass storage system, to sophisticated local graphics workstations, and by remote communications to researchers throughout the United States. The program plan is to continue acquiring the most powerful supercomputers as they become available. In the 1987/1988 time period it is anticipated that a computer with 4 times the processing speed of a Cray 2 will be obtained and by 1990 an additional supercomputer with 16 times the speed of the Cray 2. The implications of this 20-fold increase in processing power on the data communications requirements are described. The analysis was based on models of the projected workload and system architecture. The results are presented together with the estimates of their sensitivity to assumptions inherent in the models.

  9. Wireless Sensor Network for Advanced Energy Management Solutions

    SciTech Connect

    Peter J. Theisen; Bin Lu, Charles J. Luebke

    2009-09-23

    Eaton has developed an advanced energy management solution that has been deployed to several Industries of the Future (IoF) sites. This demonstrated energy savings and reduced unscheduled downtime through an improved means for performing predictive diagnostics and energy efficiency estimation. Eaton has developed a suite of online, continuous, and inferential algorithms that utilize motor current signature analysis (MCSA) and motor power signature analysis (MPSA) techniques to detect and predict the health condition and energy usage condition of motors and their connect loads. Eaton has also developed a hardware and software platform that provided a means to develop and test these advanced algorithms in the field. Results from lab validation and field trials have demonstrated that the developed advanced algorithms are able to detect motor and load inefficiency and performance degradation. Eaton investigated the performance of Wireless Sensor Networks (WSN) within various industrial facilities to understand concerns about topology and environmental conditions that have precluded broad adoption by the industry to date. A Wireless Link Assessment System (WLAS), was used to validate wireless performance under a variety of conditions. Results demonstrated that wireless networks can provide adequate performance in most facilities when properly specified and deployed. Customers from various IoF expressed interest in applying wireless more broadly for selected applications, but continue to prefer utilizing existing, wired field bus networks for most sensor based applications that will tie into their existing Computerized Motor Maintenance Systems (CMMS). As a result, wireless technology was de-emphasized within the project, and a greater focus placed on energy efficiency/predictive diagnostics. Commercially available wireless networks were only utilized in field test sites to facilitate collection of motor wellness information, and no wireless sensor network products were

  10. Lambdastation: a forwarding and admission control service to interface production network facilities with advanced research network paths

    SciTech Connect

    DeMar, Philip; Petravick, Don; /Fermilab

    2004-12-01

    Over the past several years, there has been a great deal of research effort and funding put into the deployment of optical-based, advanced technology wide-area networks. Fermilab and CalTech have initiated a project to enable our production network facilities to exploit these advanced research network facilities. Our objective is to forward designated data transfers across these advanced wide area networks on a per-flow basis, making use our capacious production-use storage systems connected to the local campus network. To accomplish this, we intend to develop a dynamically provisioned forwarding service that would provide alternate path forwarding onto available wide area advanced research networks. The service would dynamically reconfigure forwarding of specific flows within our local production-use network facilities, as well as provide an interface to enable applications to utilize the service. We call this service LambdaStation. If one envisions wide area optical network paths as high bandwidth data railways, then LambdaStation would functionally be the railroad terminal that regulates which flows at the local site get directed onto the high bandwidth data railways. LambdaStation is a DOE-funded SciDac research project in its very early stage of development.

  11. Artificial intelligence, neural network, and Internet tool integration in a pathology workstation to improve information access

    NASA Astrophysics Data System (ADS)

    Sargis, J. C.; Gray, W. A.

    1999-03-01

    The APWS allows user friendly access to several legacy systems which would normally each demand domain expertise for proper utilization. The generalized model, including objects, classes, strategies and patterns is presented. The core components of the APWS are the Microsoft Windows 95 Operating System, Oracle, Oracle Power Objects, Artificial Intelligence tools, a medical hyperlibrary and a web site. The paper includes a discussion of how could be automated by taking advantage of the expert system, object oriented programming and intelligent relational database tools within the APWS.

  12. Unattended network operations technology assessment study. Technical support for defining advanced satellite systems concepts

    NASA Technical Reports Server (NTRS)

    Price, Kent M.; Holdridge, Mark; Odubiyi, Jide; Jaworski, Allan; Morgan, Herbert K.

    1991-01-01

    The results are summarized of an unattended network operations technology assessment study for the Space Exploration Initiative (SEI). The scope of the work included: (1) identified possible enhancements due to the proposed Mars communications network; (2) identified network operations on Mars; (3) performed a technology assessment of possible supporting technologies based on current and future approaches to network operations; and (4) developed a plan for the testing and development of these technologies. The most important results obtained are as follows: (1) addition of a third Mars Relay Satellite (MRS) and MRS cross link capabilities will enhance the network's fault tolerance capabilities through improved connectivity; (2) network functions can be divided into the six basic ISO network functional groups; (3) distributed artificial intelligence technologies will augment more traditional network management technologies to form the technological infrastructure of a virtually unattended network; and (4) a great effort is required to bring the current network technology levels for manned space communications up to the level needed for an automated fault tolerance Mars communications network.

  13. Advanced Building Efficiency Testbed Initiative/Intelligent Workplace Energy Supply System; ABETI/IWESS

    SciTech Connect

    David Archer; Frederik Betz; Yun Gu; Rong Li; Flore Marion; Sophie Masson; Ming Qu; Viraj Srivastava; Hongxi Yin; Chaoqin Zhai; Rui Zhang; Elisabeth Aslanian; Berangere Lartigue

    2008-05-31

    ABETI/IWESS is a project carried out by Carnegie Mellon's Center for Building Performance and Diagnostics, the CBPD, supported by the U.S. Department of Energy/EERE, to design, procure, install, operate, and evaluate an energy supply system, an ESS, that will provide power, cooling, heating and ventilation for CBPD's Intelligent Workplace, the IW. The energy sources for this system, the IWESS, are solar radiation and bioDiesel fuel. The components of this overall system are: (1) a solar driven cooling and heating system for the IW comprising solar receivers, an absorption chiller, heat recovery exchanger, and circulation pump; (2) a bioDiesel fueled engine generator with heat recovery exchangers, one on the exhaust to provide steam and the other on the engine coolant to provide heated water; (3) a ventilation system including an enthalpy recovery wheel, an air based heat pump, an active desiccant wheel, and an air circulation fan; and (4) various convective and radiant cooling/heating units and ventilation air diffusers distributed throughout the IW. The goal of the ABETI/IWESS project is to demonstrate an energy supply system for a building space that will provide a healthy, comfortable environment for the occupants and that will reduce the quantity of energy consumed in the operation of a building space by a factor of 2 less than that of a conventional energy supply for power, cooling, heating, and ventilation based on utility power and natural gas fuel for heating.

  14. Intelligent Buildings

    SciTech Connect

    Brambley, Michael R.; Armstrong, Peter R.; Kintner-Meyer, Michael CW; Pratt, Robert G.; Katipamula, Srinivas

    2001-01-01

    The topic of "intelligent buildings" (IBs) emerged in the early 1980s. Since, the term has been used to represent a variety of related, yet differing topics, each with a slightly different focus and purpose. Wiring and networking-infrastructure companies emphasize the cabling requirements for communication in intelligent buildings and the need to accommodate future needs for higher-speed broadband. Lucent (Lucent 2000) for example, defines an IB as "...one with a completely integrated wiring architecture. A single cabling system that handles all information traffic - voice, data, video, even the big building management systems."

  15. Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

    NASA Technical Reports Server (NTRS)

    Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

    1995-01-01

    This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system.

  16. Intelligent Tutoring Systems: Formalization as Automata and Interface Design Using Neural Networks

    ERIC Educational Resources Information Center

    Curilem, S. Gloria; Barbosa, Andrea R.; de Azevedo, Fernando M.

    2007-01-01

    This article proposes a mathematical model of Intelligent Tutoring Systems (ITS), based on observations of the behaviour of these systems. One of the most important problems of pedagogical software is to establish a common language between the knowledge areas involved in their development, basically pedagogical, computing and domain areas. A…

  17. Advanced Modular "All in One" Battery System with Intelligent Autonomous Cell Balancing Management

    NASA Astrophysics Data System (ADS)

    Petitdidier, X.; Pasquier, E.; Defer, M.; Koch, M.; Knorr, W.

    2008-09-01

    A new generation of energy storage systems based on Li-ion technology emerged at the end of the last century.To perform the first tests in safe conditions, Saft designed a simple electronic.Today, all Li-ion batteries for autonomous applications such as drones, launchers, missiles, torpedoes and "human" applications such as cellular, laptop, hybrid vehicle and nearly sub-marines need a Battery Management System.The minimum in terms of functions is the overcharge and over-discharge protections.For a battery made of 2 cells connected in series or more, a balancing system is added to maintain the available energy during all the life of the battery. For stringent/demanding applications, the state of charge and state of health are calculated by one or more computers.It is now time to take benefit of the past 10 years of Saft's experience in the domain to re-evaluate the constraints of Li-ion batteries and provide customers with improved products by optimizing the battery management.Benefits of electronic for satellite applications:• Full control over battery.• Confidence whatever the possible change of conditions in environment.• The battery system can resist long exposure to gradient conditions with mitigated and stabilized impact on performances.• The balancing function allow to use all the energy of all the cells: optimize of installed energy (compact design, mass saving). It started out with the basic fact that electrochemists are not intended to be space rated electronic experts and vice versa, even if Saft has a good heritage in the electronic battery management system. Consequently, considering heritage and expertise in their respective core businesses, Saft and ASP teamed up.It became necessary to provide an "all in one" modular energy storage system with intelligent autonomous cell balancing management.

  18. Advanced fire observation by the Intelligent Infrared Sensor prototype FOCUS on the International Space Station

    NASA Astrophysics Data System (ADS)

    Oertel, D.; Haschberger, P.; Tank, V.; Lanzl, F.; Zhukov, B.; Jahn, H.; Briess, K.; Lorenz, E.; Roeser, H.-P.; Ginati, A.; Tobehn, C.; Schulte in den Bäumen, J.; Christmann, U.

    1999-01-01

    Current and planned operational space-borne Earth observation systems provide spatially, radiometrically or temporally crude data for the detection and monitoring of high temperature phenomena on the surface of our planet. High Temperature Events (HTE) very often cause environmental disasters. Such HTE are forest and savannah fires, fires of open coal mines, volcanic activities and others (e.g. fires of oil wells, pipelines etc.). A simultaneous co-registration of a combination of infrared (IR) and visible (VIS) channels is the key for a reliable autonomous on-board detection of High Temperature Events (HTE) on Earth surface, such as vegetation fires and volcano eruptions. This is the main feature of the FOCUS experiment. Furthermore there are ecology-oriented objectives of the FOCUS experiment mainly related to spectrometric/imaging remote inspection and parameter extraction of selected HTEs, and to the assessment of some ecological consequences of HTEs, such as aerosol and gas emission. Based on own experimental work and supported by Co-Investigators from Italy, Greece, France, Spain, Russia and Germany, DLR proposed in 1997 to use the International Space Station (ISS) in its early utilization phase as a platform and test-bed for an Intelligent Infrared Sensor prototype FOCUS of a future Environmental Disaster Recognition Satellite System. FOCUS is considered by ESA as an important mission combining a number of proven technologies and observation techniques to provide the scientific and operational user community with key data for the classification and monitoring of forest fires. FOCUS was selected as one of five European ``Groupings'' to be flown as an externally mounted payload during the early utilisation phase of the ISS. The FOCUS Phase A Study will be performed by OHB-System, DLR and Zeiss from September 1998 until May 1999.

  19. Advances in Artificial Neural Networks - Methodological Development and Application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

  20. Six Networking Tips to Advance Your Career Goals

    ERIC Educational Resources Information Center

    Jones, Angela

    2013-01-01

    Teachers may wonder why networking is relevant. The point of networking is to cultivate relationships for the exchange of information, services, or resources for employment or business. This may sound cold to those in the educational world, where children and youth are the No. 1 customers, but a network can be a huge support as it pertains to…

  1. Evaluation Approaches to Intelligent Computer-Assisted Instruction. Testing Study Group: The Impact of Advances in Artificial Intelligence on Test Development.

    ERIC Educational Resources Information Center

    Baker, Eva L.

    Some special problems associated with evaluating intelligent computer-assisted instruction (ICAI) programs are addressed. This paper intends to describe alternative approaches to the assessment and improvement of such applications and to provide examples of efforts undertaken and shortfalls. Issues discussed stem chiefly from the technical demands…

  2. Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment.

    PubMed

    Dilsizian, Steven E; Siegel, Eliot L

    2014-01-01

    Although advances in information technology in the past decade have come in quantum leaps in nearly every aspect of our lives, they seem to be coming at a slower pace in the field of medicine. However, the implementation of electronic health records (EHR) in hospitals is increasing rapidly, accelerated by the meaningful use initiatives associated with the Center for Medicare & Medicaid Services EHR Incentive Programs. The transition to electronic medical records and availability of patient data has been associated with increases in the volume and complexity of patient information, as well as an increase in medical alerts, with resulting "alert fatigue" and increased expectations for rapid and accurate diagnosis and treatment. Unfortunately, these increased demands on health care providers create greater risk for diagnostic and therapeutic errors. In the near future, artificial intelligence (AI)/machine learning will likely assist physicians with differential diagnosis of disease, treatment options suggestions, and recommendations, and, in the case of medical imaging, with cues in image interpretation. Mining and advanced analysis of "big data" in health care provide the potential not only to perform "in silico" research but also to provide "real time" diagnostic and (potentially) therapeutic recommendations based on empirical data. "On demand" access to high-performance computing and large health care databases will support and sustain our ability to achieve personalized medicine. The IBM Jeopardy! Challenge, which pitted the best all-time human players against the Watson computer, captured the imagination of millions of people across the world and demonstrated the potential to apply AI approaches to a wide variety of subject matter, including medicine. The combination of AI, big data, and massively parallel computing offers the potential to create a revolutionary way of practicing evidence-based, personalized medicine.

  3. A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.

    PubMed

    Li, Shan; Kang, Liying; Zhao, Xing-Ming

    2014-01-01

    With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

  4. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

    PubMed Central

    Li, Shan; Zhao, Xing-Ming

    2014-01-01

    With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks. PMID:24729969

  5. Full Service ISDN Satellite (FSIS) network model for advanced ISDN satellite design and experiments

    NASA Technical Reports Server (NTRS)

    Pepin, Gerard R.

    1992-01-01

    The Full Service Integrated Services Digital Network (FSIS) network model for advanced satellite designs describes a model suitable for discrete event simulations. A top down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ACTS and the Interim Service ISDN Satellite (ISIS) perform ISDN protocol analyses and switching decisions in the terrestrial domain, whereas FSIS makes all its analyses and decisions on-board the ISDN satellite.

  6. Enhancing accuracy of mental fatigue classification using advanced computational intelligence in an electroencephalography system.

    PubMed

    Chai, Rifai; Tran, Yvonne; Craig, Ashley; Ling, Sai Ho; Nguyen, Hung T

    2014-01-01

    A system using electroencephalography (EEG) signals could enhance the detection of mental fatigue while driving a vehicle. This paper examines the classification between fatigue and alert states using an autoregressive (AR) model-based power spectral density (PSD) as the features extraction method and fuzzy particle swarm optimization with cross mutated of artificial neural network (FPSOCM-ANN) as the classification method. Using 32-EEG channels, results indicated an improved overall specificity from 76.99% to 82.02%, an improved sensitivity from 74.92 to 78.99% and an improved accuracy from 75.95% to 80.51% when compared to previous studies. The classification using fewer EEG channels, with eleven frontal sites resulted in 77.52% for specificity, 73.78% for sensitivity and 75.65% accuracy being achieved. For ergonomic reasons, the configuration with fewer EEG channels will enhance capacity to monitor fatigue as there is less set-up time required. PMID:25570210

  7. Advancing reversible shape memory by tuning the polymer network architecture

    DOE PAGES

    Li, Qiaoxi; Zhou, Jing; Vatankhah-Varnoosfaderani, Mohammad; Nykypanchuk, Dmytro; Gang, Oleg; Sheiko, Sergei S.

    2016-02-02

    Because of counteraction of a chemical network and a crystalline scaffold, semicrystalline polymer networks exhibit a peculiar behavior—reversible shape memory (RSM), which occurs naturally without applying any external force and particular structural design. There are three RSM properties: (i) range of reversible strain, (ii) rate of strain recovery, and (iii) decay of reversibility with time, which can be improved by tuning the architecture of the polymer network. Different types of poly(octylene adipate) networks were synthesized, allowing for control of cross-link density and network topology, including randomly cross-linked network by free-radical polymerization, thiol–ene clicked network with enhanced mesh uniformity, and loosemore » network with deliberately incorporated dangling chains. It is shown that the RSM properties are controlled by average cross-link density and crystal size, whereas topology of a network greatly affects its extensibility. In conclusion, we have achieved 80% maximum reversible range, 15% minimal decrease in reversibility, and fast strain recovery rate up to 0.05 K–1, i.e., ca. 5% per 10 s at a cooling rate of 5 K/min.« less

  8. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 2: Fiber optic technology and long distance networks

    NASA Technical Reports Server (NTRS)

    1986-01-01

    The study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the Executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  9. Advanced Algorithms for Local Routing Strategy on Complex Networks

    PubMed Central

    Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K.; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

    2016-01-01

    Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks. PMID:27434502

  10. Social Networks and Career Advancement of People with Disabilities

    ERIC Educational Resources Information Center

    Kulkarni, Mukta

    2012-01-01

    Although organizational social networks are known to influence career mobility, the specific direction of this influence is different for diverse employee groups. Diversity in organizational network research has been operationalized on various dimensions such as race and ethnicity, age, religion, education, occupation, and gender. Missing in this…

  11. Advanced Algorithms for Local Routing Strategy on Complex Networks.

    PubMed

    Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

    2016-01-01

    Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70-90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks. PMID:27434502

  12. 77 FR 23643 - Advance Notice of Implementation of Full-Service Intelligent Mail Required for Automation Prices

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-20

    ... 2014. Full-Service Intelligent Mail combines use of unique scan codes with the provision of electronic... verification process based on comparing electronic documentation with scans of Intelligent Mail barcodes... mail is ] co-palletized, combined or comingled (in-house or at a different plant). The...

  13. Fractionating human intelligence.

    PubMed

    Hampshire, Adam; Highfield, Roger R; Parkin, Beth L; Owen, Adrian M

    2012-12-20

    What makes one person more intellectually able than another? Can the entire distribution of human intelligence be accounted for by just one general factor? Is intelligence supported by a single neural system? Here, we provide a perspective on human intelligence that takes into account how general abilities or "factors" reflect the functional organization of the brain. By comparing factor models of individual differences in performance with factor models of brain functional organization, we demonstrate that different components of intelligence have their analogs in distinct brain networks. Using simulations based on neuroimaging data, we show that the higher-order factor "g" is accounted for by cognitive tasks corecruiting multiple networks. Finally, we confirm the independence of these components of intelligence by dissociating them using questionnaire variables. We propose that intelligence is an emergent property of anatomically distinct cognitive systems, each of which has its own capacity.

  14. Intelligent video storage of visual evidences on site in fast deployment

    NASA Astrophysics Data System (ADS)

    Desurmont, Xavier; Bastide, Arnaud; Delaigle, Jean-Francois

    2004-07-01

    In this article we present a generic, flexible, scalable and robust approach for an intelligent real-time forensic visual system. The proposed implementation could be rapidly deployable and integrates minimum logistic support as it embeds low complexity devices (PCs and cameras) that communicate through wireless network. The goal of these advanced tools is to provide intelligent video storage of potential video evidences for fast intervention during deployment around a hazardous sector after a terrorism attack, a disaster, an air crash or before attempt of it. Advanced video analysis tools, such as segmentation and tracking are provided to support intelligent storage and annotation.

  15. An "intelligent" approach based on side-by-side cascade-correlation neural networks for estimating thermophysical properties from photothermal responses

    NASA Astrophysics Data System (ADS)

    Grieu, Stéphane; Faugeroux, Olivier; Traoré, Adama; Claudet, Bernard; Bodnar, Jean-Luc

    2015-01-01

    In the present paper, an artificial-intelligence-based approach dealing with the estimation of thermophysical properties is designed and evaluated. This new and "intelligent" approach makes use of photothermal responses obtained when subjecting materials to a light flux. So, the main objective of the present work was to estimate simultaneously both the thermal diffusivity and conductivity of materials, from front-face or rear-face photothermal responses to pseudo random binary signals. To this end, we used side-by-side feedforward neural networks trained with the cascade-correlation algorithm. In addition, computation time was a key point to consider. That is why the developed algorithms are computationally tractable.

  16. Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

    NASA Technical Reports Server (NTRS)

    Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

    1996-01-01

    The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the

  17. Advances Made in the Next Generation of Satellite Networks

    NASA Technical Reports Server (NTRS)

    Bhasin, Kul B.

    1999-01-01

    Because of the unique networking characteristics of communications satellites, global satellite networks are moving to the forefront in enhancing national and global information infrastructures. Simultaneously, broadband data services, which are emerging as the major market driver for future satellite and terrestrial networks, are being widely acknowledged as the foundation for an efficient global information infrastructure. In the past 2 years, various task forces and working groups around the globe have identified pivotal topics and key issues to address if we are to realize such networks in a timely fashion. In response, industry, government, and academia undertook efforts to address these topics and issues. A workshop was organized to provide a forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. The Satellite Networks: Architectures, Applications, and Technologies Workshop was hosted by the Space Communication Program at the NASA Lewis Research Center in Cleveland, Ohio. Nearly 300 executives and technical experts from academia, industry, and government, representing the United States and eight other countries, attended the event (June 2 to 4, 1998). The program included seven panels and invited sessions and nine breakout sessions in which 42 speakers presented on technical topics. The proceedings covers a wide range of topics: access technology and protocols, architectures and network simulations, asynchronous transfer mode (ATM) over satellite networks, Internet over satellite networks, interoperability experiments and applications, multicasting, NASA interoperability experiment programs, NASA mission applications, and Transmission Control Protocol/Internet Protocol (TCP/IP) over satellite: issues, relevance, and experience.

  18. An application of neural networks and artificial intelligence for in-core fuel management

    SciTech Connect

    Miller, L.F.; Algutifan, F.; Uhrig, R.E. )

    1992-01-01

    This paper reports the feasibility of using expert systems in combination with neural networks and neutronics calculations to improve the efficiency for obtaining optimal candidate reload core designs. The general objectives of this research are as follows: (1) generate a suitable data base and ancillary software for training neural networks that duplicate neutronics calculations. (2) develop a graphical interface with neutronics software and neural networks for manual shuffling of reload cores. (3) construct an expert system for shuffling reload cores with specified rules. (4) develp neural networks that capture the nonlinear behavior of fuel depletion. (5) integrate the neural networks and neutronics software with an expert system to specify reload cores that obtain appropriate figure of merit.

  19. Intelligence supportability in future systems

    NASA Astrophysics Data System (ADS)

    Gold, Brian; Watson, Mariah; Vayette, Corey; Fiduk, Francis

    2010-08-01

    Advanced weaponry is providing an exponential increase in intelligence data collection capabilities and the Intelligence Community (IC) is not properly positioned for the influx of intelligence supportabilitiy requirements the defense acquisition community is developing for it. The Air Force Material Command (AFMC) has initiated the Intelligence Supportability Analysis (ISA) process to allow the IC to triage programs for intelligence sensitivities as well as begin preparations within the IC for the transition of future programs to operational status. The ISA process is accomplished through system decomposition, allowing analysts to identify intelligence requirements and deficiencies. Early collaboration and engagement by program managers and intelligence analysts is crucial to the success of intelligence sensitive programs through the utilization of a repeatable analytical framework for evaluating and making cognizant trade-offs between cost, schedule and performance. Addressing intelligence supportability early in the acquisition process will also influence system design and provide the necessary lead time for intelligence community to react and resource new requirements.

  20. Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

    PubMed

    Yang, Q; Siganos, G; Faloutsos, M; Lonardi, S

    2006-01-01

    Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.

  1. Advancing Reversible Shape Memory by Tuning Network Architecture

    NASA Astrophysics Data System (ADS)

    Li, Qiaoxi; Zhou, Jing; Vatankhah Varnosfaderani, Mohammad; Nykypanchuk, Dmytro; Gang, Oleg; Sheiko, Sergei; University of north carolina at chapel hill Collaboration; Brookhaven National Lab-CFN Collaboration

    Recently, reversible shape memory (RSM) has been realized in conventional semi-crystalline elastomers without applying any external force and synthetic programming. The mechanism is ascribed to counteraction between thermodynamically driven relaxation of a strained polymer network and kinetically preferred self-seeding recrystallization of constrained network strands. In order to maximize RSM's performance in terms of (i) range of reversible strain, (ii) rate of strain recovery, and (iii) relaxation time of reversibility, we have designed a systematic series of networks with different topologies and crosslinking densities, including purposely introduced dangling chains and irregular meshes. Within a broad range of crosslink density ca. 50-1000 mol/m3, we have demonstrated that the RSM's properties improve significantly with increasing crosslink density, regardless of network topology. Actually, one of the most irregular networks with densest crosslinking allowed achieving up to 80% of the programmed strain being fully reversible, fast recovery rate up to 0.05 K-1, and less than 15% decrease of reversibility after hours of annealing at partial melt state. With this understanding and optimization of RSM, we pursue an idea of shape control through self-assembly of shape-memory particles. For this purpose, 3D printing has been employed to prepare large assemblies of particles possessing specific shapes and morphologies.

  2. High-speed parallel-processing networks for advanced architectures

    SciTech Connect

    Morgan, D.R.

    1988-06-01

    This paper describes various parallel-processing architecture networks that are candidates for eventual airborne use. An attempt at projecting which type of network is suitable or optimum for specific metafunction or stand-alone applications is made. However, specific algorithms will need to be developed and bench marks executed before firm conclusions can be drawn. Also, a conceptual projection of how these processors can be built in small, flyable units through the use of wafer-scale integration is offered. The use of the PAVE PILLAR system architecture to provide system level support for these tightly coupled networks is described. The author concludes that: (1) extremely high processing speeds implemented in flyable hardware is possible through parallel-processing networks if development programs are pursued; (2) dramatic speed enhancements through parallel processing requires an excellent match between the algorithm and computer-network architecture; (3) matching several high speed parallel oriented algorithms across the aircraft system to a limited set of hardware modules may be the most cost-effective approach to achieving speed enhancements; and (4) software-development tools and improved operating systems will need to be developed to support efficient parallel-processor use.

  3. Advances in Exponential Random Graph (p*) Models Applied to a Large Social Network

    PubMed Central

    Goodreau, Steven M.

    2007-01-01

    Recent advances in statistical network analysis based on the family of exponential random graph (ERG) models have greatly improved our ability to conduct inference on dependence in large social networks (Snijders 2002, Pattison and Robins 2002, Handcock 2002, Handcock 2003, Snijders et al. 2006, Hunter et al. 2005, Goodreau et al. 2005, previous papers this issue). This paper applies advances in both model parameterizations and computational algorithms to an examination of the structure observed in an adolescent friendship network of 1,681 actors from the National Longitudinal Study of Adolescent Health (AddHealth). ERG models of social network structure are fit using the R package statnet, and their adequacy assessed through comparison of model predictions with the observed data for higher-order network statistics. For this friendship network, the commonly used model of Markov dependence leads to the problems of degeneracy discussed by Handcock (2002, 2003). On the other hand, model parameterizations introduced by Snijders et al (2006) and Hunter and Handcock (2006) avoid degeneracy and provide reasonable fit to the data. Degree-only models did a poor job of capturing observed network structure; those that did best included terms both for heterogeneous mixing on exogenous attributes (grade and self-reported race) as well as endogenous clustering. Networks simulated from this model were largely consistent with the observed network on multiple higher-order network statistics, including the number of triangles, the size of the largest component, the overall reachability, the distribution of geodesic distances, the degree distribution, and the shared partner distribution. The ability to fit such models to large datasets and to make inference about the underling processes generating the network represents a major advance in the field of statistical network analysis. PMID:18449326

  4. Advanced clinical interpretation of the WAIS-IV and WMS-IV: prevalence of low scores varies by level of intelligence and years of education.

    PubMed

    Brooks, Brian L; Holdnack, James A; Iverson, Grant L

    2011-06-01

    Clinicians can use the base rates of low scores in healthy people to reduce the likelihood of misdiagnosing cognitive impairment. In the present study, base rates were developed for the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Memory Scale-Fourth Edition (WMS-IV) using 900 healthy adults and validated on 28 patients with moderate or severe traumatic brain injuries (TBIs). Results indicated that healthy people obtain some low scores on the WAIS-IV/WMS-IV, with prevalence rates increasing with fewer years of education and lower predicted intelligence. When applying the base rates information to the clinical sample, the TBI patients were 13 times more likely to be identified as having a low cognitive profile compared with the controls. Using the base rates information is a psychometrically advanced method for establishing criteria to determine low cognitive abilities on the WAIS-IV/WMS-IV.

  5. A Flexible Reservation Algorithm for Advance Network Provisioning

    SciTech Connect

    Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex

    2010-04-12

    Many scientific applications need support from a communication infrastructure that provides predictable performance, which requires effective algorithms for bandwidth reservations. Network reservation systems such as ESnet's OSCARS, establish guaranteed bandwidth of secure virtual circuits for a certain bandwidth and length of time. However, users currently cannot inquire about bandwidth availability, nor have alternative suggestions when reservation requests fail. In general, the number of reservation options is exponential with the number of nodes n, and current reservation commitments. We present a novel approach for path finding in time-dependent networks taking advantage of user-provided parameters of total volume and time constraints, which produces options for earliest completion and shortest duration. The theoretical complexity is only O(n2r2) in the worst-case, where r is the number of reservations in the desired time interval. We have implemented our algorithm and developed efficient methodologies for incorporation into network reservation frameworks. Performance measurements confirm the theoretical predictions.

  6. On modeling and controlling intelligent systems

    SciTech Connect

    Dress, W.B.

    1993-11-01

    The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.

  7. An intelligent wireless sensor network applied research on dynamic physiological data monitoring of athletes

    NASA Astrophysics Data System (ADS)

    Xie, Ying; Wu, Fei-qing; Li, Lin-gong

    2008-12-01

    A wireless sensor network (WSN) monitoring system was designed, because of the big labour, time-consumption, and non-real-time monitoring of the true physiological data of athlete for wire communication, which were very important for their coach. The coach, who obtained the first material, can know the physiological sports status of althletes according to these data, can intervene on them and formulate a scientific training plan. The system has the characteristic of a random layout, arbitrary additions and combined network nodes. The performance of the system for 24 athletes who were trained has been tested in the system improved LEACH-c protocol and a threshold sensitive energy efficient protocol has been applied. The experimental results showed that, while the interval time of the contact was more than 15 seconds, the network packet loss rate was less than 3 percent. The operation of the network can be considered to be relatively stable. During the test, the MAC network capacity obtained by the actual tests in the implicit terminal mode was three packets per second. Considering the costs of a node sending routing maintenance packet, a network capacity of 2 was reasonable. Based on the performance of the system for testing, the results showed that the system was stable and reliable

  8. Intelligent QoS routing algorithm based on improved AODV protocol for Ad Hoc networks

    NASA Astrophysics Data System (ADS)

    Huibin, Liu; Jun, Zhang

    2016-04-01

    Mobile Ad Hoc Networks were playing an increasingly important part in disaster reliefs, military battlefields and scientific explorations. However, networks routing difficulties are more and more outstanding due to inherent structures. This paper proposed an improved cuckoo searching-based Ad hoc On-Demand Distance Vector Routing protocol (CSAODV). It elaborately designs the calculation methods of optimal routing algorithm used by protocol and transmission mechanism of communication-package. In calculation of optimal routing algorithm by CS Algorithm, by increasing QoS constraint, the found optimal routing algorithm can conform to the requirements of specified bandwidth and time delay, and a certain balance can be obtained among computation spending, bandwidth and time delay. Take advantage of NS2 simulation software to take performance test on protocol in three circumstances and validate the feasibility and validity of CSAODV protocol. In results, CSAODV routing protocol is more adapt to the change of network topological structure than AODV protocol, which improves package delivery fraction of protocol effectively, reduce the transmission time delay of network, reduce the extra burden to network brought by controlling information, and improve the routing efficiency of network.

  9. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    PubMed

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  10. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    PubMed

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  11. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    PubMed Central

    Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  12. Intelligent Tutoring Systems

    NASA Astrophysics Data System (ADS)

    Anderson, John R.; Boyle, C. Franklin; Reiser, Brian J.

    1985-04-01

    Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP.

  13. Intelligent Tutoring Systems.

    ERIC Educational Resources Information Center

    Anderson, John R.; And Others

    1985-01-01

    Cognitive psychology, artificial intelligence, and computer technology have advanced so much that it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors have been developed for teaching students to do proofs in geometry and to write computer programs in the LISP language. (JN)

  14. Distributed networks enable advances in US space weather operations

    NASA Astrophysics Data System (ADS)

    Tobiska, W. Kent; Bouwer, S. Dave

    2011-06-01

    Space weather, the shorter-term variable impact of the Sun’s photons, solar wind particles, and interplanetary magnetic field upon the Earth’s environment, adversely affects our technological systems. These technological systems, including their space component, are increasingly being seen as a way to help solve 21st Century problems such as climate change, energy access, fresh water availability, and transportation coordination. Thus, the effects of space weather on space systems and assets must be mitigated and operational space weather using automated distributed networks has emerged as a common operations methodology. The evolution of space weather operations is described and the description of distributed network architectures is provided, including their use of tiers, data objects, redundancy, and time domain definitions. There are several existing distributed networks now providing space weather information and the lessons learned in developing those networks are discussed along with the details of examples for the Solar Irradiance Platform (SIP), Communication Alert and Prediction System (CAPS), GEO Alert and Prediction System (GAPS), LEO Alert and Prediction System (LAPS), Radiation Alert and Prediction System (RAPS), and Magnetosphere Alert and Prediction System (MAPS).

  15. Wireless Sensors and Networks for Advanced Energy Management

    SciTech Connect

    Hardy, J.E.

    2005-05-06

    Numerous national studies and working groups have identified low-cost, very low-power wireless sensors and networks as a critical enabling technology for increasing energy efficiency, reducing waste, and optimizing processes. Research areas for developing such sensor and network platforms include microsensor arrays, ultra-low power electronics and signal conditioning, data/control transceivers, and robust wireless networks. A review of some of the research in the following areas will be discussed: (1) Low-cost, flexible multi-sensor array platforms (CO{sub 2}, NO{sub x}, CO, humidity, NH{sub 3}, O{sub 2}, occupancy, etc.) that enable energy and emission reductions in applications such as buildings and manufacturing; (2) Modeling investments (energy usage and savings to drive capital investment decisions) and estimated uptime improvements through pervasive gathering of equipment and process health data and its effects on energy; (3) Robust, self-configuring wireless sensor networks for energy management; and (4) Quality-of-service for secure and reliable data transmission from widely distributed sensors. Wireless communications is poised to support technical innovations in the industrial community, with widespread use of wireless sensors forecasted to improve manufacturing production and energy efficiency and reduce emissions. Progress being made in wireless system components, as described in this paper, is helping bring these projected improvements to reality.

  16. EFL Writers' Social Networks: Impact on Advanced Academic Literacy Development

    ERIC Educational Resources Information Center

    Ferenz, Orna

    2005-01-01

    For non-native English writers, second language (L2) advanced academic literacy encompasses knowledge of the rhetorical, linguistic, social and cultural features of academic discourse as well as knowledge of English as used by their academic disciplines. Literacy is acquired through a socialization process embedded in social practice, patterned by…

  17. Advanced Networks in Dental Rich Online MEDiA (ANDROMEDA)

    NASA Astrophysics Data System (ADS)

    Elson, Bruce; Reynolds, Patricia; Amini, Ardavan; Burke, Ezra; Chapman, Craig

    There is growing demand for dental education and training not only in terms of knowledge but also skills. This demand is driven by continuing professional development requirements in the more developed economies, personnel shortages and skills differences across the European Union (EU) accession states and more generally in the developing world. There is an excellent opportunity for the EU to meet this demand by developing an innovative online flexible learning platform (FLP). Current clinical online systems are restricted to the delivery of general, knowledge-based training with no easy method of personalization or delivery of skill-based training. The PHANTOM project, headed by Kings College London is developing haptic-based virtual reality training systems for clinical dental training. ANDROMEDA seeks to build on this and establish a Flexible Learning Platform that can integrate the haptic and sensor based training with rich media knowledge transfer, whilst using sophisticated technologies such as including service-orientated architecture (SOA), Semantic Web technologies, knowledge-based engineering, business intelligence (BI) and virtual worlds for personalization.

  18. The “Wireless Sensor Networks for City-Wide Ambient Intelligence (WISE-WAI)” Project

    PubMed Central

    Casari, Paolo; Castellani, Angelo P.; Cenedese, Angelo; Lora, Claudio; Rossi, Michele; Schenato, Luca; Zorzi, Michele

    2009-01-01

    This paper gives a detailed technical overview of some of the activities carried out in the context of the “Wireless Sensor networks for city-Wide Ambient Intelligence (WISE-WAI)” project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide. These applications include long-term environmental monitoring, alarm event detection and propagation, single-sensor interrogation, localization and tracking of objects, assisted navigation, as well as fast data dissemination services to be used, e.g., to rapidly re-program all sensors over-the-air. The organization of such a large testbed requires notable efforts in terms of communication protocols and strategies, whose design must pursue scalability, energy efficiency (while sensors are connected through USB cables for logging and debugging purposes, most of them will be battery-operated), as well as the capability to support applications with diverse requirements. These efforts, the description of a subset of the results obtained so far, and of the final objectives to be met are the scope of the present paper. PMID:22408513

  19. Fusing Swarm Intelligence and Self-Assembly for Optimizing Echo State Networks.

    PubMed

    Martin, Charles E; Reggia, James A

    2015-01-01

    Optimizing a neural network's topology is a difficult problem for at least two reasons: the topology space is discrete, and the quality of any given topology must be assessed by assigning many different sets of weights to its connections. These two characteristics tend to cause very "rough." objective functions. Here we demonstrate how self-assembly (SA) and particle swarm optimization (PSO) can be integrated to provide a novel and effective means of concurrently optimizing a neural network's weights and topology. Combining SA and PSO addresses two key challenges. First, it creates a more integrated representation of neural network weights and topology so that we have just a single, continuous search domain that permits "smoother" objective functions. Second, it extends the traditional focus of self-assembly, from the growth of predefined target structures, to functional self-assembly, in which growth is driven by optimality criteria defined in terms of the performance of emerging structures on predefined computational problems. Our model incorporates a new way of viewing PSO that involves a population of growing, interacting networks, as opposed to particles. The effectiveness of our method for optimizing echo state network weights and topologies is demonstrated through its performance on a number of challenging benchmark problems. PMID:26346488

  20. Artificial intelligence techniques for colorectal cancer drug metabolism: ontology and complex network.

    PubMed

    Martínez-Romero, Marcos; Vázquez-Naya, José M; Rabuñal, Juan R; Pita-Fernández, Salvador; Macenlle, Ramiro; Castro-Alvariño, Javier; López-Roses, Leopoldo; Ulla, José L; Martínez-Calvo, Antonio V; Vázquez, Santiago; Pereira, Javier; Porto-Pazos, Ana B; Dorado, Julián; Pazos, Alejandro; Munteanu, Cristian R

    2010-05-01

    Colorectal cancer is one of the most frequent types of cancer in the world and generates important social impact. The understanding of the specific metabolism of this disease and the transformations of the specific drugs will allow finding effective prevention, diagnosis and treatment of the colorectal cancer. All the terms that describe the drug metabolism contribute to the construction of ontology in order to help scientists to link the correlated information and to find the most useful data about this topic. The molecular components involved in this metabolism are included in complex network such as metabolic pathways in order to describe all the molecular interactions in the colorectal cancer. The graphical method of processing biological information such as graphs and complex networks leads to the numerical characterization of the colorectal cancer drug metabolic network by using invariant values named topological indices. Thus, this method can help scientists to study the most important elements in the metabolic pathways and the dynamics of the networks during mutations, denaturation or evolution for any type of disease. This review presents the last studies regarding ontology and complex networks of the colorectal cancer drug metabolism and a basic topology characterization of the drug metabolic process sub-ontology from the Gene Ontology.

  1. Fusing Swarm Intelligence and Self-Assembly for Optimizing Echo State Networks

    PubMed Central

    Martin, Charles E.; Reggia, James A.

    2015-01-01

    Optimizing a neural network's topology is a difficult problem for at least two reasons: the topology space is discrete, and the quality of any given topology must be assessed by assigning many different sets of weights to its connections. These two characteristics tend to cause very “rough.” objective functions. Here we demonstrate how self-assembly (SA) and particle swarm optimization (PSO) can be integrated to provide a novel and effective means of concurrently optimizing a neural network's weights and topology. Combining SA and PSO addresses two key challenges. First, it creates a more integrated representation of neural network weights and topology so that we have just a single, continuous search domain that permits “smoother” objective functions. Second, it extends the traditional focus of self-assembly, from the growth of predefined target structures, to functional self-assembly, in which growth is driven by optimality criteria defined in terms of the performance of emerging structures on predefined computational problems. Our model incorporates a new way of viewing PSO that involves a population of growing, interacting networks, as opposed to particles. The effectiveness of our method for optimizing echo state network weights and topologies is demonstrated through its performance on a number of challenging benchmark problems. PMID:26346488

  2. Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

    PubMed

    Barton, Alan J; Valdés, Julio J; Orchard, Robert

    2009-01-01

    Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

  3. Biologically inspired intelligent decision making: a commentary on the use of artificial neural networks in bioinformatics.

    PubMed

    Manning, Timmy; Sleator, Roy D; Walsh, Paul

    2014-01-01

    Artificial neural networks (ANNs) are a class of powerful machine learning models for classification and function approximation which have analogs in nature. An ANN learns to map stimuli to responses through repeated evaluation of exemplars of the mapping. This learning approach results in networks which are recognized for their noise tolerance and ability to generalize meaningful responses for novel stimuli. It is these properties of ANNs which make them appealing for applications to bioinformatics problems where interpretation of data may not always be obvious, and where the domain knowledge required for deductive techniques is incomplete or can cause a combinatorial explosion of rules. In this paper, we provide an introduction to artificial neural network theory and review some interesting recent applications to bioinformatics problems.

  4. 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.

  5. Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

    PubMed Central

    Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

    2012-01-01

    Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

  6. Virtualized Network Control (VNC)

    SciTech Connect

    Lehman, Thomas; Guok, Chin; Ghani, Nasir

    2013-01-31

    The focus of this project was on the development of a "Network Service Plane" as an abstraction model for the control and provisioning of multi-layer networks. The primary motivation for this work were the requirements of next generation networked applications which will need to access advanced networking as a first class resource at the same level as compute and storage resources. A new class of "Intelligent Network Services" were defined in order to facilitate the integration of advanced network services into application specific workflows. This new class of network services are intended to enable real-time interaction between the application co-scheduling algorithms and the network for the purposes of workflow planning, real-time resource availability identification, scheduling, and provisioning actions.

  7. The Hybrid Application of an Inductive Learning Method and a Neural Network for Intelligent Information Retrieval.

    ERIC Educational Resources Information Center

    Cortez, Edwin M.; And Others

    1995-01-01

    Proposes an information retrieval system based on a hybrid model consisting of an inductive learning and neural network system. Evaluates the system's responses to incomplete queries and inconsistent indexing. Query terms, discriminant descriptors, and the American Documentation Institute's query and document titles used in the evaluation are…

  8. Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

    2016-05-01

    This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

  9. A Fabric of Intelligence--How Our Supercomputing Network Is Weaving the Next Human Renaissance.

    ERIC Educational Resources Information Center

    Fierheller, George

    1994-01-01

    Provides the text of the 1993 Ian P. Sharp Lecture on Information Science that discussed issues concerning the global information network, particularly as they affect Canada. Highlights include the economic value of knowledge; information technology; effects on business; the global marketplace; effects on work practices; collaboration; social…

  10. The Deployment of Sensor Network Intelligent Emission Locator (SENTINEL) for Fenceline Emission Measurements

    EPA Science Inventory

    Abstract: As part of the Petroleum Refinery Risk and Technology Review, New Source Performance Standards rule, US EPA is proposing use of two-week passive sorbant tube fenceline monitoring for benzene. With recent technological advances, low-cost time-resolved sensors may become...

  11. Intelligence and childlessness.

    PubMed

    Kanazawa, Satoshi

    2014-11-01

    Demographers debate why people have children in advanced industrial societies where children are net economic costs. From an evolutionary perspective, however, the important question is why some individuals choose not to have children. Recent theoretical developments in evolutionary psychology suggest that more intelligent individuals may be more likely to prefer to remain childless than less intelligent individuals. Analyses of the National Child Development Study show that more intelligent men and women express preference to remain childless early in their reproductive careers, but only more intelligent women (not more intelligent men) are more likely to remain childless by the end of their reproductive careers. Controlling for education and earnings does not at all attenuate the association between childhood general intelligence and lifetime childlessness among women. One-standard-deviation increase in childhood general intelligence (15 IQ points) decreases women's odds of parenthood by 21-25%. Because women have a greater impact on the average intelligence of future generations, the dysgenic fertility among women is predicted to lead to a decline in the average intelligence of the population in advanced industrial nations. PMID:25131282

  12. Intelligence and childlessness.

    PubMed

    Kanazawa, Satoshi

    2014-11-01

    Demographers debate why people have children in advanced industrial societies where children are net economic costs. From an evolutionary perspective, however, the important question is why some individuals choose not to have children. Recent theoretical developments in evolutionary psychology suggest that more intelligent individuals may be more likely to prefer to remain childless than less intelligent individuals. Analyses of the National Child Development Study show that more intelligent men and women express preference to remain childless early in their reproductive careers, but only more intelligent women (not more intelligent men) are more likely to remain childless by the end of their reproductive careers. Controlling for education and earnings does not at all attenuate the association between childhood general intelligence and lifetime childlessness among women. One-standard-deviation increase in childhood general intelligence (15 IQ points) decreases women's odds of parenthood by 21-25%. Because women have a greater impact on the average intelligence of future generations, the dysgenic fertility among women is predicted to lead to a decline in the average intelligence of the population in advanced industrial nations.

  13. Intelligent Local Avoided Collision (iLAC) MAC Protocol for Very High Speed Wireless Network

    NASA Astrophysics Data System (ADS)

    Hieu, Dinh Chi; Masuda, Akeo; Rabarijaona, Verotiana Hanitriniala; Shimamoto, Shigeru

    Future wireless communication systems aim at very high data rates. As the medium access control (MAC) protocol plays the central role in determining the overall performance of the wireless system, designing a suitable MAC protocol is critical to fully exploit the benefit of high speed transmission that the physical layer (PHY) offers. In the latest 802.11n standard [2], the problem of long overhead has been addressed adequately but the issue of excessive colliding transmissions, especially in congested situation, remains untouched. The procedure of setting the backoff value is the heart of the 802.11 distributed coordination function (DCF) to avoid collision in which each station makes its own decision on how to avoid collision in the next transmission. However, collision avoidance is a problem that can not be solved by a single station. In this paper, we introduce a new MAC protocol called Intelligent Local Avoided Collision (iLAC) that redefines individual rationality in choosing the backoff counter value to avoid a colliding transmission. The distinguishing feature of iLAC is that it fundamentally changes this decision making process from collision avoidance to collaborative collision prevention. As a result, stations can avoid colliding transmissions with much greater precision. Analytical solution confirms the validity of this proposal and simulation results show that the proposed algorithm outperforms the conventional algorithms by a large margin.

  14. Orthogonal Patterns In A Binary Neural Network

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1991-01-01

    Report presents some recent developments in theory of binary neural networks. Subject matter relevant to associate (content-addressable) memories and to recognition of patterns - both of considerable importance in advancement of robotics and artificial intelligence. When probed by any pattern, network converges to one of stored patterns.

  15. Issues in Applying Bio-Inspiration, Cognitive Critical Mass and Developmental-Inspired Principles to Advanced Intelligent Systems

    NASA Astrophysics Data System (ADS)

    Berg-Cross, Gary; Samsonovich, Alexei V.

    This Chapter summarizes ideas presented at the special PerMIS 2008 session on Biological Inspiration for Intelligent Systems. Bio-inspired principles of development and evolution are a special part of the bio-models and principles that can be used to improve intelligent systems and related artifacts. Such principles are not always explicit. They represent an alternative to incremental engineering expansion using new technology to replicate human intelligent capabilities. They are more evident in efforts to replicate and produce a “critical mass” of higher cognitive functions of the human mind or their emergence through cognitive developmental robotics (DR) and self-regulated learning (SRL). DR approaches takes inspiration from natural processes, so that intelligently engineered systems may create solutions to problems in ways similar to what we hypothesize is occurring with biologics in their natural environment. This Chapter discusses how an SRL-based approach to bootstrap a “critical mass” can be assessed by a set of cognitive tests. It also uses a three-level bio-inspired framework to illustrate methodological issues in DR research. The approach stresses the importance of using bio-realistic developmental principles to guide and constrain research. Of particular importance is keeping models and implementation separate to avoid the possible of falling into a Ptolemaic paradigm that may lead to endless tweaking of models. Several of Lungarella's design principles [36] for developmental robotics are discussed as constraints on intelligence as it emerges from an ecologically balanced, three-way interaction between an agents' control systems, physical embodiment, and the external environment. The direction proposed herein is to explore such principles to avoid slavish following of superficial bio-inspiration. Rather we should proceed with a mature and informed developmental approach using developmental principles based on our incremental understanding of how

  16. Enhancing nuclear power plant performance through the use of artificial intelligence

    SciTech Connect

    Maren, A.J.; Miller, L.F.; Tsoukalas, L.H.; Uhrig, R.E.; Upadhyaya, B.R.

    1992-03-31

    The objective of this research was to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important objective, was to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants.

  17. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.

    PubMed

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.

  18. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis

    PubMed Central

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

  19. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.

    PubMed

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

  20. Symbiotic intelligence: Self-organizing knowledge on distributed networks, driven by human interaction

    SciTech Connect

    Johnson, N.; Joslyn, C.; Rocha, L.; Smith, S.; Kantor, M.; Rasmussen, S. |

    1998-07-01

    -organizing knowledge formation from this symbiotic intelligence exemplifies a new type of self-organizing system, one without dissipation and not constrained by limited resources.

  1. Intelligent nonsingular terminal sliding-mode control using MIMO Elman neural network for piezo-flexural nanopositioning stage.

    PubMed

    Lin, Faa-Jeng; Lee, Shih-Yang; Chou, Po-Huan

    2012-12-01

    The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS.

  2. Network management and signalling standards for CCSDS advanced orbiting system communication systems

    NASA Astrophysics Data System (ADS)

    Pietras, John

    The Consultative Committee for Space Data Systems (CCSDS) is an international organization chartered to develop and adopt communications protocols and data processing standards suitable for use in space-related communication and data processing systems. This paper briefly describes the CCSDS network management environment and reviews the current status of CCSDS recommendations for network management functional capability, use of internal standard for network management, and composition of signaling systems in support of the advanced orbiting systems services typified by the international Space Station Freedom Program. A timetable for future work in this area is presented.

  3. Neural network setpoint control of an advanced test reactor experiment loop simulation

    SciTech Connect

    Cordes, G.A.; Bryan, S.R.; Powell, R.H.; Chick, D.R.

    1990-09-01

    This report describes the design, implementation, and application of artificial neural networks to achieve temperature and flow rate control for a simulation of a typical experiment loop in the Advanced Test Reactor (ATR) located at the Idaho National Engineering Laboratory (INEL). The goal of the project was to research multivariate, nonlinear control using neural networks. A loop simulation code was adapted for the project and used to create a training set and test the neural network controller for comparison with the existing loop controllers. The results for three neural network designs are documented and compared with existing loop controller action. The neural network was shown to be as accurate at loop control as the classical controllers in the operating region represented by the training set. 9 refs., 28 figs., 2 tabs.

  4. Perception system with scene understanding capabilities upon network-symbolic models for intelligent tactical behavior of mobile robots in real-world environments

    NASA Astrophysics Data System (ADS)

    Kuvich, Gary

    2005-10-01

    Tactical behavior of UGVs, which is needed for successful autonomous off-road driving, can be in many cases achieved by covering most possible driving situations with a set of rules and switching into a "drive-me-away" semi-autonomous mode when no such rule exists. However, the unpredictable and rapidly changing nature of combat situations requires more intelligent tactical behavior that must be based on predictive situation awareness with ongoing scene understanding and fast autonomous decision making. The implementation of image understanding and active vision is possible in the form of biologically inspired Network-Symbolic models, which combine the power of Computational Intelligence with graph and diagrammatic representation of knowledge. A Network-Symbolic system converts image information into an "understandable" Network-Symbolic format, which is similar to relational knowledge models. The traditional linear bottom-up "segmentation-grouping-learning-recognition" approach cannot provide a reliable separation of an object from its background/clutter, while human vision unambiguously solves this problem. An Image/Video Analysis that is based on Network-Symbolic approach is a combination of recursive hierarchical bottom-up and top-down processes. Logic of visual scenes can be captured in the Network-Symbolic models and used for the reliable disambiguation of visual information, including object detection and identification. Such a system can better interpret images/video for situation awareness, target recognition, navigation and actions and seamlessly integrates into 4D/RCS architecture.

  5. Artificial neural networks and approximate reasoning for intelligent control in space

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1991-01-01

    A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

  6. Case Study IV: Carnegie Foundation for the Advancement of Teaching's Networked Improvement Communities (NICs)

    ERIC Educational Resources Information Center

    Coburn, Cynthia E.; Penuel, William R.; Geil, Kimberly E.

    2015-01-01

    The Carnegie Foundation for the Advancement of Teaching is a nonprofit, operating foundation with a long tradition of developing and studying ways to improve teaching practice. For the past three years, the Carnegie Foundation has initiated three different Networked Improvement Communities (NICs). The first, Quantway, is addressing the high…

  7. Intelligent Tutor

    NASA Technical Reports Server (NTRS)

    1990-01-01

    NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

  8. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    PubMed Central

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  9. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  10. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  11. Building a multicenter telehealth network to advance chronic disease management.

    PubMed

    Khairat, Saif; Wijesinghe, Namal; Wolfson, Julian; Scott, Rob; Simkus, Ray

    2014-01-01

    The use of telehealth solutions has proved to improve clinical management of chronic diseases, expand access to healthcare services and clinicians, and reduce healthcare-related costs. The project aims at improving Heart Failure (HF) management through the utilization of a Telemedicine and Personal Health Records systems that will assist HF specialist in Colombo, Sri Lanka to monitor and consult with remote HF patients. A telehealth network will be built at an international site that connects five remote telehealth clinics to a central clinic at a major University Hospital in Sri Lanka where HF specialists are located. In this study, 200 HF patients will be recruited for nine months, 100 patients will be randomly selected for the treatment group and the other 100 will be selected for the control group. Pre, mid, and post study surveys will be conducted to assess the efficacy and satisfaction levels of patients with both care models. Moreover, clinical outcomes will be collected to evaluate the impact of the intervention on the treatment patients compared to control patients. The research aims at enhancing Heart Failure management through eliminating current health challenges and healthcare-related financial burdens.

  12. The application of integrated knowledge-based systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

    NASA Technical Reports Server (NTRS)

    Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris

    1992-01-01

    One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through BRAIN, an integrated network of both human and computer elements. BRAIN will function as an advisor to mission managers by assessing the risk of inflight biomedical problems and recommending appropriate countermeasures. Described here is a joint effort among various NASA elements to develop BRAIN and the Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of knowledge acquisition, integration of IDRA components, the use of expert systems to automate the biomedical prediction process, development of a user friendly interface, and integration of IDRA and ExerCISys systems. Because C language, CLIPS and the X-Window System are portable and easily integrated, they were chosen ss the tools for the initial IDRA prototype.

  13. Intelligent systems technology infrastructure for integrated systems

    NASA Technical Reports Server (NTRS)

    Lum, Henry, Jr.

    1991-01-01

    Significant advances have occurred during the last decade in intelligent systems technologies (a.k.a. knowledge-based systems, KBS) including research, feasibility demonstrations, and technology implementations in operational environments. Evaluation and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent systems technologies can be realized for Automated Rendezvous and Capture applications. The successful implementation of these technologies involve a complex system infrastructure integrating the requirements of transportation, vehicle checkout and health management, and communication systems without compromise to systems reliability and performance. The resources that must be invoked to accomplish these tasks include remote ground operations and control, built-in system fault management and control, and intelligent robotics. To ensure long-term evolution and integration of new validated technologies over the lifetime of the vehicle, system interfaces must also be addressed and integrated into the overall system interface requirements. An approach for defining and evaluating the system infrastructures including the testbed currently being used to support the on-going evaluations for the evolutionary Space Station Freedom Data Management System is presented and discussed. Intelligent system technologies discussed include artificial intelligence (real-time replanning and scheduling), high performance computational elements (parallel processors, photonic processors, and neural networks), real-time fault management and control, and system software development tools for rapid prototyping capabilities.

  14. Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON.

    PubMed

    Lytton, William W; Seidenstein, Alexandra H; Dura-Bernal, Salvador; McDougal, Robert A; Schürmann, Felix; Hines, Michael L

    2016-10-01

    Large multiscale neuronal network simulations are of increasing value as more big data are gathered about brain wiring and organization under the auspices of a current major research initiative, such as Brain Research through Advancing Innovative Neurotechnologies. The development of these models requires new simulation technologies. We describe here the current use of the NEURON simulator with message passing interface (MPI) for simulation in the domain of moderately large networks on commonly available high-performance computers (HPCs). We discuss the basic layout of such simulations, including the methods of simulation setup, the run-time spike-passing paradigm, and postsimulation data storage and data management approaches. Using the Neuroscience Gateway, a portal for computational neuroscience that provides access to large HPCs, we benchmark simulations of neuronal networks of different sizes (500-100,000 cells), and using different numbers of nodes (1-256). We compare three types of networks, composed of either Izhikevich integrate-and-fire neurons (I&F), single-compartment Hodgkin-Huxley (HH) cells, or a hybrid network with half of each. Results show simulation run time increased approximately linearly with network size and decreased almost linearly with the number of nodes. Networks with I&F neurons were faster than HH networks, although differences were small since all tested cells were point neurons with a single compartment. PMID:27557104

  15. Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON.

    PubMed

    Lytton, William W; Seidenstein, Alexandra H; Dura-Bernal, Salvador; McDougal, Robert A; Schürmann, Felix; Hines, Michael L

    2016-10-01

    Large multiscale neuronal network simulations are of increasing value as more big data are gathered about brain wiring and organization under the auspices of a current major research initiative, such as Brain Research through Advancing Innovative Neurotechnologies. The development of these models requires new simulation technologies. We describe here the current use of the NEURON simulator with message passing interface (MPI) for simulation in the domain of moderately large networks on commonly available high-performance computers (HPCs). We discuss the basic layout of such simulations, including the methods of simulation setup, the run-time spike-passing paradigm, and postsimulation data storage and data management approaches. Using the Neuroscience Gateway, a portal for computational neuroscience that provides access to large HPCs, we benchmark simulations of neuronal networks of different sizes (500-100,000 cells), and using different numbers of nodes (1-256). We compare three types of networks, composed of either Izhikevich integrate-and-fire neurons (I&F), single-compartment Hodgkin-Huxley (HH) cells, or a hybrid network with half of each. Results show simulation run time increased approximately linearly with network size and decreased almost linearly with the number of nodes. Networks with I&F neurons were faster than HH networks, although differences were small since all tested cells were point neurons with a single compartment.

  16. Intelligent microchip networks: an agent-on-chip synthesis framework for the design of smart and robust sensor networks

    NASA Astrophysics Data System (ADS)

    Bosse, Stefan

    2013-05-01

    Sensorial materials consisting of high-density, miniaturized, and embedded sensor networks require new robust and reliable data processing and communication approaches. Structural health monitoring is one major field of application for sensorial materials. Each sensor node provides some kind of sensor, electronics, data processing, and communication with a strong focus on microchip-level implementation to meet the goals of miniaturization and low-power energy environments, a prerequisite for autonomous behaviour and operation. Reliability requires robustness of the entire system in the presence of node, link, data processing, and communication failures. Interaction between nodes is required to manage and distribute information. One common interaction model is the mobile agent. An agent approach provides stronger autonomy than a traditional object or remote-procedure-call based approach. Agents can decide for themselves, which actions are performed, and they are capable of flexible behaviour, reacting on the environment and other agents, providing some degree of robustness. Traditionally multi-agent systems are abstract programming models which are implemented in software and executed on program controlled computer architectures. This approach does not well scale to micro-chip level and requires full equipped computers and communication structures, and the hardware architecture does not consider and reflect the requirements for agent processing and interaction. We propose and demonstrate a novel design paradigm for reliable distributed data processing systems and a synthesis methodology and framework for multi-agent systems implementable entirely on microchip-level with resource and power constrained digital logic supporting Agent-On-Chip architectures (AoC). The agent behaviour and mobility is fully integrated on the micro-chip using pipelined communicating processes implemented with finite-state machines and register-transfer logic. The agent behaviour

  17. Artificial vision by multi-layered neural networks: neocognitron and its advances.

    PubMed

    Fukushima, Kunihiko

    2013-01-01

    The neocognitron is a neural network model proposed by Fukushima (1980). Its architecture was suggested by neurophysiological findings on the visual systems of mammals. It is a hierarchical multi-layered network. It acquires the ability to robustly recognize visual patterns through learning. Although the neocognitron has a long history, modifications of the network to improve its performance are still going on. For example, a recent neocognitron uses a new learning rule, named add-if-silent, which makes the learning process much simpler and more stable. Nevertheless, a high recognition rate can be kept with a smaller scale of the network. Referring to the history of the neocognitron, this paper discusses recent advances in the neocognitron. We also show that various new functions can be realized by, for example, introducing top-down connections to the neocognitron: mechanism of selective attention, recognition and completion of partly occluded patterns, restoring occluded contours, and so on.

  18. The Effects of a Dynamic Spectrum Access Overlay in LTE-Advanced Networks

    SciTech Connect

    Juan D. Deaton; Ryan E. Irwin; Luiz A. DaSilva

    2011-05-01

    As early as 2014, mobile network operators’ spectral capacity will be overwhelmed by the demand brought on by new devices and applications. To augment capacity and meet this demand, operators may choose to deploy a Dynamic Spectrum Access (DSA) overlay. The signaling and functionality required by such an overlay have not yet been fully considered in the architecture of the planned Long Term Evolution Advanced (LTE+) networks. This paper presents a Spectrum Accountability framework to be integrated into LTE+ architectures, defining specific element functionality, protocol interfaces, and signaling flow diagrams required to enforce the rights and responsibilities of primary and secondary users. We also quantify, through integer programs, the benefits of using DSA channels to augment capacity under a scenario in which LTE+ network can opportunistically use TV and GSM spectrum. The framework proposed here may serve as a guide in the development of future LTE+ network standards that account for DSA.

  19. Advanced information society(2)

    NASA Astrophysics Data System (ADS)

    Masuyama, Keiichi

    Our modern life is full of information and information infiltrates into our daily life. Networking of the telecommunication is extended to society, company, and individual level. Although we have just entered the advanced information society, business world and our daily life have been steadily transformed by the advancement of information network. This advancement of information brings a big influence on economy, and will play they the main role in the expansion of domestic demands. This paper tries to view the image of coming advanced information society, focusing on the transforming businessman's life and the situation of our daily life, which became wealthy by the spread of daily life information and the visual information by satellite system, in the development of the intelligent city.

  20. Network reconfiguration algorithm for automated distribution systems based on artificial intelligence approach

    SciTech Connect

    Kyunghee Jung; Hoyong Kim; Yunseok Ko . Dept. of Distribution System)

    1993-10-01

    This study develops an expert system to solve the problem of the main transformer (MTr) or feeder overload and the feeder constraint violation in automated distribution systems, where each feeder is subject to the thermal overload and voltage drop limits. Then, the objective is to perform the network reconfiguration by switching the tie and sectionalizing switches so that the system violation is removed, while achieving the load balance of the MTrs and feeders with a fewer number of switching operations. Since the switching operation in the practical system does not cause the large change in the voltage, an approximation method is used in order to check the voltage violation, instead of a full ac load flow solution. To reduce the search space, an expert system based on heuristic rules is presented, and implemented in Prolog. This system adopts the best-first tree search technique. List processing and recursive programming techniques are then utilized to solve the combinatorial type optimization problem. The computational results are also prepared to show the performance of the heuristic algorithms developed.

  1. Cross-language differences in the brain network subserving intelligible speech.

    PubMed

    Ge, Jianqiao; Peng, Gang; Lyu, Bingjiang; Wang, Yi; Zhuo, Yan; Niu, Zhendong; Tan, Li Hai; Leff, Alexander P; Gao, Jia-Hong

    2015-03-10

    How is language processed in the brain by native speakers of different languages? Is there one brain system for all languages or are different languages subserved by different brain systems? The first view emphasizes commonality, whereas the second emphasizes specificity. We investigated the cortical dynamics involved in processing two very diverse languages: a tonal language (Chinese) and a nontonal language (English). We used functional MRI and dynamic causal modeling analysis to compute and compare brain network models exhaustively with all possible connections among nodes of language regions in temporal and frontal cortex and found that the information flow from the posterior to anterior portions of the temporal cortex was commonly shared by Chinese and English speakers during speech comprehension, whereas the inferior frontal gyrus received neural signals from the left posterior portion of the temporal cortex in English speakers and from the bilateral anterior portion of the temporal cortex in Chinese speakers. Our results revealed that, although speech processing is largely carried out in the common left hemisphere classical language areas (Broca's and Wernicke's areas) and anterior temporal cortex, speech comprehension across different language groups depends on how these brain regions interact with each other. Moreover, the right anterior temporal cortex, which is crucial for tone processing, is equally important as its left homolog, the left anterior temporal cortex, in modulating the cortical dynamics in tone language comprehension. The current study pinpoints the importance of the bilateral anterior temporal cortex in language comprehension that is downplayed or even ignored by popular contemporary models of speech comprehension.

  2. Cross-language differences in the brain network subserving intelligible speech

    PubMed Central

    Ge, Jianqiao; Peng, Gang; Lyu, Bingjiang; Wang, Yi; Zhuo, Yan; Niu, Zhendong; Tan, Li Hai; Leff, Alexander P.; Gao, Jia-Hong

    2015-01-01

    How is language processed in the brain by native speakers of different languages? Is there one brain system for all languages or are different languages subserved by different brain systems? The first view emphasizes commonality, whereas the second emphasizes specificity. We investigated the cortical dynamics involved in processing two very diverse languages: a tonal language (Chinese) and a nontonal language (English). We used functional MRI and dynamic causal modeling analysis to compute and compare brain network models exhaustively with all possible connections among nodes of language regions in temporal and frontal cortex and found that the information flow from the posterior to anterior portions of the temporal cortex was commonly shared by Chinese and English speakers during speech comprehension, whereas the inferior frontal gyrus received neural signals from the left posterior portion of the temporal cortex in English speakers and from the bilateral anterior portion of the temporal cortex in Chinese speakers. Our results revealed that, although speech processing is largely carried out in the common left hemisphere classical language areas (Broca’s and Wernicke’s areas) and anterior temporal cortex, speech comprehension across different language groups depends on how these brain regions interact with each other. Moreover, the right anterior temporal cortex, which is crucial for tone processing, is equally important as its left homolog, the left anterior temporal cortex, in modulating the cortical dynamics in tone language comprehension. The current study pinpoints the importance of the bilateral anterior temporal cortex in language comprehension that is downplayed or even ignored by popular contemporary models of speech comprehension. PMID:25713366

  3. An Examination of Two Policy Networks Involved in Advancing Smokefree Policy Initiatives

    PubMed Central

    Moreland-Russell, Sarah; Carothers, Bobbi J.

    2015-01-01

    This study examines smokefree policy networks in two cities—Kansas City and St. Louis, Missouri—one that was successful in achieving widespread policy success, and one that was not. Descriptive social network analyses and visual network mapping were used to compare importance and contact relationships among actors involved in the smokefree policy initiatives. In Kansas City, where policy adoption was achieved, there was a higher level of connectivity among members, with network members being in contact with an average of more than five people, compared to just over two people for the St. Louis network. For both cities, despite being recognized as important, politicians were in contact with the fewest number of people. Results highlight the critical need to actively engage a variety of stakeholders when attempting city wide public health policy change. As evident by the success in smokefree policy adoption throughout Kansas City compared to St. Louis, closer linkages and continued communication among stakeholders including the media, coalitions, public health agencies, policymakers, and other partners are essential if we are to advance and broaden the impact of public health policy. Results indicate that the presence of champions, or those that play leadership roles in actively promoting policy by linking individuals and organizations, play an important role in advancing public health policy. Those working in public health should examine their level of engagement with the policy process and implement strategies for improving that engagement through relationship building and ongoing interactions with a variety of stakeholders, including policymakers. PMID:26371022

  4. An Examination of Two Policy Networks Involved in Advancing Smokefree Policy Initiatives.

    PubMed

    Moreland-Russell, Sarah; Carothers, Bobbi J

    2015-09-01

    This study examines smokefree policy networks in two cities—Kansas City and St. Louis, Missouri—one that was successful in achieving widespread policy success, and one that was not. Descriptive social network analyses and visual network mapping were used to compare importance and contact relationships among actors involved in the smokefree policy initiatives. In Kansas City, where policy adoption was achieved, there was a higher level of connectivity among members, with network members being in contact with an average of more than five people, compared to just over two people for the St. Louis network. For both cities, despite being recognized as important, politicians were in contact with the fewest number of people. Results highlight the critical need to actively engage a variety of stakeholders when attempting city wide public health policy change. As evident by the success in smokefree policy adoption throughout Kansas City compared to St. Louis, closer linkages and continued communication among stakeholders including the media, coalitions, public health agencies, policymakers, and other partners are essential if we are to advance and broaden the impact of public health policy. Results indicate that the presence of champions, or those that play leadership roles in actively promoting policy by linking individuals and organizations, play an important role in advancing public health policy. Those working in public health should examine their level of engagement with the policy process and implement strategies for improving that engagement through relationship building and ongoing interactions with a variety of stakeholders, including policymakers. PMID:26371022

  5. An Examination of Two Policy Networks Involved in Advancing Smokefree Policy Initiatives.

    PubMed

    Moreland-Russell, Sarah; Carothers, Bobbi J

    2015-09-01

    This study examines smokefree policy networks in two cities—Kansas City and St. Louis, Missouri—one that was successful in achieving widespread policy success, and one that was not. Descriptive social network analyses and visual network mapping were used to compare importance and contact relationships among actors involved in the smokefree policy initiatives. In Kansas City, where policy adoption was achieved, there was a higher level of connectivity among members, with network members being in contact with an average of more than five people, compared to just over two people for the St. Louis network. For both cities, despite being recognized as important, politicians were in contact with the fewest number of people. Results highlight the critical need to actively engage a variety of stakeholders when attempting city wide public health policy change. As evident by the success in smokefree policy adoption throughout Kansas City compared to St. Louis, closer linkages and continued communication among stakeholders including the media, coalitions, public health agencies, policymakers, and other partners are essential if we are to advance and broaden the impact of public health policy. Results indicate that the presence of champions, or those that play leadership roles in actively promoting policy by linking individuals and organizations, play an important role in advancing public health policy. Those working in public health should examine their level of engagement with the policy process and implement strategies for improving that engagement through relationship building and ongoing interactions with a variety of stakeholders, including policymakers.

  6. From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support

    PubMed Central

    Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

    2016-01-01

    Objectives 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; 3) To ensure the BN model can be used for interventional analysis; 4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. Method The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. Results When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. Conclusions This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of

  7. [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. PMID:22826960

  8. Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

    NASA Astrophysics Data System (ADS)

    Radev, Dimitar; Lokshina, Izabella

    2010-11-01

    The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

  9. Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

    PubMed

    Frantz, Terrill L

    2012-01-01

    This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities.

  10. Advanced Learning Technologies and Learning Networks and Their Impact on Future Aerospace Workforce

    NASA Technical Reports Server (NTRS)

    Noor, Ahmed K. (Compiler)

    2003-01-01

    This document contains the proceedings of the training workshop on Advanced Learning Technologies and Learning Networks and their impact on Future Aerospace Workforce. The workshop was held at the Peninsula Workforce Development Center, Hampton, Virginia, April 2 3, 2003. The workshop was jointly sponsored by Old Dominion University and NASA. Workshop attendees came from NASA, other government agencies, industry, and universities. The objectives of the workshop were to: 1) provide broad overviews of the diverse activities related to advanced learning technologies and learning environments, and 2) identify future directions for research that have high potential for aerospace workforce development. Eighteen half-hour overviewtype presentations were made at the workshop.

  11. Artificial intelligence in medicine.

    PubMed Central

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  12. Toward intelligent flight control

    NASA Technical Reports Server (NTRS)

    Stengel, Robert F.

    1993-01-01

    Flight control systems can benefit by being designed to emulate functions of natural intelligence. Intelligent control functions fall in three categories: declarative, procedural, and reflexive. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are more-or-less spontaneous and are similar to inner-loop control and estimation. Intelligent flight control systems will contain a hierarchy of expert systems, procedural algorithms, and computational neural networks, each expanding on prior functions to improve mission capability to increase the reliability and safety of flight and to ease pilot workload.

  13. Intelligent tutoring systems

    SciTech Connect

    Anderson, J.R.; Boyle, C.F.; Reiser, B.J.

    1985-04-26

    Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP. 19 references, 2 figures.

  14. Intelligent tutoring systems.

    PubMed

    Anderson, J R; Boyle, C F; Reiser, B J

    1985-04-26

    Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors. Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP. PMID:17746875

  15. 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.

  16. Highlights of pancreatobiliary endoscopy in international digestive endoscopy network 2012: how much has it advanced?

    PubMed

    Dong, Seok Ho

    2012-09-01

    The pancreatobiliary organ is composed of one of the most complicated structures and complex physiological functions among other digestive organs in our body. This is why endoscopic procedure in pancreaticobiliary system requires rather complicated techniques. In International Digestive Endoscopy Network (IDEN) 2012, many interesting pancreatobiliay endoscopy related topics were presented. Basic procedures like endoscopic papillary balloon dilation (EPBD), advanced techniques like endoscopic necrosectomy, prevention and management of post-ERCP pancreatitis, and spyglass system are reviewed in this highlight summary.

  17. An infrastructure with a unified control plane to integrate IP into optical metro networks to provide flexible and intelligent bandwidth on demand for cloud computing

    NASA Astrophysics Data System (ADS)

    Yang, Wei; Hall, Trevor

    2012-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users and the nature of the Internet traffic will undertake a fundamental transformation. Consequently, the current Internet will no longer suffice for serving cloud traffic in metro areas. This work proposes an infrastructure with a unified control plane that integrates simple packet aggregation technology with optical express through the interoperation between IP routers and electrical traffic controllers in optical metro networks. The proposed infrastructure provides flexible, intelligent, and eco-friendly bandwidth on demand for cloud computing in metro areas.

  18. Intelligent Vehicle Health Management

    NASA Technical Reports Server (NTRS)

    Paris, Deidre E.; Trevino, Luis; Watson, Michael D.

    2005-01-01

    objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

  19. Intelligent user interface for intelligent multimedia repository

    NASA Astrophysics Data System (ADS)

    Rhee, Phill-Kyu; Kim, Yong-Hwan; Sim, B. S.; Zhoo, Z. C.; Park, D.-I.

    1997-10-01

    Recently, much effort has been made for efficiency of user interface since the assumption of expertise or well-trained users is nor more valid these days. Today's users of computer systems are expanded to ordinary people. Furthermore, too much network accessible information resources in the form of various media increases rapidly everyday. The primary goal of the intelligent multimedia repository (IMR) is to assist users in accessing multimedia information efficiently. Primary users of the IMR are assumed to be novice users even though the system can be used for users at different levels of expertise. Users are not well-trained people in using computer system. Thus, the semantic gap between users and the system must be mainly reduced form the system site. The technology of intelligent user interface is adopted to minimize the semantic gap. For the intelligent user interface of been designed and developed. Machine learning technologies have been employed to provide user adaptation/intelligent capability to the system. The IUI of the IMR consist user interface manager (UIM), and user model (UM). The UIM performs the function of managing intelligent user interface. The UM stores the behavioral knowledge of the user. The UM stores the history of query and response interactions to absorb communication errors due to semantic gaps between the user and the IMR. The UM is implemented by decision tree based case- based reasoning and back propagation neural networks. Experimental result show the IUI can improve the performance of the IMR.

  20. Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

    NASA Astrophysics Data System (ADS)

    Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

    2015-12-01

    The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

  1. F-15 837 IFCS Intelligent Flight Control System Project

    NASA Technical Reports Server (NTRS)

    Bosworth, John T.

    2007-01-01

    This viewgraph presentation reviews the use of Intelligent Flight Control System (IFCS) for the F-15. The goals of the project are: (1) Demonstrate Revolutionary Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions (2) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs. The motivation for the development are to reduce the chance and skill required for survival.

  2. The 18th Annual Intelligent Ground Vehicle Competition: trends and influences for intelligent ground vehicle control

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.; Frederick, Philip; Smuda, William

    2011-01-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 18 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 75 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

  3. Intelligent Intelligence Testing.

    ERIC Educational Resources Information Center

    Pedrini, Bonnie; Pedrini, D. T.

    Intelligence tests should be used to help persons; they should not be used to penalize persons. Furthermore, our focus should be on treatment; it should not be on labeling. IQ testers often stigmatize young children and poor persons (children, adolescents, adults). Large groups of Black Americans, Spanish Americans, and Indian Americans are…

  4. Basic parameter estimation of binary neutron star systems by the advanced LIGO/Vigro network

    SciTech Connect

    Rodriguez, Carl L.; Farr, Benjamin; Raymond, Vivien; Farr, Will M.; Littenberg, Tyson B.; Fazi, Diego; Kalogera, Vicky

    2014-04-01

    Within the next five years, it is expected that the Advanced LIGO/Virgo network will have reached a sensitivity sufficient to enable the routine detection of gravitational waves. Beyond the initial detection, the scientific promise of these instruments relies on the effectiveness of our physical parameter estimation capabilities. A major part of this effort has been toward the detection and characterization of gravitational waves from compact binary coalescence, e.g., the coalescence of binary neutron stars. While several previous studies have investigated the accuracy of parameter estimation with advanced detectors, the majority have relied on approximation techniques such as the Fisher Matrix which are insensitive to the non-Gaussian nature of the gravitational wave posterior distribution function. Here we report average statistical uncertainties that will be achievable for strong detection candidates (S/N = 20) over a comprehensive sample of source parameters. We use the Markov Chain Monte Carlo based parameter estimation software developed by the LIGO/Virgo Collaboration with the goal of updating the previously quoted Fisher Matrix bounds. We find the recovery of the individual masses to be fractionally within 9% (15%) at the 68% (95%) credible intervals for equal-mass systems, and within 1.9% (3.7%) for unequal-mass systems. We also find that the Advanced LIGO/Virgo network will constrain the locations of binary neutron star mergers to a median uncertainty of 5.1 deg{sup 2} (13.5 deg{sup 2}) on the sky. This region is improved to 2.3 deg{sup 2} (6 deg{sup 2}) with the addition of the proposed LIGO India detector to the network. We also report the average uncertainties on the luminosity distances and orbital inclinations of strong detections that can be achieved by different network configurations.

  5. Advanced Communication Technology Satellite (ACTS) Very Small Aperture Terminal (VSAT) Network Control Performance

    NASA Technical Reports Server (NTRS)

    Coney, T. A.

    1996-01-01

    This paper discusses the performance of the network control function for the Advanced Communications Technology Satellite (ACTS) very small aperture terminal (VSAT) full mesh network. This includes control of all operational activities such as acquisition, synchronization, timing and rain fade compensation as well as control of all communications activities such as on-demand integrated services (voice, video, and date) connects and disconnects Operations control is provided by an in-band orderwire carried in the baseboard processor (BBP) control burst, the orderwire burst, the reference burst, and the uplink traffic burst. Communication services are provided by demand assigned multiple access (DAMA) protocols. The ACTS implementation of DAMA protocols ensures both on-demand and integrated voice, video and data services. Communications services control is also provided by the in-band orderwire but uses only the reference burst and the uplink traffic burst. The performance of the ACTS network control functions have been successfully tested during on-orbit checkout and in various VSAT networks in day to day operations. This paper discusses the network operations and services control performance.

  6. Lightning Radio Source Retrieval Using Advanced Lightning Direction Finder (ALDF) Networks

    NASA Technical Reports Server (NTRS)

    Koshak, William J.; Blakeslee, Richard J.; Bailey, J. C.

    1998-01-01

    A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing and arrival time of lightning radio emissions. Solutions for the plane (i.e., no Earth curvature) are provided that implement all of tile measurements mentioned above. Tests of the retrieval method are provided using computer-simulated data sets. We also introduce a quadratic planar solution that is useful when only three arrival time measurements are available. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in source location. Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. In the absence of measurement errors, quadratic root degeneracy (no source location ambiguity) is shown to exist exactly on the outer sensor baselines for arbitrary non-collinear network geometries. The accuracy of the quadratic planar method is tested with computer generated data sets. The results are generally better than those obtained from the three station linear planar method when bearing errors are about 2 deg. We also note some of the advantages and disadvantages of these methods over the nonlinear method of chi(sup 2) minimization employed by the National Lightning Detection Network (NLDN) and discussed in Cummins et al.(1993, 1995, 1998).

  7. Recent advances on distributed filtering for stochastic systems over sensor networks

    NASA Astrophysics Data System (ADS)

    Ding, Derui; Wang, Zidong; Shen, Bo

    2014-05-01

    Sensor networks comprising of tiny, power-constrained nodes with sensing, computation, and wireless communication capabilities are gaining popularity due to their potential application in a wide variety of environments like monitoring of environmental attributes and various military and civilian applications. Considering the limited power and communication resources of the sensor nodes, the strategy of the distributed information processing is widely exploited. Therefore, it would be interesting to examine how the topology, network-induced phenomena, and power constraints influence the distributed filtering performance and to obtain some suitable schemes in order to solve the addressed distributed filter design problem. In this paper, we aim to survey some recent advances on the distributed filtering and distributed state estimation problems over the sensor networks with various performance requirements and/or randomly occurring network-induced phenomena. First, some practical filter structures are addressed in detail. Then, the developments of the distributed Kalman filtering, distributed state estimation based on the stability or mean-square error analysis, and distributed ? filtering are systematically reviewed. In addition, latest results on the distributed filtering or state estimation over sensor networks are discussed in great detail and some challenges are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out.

  8. Directory-based battlespace awareness intelligent system

    NASA Astrophysics Data System (ADS)

    Cheng, Bo-Chao; Shen, Chien-Chung; Wu, Tsong-Ho

    1999-07-01

    To win the next war decisively with minimal causalities, both commanders and warfighters must rely on advanced battlespace awareness capabilities to acquire, exchange, and employ precise and accurate information throughout the battlespace to support warfighting activities. However, the chaotic situation of the battlespace usually prevents accurate delivery of information and correct provisioning of services. For example, messages sent by a warfighter to report medical emergency may not be delivered to the right command hierarchy and battlespace intelligence may not be delivered to the right warfighter due to the location of the warfighter. In this paper, we propose and describe an infrastructure, called the Battlespace AwarenessS Intelligent System (BASIS), to facilitate value-added battlespace awareness services based on location information of warfighters and network equipment.

  9. A New Approach in Advance Network Reservation and Provisioning for High-Performance Scientific Data Transfers

    SciTech Connect

    Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex

    2010-01-28

    Scientific applications already generate many terabytes and even petabytes of data from supercomputer runs and large-scale experiments. The need for transferring data chunks of ever-increasing sizes through the network shows no sign of abating. Hence, we need high-bandwidth high speed networks such as ESnet (Energy Sciences Network). Network reservation systems, i.e. ESnet's OSCARS (On-demand Secure Circuits and Advance Reservation System) establish guaranteed bandwidth of secure virtual circuits at a certain time, for a certain bandwidth and length of time. OSCARS checks network availability and capacity for the specified period of time, and allocates requested bandwidth for that user if it is available. If the requested reservation cannot be granted, no further suggestion is returned back to the user. Further, there is no possibility from the users view-point to make an optimal choice. We report a new algorithm, where the user specifies the total volume that needs to be transferred, a maximum bandwidth that he/she can use, and a desired time period within which the transfer should be done. The algorithm can find alternate allocation possibilities, including earliest time for completion, or shortest transfer duration - leaving the choice to the user. We present a novel approach for path finding in time-dependent networks, and a new polynomial algorithm to find possible reservation options according to given constraints. We have implemented our algorithm for testing and incorporation into a future version of ESnet?s OSCARS. Our approach provides a basis for provisioning end-to-end high performance data transfers over storage and network resources.

  10. Italy's Intelligent Educational Training Station

    ERIC Educational Resources Information Center

    Ponti, Giorgio

    2005-01-01

    The Intelligent Educational Training Station has been developed in Italy to meet emerging school building needs. The project, for schools from the primary to upper secondary level, proposes flexible architecture for an "intelligent school" network, and was developed by CISEM, the Centre for Educational Innovation and Experimentation of Milan.

  11. Smart x-ray beam position monitor system using artificial intelligence methods for the Advanced Photon Source insertion-device beamlines

    SciTech Connect

    Shu, D.; Ding, H.; Barraza, J.; Kuzay, T.M.; Haeffner, D.; Ramanathan, M.

    1997-09-01

    At the Advanced Photon Source (APS), each insertion device (ID) beamline front-end has two XBPMs to monitor the X-ray beam position for both that vertical and horizontal directions. Performance challenges for a conventional photoemission type X-ray beam position monitor (XBPM) during operations are contamination of the signal from the neighboring bending magnet sources and the sensitivity of the XBPM to the insertion device (ID) gap variations. Problems are exacerbated because users change the ID gap during their operations, and hence the percentage level of the contamination in the front end XBPM signals varies. A smart XBPM system with a high speed digital signal processor has been built at the Advanced Photon Source for the ID beamline front ends. The new version of the software, which uses an artificial intelligence method, provides a self learning and self-calibration capability to the smart XBPM system. The structure of and recent test results with the system are presented in this paper.

  12. A Primer on Artificial Intelligence.

    ERIC Educational Resources Information Center

    Leal, Ralph A.

    A survey of literature on recent advances in the field of artificial intelligence provides a comprehensive introduction to this field for the non-technical reader. Important areas covered are: (1) definitions, (2) the brain and thinking, (3) heuristic search, and (4) programing languages used in the research of artificial intelligence. Some…

  13. The language of artificial intelligence

    SciTech Connect

    Berk, A.A.

    1984-01-01

    This is a guide to LISP. It clarifies data structures and recursion via examples and practical explanations, uses BASIC as a reference point throughout (enabling comparisons with LISP), and stresses artificial intelligence applications. Contents: Introduction to Artificial Intelligence. The Fundamentals of LISP. Functions. Conditionals and Loops. Further LISP Processing. Recursion. More Advanced Uses of Functions. LISP Programming and AI. Standard LISP Functions.

  14. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Waltz, David L.

    1982-01-01

    Describes kinds of results achieved by computer programs in artificial intelligence. Topics discussed include heuristic searches, artificial intelligence/psychology, planning program, backward chaining, learning (focusing on Winograd's blocks to explore learning strategies), concept learning, constraint propagation, language understanding…

  15. Collective-Intelligence Recommender Systems: Advancing Computer Tailoring for Health Behavior Change Into the 21st Century

    PubMed Central

    Cutrona, Sarah L; Kinney, Rebecca L; Marlin, Benjamin M; Mazor, Kathleen M; Lemon, Stephenie C; Houston, Thomas K

    2016-01-01

    Background What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based CTHC with empirical recommender systems could be evaluated as the next frontier for CTHC. Objective The objective of our study was to uncover barriers and challenges to using recommender systems in health promotion. Methods We conducted a focused literature review, interviewed subject experts (n=8), and synthesized the results. Results We describe (1) limitations of current CTHC systems, (2) advantages of incorporating recommender systems to move CTHC forward, and (3) challenges to incorporating recommender systems into CTHC. Based on the evidence presented, we propose a future research agenda for CTHC systems. Conclusions We promote discussion of ways to move CTHC into the 21st century by incorporation of recommender systems. PMID:26952574

  16. Competitive Intelligence.

    ERIC Educational Resources Information Center

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  17. Organisational Intelligence

    ERIC Educational Resources Information Center

    Yolles, Maurice

    2005-01-01

    Purpose: Seeks to explore the notion of organisational intelligence as a simple extension of the notion of the idea of collective intelligence. Design/methodology/approach: Discusses organisational intelligence using previous research, which includes the Purpose, Properties and Practice model of Dealtry, and the Viable Systems model. Findings: The…

  18. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Thornburg, David D.

    1986-01-01

    Overview of the artificial intelligence (AI) field provides a definition; discusses past research and areas of future research; describes the design, functions, and capabilities of expert systems and the "Turing Test" for machine intelligence; and lists additional sources for information on artificial intelligence. Languages of AI are also briefly…

  19. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  20. Recent advances on optical reflectometry for access network diagnostics and distributed sensing

    NASA Astrophysics Data System (ADS)

    He, Zuyuan; Fan, Xinyu; Liu, Qingwen; Du, Jiangbing

    2015-07-01

    In this invited talk, we will present the advances in research and development activities of optical reflectometry in our laboratory. The performance of phase-sensitive coherent OTDR, which is developed for distributed vibration measurement, is reported with the results of field tests. The performance of time-gated digital OFDR, which is developed for optical access network diagnostics, is also reported. We will also discuss how to increase the frequency sweep span of the linearly-swept optical source, a very important part for improving the performance of optical reflectometry.

  1. Resource Allocation and Power Management Schemes in an LTE-Advanced Femtocell Network

    NASA Astrophysics Data System (ADS)

    Lee, Byung-Bog; Yu, Jae-Hak; Lee, In-Hwan; Pyo, Cheol-Sig; Kim, Se-Jin

    In this letter, we introduce two different resource allocation and Tx power management schemes, called resource control and fixed power (RCFP) and fixed resource and power control (FRPC), in an LTE-Advanced femtocell network. We analyze and compare the two schemes in terms of the system throughput for downlink and energy consumption of home evolved NodeB (HeNB) Tx power according to the number of HeNBs and home user equipment (HUE)'s user traffic density (C). The simulation results show that the FRPC scheme has better performance in terms of system throughput for macro user equipments (MUEs) and energy consumption in low C.

  2. Intelligent Systems For Aerospace Engineering: An Overview

    NASA Technical Reports Server (NTRS)

    KrishnaKumar, K.

    2003-01-01

    Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

  3. Intelligent Systems for Aerospace Engineering: An Overview

    NASA Technical Reports Server (NTRS)

    Krishnakumar, Kalmanje; Clancey, Daniel (Technical Monitor)

    2002-01-01

    Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

  4. Advanced digital signal processing for short-haul and access network

    NASA Astrophysics Data System (ADS)

    Zhang, Junwen; Yu, Jianjun; Chi, Nan

    2016-02-01

    Digital signal processing (DSP) has been proved to be a successful technology recently in high speed and high spectrum-efficiency optical short-haul and access network, which enables high performances based on digital equalizations and compensations. In this paper, we investigate advanced DSP at the transmitter and receiver side for signal pre-equalization and post-equalization in an optical access network. A novel DSP-based digital and optical pre-equalization scheme has been proposed for bandwidth-limited high speed short-distance communication system, which is based on the feedback of receiver-side adaptive equalizers, such as least-mean-squares (LMS) algorithm and constant or multi-modulus algorithms (CMA, MMA). Based on this scheme, we experimentally demonstrate 400GE on a single optical carrier based on the highest ETDM 120-GBaud PDM-PAM-4 signal, using one external modulator and coherent detection. A line rate of 480-Gb/s is achieved, which enables 20% forward-error correction (FEC) overhead to keep the 400-Gb/s net information rate. The performance after fiber transmission shows large margin for both short range and metro/regional networks. We also extend the advanced DSP for short haul optical access networks by using high order QAMs. We propose and demonstrate a high speed multi-band CAP-WDM-PON system on intensity modulation, direct detection and digital equalizations. A hybrid modified cascaded MMA post-equalization schemes are used to equalize the multi-band CAP-mQAM signals. Using this scheme, we successfully demonstrates 550Gb/s high capacity WDMPON system with 11 WDM channels, 55 sub-bands, and 10-Gb/s per user in the downstream over 40-km SMF.

  5. Facilitating career advancement for women in the Geosciences through the Earth Science Women's Network (ESWN)

    NASA Astrophysics Data System (ADS)

    Hastings, M. G.; Kontak, R.; Holloway, T.; Kogan, M.; Laursen, S. L.; Marin-Spiotta, E.; Steiner, A. L.; Wiedinmyer, C.

    2011-12-01

    The Earth Science Women's Network (ESWN) is a network of women geoscientists, many of who are in the early stages of their careers. The mission of ESWN is to promote career development, build community, provide informal mentoring and support, and facilitate professional collaborations, all towards making women successful in their scientific careers. ESWN currently connects over 1000 women across the globe, and includes graduate students, postdoctoral associates, faculty from a diversity of colleges and universities, program managers, and government, non-government and industry researchers. ESWN facilitates communication between its members via an email listserv and in-person networking events, and also provides resources to the broader community through the public Earth Science Jobs Listserv that hosts over 1800 subscribers. With funding from a NSF ADVANCE PAID grant, our primary goals include growing our membership to serve a wider section of the geosciences community, designing and administering career development workshops, promoting professional networking at major scientific conferences, and developing web resources to build connections, collaborations, and peer mentoring for and among women in the Earth Sciences. Recognizing that women in particular face a number of direct and indirect biases while navigating their careers, we aim to provide a range of opportunities for professional development that emphasize different skills at different stages of career. For example, ESWN-hosted mini-workshops at national scientific conferences have targeted skill building for early career researchers (e.g., postdocs, tenure-track faculty), with a recent focus on raising extramural research funding and best practices for publishing in the geosciences literature. More concentrated, multi-day professional development workshops are offered annually with varying themes such as Defining Your Research Identity and Building Leadership Skills for Success in Scientific Organizations

  6. Building a Governance Strategy for CER: The Patient Outcomes Research to Advance Learning (PORTAL) Network Experience

    PubMed Central

    Paolino, Andrea R.; McGlynn, Elizabeth A.; Lieu, Tracy; Nelson, Andrew F.; Prausnitz, Stephanie; Horberg, Michael A.; Arterburn, David E.; Gould, Michael K.; Laws, Reesa L.; Steiner, John F.

    2016-01-01

    Introduction: The Patient Outcomes Research to Advance Learning (PORTAL) Network was established with funding from the Patient-Centered Outcomes Research Institute (PCORI) in 2014. The PORTAL team adapted governance structures and processes from past research network collaborations. We will review and outline the structures and processes of the PORTAL governance approach and describe how proactively focusing on priority areas helped us to facilitate an ambitious research agenda. Background: For years a variety of funders have supported large-scale infrastructure grants to promote the use of clinical datasets to answer important comparative effectiveness research (CER) questions. These awards have provided the impetus for health care systems to join forces in creating clinical data research networks. Often, these scientific networks do not develop governance processes proactively or systematically, and address issues only as problems arise. Even if network leaders and collaborators foresee the need to develop governance approaches, they may underestimate the time and effort required to develop sound processes. The resulting delays can impede research progress. Innovation: Because the PORTAL sites had built trust and a foundation of collaboration by participating with one another in past research networks, essential elements of effective governance such as guiding principles, decision making processes, project governance, data governance, and stakeholders in governance were familiar to PORTAL investigators. This trust and familiarity enabled the network to rapidly prioritize areas that required sound governance approaches: responding to new research opportunities, creating a culture of trust and collaboration, conducting individual studies, within the broader network, assigning responsibility and credit to scientific investigators, sharing data while protecting privacy/security, and allocating resources. The PORTAL Governance Document, complete with a Toolkit of

  7. Latest developments in advanced network management and cross-sharing of next-generation flux stations

    NASA Astrophysics Data System (ADS)

    Burba, George; Johnson, Dave; Velgersdyk, Michael; Begashaw, Israel; Allyn, Douglas

    2016-04-01

    In recent years, spatial and temporal flux data coverage improved significantly and on multiple scales, from a single station to continental networks, due to standardization, automation, and management of the data collection, and better handling of the extensive amounts of generated data. However, operating budgets for flux research items, such as labor, travel, and hardware, are becoming more difficult to acquire and sustain. With more stations and networks, larger data flows from each station, and smaller operating budgets, modern tools are required to effectively and efficiently handle the entire process, including sharing data among collaborative groups. On one hand, such tools can maximize time dedicated to publications answering research questions, and minimize time and expenses spent on data acquisition, processing, quality control and overall station management. On the other hand, cross-sharing the stations with external collaborators may help leverage available funding, and promote data analyses and publications. A new low-cost, advanced system, FluxSuite, utilizes a combination of hardware, software and web-services to address these specific demands. It automates key stages of flux workflow, minimizes day-to-day site management, and modernizes the handling of data flows: (i) The system can be easily incorporated into a new flux station, or as un upgrade to many presently operating flux stations, via weatherized remotely-accessible microcomputer, SmartFlux 2, with fully digital inputs (ii) Each next-generation station will measure all parameters needed for flux computations in a digital and PTP time-synchronized mode, accepting digital signals from a number of anemometers and data loggers (iii) The field microcomputer will calculate final fully-processed flux rates in real time, including computation-intensive Fourier transforms, spectra, co-spectra, multiple rotations, stationarity, footprint, etc. (iv) Final fluxes, radiation, weather and soil data will

  8. Neuroanatomical Correlates of Intelligence

    ERIC Educational Resources Information Center

    Luders, Eileen; Narr, Katherine L.; Thompson, Paul M.; Toga, Arthur W.

    2009-01-01

    With the advancement of image acquisition and analysis methods in recent decades, unique opportunities have emerged to study the neuroanatomical correlates of intelligence. Traditional approaches examining global measures have been complemented by insights from more regional analyses based on pre-defined areas. Newer state-of-the-art approaches…

  9. Artificial intelligence. Second edition

    SciTech Connect

    Winston, P.H.

    1984-01-01

    This book introduces the basic concepts of the field of artificial intelligence. It contains material covering the latest advances in control, representation, language, vision, and problem solving. Problem solving in design and analysis systems is addressed. Mitcell's version-space learning procedure, Morevec's reduced-images stereo procedure, and the Strips problem solver are covered.

  10. Experimental demonstration of large capacity WSDM optical access network with multicore fibers and advanced modulation formats.

    PubMed

    Li, Borui; Feng, Zhenhua; Tang, Ming; Xu, Zhilin; Fu, Songnian; Wu, Qiong; Deng, Lei; Tong, Weijun; Liu, Shuang; Shum, Perry Ping

    2015-05-01

    Towards the next generation optical access network supporting large capacity data transmission to enormous number of users covering a wider area, we proposed a hybrid wavelength-space division multiplexing (WSDM) optical access network architecture utilizing multicore fibers with advanced modulation formats. As a proof of concept, we experimentally demonstrated a WSDM optical access network with duplex transmission using our developed and fabricated multicore (7-core) fibers with 58.7km distance. As a cost-effective modulation scheme for access network, the optical OFDM-QPSK signal has been intensity modulated on the downstream transmission in the optical line terminal (OLT) and it was directly detected in the optical network unit (ONU) after MCF transmission. 10 wavelengths with 25GHz channel spacing from an optical comb generator are employed and each wavelength is loaded with 5Gb/s OFDM-QPSK signal. After amplification, power splitting, and fan-in multiplexer, 10-wavelength downstream signal was injected into six outer layer cores simultaneously and the aggregation downstream capacity reaches 300 Gb/s. -16 dBm sensitivity has been achieved for 3.8 × 10-3 bit error ratio (BER) with 7% Forward Error Correction (FEC) limit for all wavelengths in every core. Upstream signal from ONU side has also been generated and the bidirectional transmission in the same core causes negligible performance degradation to the downstream signal. As a universal platform for wired/wireless data access, our proposed architecture provides additional dimension for high speed mobile signal transmission and we hence demonstrated an upstream delivery of 20Gb/s per wavelength with QPSK modulation formats using the inner core of MCF emulating a mobile backhaul service. The IQ modulated data was coherently detected in the OLT side. -19 dBm sensitivity has been achieved under the FEC limit and more than 18 dB power budget is guaranteed.

  11. Enhancing nuclear power plant performance through the use of artificial intelligence. Final (third annual) report, June 1, 1990--March 31, 1992: Part 1, Overview and publications

    SciTech Connect

    Maren, A.J.; Miller, L.F.; Tsoukalas, L.H.; Uhrig, R.E.; Upadhyaya, B.R.

    1992-03-31

    The objective of this research was to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important objective, was to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants.

  12. Research on Intelligent Synthesis Environments

    NASA Technical Reports Server (NTRS)

    Noor, Ahmed K.; Lobeck, William E.

    2002-01-01

    Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

  13. Research on Intelligent Synthesis Environments

    NASA Astrophysics Data System (ADS)

    Noor, Ahmed K.; Loftin, R. Bowen

    2002-12-01

    Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

  14. Design of AN Intelligent Individual Evacuation Model for High Rise Building Fires Based on Neural Network Within the Scope of 3d GIS

    NASA Astrophysics Data System (ADS)

    Atila, U.; Karas, I. R.; Turan, M. K.; Rahman, A. A.

    2013-09-01

    One of the most dangerous disaster threatening the high rise and complex buildings of today's world including thousands of occupants inside is fire with no doubt. When we consider high population and the complexity of such buildings it is clear to see that performing a rapid and safe evacuation seems hard and human being does not have good memories in case of such disasters like world trade center 9/11. Therefore, it is very important to design knowledge based realtime interactive evacuation methods instead of classical strategies which lack of flexibility. This paper presents a 3D-GIS implementation which simulates the behaviour of an intelligent indoor pedestrian navigation model proposed for a self -evacuation of a person in case of fire. The model is based on Multilayer Perceptron (MLP) which is one of the most preferred artificial neural network architecture in classification and prediction problems. A sample fire scenario following through predefined instructions has been performed on 3D model of the Corporation Complex in Putrajaya (Malaysia) and the intelligent evacuation process has been realized within a proposed 3D-GIS based simulation.

  15. Intelligent route surveillance

    NASA Astrophysics Data System (ADS)

    Schoemaker, Robin; Sandbrink, Rody; van Voorthuijsen, Graeme

    2009-05-01

    Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent ground sensor networks use simple sensing nodes, e.g. seismic, magnetic, radar, or acoustic, or combinations of these in one housing. The nodes deliver rudimentary data at any time to be processed with software that filters out the required information. At TNO (Netherlands Organisation for Applied Scientific Research) research has started on how to equip a sensor network with data analysis software to determine whether behaviour is suspicious or not. Furthermore, the nodes should be expendable, if necessary, and be small in size such that they are hard to detect by adversaries. The network should be self-configuring and self-sustaining and should be reliable, efficient, and effective during operational tasks - especially route surveillance - as well as robust in time and space. If data from these networks are combined with data from other remote sensing devices (e.g. UAVs (Unmanned Aerial Vehicles)/aerostats), an even more accurate assessment of the tactical situation is possible. This paper shall focus on the concepts of operation towards a working intelligent route surveillance (IRS) research demonstrator network for monitoring suspicious behaviour in IED sensitive domains.

  16. Learning for intelligent mobile robots

    NASA Astrophysics Data System (ADS)

    Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

    2003-10-01

    Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A

  17. Reconfigurable Robust Routing for Mobile Outreach Network

    NASA Technical Reports Server (NTRS)

    Lin, Ching-Fang

    2010-01-01

    The Reconfigurable Robust Routing for Mobile Outreach Network (R3MOO N) provides advanced communications networking technologies suitable for the lunar surface environment and applications. The R3MOON techn ology is based on a detailed concept of operations tailored for luna r surface networks, and includes intelligent routing algorithms and wireless mesh network implementation on AGNC's Coremicro Robots. The product's features include an integrated communication solution inco rporating energy efficiency and disruption-tolerance in a mobile ad h oc network, and a real-time control module to provide researchers an d engineers a convenient tool for reconfiguration, investigation, an d management.

  18. Bio-Intelligence: A Research Program Facilitating the Development of New Paradigms for Tomorrow's Patient Care

    NASA Astrophysics Data System (ADS)

    Phan, Sieu; Famili, Fazel; Liu, Ziying; Peña-Castillo, Lourdes

    The advancement of omics technologies in concert with the enabling information technology development has accelerated biological research to a new realm in a blazing speed and sophistication. The limited single gene assay to the high throughput microarray assay and the laborious manual count of base-pairs to the robotic assisted machinery in genome sequencing are two examples to name. Yet even more sophisticated, the recent development in literature mining and artificial intelligence has allowed researchers to construct complex gene networks unraveling many formidable biological puzzles. To harness these emerging technologies to their full potential to medical applications, the Bio-intelligence program at the Institute for Information Technology, National Research Council Canada, aims to develop and exploit artificial intelligence and bioinformatics technologies to facilitate the development of intelligent decision support tools and systems to improve patient care - for early detection, accurate diagnosis/prognosis of disease, and better personalized therapeutic management.

  19. International Workshop on Intelligent Materials, Tsukuba, Japan, Mar. 15-17, 1989, Proceedings

    NASA Astrophysics Data System (ADS)

    The present conference discusses the trend toward smart-materials development in the formulation of advanced metallic substances, the biomimetic processing of ceramics and composites, the biochemistry and pharmacology of intelligent materials, the design of molecular assemblies to attain intelligent materials, a structured neural network for connectionist intelligent systems, artificial extracellular metrices for guiding nerve fiber growth direction, and the structural design of biomimetic composites. Also discussed are design criteria for organic and polymeric intelligent materials, the control of a two-dimensional protein molecule array for bioelectronics, the electronic modulation of biomaterial functions, the biomimetic approaches to the design of materials for artificial tactile perception, and mechanochemical devices using polymer gels, and integrated micromotion systems.

  20. The prediction of the building precision in the Laser Engineered Net Shaping process using advanced networks

    NASA Astrophysics Data System (ADS)

    Lu, Z. L.; Li, D. C.; Lu, B. H.; Zhang, A. F.; Zhu, G. X.; Pi, G.

    2010-05-01

    Laser Engineered Net Shaping (LENS) is an advanced manufacturing technology, but it is difficult to control the depositing height (DH) of the prototype because there are many technology parameters influencing the forming process. The effect of main parameters (laser power, scanning speed and powder feeding rate) on the DH of single track is firstly analyzed, and then it shows that there is the complex nonlinear intrinsic relationship between them. In order to predict the DH, the back propagation (BP) based network improved with Adaptive learning rate and Momentum coefficient (AM) algorithm, and the least square support vector machine (LS-SVM) network are both adopted. The mapping relationship between above parameters and the DH is constructed according to training samples collected by LENS experiments, and then their generalization ability, function-approximating ability and real-time are contrastively investigated. The results show that although the predicted result by the BP-AM approximates the experimental result, above performance index of the LS-SVM are better than those of the BP-AM. Finally, high-definition thin-walled parts of AISI316L are successfully fabricated. Hence, the LS-SVM network is more suitable for the prediction of the DH.

  1. A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

    NASA Astrophysics Data System (ADS)

    Yang, Wei; Hall, Trevor J.

    2013-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

  2. An intelligent inter-domain routing scheme under the consideration of diffserv QoS and energy saving in multi-domain software-defined flexible optical networks

    NASA Astrophysics Data System (ADS)

    Zhao, Jijun; Li, Fengyun; Ren, Danping; Hu, Jinhua; Yao, Qiuyan; Li, Wei

    2016-05-01

    Large scale multi-domain software-defined optical networks (SDON) provisioning has become a key area with increased scalable bandwidth services across wider network regions. Although distributed schemes could achieve lightpath routing by the ergodic process of domain boundary nodes, it increases the complexity of the signaling procedure and deployment of the interface. Moreover, the physical impairments are always the main factor of the infrastructure layer in SDON, which affect the transmission quality of the signal. Meanwhile, with increasing energy consumption of the Internet, it is imperative to design energy-efficient networks. To address the above issues, in this paper, an intelligent inter-domain routing scheme, which is supported by hierarchical control plane architecture, is presented based on sub-topology graph under the consideration of diffserv quality-of-service (QoS) and energy saving. The proposed scheme could achieve multi-domain quality of transmission (QoT), energy aware routing and spectrum assignment (RSA). We explore the scenarios where the multi-domain SDON achieve energy efficiency on the basis of meeting the QoT requirement. The blocking, energy consumption and average set up delay performances of the proposed schemes are estimated. The results indicate that the introduction of sub-topology in multi-domain RSA scheme has the better performance comparing with the distributed scheme.

  3. The Evolution of Technology in the Deep Space Network: A History of the Advanced Systems Program

    NASA Technical Reports Server (NTRS)

    Layland, J. W.; Rauch, L. L.

    1994-01-01

    The Deep Space Network (DSN) of 1995 might be described as the evolutionary result of 45 years of deep space communication and navigation, together with the synergistic activities of radio science and radar and radio astronomy. But the evolution of the DSN did not just happen - it was carefully planned and created. The evolution of the DSN has been an ongoing engineering activity, and engineering is a process of problem solving under constraints, one of which is technology. In turn, technology is the knowledge base providing the capability and experience for practical application of various areas of science, when needed. The best engineering solutions result from optimization under the fewest constraints, and if technology needs are well anticipated (ready when needed), then the most effective engineering solution is possible. Throughout the history of the DSN it has been the goal and function of DSN advanced technology development (designated the DSN Advanced Systems Program from 1963 through 1994) to supply the technology needs of the DSN when needed, and thus to minimize this constraint on DSN engineering. Technology often takes considerable time to develop, and when that happens, it is important to have anticipated engineering needs; at times, this anticipation has been by as much as 15 years. Also, on a number of occasions, mission malfunctions or emergencies have resulted in unplanned needs for technology that has, in fact, been available from the reservoir of advanced technology provided by the DSN Advanced Systems Program. Sometimes, even DSN engineering personnel fail to realize that the organization of JPL permits an overlap of DSN advanced technology activities with subsequent engineering activities. This can result in the flow of advanced technology into DSN engineering in a natural and sometimes almost unnoticed way. In the following pages, we will explore some of the many contributions of the DSN Advanced Systems Program that were provided to DSN

  4. The Convergence of Intelligences

    NASA Astrophysics Data System (ADS)

    Diederich, Joachim

    Minsky (1985) argued an extraterrestrial intelligence may be similar to ours despite very different origins. ``Problem- solving'' offers evolutionary advantages and individuals who are part of a technical civilisation should have this capacity. On earth, the principles of problem-solving are the same for humans, some primates and machines based on Artificial Intelligence (AI) techniques. Intelligent systems use ``goals'' and ``sub-goals'' for problem-solving, with memories and representations of ``objects'' and ``sub-objects'' as well as knowledge of relations such as ``cause'' or ``difference.'' Some of these objects are generic and cannot easily be divided into parts. We must, therefore, assume that these objects and relations are universal, and a general property of intelligence. Minsky's arguments from 1985 are extended here. The last decade has seen the development of a general learning theory (``computational learning theory'' (CLT) or ``statistical learning theory'') which equally applies to humans, animals and machines. It is argued that basic learning laws will also apply to an evolved alien intelligence, and this includes limitations of what can be learned efficiently. An example from CLT is that the general learning problem for neural networks is intractable, i.e. it cannot be solved efficiently for all instances (it is ``NP-complete''). It is the objective of this paper to show that evolved intelligences will be constrained by general learning laws and will use task-decomposition for problem-solving. Since learning and problem-solving are core features of intelligence, it can be said that intelligences converge despite very different origins.

  5. Intelligent Elements for ISHM

    NASA Technical Reports Server (NTRS)

    Schmalzel, John L.; Morris, Jon; Turowski, Mark; Figueroa, Fernando; Oostdyk, Rebecca

    2008-01-01

    There are a number of architecture models for implementing Integrated Systems Health Management (ISHM) capabilities. For example, approaches based on the OSA-CBM and OSA-EAI models, or specific architectures developed in response to local needs. NASA s John C. Stennis Space Center (SSC) has developed one such version of an extensible architecture in support of rocket engine testing that integrates a palette of functions in order to achieve an ISHM capability. Among the functional capabilities that are supported by the framework are: prognostic models, anomaly detection, a data base of supporting health information, root cause analysis, intelligent elements, and integrated awareness. This paper focuses on the role that intelligent elements can play in ISHM architectures. We define an intelligent element as a smart element with sufficient computing capacity to support anomaly detection or other algorithms in support of ISHM functions. A smart element has the capabilities of supporting networked implementations of IEEE 1451.x smart sensor and actuator protocols. The ISHM group at SSC has been actively developing intelligent elements in conjunction with several partners at other Centers, universities, and companies as part of our ISHM approach for better supporting rocket engine testing. We have developed several implementations. Among the key features for these intelligent sensors is support for IEEE 1451.1 and incorporation of a suite of algorithms for determination of sensor health. Regardless of the potential advantages that can be achieved using intelligent sensors, existing large-scale systems are still based on conventional sensors and data acquisition systems. In order to bring the benefits of intelligent sensors to these environments, we have also developed virtual implementations of intelligent sensors.

  6. Advanced topics in character recongition and document analysis: research works in intelligent image and document research lab, Tsinghua University

    NASA Astrophysics Data System (ADS)

    Ding, Xiaoqing

    2009-01-01

    Character Recognition and Document Retrieval still are very interesting research area although great progress in performance has been made over the last decades. Advanced research topics in character recognition and Document analysis are introduced in this paper, which include the further research in Tsinghai University on handwritten Chinese character recognition, multilingual character recognition and writer identification. In handwritten Chinese character recognition a special cascade MQDF classifier is discussed for unconstrained cursive handwritten Chinese Character recognition and an optimum handwritten strip recognition algorithm is introduced. In writer identification content dependent and content independent algorithms are discussed. In multilingual character recognition a THOCR multilingual, including Japanese, Korean, Tibetan, Mongolian, Uyghur, Arabic document recognition system is introduced in this paper.

  7. Plant intelligence.

    PubMed

    Trewavas, Anthony

    2005-09-01

    Intelligent behavior is a complex adaptive phenomenon that has evolved to enable organisms to deal with variable environmental circumstances. Maximizing fitness requires skill in foraging for necessary resources (food) in competitive circumstances and is probably the activity in which intelligent behavior is most easily seen. Biologists suggest that intelligence encompasses the characteristics of detailed sensory perception, information processing, learning, memory, choice, optimisation of resource sequestration with minimal outlay, self-recognition, and foresight by predictive modeling. All these properties are concerned with a capacity for problem solving in recurrent and novel situations. Here I review the evidence that individual plant species exhibit all of these intelligent behavioral capabilities but do so through phenotypic plasticity, not movement. Furthermore it is in the competitive foraging for resources that most of these intelligent attributes have been detected. Plants should therefore be regarded as prototypical intelligent organisms, a concept that has considerable consequences for investigations of whole plant communication, computation and signal transduction.

  8. Amplify scientific discovery with artificial intelligence

    SciTech Connect

    Gil, Yolanda; Greaves, Mark T.; Hendler, James; Hirsch, Hyam

    2014-10-10

    Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automated language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.

  9. Method for detection and reconstruction of gravitational wave transients with networks of advanced detectors

    NASA Astrophysics Data System (ADS)

    Klimenko, S.; Vedovato, G.; Drago, M.; Salemi, F.; Tiwari, V.; Prodi, G. A.; Lazzaro, C.; Ackley, K.; Tiwari, S.; Da Silva, C. F.; Mitselmakher, G.

    2016-02-01

    We present a method for detection and reconstruction of the gravitational wave (GW) transients with the networks of advanced detectors. Originally designed to search for transients with the initial GW detectors, it uses significantly improved algorithms, which enhance both the low-latency searches with rapid localization of GW events for the electromagnetic follow-up and high confidence detection of a broad range of the transient GW sources. In this paper, we present the analytic framework of the method. Following a short description of the core analysis algorithms, we introduce a novel approach to the reconstruction of the GW polarization from a pattern of detector responses to a GW signal. This polarization pattern is a unique signature of an arbitrary GW signal that can be measured independently from the other source parameters. The polarization measurements enable rapid reconstruction of the GW waveforms, sky localization, and helps identification of the source origin.

  10. Perspectives on Advanced Learning Technologies and Learning Networks and Future Aerospace Workforce Environments

    NASA Technical Reports Server (NTRS)

    Noor, Ahmed K. (Compiler)

    2003-01-01

    An overview of the advanced learning technologies is given in this presentation along with a brief description of their impact on future aerospace workforce development. The presentation is divided into five parts (see Figure 1). In the first part, a brief historical account of the evolution of learning technologies is given. The second part describes the current learning activities. The third part describes some of the future aerospace systems, as examples of high-tech engineering systems, and lists their enabling technologies. The fourth part focuses on future aerospace research, learning and design environments. The fifth part lists the objectives of the workshop and some of the sources of information on learning technologies and learning networks.

  11. Recent advances on techniques and theories of feedforward networks with supervised learning

    NASA Astrophysics Data System (ADS)

    Xu, Lei; Klasa, Stan

    1992-07-01

    The rediscovery and popularization of the back propagation training technique for multilayer perceptrons as well as the invention of the Boltzmann Machine learning algorithm has given a new boost to the study of supervised learning networks. In recent years, besides the widely spread applications and the various further improvements of the classical back propagation technique, many new supervised learning models, techniques as well as theories, have also been proposed in a vast number of publications. This paper tries to give a rather systematical review on the recent advances on supervised learning techniques and theories for static feedforward networks. We summarize a great number of developments into four aspects: (1) Various improvements and variants made on the classical back propagation techniques for multilayer (static) perceptron nets, for speeding up training, avoiding local minima, increasing the generalization ability, as well as for many other interesting purposes. (2) A number of other learning methods for training multilayer (static) perceptron, such as derivative estimation by perturbation, direct weight update by perturbation, genetic algorithms, recursive least square estimate and extended Kalman filter, linear programming, the policy of fixing one layer while updating another, constructing networks by converting decision tree classifiers, and others. (3) Various other feedforward models which are also able to implement function approximation, probability density estimation and classification, including various models of basis function expansion (e.g., radial basis functions, restricted coulomb energy, multivariate adaptive regression splines, trigonometric and polynomial bases, projection pursuit, basis function tree, and may others), and several other supervised learning models. (4) Models with complex structures, e.g., modular architecture, hierarchy architecture, and others. (5) A number of theoretical issues involving the universal

  12. NASA/ARC proposed training in intelligent control

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1990-01-01

    Viewgraphs on NASA Ames Research Center proposed training in intelligent control was presented. Topics covered include: fuzzy logic control; neural networks in control; artificial intelligence in control; hybrid approaches; hands on experience; and fuzzy controllers.

  13. Comparison of Advection–Diffusion Models and Neural Networks for Prediction of Advanced Water Treatment Effluent

    PubMed Central

    Mortula, Mohammed Maruf; Abdalla, Jamal; Ghadban, Ahmad A.

    2012-01-01

    Abstract An artificial neural network (ANN) can help in the prediction of advanced water treatment effluent and thus facilitate design practices. In this study, sets of 225 experimental data were obtained from a wastewater treatment process for the removal of phosphorus using oven-dried alum residuals in fixed-bed adsorbers. Five input variables (pH, initial phosphorus concentration, wastewater flow rate, porosity, and time) were used to test the efficiency of phosphorus removal at different times, and ANNs were then used to predict the effluent phosphorus concentration. Results of experiments that were conducted for different values of the input parameters made up the data used to train and test a multilayer perceptron using the back-propagation algorithm of the ANN. Values predicted by the ANN and the experimentally measured values were compared, and the accuracy of the ANN was evaluated. When ANN results were compared to the experimental results, it was concluded that the ANN results were accurate, especially during conditions of high phosphorus concentration. While the ANN model was able to predict the breakthrough point with good accuracy, the conventional advection–diffusion equation was not as accurate. A parametric study conducted to examine the effect of the initial pH and initial phosphorus concentration on the effluent phosphorus concentration at different times showed that lower influent pH values are the most suitable for this advanced treatment system. PMID:22783063

  14. Modeling, Simulation and Analysis of Complex Networked Systems: A Program Plan for DOE Office of Advanced Scientific Computing Research

    SciTech Connect

    Brown, D L

    2009-05-01

    Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex networked systems

  15. Optimized intelligent control of a 2-degree of freedom robot for rehabilitation of lower limbs using neural network and genetic algorithm

    PubMed Central

    2013-01-01

    Background There is an increasing trend in using robots for medical purposes. One specific area is rehabilitation. Rehabilitation is one of the non-drug treatments in community health which means the restoration of the abilities to maximize independence. It is a prolonged work and costly labor. On the other hand, by using the flexible and efficient robots in rehabilitation area, this process will be more useful for handicapped patients. Methods In this study, a rule-based intelligent control methodology is proposed to mimic the behavior of a healthy limb in a satisfactory way by a 2-DOF planar robot. Inverse kinematic of the planar robot will be solved by neural networks and control parameters will be optimized by genetic algorithm, as rehabilitation progress. Results The results of simulations are presented by defining a physiotherapy simple mode on desired trajectory. MATLAB/Simulink is used for simulations. The system is capable of learning the action of the physiotherapist for each patient and imitating this behaviour in the absence of a physiotherapist that can be called robotherapy. Conclusions In this study, a therapeutic exercise planar 2-DOF robot is designed and controlled for lower-limb rehabilitation. The robot manipulator is controlled by combination of hybrid and adaptive controls. Some safety factors and stability constraints are defined and obtained. The robot is stopped when the safety factors are not satisfied. Kinematics of robot is estimated by an MLP neural network and proper control parameters are achieved using GA optimization. PMID:23945420

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  17. An intelligent robotic aid system for human services

    NASA Technical Reports Server (NTRS)

    Kawamura, K.; Bagchi, S.; Iskarous, M.; Pack, R. T.; Saad, A.

    1994-01-01

    The long term goal of our research at the Intelligent Robotic Laboratory at Vanderbilt University is to develop advanced intelligent robotic aid systems for human services. As a first step toward our goal, the current thrusts of our R&D are centered on the development of an intelligent robotic aid called the ISAC (Intelligent Soft Arm Control). In this paper, we describe the overall system architecture and current activities in intelligent control, adaptive/interactive control and task learning.

  18. Making the Net More Intelligent.

    ERIC Educational Resources Information Center

    Somers, Doug

    1998-01-01

    Discusses how service providers can address the challenge of costs and the need for attractive services valuable to business customers. Focuses on Internet service control; applying intelligent networking features to the internet working services dilemma; and providing access control over network-based applications for Internet virtual private…

  19. Artificial intelligence

    SciTech Connect

    Firschein, O.

    1984-01-01

    This book presents papers on artificial intelligence. Topics considered include knowledge engineering, expert systems, applications of artificial intelligence to scientific reasoning, planning and problem solving, error recovery in robots through failure reason analysis, programming languages, natural language, speech recognition, map-guided interpretation of remotely-sensed imagery, and image understanding architectures.

  20. Moving from a static to a dynamic optical network: how carriers benefit from next-generation intelligent optical engines

    NASA Astrophysics Data System (ADS)

    MacDonald, Robert; Facca, Horacio

    2001-07-01

    Today's local, inter-exchange, and transnational carriers are caught in an unfortunate predicament. On one hand, they need to reduce customer churn while meeting their clients' growing bandwidth and service provisioning needs and defending against competitive pressures from other carriers. This is driving service providers to make continued improvements and investments in their optical network infrastructure. For most carriers, there is a clear recognition that the path to business success requires a migration from a 'static' optical network to a 'dynamic' optical network, one that facilitates system design and service provisioning. On the other hand, carriers are under extreme pressure to manage down capital expenditures and improve network-operating efficiencies (reducing expenses) resulting in improved balance sheet, income and cash flow statements. This paper will review the provisioning issues and constraints associated with static networks and the benefits, both economic and process, gained by migrating to a dynamic network. The key objective is to describe several currently available and practical methods to dynamically deploy, provision and manage optical services using 'keystrokes, instead of truck rolls'.

  1. Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

    PubMed

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2013-07-01

    Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective.

  2. Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

    PubMed

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2013-07-01

    Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. PMID:23668338

  3. Intelligent Potroom Operation

    SciTech Connect

    Jan Berkow; Larry Banta

    2003-07-29

    The Intelligent Potroom Operation project focuses on maximizing the performance of an aluminum smelter by innovating components for an intelligent manufacturing system. The Intelligent Potroom Advisor (IPA) monitors process data to identify reduction cells exhibiting behaviors that require immediate attention. It then advises operational personnel on those heuristic-based actions to bring the cell back to an optimal operating state in order to reduce the duration and frequency of substandard reduction cell performance referred to as ''Off-Peak Modes'' (OPMs). Techniques developed to identify cells exhibiting OPMs include the use of a finite element model-based cell state estimator for defining the cell's current operating state via advanced cell noise analyses. In addition, rule induction was also employed to identify statistically significant complex behaviors that occur prior to OPMs. The intelligent manufacturing system design, concepts and formalisms developed in this project w ere used as a basis for an intelligent manufacturing system design. Future research will incorporate an adaptive component to automate continuous process improvement, a technology platform with the potential to improve process performance in many of the other Industries of the Future applications as well.

  4. Mental, neuropsychic, and brain patterns of defense. Neuropsychic defense continua from psychopathology to the particularly human parallel networks that are problematic for artificial intelligence.

    PubMed

    Forrest, D V

    1991-01-01

    The synthesis of psychodynamic and neuroscientific data may be advanced by the study of similarly configured specific patterns of defense along continua from the normal and neurotic mental mechanisms of defenses, through what might be termed neuropsychiatric defenses influenced by the neurological state, to the more clearly neurological cortical reactions. These similar patterns and continua are the particularly human way brain adds its flavor of organism to mind, and the way in which all the psychodynamic mechanisms are specifically imbedded in brain. A purely psychological psychodynamics lacking this medical perspective fails to model human mental processes and reflects problems with artificial intelligence models that do not model brain. The pathological reactions that we address in psychiatry and neuropsychiatry interfere with and thereby reveal parallel processing features in (1) analogical and metaphorical thinking; (2) reduplication, redundancy, and repetitiveness; (3) self, person, and environmental recognition, including transference processes; (4) approximation and statistical inference; (5) spatiality and motor control; (6) affectivity, perception of sensations and sexuality; (7) projective mechanisms; and (8) problem solving by optimization, vectorial summation, and the mutual interaction of interconnected agencies. The new concepts in artificial intelligence built upon brainlike structures called neural nets portend great economies, emergent natural features that are more like human processes, and hierarchical and cyclic organizational demands. Medical psychoanalysts who comprehend dynamic and brain mechanisms and can describe them in terms that refer to both domains and their interaction should find increasing theoretical and practical convergence of their work with the emerging study and modeling of these processes by new forms of computers.

  5. Creative-Dynamics Approach To Neural Intelligence

    NASA Technical Reports Server (NTRS)

    Zak, Michail A.

    1992-01-01

    Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

  6. More About Architecture For Intelligent Robotic Control

    NASA Technical Reports Server (NTRS)

    Fiorini, Paolo; Chang, Jeffrey

    1992-01-01

    Boolean neural networks proposed to implement part of intermediate level of hierarchical architecture of control system for artificially intelligent control of robot hand. Concept described in "Architecture for Intelligent Control of Robotic Tasks" (NPO-17871). Rule level of architecture implemented in two Boolean neural networks operated and updated in alternation. No explicit programming of network. Internal configuration not unique but, depends on initial state and history of previous adaptations. Accepts new rules sequentially presented by external controller.

  7. Sandia`s research network for Supercomputing `93: A demonstration of advanced technologies for building high-performance networks

    SciTech Connect

    Gossage, S.A.; Vahle, M.O.

    1993-12-01

    Supercomputing `93, a high-performance computing and communications conference, was held November 15th through 19th, 1993 in Portland, Oregon. For the past two years, Sandia National Laboratories has used this conference to showcase and focus its communications and networking endeavors. At the 1993 conference, the results of Sandia`s efforts in exploring and utilizing Asynchronous Transfer Mode (ATM) and Synchronous Optical Network (SONET) technologies were vividly demonstrated by building and operating three distinct networks. The networks encompassed a Switched Multimegabit Data Service (SMDS) network running at 44.736 megabits per second, an ATM network running on a SONET circuit at the Optical Carrier (OC) rate of 155.52 megabits per second, and a High Performance Parallel Interface (HIPPI) network running over a 622.08 megabits per second SONET circuit. The SMDS and ATM networks extended from Albuquerque, New Mexico to the showroom floor, while the HIPPI/SONET network extended from Beaverton, Oregon to the showroom floor. This paper documents and describes these networks.

  8. A Collaborative Education Network for Advancing Climate Literacy using Data Visualization Technology

    NASA Astrophysics Data System (ADS)

    McDougall, C.; Russell, E. L.; Murray, M.; Bendel, W. B.

    2013-12-01

    among members, we have, collectively, been able to advance all of our efforts. The member institutions, through regular face-to-face workshops and an online community, share practices in creation and cataloging of datasets, new methods for delivering content via SOS, and updates on the SOS system and software. One hallmark of the SOS Users Collaborative Network is that it exemplifies an ideal partnership between federal science agencies and informal science education institutions. The science agencies (including NOAA, NASA, and the Department of Energy) provide continuously updated global datasets, scientific expertise, funding, and support. In turn, museums act as trusted public providers of scientific information, provide audience-appropriate presentations, localized relevance to global phenomena and a forum for discussing the complex science and repercussions of global change. We will discuss the characteristics of this Network that maximize collaboration and what we're learning as a community to improve climate literacy.

  9. An Intelligent Approach to Educational Data: Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks

    ERIC Educational Resources Information Center

    Kayri, Murat

    2015-01-01

    The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…

  10. Feasibility of a Networked Air Traffic Infrastructure Validation Environment for Advanced NextGen Concepts

    NASA Technical Reports Server (NTRS)

    McCormack, Michael J.; Gibson, Alec K.; Dennis, Noah E.; Underwood, Matthew C.; Miller,Lana B.; Ballin, Mark G.

    2013-01-01

    Abstract-Next Generation Air Transportation System (NextGen) applications reliant upon aircraft data links such as Automatic Dependent Surveillance-Broadcast (ADS-B) offer a sweeping modernization of the National Airspace System (NAS), but the aviation stakeholder community has not yet established a positive business case for equipage and message content standards remain in flux. It is necessary to transition promising Air Traffic Management (ATM) Concepts of Operations (ConOps) from simulation environments to full-scale flight tests in order to validate user benefits and solidify message standards. However, flight tests are prohibitively expensive and message standards for Commercial-off-the-Shelf (COTS) systems cannot support many advanced ConOps. It is therefore proposed to simulate future aircraft surveillance and communications equipage and employ an existing commercial data link to exchange data during dedicated flight tests. This capability, referred to as the Networked Air Traffic Infrastructure Validation Environment (NATIVE), would emulate aircraft data links such as ADS-B using in-flight Internet and easily-installed test equipment. By utilizing low-cost equipment that is easy to install and certify for testing, advanced ATM ConOps can be validated, message content standards can be solidified, and new standards can be established through full-scale flight trials without necessary or expensive equipage or extensive flight test preparation. This paper presents results of a feasibility study of the NATIVE concept. To determine requirements, six NATIVE design configurations were developed for two NASA ConOps that rely on ADS-B. The performance characteristics of three existing in-flight Internet services were investigated to determine whether performance is adequate to support the concept. Next, a study of requisite hardware and software was conducted to examine whether and how the NATIVE concept might be realized. Finally, to determine a business case

  11. Distributed Intelligence.

    ERIC Educational Resources Information Center

    McLagan, Patricia A.

    2003-01-01

    Distributed intelligence occurs when people in an organization take responsibility for creating innovations, solving problems, and making decisions. Organizations that have it excel in their markets and the global environment. (Author/JOW)

  12. Structure and weights optimisation of a modified Elman network emotion classifier using hybrid computational intelligence algorithms: a comparative study

    NASA Astrophysics Data System (ADS)

    Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood

    2015-10-01

    Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.

  13. Intelligent Foreign Particle Inspection Machine for Injection Liquid Examination Based on Modified Pulse-Coupled Neural Networks

    PubMed Central

    Ge, Ji; Wang, YaoNan; Zhou, BoWen; Zhang, Hui

    2009-01-01

    A biologically inspired spiking neural network model, called pulse-coupled neural networks (PCNN), has been applied in an automatic inspection machine to detect visible foreign particles intermingled in glucose or sodium chloride injection liquids. Proper mechanisms and improved spin/stop techniques are proposed to avoid the appearance of air bubbles, which increases the algorithms' complexity. Modified PCNN is adopted to segment the difference images, judging the existence of foreign particles according to the continuity and smoothness properties of their moving traces. Preliminarily experimental results indicate that the inspection machine can detect the visible foreign particles effectively and the detection speed, accuracy and correct detection rate also satisfying the needs of medicine preparation. PMID:22412318

  14. Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues

    PubMed Central

    Rassam, Murad A.; Zainal, Anazida; Maarof, Mohd Aizaini

    2013-01-01

    Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept “Internet of Things” has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed. PMID:23966182

  15. Evaluation drought response of tropical dry forests using advanced wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Sanchez-Azofeifa, G. A.

    2015-12-01

    Understanding of the effects of persistent drought in tropical dry forests has not been fully studied until today. In this presentation we will discuss one of the first results on the response of tropical dry forests to drought using advanced wireless sensor networks and canopy phenology towers, that provide hyper-temporal information on micro-meteorological variables such Temperature, relative humidity, and Vapor Pressure Deficit (VPD). In addition, we will evaluate drought response to as function of the Fraction of the Photosynthetic Active Radiation (FPAR), and the Normalized Difference Vegetation Index (NDVI). Our work is conducted at the Santa Rosa Environmental Monitoring Super Site (NR-EMSS) located at the Guancaste Province, Costa Rica, Central America. Our results indicate significant changes in terms of FPAR, VPD manifested via strong changes on NDVI. Our results pose questions about the resilience of these understudied tropical ecosystems and their long-term survival under severe and persistent drought conditions. This results provide a reference framework for the need of more integrated research on the Central American Dry Forest corridor where just between Costa Rica and Nicaragua over 100,000 families are facing strong drought conditions.

  16. Development of intelligent systems based on Bayesian regularization network and neuro-fuzzy models for mass detection in mammograms: A comparative analysis.

    PubMed

    Mahersia, Hela; Boulehmi, Hela; Hamrouni, Kamel

    2016-04-01

    Female breast cancer is the second most common cancer in the world. Several efforts in artificial intelligence have been made to help improving the diagnostic accuracy at earlier stages. However, the identification of breast abnormalities, like masses, on mammographic images is not a trivial task, especially for dense breasts. In this paper we describe our novel mass detection process that includes three successive steps of enhancement, characterization and classification. The proposed enhancement system is based mainly on the analysis of the breast texture. First of all, a filtering step with morphological operators and soft thresholding is achieved. Then, we remove from the filtered breast region, all the details that may interfere with the eventual masses, including pectoral muscle and galactophorous tree. The pixels belonging to this tree will be interpolated and replaced by the average of the neighborhood. In the characterization process, measurement of the Gaussian density in the wavelet domain allows the segmentation of the masses. Finally, a comparative classification mechanism based on the Bayesian regularization back-propagation networks and ANFIS techniques is proposed. The tests were conducted on the MIAS database. The results showed the robustness of the proposed enhancement method. PMID:26831269

  17. Artificial intelligence approach with the use of artificial neural networks for the creation of a forecasting model of Plasmopara viticola infection.

    PubMed

    Bugliosi, R; Spera, G; La Torre, A; Campoli, L; Scaglione, M

    2006-01-01

    Most of the forecasting models of Plasmopara viticola infections are based upon empiric correlations between meteorological/environmental data and pathogen outbreak. These models generally overestimate the risk of infections and induce to treat the vineyard even if it should be not necessary. In rare cases they underrate the risk of infection leaving the pathogen to breakout. Starting from these considerations we have decided to approach the problem from another point of view utilizing Artificial Intelligence techniques for data elaboration and analysis. Meanwhile the same data have been studied with a more classic approach with statistical tools to verify the impact of a large data collection on the standard data analysis methods. A network of RTUs (Remote Terminal Units) distributed all over the Italian national territory transmits 12 environmental parameters every 15 minutes via radio or via GPRS to a centralized Data Base. Other pedologic data is collected directly from the field and sent via Internet to the centralized data base utilizing Personal Digital Assistants (PDAs) running a specific software. Data is stored after having been preprocessed, to guarantee the quality of the information. The subsequent analysis has been realized mostly with Artificial Neural Networks (ANNs). Collecting and analizing data in this way will probably bring us to the possibility of preventing Plasmospara viticola infection starting from the environmental conditions in this very complex context. The aim of this work is to forecast the infection avoiding the ineffective use of the plant protection products in agriculture. Applying different analysis models we will try to find the best ANN capable of forecasting with an high level of affordability.

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

    PubMed

    Shahzad, Aamir; Lee, Malrey; Xiong, Neal Naixue; Jeong, Gisung; Lee, Young-Keun; Choi, Jae-Young; Mahesar, Abdul Wheed; Ahmad, Iftikhar

    2016-01-01

    In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interconnection (OSI) model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB) is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design. PMID:26950129

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

    PubMed Central

    Shahzad, Aamir; Lee, Malrey; Xiong, Neal Naixue; Jeong, Gisung; Lee, Young-Keun; Choi, Jae-Young; Mahesar, Abdul Wheed; Ahmad, Iftikhar

    2016-01-01

    In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interconnection (OSI) model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB) is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design. PMID:26950129

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

    PubMed

    Shahzad, Aamir; Lee, Malrey; Xiong, Neal Naixue; Jeong, Gisung; Lee, Young-Keun; Choi, Jae-Young; Mahesar, Abdul Wheed; Ahmad, Iftikhar

    2016-03-03

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

  1. Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

    NASA Technical Reports Server (NTRS)

    Broderick, Ron

    1997-01-01

    The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network

  2. Intelligent Systems Technologies and Utilization of Earth Observation Data

    NASA Technical Reports Server (NTRS)

    Ramapriyan, H. K.; McConaughy, G. R.; Morse, H. S.

    2004-01-01

    The addition of raw data and derived geophysical parameters from several Earth observing satellites over the last decade to the data held by NASA data centers has created a data rich environment for the Earth science research and applications communities. The data products are being distributed to a large and diverse community of users. Due to advances in computational hardware, networks and communications, information management and software technologies, significant progress has been made in the last decade in archiving and providing data to users. However, to realize the full potential of the growing data archives, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system (KBS). Potential Intelligent Archive concepts include: 1) Mining archived data holdings to improve metadata to facilitate data access and usability; 2) Building intelligence about transformations on data, information, knowledge, and accompanying services; 3) Recognizing the value of results, indexing and formatting them for easy access; 4) Interacting as a cooperative node in a web of distributed systems to perform knowledge building; and 5) Being aware of other nodes in the KBS, participating in open systems interfaces and protocols for virtualization, and achieving collaborative interoperability.

  3. An Experiential Approach to Cultural Intelligence Education

    ERIC Educational Resources Information Center

    MacNab, Brent R.

    2012-01-01

    Cultural intelligence (CQ) represents a promising advancement in the area of cross-cultural training and management. Experiential approaches for CQ development have been proposed as highly effective; however, there is a lack of CQ-specific approaches in the management literature. This work overviews the concept of cultural intelligence and its…

  4. Binet and the Nature of Intelligence Theory.

    ERIC Educational Resources Information Center

    Nash, Roy

    1987-01-01

    An argument that Binet must be regarded as a major theoretician of functional intelligence and should be considered for what is regarded as classical intelligence theory is advanced. A discourse on Binet's theory, its intellectual context and the developments it fostered is given. (JL)

  5. Security Aspects of Smart Cards vs. Embedded Security in Machine-to-Machine (M2M) Advanced Mobile Network Applications

    NASA Astrophysics Data System (ADS)

    Meyerstein, Mike; Cha, Inhyok; Shah, Yogendra

    The Third Generation Partnership Project (3GPP) standardisation group currently discusses advanced applications of mobile networks such as Machine-to-Machine (M2M) communication. Several security issues arise in these contexts which warrant a fresh look at mobile networks’ security foundations, resting on smart cards. This paper contributes a security/efficiency analysis to this discussion and highlights the role of trusted platform technology to approach these issues.

  6. Advanced Clinical Interpretation of the WAIS-IV and WMS-IV: Prevalence of Low Scores Varies by Level of Intelligence and Years of Education

    ERIC Educational Resources Information Center

    Brooks, Brian L.; Holdnack, James A.; Iverson, Grant L.

    2011-01-01

    Clinicians can use the base rates of low scores in healthy people to reduce the likelihood of misdiagnosing cognitive impairment. In the present study, base rates were developed for the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Memory Scale-Fourth Edition (WMS-IV) using 900 healthy adults and validated on 28 patients…

  7. Intelligence: Theories and Testing.

    ERIC Educational Resources Information Center

    Papanastasiou, Elena C.

    This paper reviews what is known about intelligence and the use of intelligence tests. Environmental and hereditary factors that affect performance on intelligence tests are reviewed, along with various theories that have been proposed about the basis of intelligence. Intelligence tests do not test intelligence per se but make inferences about a…

  8. Advanced controlling of anaerobic digestion by means of hierarchical neural networks.

    PubMed

    Holubar, Peter; Zani, Loredana; Hager, Michael; Fröschl, Walter; Radak, Zorana; Braun, Rudolf

    2002-05-01

    In this work several feed-forward back propagation neural networks (FFBP) were trained in order to model, and subsequently control, methane production in anaerobic digesters. To produce data for the training of the neural nets, four anaerobic continuous stirred tank reactors were operated in steady-state conditions at organic loading rates (Br) of about 2 kg m(-3) d(-1) chemical oxygen demand, and disturbed by pulse-like increase of the organic loading rate. For the pulses additional carbon sources like flour, sucrose, 1,2-diethylen glycol or vegetable oil were added to the basic feed, which consisted of surplus and primary sludge of a local waste-water treatment plant, to increase the chemical oxygen demand. Measured parameters were: gas composition, methane production rate, volatile fatty acid concentration, pH, redox potential, volatile suspended solids and chemical oxygen demand of feed and effluent. A hierarchical system of nets was developed and embedded in a decision support system to find out which is the best feeding profile for the next time steps in advance. A 3-3-1 FFBP simulated the pH with a regression coefficient of 0.82. A 9-3-3 FFBP simulated the volatile fatty acid concentration in the sludge with a regression coefficient of 0.86. And a 9-3-2 FFBP simulated the gas production and gas composition with a regression coefficient of 0.90 and 0.80, respectively. A lab-scale anaerobic continuous stirred tank reactor controlled by this tool was able to maintain a methane concentration of about 60% at a rather high gas production rate of between 5 and 5.6 m3 m(-3) d(-1).

  9. Earthquake Detection and Location Capabilities of the Advanced National Seismic Network

    NASA Astrophysics Data System (ADS)

    McNamara, D. E.; Buland, R. P.; Benz, H. M.; Leith, W.

    2004-12-01

    We have computed minimum earthquake moment magnitude, Mw, detection thresholds for a 1x1 degree grid across the US using the existing backbone stations of the Advanced National Seismic System (ANSS). For every grid point we compute the minimum Mw for which the P phase should be detectable by at least five ANSS stations. Detection is declared at a station when body wave power levels produced for a given Mw are above the frequency dependent 80th percentile noise level for the station. Noise levels were determined in a previous study from probability density functions of noise spectra computed for each ANSS backbone station (McNamara and Buland, 2004). To model event power levels, earthquake moment, Mo, is computed as a function of apparent corner frequency using the source scaling formulas of Brune (1970, 1971). The apparent corner frequency is the frequency at which body wave spectral amplitudes are maximum as a result of attenuation and short period filters applied during NEIC phase picking. The corresponding moment magnitude, Mw, is computed after Kanamori (1977). Body wave amplitudes are then computed for each station depending on the distance and attenuation along each raypath. Amplitude is then converted to power (dB) and compared to station noise levels. The fifth lowest power, above station noise levels then corresponds to the minimum earthquake magnitude for that particular grid point. Our theoretical minimum Mw threshold compares favorably to magnitude thresholds determined from USGS PDE catalogs. We also model the regional variation in event location improvement with the installation of planned ANSS backbone stations. Results from this study are useful for characterizing the performance of existing ANSS broadband stations, for detecting operational problems, and should be relevant to the future siting of ANSS backbone stations. Results from this analysis are also used to optimize the distribution of ANSS regional network stations.

  10. Advanced controlling of anaerobic digestion by means of hierarchical neural networks.

    PubMed

    Holubar, Peter; Zani, Loredana; Hager, Michael; Fröschl, Walter; Radak, Zorana; Braun, Rudolf

    2002-05-01

    In this work several feed-forward back propagation neural networks (FFBP) were trained in order to model, and subsequently control, methane production in anaerobic digesters. To produce data for the training of the neural nets, four anaerobic continuous stirred tank reactors were operated in steady-state conditions at organic loading rates (Br) of about 2 kg m(-3) d(-1) chemical oxygen demand, and disturbed by pulse-like increase of the organic loading rate. For the pulses additional carbon sources like flour, sucrose, 1,2-diethylen glycol or vegetable oil were added to the basic feed, which consisted of surplus and primary sludge of a local waste-water treatment plant, to increase the chemical oxygen demand. Measured parameters were: gas composition, methane production rate, volatile fatty acid concentration, pH, redox potential, volatile suspended solids and chemical oxygen demand of feed and effluent. A hierarchical system of nets was developed and embedded in a decision support system to find out which is the best feeding profile for the next time steps in advance. A 3-3-1 FFBP simulated the pH with a regression coefficient of 0.82. A 9-3-3 FFBP simulated the volatile fatty acid concentration in the sludge with a regression coefficient of 0.86. And a 9-3-2 FFBP simulated the gas production and gas composition with a regression coefficient of 0.90 and 0.80, respectively. A lab-scale anaerobic continuous stirred tank reactor controlled by this tool was able to maintain a methane concentration of about 60% at a rather high gas production rate of between 5 and 5.6 m3 m(-3) d(-1). PMID:12153025

  11. An investigation of interference coordination in heterogeneous network for LTE-Advanced systems

    NASA Astrophysics Data System (ADS)

    Hasan, M. K.; Ismail, A. F.; H, Aisha-Hassan A.; Abdullah, Khaizuran; Ramli, H. A. M.

    2013-12-01

    The novel "femtocell" in Heterogeneous Network (HetNet) for LTE-Advanced (LTE-A) set-up will allow Malaysian wireless telecommunication operators (Maxis, Celcom, Digi, U-Mobile, P1, YTL and etc2.) to extend connectivity coverage where access would otherwise be limited or unavailable, particularly indoors of large building complexes. A femtocell is a small-sized cellular base station that encompasses all the functionality of a typical station. It therefore allows a simpler and self-contained deployment including private residences. For the Malaysian service providers, the main attractions of femtocell usage are the improvements to both coverage and capacity. The operators can provide a better service to end-users in turn reduce much of the agitations and complaints. There will be opportunity for new services at reduced cost. In addition, the operator not only benefits from the improved capacity and coverage but also can reduce both capital expenditure and operating expense i.e. alternative to brand new base station or macrocell installation. Interference is a key issue associated with femtocell development. There are a large number of issues associated with interference all of which need to be investigated, identified, quantified and solved. This is to ensure that the deployment of any femtocells will take place successfully. Among the most critical challenges in femtocell deployment is the interference between femtocell-to-macrocell and femtocell-to-femtocell in HetNets. In this paper, all proposed methods and algorithms will be investigated in the OFDMA femtocell system considering HetNet scenarios for LTE-A.

  12. General Intelligence as a Domain-Specific Adaptation

    ERIC Educational Resources Information Center

    Kanazawa, Satoshi

    2004-01-01

    General intelligence (g) poses a problem for evolutionary psychology's modular view of the human brain. The author advances a new evolutionary psychological theory of the evolution of general intelligence and argues that general intelligence evolved as a domain-specific adaptation for the originally limited sphere of evolutionary novelty in the…

  13. Machine intelligence and robotics: Report of the NASA study group

    NASA Technical Reports Server (NTRS)

    1980-01-01

    Opportunities for the application of machine intelligence and robotics in NASA missions and systems were identified. The benefits of successful adoption of machine intelligence and robotics techniques were estimated and forecasts were prepared to show their growth potential. Program options for research, advanced development, and implementation of machine intelligence and robot technology for use in program planning are presented.

  14. Designing Distributed Learning Environments with Intelligent Software Agents

    ERIC Educational Resources Information Center

    Lin, Fuhua, Ed.

    2005-01-01

    "Designing Distributed Learning Environments with Intelligent Software Agents" reports on the most recent advances in agent technologies for distributed learning. Chapters are devoted to the various aspects of intelligent software agents in distributed learning, including the methodological and technical issues on where and how intelligent agents…

  15. Obstacles in Advancement of Young Female Geoscientists: Research Results from the Earth Science Women's Network (ESWN)

    NASA Astrophysics Data System (ADS)

    Kogan, M.; Laursen, S. L.

    2011-12-01

    While the number of women receiving advanced degrees in the geosciences has been rising, the faces of scientific leaders in academia remain dominantly male. Women are currently underrepresented in tenure-track positions in Earth science departments at research universities. Additionally, women are less likely to have more senior positions within their academic institutions. ESWN is a peer-mentoring network of early career women in the Earth sciences. We conducted a survey of ESWN members as part of an evaluation-with-research study that aims to determine the career needs of young female geoscientists. We also conducted a survey of the co-ed Earth Science Jobs list also run by ESWN and used its male and female members as comparison samples. The survey data provide insight into critical career junctures for women in geosciences and identify salient issues that institutions will need to address to successfully recruit, retain and promote women scientists. Prior research has shown that women are subjected to unintended and unrecognized biases that can have an ultimate impact on their productivity, advancement, and success. Our data corroborate these findings: women consistently rated the professional atmosphere in their departments and their interactions with colleagues less favorably than men. Moreover, women indicated lower rates of collaboration with colleagues in their unit compared to their male peers. Possibly due to this discrepancy in collaboration, women also reported lower research productivity than men in our study. Attaining work/life balance is a particular concern to early-career scientists, especially since tenure clock and the biological clock can coincide and reduce the opportunity for women to achieve tenure and have children. Family issues may impact the success of women in academic careers, such as travel to meetings and field work. Our research shows that women's partners more often worked in STEM fields, potentially complicating women's careers by

  16. Intelligent imaging systems for automotive applications

    NASA Astrophysics Data System (ADS)

    Thompson, Chris; Huang, Yingping; Fu, Shan

    2004-03-01

    In common with many other application areas, visual signals are becoming an increasingly important information source for many automotive applications. For several years CCD cameras have been used as research tools for a range of automotive applications. Infrared cameras, RADAR and LIDAR are other types of imaging sensors that have also been widely investigated for use in cars. This paper will describe work in this field performed in C2VIP over the last decade - starting with Night Vision Systems and looking at various other Advanced Driver Assistance Systems. Emerging from this experience, we make the following observations which are crucial for "intelligent" imaging systems: 1. Careful arrangement of sensor array. 2. Dynamic-Self-Calibration. 3. Networking and processing. 4. Fusion with other imaging sensors, both at the image level and the feature level, provides much more flexibility and reliability in complex situations. We will discuss how these problems can be addressed and what are the outstanding issues.

  17. Artificial Intelligence

    SciTech Connect

    Shirai, Y.; Tsujii, Jun-ichi

    1985-01-01

    Based on the Japanese 5th Generation Computer Program, this volume provides coverage of the fundamental concepts and various techniques in the different applications of Artificial Intelligence. Also presented are the methods which can be used to put these concepts and techniques into practice. Explanations are presented of all the basic topics in the field, including the representation of problems; searching techniques; the control of problem solving; programming languages for Al, such as LISP, PLANNER, CONNIVER, and PROLOG; the representation and utilization of knowledge; and the approach to human intelligence.

  18. Intelligent Fasteners

    NASA Technical Reports Server (NTRS)

    1997-01-01

    Under a Small Business Innovation Research contract from Marshall Space Flight Center, Ultrafast, Inc. developed the world's first, high-temperature resistant, "intelligent" fastener. NASA needed a critical-fastening appraisal and validation of spacecraft segments that are coupled together in space. The intelligent-bolt technology deletes the self-defeating procedure of having to untighten the fastener, and thus upset the joint, during inspection and maintenance. The Ultrafast solution yielded an innovation that is likely to revolutionize manufacturing assembly, particularly the automobile industry. Other areas of application range from aircraft, computers and fork-lifts to offshore platforms, buildings, and bridges.

  19. Artificial intelligence at CSM

    SciTech Connect

    Braun, G.; Jones, J.E.

    1985-08-01

    The recent developments in artificial intelligence have been cited as being the most significant technological advancement in computer science in the twentieth century. Machines that can mimic human reasoning will have a great impact upon our civilization. The way we think, learn, and work will be changed in a profound way. It is for these reasons that the Colorado School of Mines, in order to maintain its reputation of quality engineering education, has entered the AI field. CSM presently is evaluating artificial intelligence for applications in the mineral industries; decision support systems, process control, machine vision, data acquisition and analysis, etc. Future plans are to move AI out of the research laboratories and into the curriculum. An understanding of the concepts and unlimited power of the application of AI will enhance the engineering methods of Mines graduates. 6 references.

  20. Establishing a communications-intensive network to resolve artificial intelligence issues within NASA's Space Station Freedom research centers community

    NASA Technical Reports Server (NTRS)

    Howard, E. Davis, III

    1990-01-01

    MITRE Corporation's, A Review of Space Station Freedom Program Capabilities for the Development and Application of Advanced Automation, cites as a critical issue the following situation, extant at the NASA facilities visited in the course of preparing the review: The major issues noted with regard to design and research facilities deal with cooperative problem solving, technology transfer, and communication between these facilities. While the authors were visiting lab and test beds to collect information, personnel at many of these facilities were interested in any information they could collect on activities at other facilities. A formal means of gathering this information could not be identified by these personnel. While communication between some facilities was taking place or was planned, for technology transfer or coordination of schedules (e.g., for SADP demonstrations), poor communication between these facilities could lead to a lack of technical standards, duplication of effort, poorly defined interfaces, scheduling problems, and increased cost. Formal mechanisms by which effective communication and cooperative problem solving can take place, and information can be disseminated, must be defined. A solution is proposed for the communications aspects of the issues addressed above; and offered at the same time a solution which can prove effective in dealing with some of the problems being encountered with expertise being lost via retirement or defection to the private sector. The proffered recommendations are recognizably cost-effective and tap the rising sector of expert knowledge being produced by the American academic community.

  1. Plant intelligence

    PubMed Central

    Lipavská, Helena; Žárský, Viktor

    2009-01-01

    The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

  2. Civic Intelligence.

    ERIC Educational Resources Information Center

    Mathews, David

    1985-01-01

    Social studies must educate students to be socially responsible, civically competent persons. In addition to encouraging civic literacy, civic values, and civic skill, teachers need to help students develop civic-mindedness. The objective of the NCSS' National Issues Forum in the Classroom Project is to develop students' civic intelligence. (RM)

  3. Intelligence Studies

    ERIC Educational Resources Information Center

    Monaghan, Peter

    2009-01-01

    To make an academic study of matters inherently secret and potentially explosive seems a tall task. But a growing number of scholars are drawn to understanding spycraft. The interdisciplinary field of intelligence studies is mushrooming, as scholars trained in history, international studies, and political science examine such subjects as the…

  4. Speech Intelligibility

    NASA Astrophysics Data System (ADS)

    Brand, Thomas

    Speech intelligibility (SI) is important for different fields of research, engineering and diagnostics in order to quantify very different phenomena like the quality of recordings, communication and playback devices, the reverberation of auditoria, characteristics of hearing impairment, benefit using hearing aids or combinations of these things.

  5. Water Intelligence and the Cyber-Infrastructure Revolution

    NASA Astrophysics Data System (ADS)

    Cline, D. W.

    2015-12-01

    As an intrinsic factor in national security, the global economy, food and energy production, and human and ecological health, fresh water resources are increasingly being considered by an ever-widening array of stakeholders. The U.S. intelligence community has identified water as a key factor in the Nation's security risk profile. Water industries are growing rapidly, and seek to revolutionize the role of water in the global economy, making water an economic value rather than a limitation on operations. Recent increased focus on the complex interrelationships and interdependencies between water, food, and energy signal a renewed effort to move towards integrated water resource management. Throughout all of this, hydrologic extremes continue to wreak havoc on communities and regions around the world, in some cases threatening long-term economic stability. This increased attention on water coincides with the "second IT revolution" of cyber-infrastructure (CI). The CI concept is a convergence of technology, data, applications and human resources, all coalescing into a tightly integrated global grid of computing, information, networking and sensor resources, and ultimately serving as an engine of change for collaboration, education and scientific discovery and innovation. In the water arena, we have unprecedented opportunities to apply the CI concept to help address complex water challenges and shape the future world of water resources - on both science and socio-economic application fronts. Providing actionable local "water intelligence" nationally or globally is now becoming feasible through high-performance computing, data technologies, and advanced hydrologic modeling. Further development on all of these fronts appears likely and will help advance this much-needed capability. Lagging behind are water observation systems, especially in situ networks, which need significant innovation to keep pace with and help fuel rapid advancements in water intelligence.

  6. Networks as a type of social entrepreneurship to advance population health.

    PubMed

    Wei-Skillern, Jane

    2010-11-01

    A detailed case study from the field of social entrepreneurship is used to illustrate the network approach, which does not require more resources but rather makes better use of existing resources. Leaders in public health can use networks to overcome some of the barriers that inhibit the widespread adoption of a population health approach to community health. Public health leaders who embrace social entrepreneurship may be better able to accomplish their missions by building their networks rather than just their organizations. PMID:20950527

  7. Networks as a type of social entrepreneurship to advance population health.

    PubMed

    Wei-Skillern, Jane

    2010-11-01

    A detailed case study from the field of social entrepreneurship is used to illustrate the network approach, which does not require more resources but rather makes better use of existing resources. Leaders in public health can use networks to overcome some of the barriers that inhibit the widespread adoption of a population health approach to community health. Public health leaders who embrace social entrepreneurship may be better able to accomplish their missions by building their networks rather than just their organizations.

  8. Advanced biomaterial strategies to transplant preformed micro-tissue engineered neural networks into the brain

    NASA Astrophysics Data System (ADS)

    Harris, J. P.; Struzyna, L. A.; Murphy, P. L.; Adewole, D. O.; Kuo, E.; Cullen, D. K.

    2016-02-01

    Objective. Connectome disruption is a hallmark of many neurological diseases and trauma with no current strategies to restore lost long-distance axonal pathways in the brain. We are creating transplantable micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of embedded neurons and long axonal tracts to integrate with the nervous system to physically reconstitute lost axonal pathways. Approach. We advanced micro-tissue engineering techniques to generate micro-TENNs consisting of discrete populations of mature primary cerebral cortical neurons spanned by long axonal fascicles encased in miniature hydrogel micro-columns. Further, we improved the biomaterial encasement scheme by adding a thin layer of low viscosity carboxymethylcellulose (CMC) to enable needle-less insertion and rapid softening for mechanical similarity with brain tissue. Main results. The engineered architecture of cortical micro-TENNs facilitated robust neuronal viability and axonal cytoarchitecture to at least 22 days in vitro. Micro-TENNs displayed discrete neuronal populations spanned by long axonal fasciculation throughout the core, thus mimicking the general systems-level anatomy of gray matter—white matter in the brain. Additionally, micro-columns with thin CMC-coating upon mild dehydration were able to withstand a force of 893 ± 457 mN before buckling, whereas a solid agarose cylinder of similar dimensions was predicted to withstand less than 150 μN of force. This thin CMC coating increased the stiffness by three orders of magnitude, enabling needle-less insertion into brain while significantly reducing the footprint of previous needle-based delivery methods to minimize insertion trauma. Significance. Our novel micro-TENNs are the first strategy designed for minimally invasive implantation to facilitate nervous system repair by simultaneously providing neuronal replacement and physical reconstruction of long-distance axon pathways in the brain

  9. Advanced Test Reactor -- Testing Capabilities and Plans AND Advanced Test Reactor National Scientific User Facility -- Partnerships and Networks

    SciTech Connect

    Frances M. Marshall

    2008-07-01

    The Advanced Test Reactor (ATR), at the Idaho National Laboratory (INL), is one of the world’s premier test reactors for providing the capability for studying the effects of intense neutron and gamma radiation on reactor materials and fuels. The physical configuration of the ATR, a 4-leaf clover shape, allows the reactor to be operated at different power levels in the corner “lobes” to allow for different testing conditions for multiple simultaneous experiments. The combination of high flux (maximum thermal neutron fluxes of 1E15 neutrons per square centimeter per second and maximum fast [E>1.0 MeV] neutron fluxes of 5E14 neutrons per square centimeter per second) and large test volumes (up to 122 cm long and 12.7 cm diameter) provide unique testing opportunities. For future research, some ATR modifications and enhancements are currently planned. In 2007 the US Department of Energy designated the ATR as a National Scientific User Facility (NSUF) to facilitate greater access to the ATR for material testing research by a broader user community. This paper provides more details on some of the ATR capabilities, key design features, experiments, and plans for the NSUF.

  10. Advanced Bibliometric Methods To Model the Relationship between Entry Behavior and Networking in Emerging Technological Communities.

    ERIC Educational Resources Information Center

    Debackere, Koenraad; Clarysse, Bart

    1998-01-01

    Technological communities used bibliometric data on 411 plant biotechnology organizations to study the effect of field density and structure of the research and development network. Findings indicate the usefulness of bibliometric data in mapping change in technological communities and in the effects of networking on entry behavior. (PEN)

  11. LambdaStation: Exploiting Advance Networks In Data Intensive High Energy Physics Applications

    SciTech Connect

    Harvey B. Newman

    2009-09-11

    Lambda Station software implements selective, dynamic, secure path control between local storage & analysis facilities, and high bandwidth, wide-area networks (WANs). It is intended to facilitate use of desirable, alternate wide area network paths which may only be intermittently available, or subject to policies that restrict usage to specified traffic. Lambda Station clients gain awareness of potential alternate network paths via Clarens-based web services, including path characteristics such as bandwidth and availability. If alternate path setup is requested and granted, Lambda Station will configure the local network infrastructure to properly forward designated data flows via the alternate path. A fully functional implementation of Lambda Station, capable of dynamic alternate WAN path setup and teardown, has been successfully developed. A limited Lambda Station-awareness capability within the Storage Resource Manager (SRM) product has been developed. Lambda Station has been successfully tested in a number of venues, including Super Computing 2008. LambdaStation software, developed by the Fermilab team, enables dynamic allocation of alternate network paths for high impact traffic and to forward designated flows across LAN. It negotiates with reservation and provisioning systems of WAN control planes, be it based on SONET channels, demand tunnels, or dynamic circuit networks. It creates End-To-End circuit between single hosts, computer farms or networks with predictable performance characteristics, preserving QoS if supported in LAN and WAN and tied security policy allowing only specific traffic to be forwarded or received through created path. Lambda Station project also explores Network Awareness capabilities.

  12. Application of neural networks to prediction of advanced composite structures mechanical response and behavior

    NASA Technical Reports Server (NTRS)

    Cios, K. J.; Vary, A.; Berke, L.; Kautz, H. E.

    1992-01-01

    Two types of neural networks were used to evaluate acousto-ultrasonic (AU) data for material characterization and mechanical reponse prediction. The neural networks included a simple feedforward network (backpropagation) and a radial basis functions network. Comparisons of results in terms of accuracy and training time are given. Acousto-ultrasonic (AU) measurements were performed on a series of tensile specimens composed of eight laminated layers of continuous, SiC fiber reinforced Ti-15-3 matrix. The frequency spectrum was dominated by frequencies of longitudinal wave resonance through the thickness of the specimen at the sending transducer. The magnitude of the frequency spectrum of the AU signal was used for calculating a stress-wave factor based on integrating the spectral distribution function and used for comparison with neural networks results.

  13. Faculty Peer Networks: Role and Relevance in Advancing Agency and Gender Equity

    ERIC Educational Resources Information Center

    O'Meara, KerryAnn; Stromquist, Nelly P.

    2015-01-01

    Organisational efforts to alter gender asymmetries are relatively rare, yet they are taking place in a number of universities. In the USA, sponsored by the National Science Foundation, ADVANCE programmes implement a number of interventions to improve the recruitment, retention, and advancement of women faculty. This study focused on one common…

  14. An intercomparison of artificial intelligence approaches for polar scene identification

    SciTech Connect

    Tovinkere, V.R.; Penaloza, M.; Logar, A.; Lee, J.; Weger, R.C.; Berendes, T.A.; Welch, R.M. )

    1993-03-20

    Six advanced very high resolution radiometer local area coverage arctic scenes are classified into 10 classes. These include water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over ice, cumulus over water, and multilayer cloudiness. Eight spectral and textural features are computed. The textural features are based upon the gray level difference vector method. Six different artificial intelligence classifiers are examined: (1) the feed forward back propagation neural network; (2) the probabilistic neural network; (3) the hybrid back propagation neural network; (4) the [open quotes]don't care[close quotes] perceptron network; (5) the [open quotes]don't care[close quotes] back propagation neural network; and (6) a fuzzy logic-based expert system. Accuracies in excess of 95% are obtained for all but the hybrid neural network. The [open quotes]don't care[close quotes] back propagation neural network produces the highest accuracies and also has low CPU requirements. Thin fog/stratus over ice is the class consistently with the lowest accuracy, often misclassified as broken sea ice. Water, land, cirrus over ice, and snow-covered mountains are all classified with high accuracy ([ge]98%). The high accuracy achieved in the present study can be traced to (1) accurate classifiers; (2) an excellent choice for the feature vector, and (3) accurate labeling. A sophisticated new interactive visual image classification system is used for the labeling. 33 refs., 8 figs., 7 tabs.

  15. Team B Intelligence Coups

    ERIC Educational Resources Information Center

    Mitchell, Gordon R.

    2006-01-01

    The 2003 Iraq prewar intelligence failure was not simply a case of the U.S. intelligence community providing flawed data to policy-makers. It also involved subversion of the competitive intelligence analysis process, where unofficial intelligence boutiques "stovepiped" misleading intelligence assessments directly to policy-makers and undercut…

  16. Neurotechnology for intelligence analysts

    NASA Astrophysics Data System (ADS)

    Kruse, Amy A.; Boyd, Karen C.; Schulman, Joshua J.

    2006-05-01

    Geospatial Intelligence Analysts are currently faced with an enormous volume of imagery, only a fraction of which can be processed or reviewed in a timely operational manner. Computer-based target detection efforts have failed to yield the speed, flexibility and accuracy of the human visual system. Rather than focus solely on artificial systems, we hypothesize that the human visual system is still the best target detection apparatus currently in use, and with the addition of neuroscience-based measurement capabilities it can surpass the throughput of the unaided human severalfold. Using electroencephalography (EEG), Thorpe et al1 described a fast signal in the brain associated with the early detection of targets in static imagery using a Rapid Serial Visual Presentation (RSVP) paradigm. This finding suggests that it may be possible to extract target detection signals from complex imagery in real time utilizing non-invasive neurophysiological assessment tools. To transform this phenomenon into a capability for defense applications, the Defense Advanced Research Projects Agency (DARPA) currently is sponsoring an effort titled Neurotechnology for Intelligence Analysts (NIA). The vision of the NIA program is to revolutionize the way that analysts handle intelligence imagery, increasing both the throughput of imagery to the analyst and overall accuracy of the assessments. Successful development of a neurobiologically-based image triage system will enable image analysts to train more effectively and process imagery with greater speed and precision.

  17. Artificial Intelligence.

    PubMed

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  18. Artificial Intelligence.

    PubMed

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve. PMID:26957450

  19. A Research Program on Artificial Intelligence in Process Engineering.

    ERIC Educational Resources Information Center

    Stephanopoulos, George

    1986-01-01

    Discusses the use of artificial intelligence systems in process engineering. Describes a new program at the Massachusetts Institute of Technology which attempts to advance process engineering through technological advances in the areas of artificial intelligence and computers. Identifies the program's hardware facilities, software support,…

  20. The advancement of chemical cross-linking and mass spectrometry for structural proteomics: from single proteins to protein interaction networks.

    PubMed

    Sinz, Andrea

    2014-12-01

    During the last 15 years, chemical cross-linking combined with mass spectrometry (MS) and computational modeling has advanced from investigating 3D-structures of isolated proteins to deciphering protein interaction networks. In this article, the author discusses the advent, the development and the current status of the chemical cross-linking/MS strategy in the context of recent technological developments. A direct way to probe in vivo protein-protein interactions is by site-specific incorporation of genetically encoded photo-reactive amino acids or by non-directed incorporation of photo-reactive amino acids. As the chemical cross-linking/MS approach allows the capture of transient and weak interactions, it has the potential to become a routine technique for unraveling protein interaction networks in their natural cellular environment.

  1. Simulation and intelligent vehicle highway systems

    SciTech Connect

    Rathi, A.K. ); Santiago, A.J. )

    1992-01-01

    Intelligent Vehicle Highway Systems (IVHS) is based on the premise of using advanced technologies in telecommunication, electronics, and computers to improve the nature and quality of highway travel while making it safer and more efficient. The safety benefits of the IVHS systems are unquestioned; however, there are different levels of optimism about the operational benefits of these systems. While there is a broad consensus that IVHS can improve the flow of traffic, and thus mobility, currently there is very limited empirical evidence or analytical basis to support this optimism. The lack of analytical framework for design, analysis, and evaluation of IVHS concepts will continue to fuel the debate between the skeptics and the advocates of IVHS. Computer simulation is likely to play a major role in the analysis and assessment of the IVHS technologies. In this paper, we attempt to identify the simulation modelling needs to support the IVHS functional areas dealing with traffic flow on highway networks. The paper outlines the envisioned IVHS operational environment. Functional requirements for the simulation modelling system that could be used to support the development and testing of IVHS concepts, namely Advanced Traffic Management Systems (ATMS) and Advanced Traveller Information Systems (ATIS), are defined. Simulation modelling research and development needs to support the design and evaluations of IVHS concepts are described. The paper concludes by presenting on-going work on the traffic simulation models at the Oak Ridge National Laboratory.

  2. Simulation and intelligent vehicle highway systems

    SciTech Connect

    Rathi, A.K.; Santiago, A.J.

    1992-09-01

    Intelligent Vehicle Highway Systems (IVHS) is based on the premise of using advanced technologies in telecommunication, electronics, and computers to improve the nature and quality of highway travel while making it safer and more efficient. The safety benefits of the IVHS systems are unquestioned; however, there are different levels of optimism about the operational benefits of these systems. While there is a broad consensus that IVHS can improve the flow of traffic, and thus mobility, currently there is very limited empirical evidence or analytical basis to support this optimism. The lack of analytical framework for design, analysis, and evaluation of IVHS concepts will continue to fuel the debate between the skeptics and the advocates of IVHS. Computer simulation is likely to play a major role in the analysis and assessment of the IVHS technologies. In this paper, we attempt to identify the simulation modelling needs to support the IVHS functional areas dealing with traffic flow on highway networks. The paper outlines the envisioned IVHS operational environment. Functional requirements for the simulation modelling system that could be used to support the development and testing of IVHS concepts, namely Advanced Traffic Management Systems (ATMS) and Advanced Traveller Information Systems (ATIS), are defined. Simulation modelling research and development needs to support the design and evaluations of IVHS concepts are described. The paper concludes by presenting on-going work on the traffic simulation models at the Oak Ridge National Laboratory.

  3. A flexible state-space approach for the modeling of metabolic networks II: advanced interrogation of hybridoma metabolism.

    PubMed

    Baughman, Adam C; Sharfstein, Susan T; Martin, Lealon L

    2011-03-01

    Having previously introduced the mathematical framework of topological metabolic analysis (TMA) - a novel optimization-based technique for modeling metabolic networks of arbitrary size and complexity - we demonstrate how TMA facilitates unique methods of metabolic interrogation. With the aid of several hybridoma metabolic investigations as case-studies (Bonarius et al., 1995, 1996, 2001), we first establish that the TMA framework identifies biologically important aspects of the metabolic network under investigation. We also show that the use of a structured weighting approach within our objective provides a substantial modeling benefit over an unstructured, uniform, weighting approach. We then illustrate the strength of TAM as an advanced interrogation technique, first by using TMA to prove the existence of (and to quantitatively describe) multiple topologically distinct configurations of a metabolic network that each optimally model a given set of experimental observations. We further show that such alternate topologies are indistinguishable using existing stoichiometric modeling techniques, and we explain the biological significance of the topological variables appearing within our model. By leveraging the manner in which TMA implements metabolite inputs and outputs, we also show that metabolites whose possible metabolic fates are inadequately described by a given network reconstruction can be quickly identified. Lastly, we show how the use of the TMA aggregate objective function (AOF) permits the identification of modeling solutions that can simultaneously consider experimental observations, underlying biological motivations, or even purely engineering- or design-based goals.

  4. National Institute of Biomedical Imaging and Bioengineering Point-of-Care Technology Research Network: Advancing Precision Medicine

    PubMed Central

    Ford Carleton, Penny; Parrish, John A.; Collins, John M.; Crocker, J. Benjamin; Dixon, Ronald F.; Edgman-Levitan, Susan; Lewandrowski, Kent B.; Stahl, James E.; Klapperich, Catherine; Cabodi, Mario; Gaydos, Charlotte A.; Rompalo, Anne M.; Manabe, Yukari; Wang, Tza-Huei; Rothman, Richard; Geddes, Chris D.; Widdice, Lea; Jackman, Joany; Mathura, Rishi A.; Lash, Tiffani Bailey

    2016-01-01

    To advance the development of point-of-care technology (POCT), the National Institute of Biomedical Imaging and Bioengineering established the POCT Research Network (POCTRN), comprised of Centers that emphasize multidisciplinary partnerships and close facilitation to move technologies from an early stage of development into clinical testing and patient use. This paper describes the POCTRN and the three currently funded Centers as examples of academic-based organizations that support collaborations across disciplines, institutions, and geographic regions to successfully drive innovative solutions from concept to patient care. PMID:27730014

  5. New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background

    PubMed Central

    Penco, Silvana; Buscema, Massimo; Patrosso, Maria Cristina; Marocchi, Alessandro; Grossi, Enzo

    2008-01-01

    Background Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis Results Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase

  6. SCIGN; new Southern California GPS network advances the study of earthquakes

    USGS Publications Warehouse

    Hudnut, Ken; King, Nancy

    2001-01-01

    Southern California is a giant jigsaw puzzle, and scientists are now using GPS satellites to track the pieces. These puzzle pieces are continuously moving, slowly straining the faults in between. That strain is then eventually released in earthquakes. The innovative Southern California Integrated GPS Network (SCIGN) tracks the motions of these pieces over most of southern California with unprecedented precision. This new network greatly improves the ability to assess seismic hazards and quickly measure the larger displacements that occur during and immediatelyafter earthquakes.

  7. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 1: Executive summary

    NASA Technical Reports Server (NTRS)

    1986-01-01

    Over the past two decades, fiber optics has emerged as a highly practical and cost-efficient communications technology. Its competitiveness vis-a-vis other transmission media, especially satellite, has become a critical question. This report studies the likely evolution and application of fiber optic networks in the United States to the end of the century. The outlook for the technology of fiber systems is assessed and forecast, scenarios of the evolution of fiber optic network development are constructed, and costs to provide service are determined and examined parametrically as a function of network size and traffic carried. Volume 1 consists of the Executive Summary. Volume 2 focuses on fiber optic technology and long distance fiber optic networks. Volume 3 develops a traffic and financial model of a nationwide long distance transmission network. Among the study's most important conclusions are: revenue requirements per circuit for LATA-to-LATA fiber optic links are less than one cent per call minute; multiplex equipment, which is likely to be required in any competing system, is the largest contributor to circuit costs; the potential capacity of fiber optic cable is very large and as yet undefined; and fiber optic transmission combined with other network optimization schemes can lead to even lower costs than those identified in this study.

  8. The Effects of a Dynamic Spectrum Access Overlay in LTE-Advanced Networks

    SciTech Connect

    Juan D. Deaton; Ryan E. lrwin; Luiz A. DaSilva

    2011-05-01

    As early as 2014, wireless network operators spectral capacity will be overwhelmed by a data tsunami brought on by new devices and applications. To augment spectral capacity, operators could deploy a Dynamic Spectrum Access (DSA) overlay. In the light of the many planned Long Term Evolution (LTE) network deployments, the affects of a DSA overlay have not been fully considered into the existing LTE standards. Coalescing many different aspects of DSA, this paper develops the Spectrum Accountability (SA) framework. The SA framework defines specific network element functionality, protocol interfaces, and signaling flow diagrams for LTE to support service requests and enforce rights of responsibilities of primary and secondary users, respectively. We also include a network simulation to quantify the benefits of using DSA channels to augment capacity. Based on our simulation we show that, network operators can benefit up to %40 increase in operating capacity when sharing DSA bands to augment spectral capacity. With our framework, this paper could serve as an guide in developing future LTE network standards that include DSA.

  9. Advanced data compression promises the next big leap in network performance

    NASA Astrophysics Data System (ADS)

    Holtz, Klaus E.; Holtz, Eric S.; Kalienky, Diana

    1998-09-01

    Three recently introduced technologies: a new Autosophy information theory; fast Content Addressable Memories; and Packet Switching protocols, are combined in data compression chipsets to improve network throughput with real-time lossless text and image compression. Compared with the cost of putting new cables into the ground or launching new satellites, data compression chipsets offer a much less expensive alternative for improving the bandwidth of broadband communication networks. Data compression is based on a new Autosophy information theory in which, in contrast to Shannon's theory, communication is determined only by the data content. In addition to high lossless data compression, this also provides virtually unbreakable 'codebook' encryption and easier communication via packet switching networks. The Autosophy theories provide eight known classes of self-learning Omni Dimensional Networks. Only the serial network is explained here for use in compressed text and video communications. A new Content Addressable Read Only Memory (CAROM) may increase data compression speed to more than 20 Million symbols per second, fast enough for virtually any network speed.

  10. An intelligent approach to nanotechnology

    NASA Astrophysics Data System (ADS)

    Demming, Anna

    2013-11-01

    intelligence and machine learning approaches already offer a potent suite of tools to nanotechnology researchers with very practical benefits. Even as far back as 1995 David Whitehouse—Editor-in-Chief of Nanotechnology when the journal was launched almost 25 years ago—and W L Wang reported on the relevance of neural networks in scanning probe imaging [10]. Couple the progress in applying artificial intelligence with the advances in mimicking biological neurons with nanostructures that has been highlighted in our recent synaptic electronics special issue [11] and it seems we may be on the cusp of a new phase in the relationship between man and machine. References [1] Sacha G M and Varona P 2013 Artificial intelligence in nanotechnology Nanotechnology 24 452002 [2] Park K H, Im S H and Park O O 2011 The size control of silver nanocrystals with different polyols and its application to low-reflection coating materials Nanotechnology 22 045602 [3] Pradhan N, Pal A and Pal T 2002 Silver nanoparticle catalyzed reduction of aromatic nitro compounds Colloids Surf. A 196 247-57 [4] Ma K, Cui Q, Liu G, Wu F, Xu S and Shao Y 2011 DNA abasic site-directed formation of fluorescent silver nanoclusters for selective nucleobase recognition Nanotechnology 22 305502 [5] Doering W E and Nie S 2002 Single-molecule and single-nanoparticle SERS: examining the roles of surface active sites and chemical enhancement J. Phys. Chem. B 106 311-7 [6] Wang J X, Sun X W, Yang Y, Huang H, Lee Y C, Tan O K and Vayssieres L 2006 Hydrothermally grown oriented ZnO nanorod arrays for gas sensing applications Nanotechnology 17 4995-8 [7] Kong X Y, Ding Y and Wang Z L 2004 Metal-semiconductor Zn-ZnO core-shell nanobelts and nanotubes J. Phys. Chem. B 108 570-4 [8] Zhang H, Yang D, Ma X, Ji Y, Xu J and Que D 2004 Synthesis of flower-like ZnO nanostructures by an organic-free hydrothermal process Nanotechnology 15 622-6 [9] Romano G, Mantini G, Carlo A D, D'Amico A, Falconi C and Wang Z L 2011 Piezoelectric

  11. Trends in Artificial Intelligence.

    ERIC Educational Resources Information Center

    Hayes, Patrick

    1978-01-01

    Discusses the foundations of artificial intelligence as a science and the types of answers that may be given to the question, "What is intelligence?" The paradigms of artificial intelligence and general systems theory are compared. (Author/VT)

  12. An Intelligent Tutoring System.

    ERIC Educational Resources Information Center

    Corbett, Albert

    1988-01-01

    Discusses a research project that uses artificial intelligence techniques to help teach programing. Describes principles and implementation of the LISP Intelligent Tutoring System (LISPITS). Explains how the artificial intelligence technique was developed and possible future research. (MVL)

  13. Intelligent Design and Intelligent Failure

    NASA Technical Reports Server (NTRS)

    Jerman, Gregory

    2015-01-01

    Good Evening, my name is Greg Jerman and for nearly a quarter century I have been performing failure analysis on NASA's aerospace hardware. During that time I had the distinct privilege of keeping the Space Shuttle flying for two thirds of its history. I have analyzed a wide variety of failed hardware from simple electrical cables to cryogenic fuel tanks to high temperature turbine blades. During this time I have found that for all the time we spend intelligently designing things, we need to be equally intelligent about understanding why things fail. The NASA Flight Director for Apollo 13, Gene Kranz, is best known for the expression "Failure is not an option." However, NASA history is filled with failures both large and small, so it might be more accurate to say failure is inevitable. It is how we react and learn from our failures that makes the difference.

  14. A Neural Network Aero Design System for Advanced Turbo-Engines

    NASA Technical Reports Server (NTRS)

    Sanz, Jose M.

    1999-01-01

    An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

  15. The 19th Annual Intelligent Ground Vehicle Competition: student built autonomous ground vehicles

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.

    2012-01-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 19 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from almost 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

  16. The 20th annual intelligent ground vehicle competition: building a generation of robotists

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.; Kosinski, Andrew

    2013-01-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 20 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

  17. The 21st annual intelligent ground vehicle competition: robotists for the future

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.

    2013-12-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 21 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the fourday competition are highlighted. Finally, an assessment of the competition based on participation is presented.

  18. Advancement in the application of neural networks for short-term load forecasting

    SciTech Connect

    Peng, T.M.; Hubele, N.F.; Karady, G.G. )

    1992-02-01

    In this paper an improved neural network approach is proposed to produce short-term electric load forecasts. A new strategy, suitable for selecting the training cases for the neural network, is presented. This strategy uses a minimum distance measurement to identify the appropriate historical patterns of load and temperature readings to be used to estimate the network weights. This strategy has the advantage of circumventing the problem of holidays and drastic changes in weather patterns, which make the most recent observations unlikely candidates for training the network. In addition, an improved neural network algorithm is proposed. This algorithm includes a combination of linear and nonlinear terms which map past load and temperature inputs to the load forecast output. The new search strategy and algorithm demonstrate improved accuracy over other methods when tested using two years of utility data. In addition to reporting the summary statistics of average and standard deviation of absolute percentage error, an alternate method using a cumulative distribution plot for presenting load forecasting results is demonstrated.

  19. Advances in cables and outside plant for cable television and optical fibre local networks

    NASA Astrophysics Data System (ADS)

    Bridle, Peter

    1986-11-01

    During 1985 Bristish Telecom commenced the installation of a number of cable television systems in the United Kingdom. One of these systems, in Westminster, London, is of the Switched Star type, developed by the British Telecom Research Laboratories. The network comprises optical fiber cable between the head-end and the cabinet-mounted switch, and coaxial cable between the switch and the customer. A number of new outside plant products have been developed to meet the special requirements of the Westminister installation. This earlier work, together with the experience gained from the installation of optical fibers in the British Telecom trunk and junction networks, formed an ideal basis for evolving the line plant necessary to enable BT to introduce singlemode optical fiber into the local network. A range of cables is being developed by UK companies, suitable for installing in the harsh environment of the local network. Joint organizers and flexibility nodes are being introduced, both for underground application and for within the exchange and customer's premises. In addition blown-fiber techniques are being used to introduce fiber into these networks.

  20. The Present and Future Opportunities of the Rare Cancer Network: An International Consortium for Advancement of Oncologic Care.

    PubMed

    2015-09-01

    To date, the Rare Cancer Network (RCN) has initiated more than 90 studies and 54 peer-reviewed publications were produced as a result. The Second International Symposium of the Rare Cancer Network recently took place in Istanbul, Turkey on April 17-18, 2015, and update was given on multiple currently ongoing projects, while also giving room for new proposals which will shape the direction of future studies for the group. This companion issue of the RCN Proceedings summarized the findings of this meeting, while also serving as a call for fresh projects and papers which will continue to energize the group and advance the oncologic science. A brief introduction to the principles, history, and vision of the RCN was also included. To review, the academic year of 2014-15 marked an enormous success for the international members of the RCN, with the generation of 8 fully published papers and more than 12 newly proposed topics. By the collective efforts of all RCN members, in the future, we look forward to the upcoming opportunities in continuing to advance the standard of chemo- and radiotherapeutic oncologic care for selected rare tumor topics. The studies of these rare cancers often do not allow the design and execution of prospectively enrolled trials; however, these uncommon malignancies do impact the humankind and add to its suffering globally in significant ways. PMID:26500735