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Sample records for advanced intelligent network

  1. Functional brain network efficiency predicts intelligence.

    PubMed

    Langer, Nicolas; Pedroni, Andreas; Gianotti, Lorena R R; Hänggi, Jürgen; Knoch, Daria; Jäncke, Lutz

    2012-06-01

    The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

  2. An Advanced Orbiting Systems Approach to Quality of Service in Space-Based Intelligent Communication Networks

    NASA Technical Reports Server (NTRS)

    Riha, Andrew P.

    2005-01-01

    As humans and robotic technologies are deployed in future constellation systems, differing traffic services will arise, e.g., realtime and non-realtime. In order to provide a quality of service framework that would allow humans and robotic technologies to interoperate over a wide and dynamic range of interactions, a method of classifying data as realtime or non-realtime is needed. In our paper, we present an approach that leverages the Consultative Committee for Space Data Systems (CCSDS) Advanced Orbiting Systems (AOS) data link protocol. Specifically, we redefine the AOS Transfer Frame Replay Flag in order to provide an automated store-and-forward approach on a per-service basis for use in the next-generation Interplanetary Network. In addition to addressing the problem of intermittent connectivity and associated services, we propose a follow-on methodology for prioritizing data through further modification of the AOS Transfer Frame.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Advanced Network Security Project

    DTIC Science & Technology

    2005-12-01

    network. The network observed was the Abilene network of the University Consortium for Advanced Internet Development (UCAID), often known as “ Internet2 ...for Advanced Internet Development (UCAID), often known as “ Internet2 .” This contract was heavily operational in nature, as opposed to a contract

  9. 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.

  10. Advanced traffic control strategies for intelligent vehicle highway systems

    NASA Astrophysics Data System (ADS)

    Gartner, Nathan H.; Stamatiadis, C.; Tarnoff, P. J.

    1995-01-01

    This paper discusses traffic signal control strategies that are suitable for advanced traffic management within IVHS (Intelligent Vehicle Highway Systems). The strategies consist of a multi-level design for the real-time, traffic-adaptive control of the urban signal network system. Each control level has different response characteristics, with the more advanced levels incorporating in a nested fashion the capabilities of the lower levels. A principal goal of the new multi-level design is to invoke a selected control strategy when it can provide the greatest benefit.

  11. Advances in learning for intelligent mobile robots

    NASA Astrophysics Data System (ADS)

    Hall, Ernest L.; Ghaffari, Masoud; Liao, Xiaoqun S.; Alhaj Ali, Souma M.

    2004-10-01

    Intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths to accomplish a variety of tasks. Such machines have many potential useful applications in medicine, defense, industry and even the home so that the design of such machines is a challenge with great potential rewards. Even though intelligent systems may have symbiotic closure that permits them to make a decision or take an action without external inputs, sensors such as vision permit sensing of the environment and permit precise adaptation to changes. Sensing and adaptation define a reactive system. However, in many applications some form of learning is also desirable or perhaps even required. A further level of intelligence called understanding may involve not only sensing, adaptation and learning but also creative, perceptual solutions involving models of not only the eyes and brain but also the mind. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots with examples of adaptive, creative and perceptual learning. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots that could lead to important beneficial applications.

  12. Advanced Polymer Network Structures

    DTIC Science & Technology

    2016-02-01

    13. SUPPLEMENTARY NOTES 14. ABSTRACT Polymer networks and gels are important classes of materials for defense applications . In an effort to......it is no longer needed. Do not return it to the originator. ARL-TR-7612 ● FEB 2016 US Army Research Laboratory Advanced Polymer

  13. Human Intelligence: An Introduction to Advances in Theory and Research.

    ERIC Educational Resources Information Center

    Lohman, David F.

    1989-01-01

    Recent advances in three research traditions are summarized: trait theories of intelligence, information-processing theories of intelligence, and general theories of thinking. Work on fluid and crystallized abilities by J. Horn and R. Snow, mental speed, spatial visualization, cognitive psychology, artificial intelligence, and the construct of…

  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. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  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. Integrated intelligent systems in advanced reactor control rooms

    SciTech Connect

    Beckmeyer, R.R.

    1989-01-01

    An intelligent, reactor control room, information system is designed to be an integral part of an advanced control room and will assist the reactor operator's decision making process by continuously monitoring the current plant state and providing recommended operator actions to improve that state. This intelligent system is an integral part of, as well as an extension to, the plant protection and control systems. This paper describes the interaction of several functional components (intelligent information data display, technical specifications monitoring, and dynamic procedures) of the overall system and the artificial intelligence laboratory environment assembled for testing the prototype. 10 refs., 5 figs.

  2. 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.

  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. A Deeper Level of Network Intelligence: Combating Cyber Warfare

    DTIC Science & Technology

    2010-04-01

    A Deeper Level of Network Intelligence: Combating Cyber Warfare This information is provided for your review only and is not for any distribution...A Deeper Level of Network Intelligence: Combating Cyber Warfare 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

  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. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. Intelligent Software Tools for Advanced Computing

    SciTech Connect

    Baumgart, C.W.

    2001-04-03

    Feature extraction and evaluation are two procedures common to the development of any pattern recognition application. These features are the primary pieces of information which are used to train the pattern recognition tool, whether that tool is a neural network, a fuzzy logic rulebase, or a genetic algorithm. Careful selection of the features to be used by the pattern recognition tool can significantly streamline the overall development and training of the solution for the pattern recognition application. This report summarizes the development of an integrated, computer-based software package called the Feature Extraction Toolbox (FET), which can be used for the development and deployment of solutions to generic pattern recognition problems. This toolbox integrates a number of software techniques for signal processing, feature extraction and evaluation, and pattern recognition, all under a single, user-friendly development environment. The toolbox has been developed to run on a laptop computer, so that it may be taken to a site and used to develop pattern recognition applications in the field. A prototype version of this toolbox has been completed and is currently being used for applications development on several projects in support of the Department of Energy.

  14. 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.

  15. Pattern recognition, neural networks, and artificial intelligence

    NASA Astrophysics Data System (ADS)

    Bezdek, James C.

    1991-03-01

    We write about the relationship between numerical patten recognition and neural-like computation networks. Extensive research that proposes the use of neural models for a wide variety of applications has been conducted in the past few years. Sometimes justification for investigating the potential of neural nets (NNs) is obvious. On the other hand, current enthusiasm for this approach has also led to the use of neural models when the apparent rationale for their use has been justified by what is best described as 'feeding frenzy'. In this latter instance there is at times concomitant lack of concern about many 'side issues' connected with algorithms (e.g., complexity, convergence, stability, robustness and performance validation) that need attention before any computational model becomes part of an operation system. These issues are examined with a view towards guessing how best to integrate and exploit the promise of the neural approach with there efforts aimed at advancing the art and science of pattern recognition and its applications in fielded systems in the next decade.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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)

  1. Advanced radio over fiber network technologies.

    PubMed

    Novak, Dalma; Waterhouse, Rod

    2013-09-23

    The evolution of wireless communication networks supporting emerging broadband services and applications offers new opportunities for realizing integrated optical and wireless network infrastructures. We report on some of our recent activities investigating advanced technologies for next generation converged optical wireless networks. Developments in Active Antenna Systems, mobile fronthaul architectures, and 60 GHz fiber distributed wireless networks are described. We also discuss the potential for analog radio over fiber distribution links as a viable solution for meeting the capacity requirements of new network architectures.

  2. Intelligent neural network classifier for automatic testing

    NASA Astrophysics Data System (ADS)

    Bai, Baoxing; Yu, Heping

    1996-10-01

    This paper is concerned with an application of a multilayer feedforward neural network for the vision detection of industrial pictures, and introduces a high characteristics image processing and recognizing system which can be used for real-time testing blemishes, streaks and cracks, etc. on the inner walls of high-accuracy pipes. To take full advantage of the functions of the artificial neural network, such as the information distributed memory, large scale self-adapting parallel processing, high fault-tolerance ability, this system uses a multilayer perceptron as a regular detector to extract features of the images to be inspected and classify them.

  3. 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.

  4. 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

  5. Advances in Intelligence Research: What Should be Expected in the XXI Century (Questions & Answers).

    PubMed

    Colom, Roberto

    2016-12-06

    Here I briefly delineate my view about the main question of this International Seminar, namely, what should we expecting from the XXI Century regarding the advancements in intelligence research. This view can be summarized as 'The Brain Connection' (TBC), meaning that neuroscience will be of paramount relevance for increasing our current knowledge related to the key question: why are some people smarter than others? We need answers to the issue of what happens in our brains when the genotype and the environment are integrated. The scientific community has devoted great research efforts, ranging from observable behavior to hidden genetics, but we are still far from having a clear general picture of what it means to be more or less intelligent. After the discussion held with the panel of experts participating in the seminar, it is concluded that advancements will be more solid and safe increasing the collaboration of scientists with shared research interests worldwide. Paralleling current sophisticated analyses of how the brain computes, nowadays science may embrace a network approach.

  6. Advanced Wireless Integrated Navy Network

    DTIC Science & Technology

    2005-03-01

    Basing visualization of wireless technologies, Ad Hoc networks , network protocols, real-time resource allocation, Ultra Wideband (UWB) communications...4.1 TIP #1: Distributed MIMO UWB sensor networks incorporating software radio 67 4.2 TIP #2: Close-in UWB wireless with applications to Sea- Basing 68...4.3 TIP #3: Secure Ad Hoc Networks 73 4.4 TIP #4: Integration of Close-in UWB wireless with ESM crane for Sea Basing applications 75 5. FINANCIAL REPORT

  7. 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.

  8. TIS: an Intelligent Gateway Computer for information and modeling networks. Overview

    SciTech Connect

    Hampel, V.E.; Bailey, C.; Kawin, R.A.; Lann, N.A.; McGrogan, S.K.; Scott, W.S.; Stammers, S.M.; Thomas, J.L.

    1983-08-01

    The Technology Information System (TIS) is being used 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 elsewhere, by means of a master directory and automated access procedures. Other geographically distributed information centers accessible through TIS include federal and commercial systems like DOE/RECON, NASA/RECON, DOD/DROLS, DOT/TIC, CIS, and DIALOG in the United States, the chemical information systems DARC in France, and DECHEMA in West Germany. New centers are added as required.

  9. 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

  10. 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.

  11. 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.

  12. Advanced Wireless Integrated Navy Network - AWINN

    DTIC Science & Technology

    2005-09-30

    progress report No. 3 on AWINN hardware and software configurations of smart, wideband, multi-function antennas , secure configurable platform, close-in...and Robust Networks Visualization of Wireless Technology and Ad Hoc Networks Technology Integration Projects The Advanced Antennas Group has completed a...comprehensive investigation of Wideband and Ultra Wideband (UWB) antennas for the AWINN projects. The investigation concluded that Tapered Slot

  13. 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

  14. 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.

  15. A fuzzy neural network for intelligent data processing

    NASA Astrophysics Data System (ADS)

    Xie, Wei; Chu, Feng; Wang, Lipo; Lim, Eng Thiam

    2005-03-01

    In this paper, we describe an incrementally generated fuzzy neural network (FNN) for intelligent data processing. This FNN combines the features of initial fuzzy model self-generation, fast input selection, partition validation, parameter optimization and rule-base simplification. A small FNN is created from scratch -- there is no need to specify the initial network architecture, initial membership functions, or initial weights. Fuzzy IF-THEN rules are constantly combined and pruned to minimize the size of the network while maintaining accuracy; irrelevant inputs are detected and deleted, and membership functions and network weights are trained with a gradient descent algorithm, i.e., error backpropagation. Experimental studies on synthesized data sets demonstrate that the proposed Fuzzy Neural Network is able to achieve accuracy comparable to or higher than both a feedforward crisp neural network, i.e., NeuroRule, and a decision tree, i.e., C4.5, with more compact rule bases for most of the data sets used in our experiments. The FNN has achieved outstanding results for cancer classification based on microarray data. The excellent classification result for Small Round Blue Cell Tumors (SRBCTs) data set is shown. Compared with other published methods, we have used a much fewer number of genes for perfect classification, which will help researchers directly focus their attention on some specific genes and may lead to discovery of deep reasons of the development of cancers and discovery of drugs.

  16. Advanced local area network concepts

    NASA Technical Reports Server (NTRS)

    Grant, Terry

    1985-01-01

    Development of a good model of the data traffic requirements for Local Area Networks (LANs) onboard the Space Station is the driving problem in this work. A parameterized workload model is under development. An analysis contract has been started specifically to capture the distributed processing requirements for the Space Station and then to develop a top level model to simulate how various processing scenarios can handle the workload and what data communication patterns result. A summary of the Local Area Network Extendsible Simulator 2 Requirements Specification and excerpts from a grant report on the topological design of fiber optic local area networks with application to Expressnet are given.

  17. Some recent advances of intelligent health monitoring systems for civil infrastructures in HIT

    NASA Astrophysics Data System (ADS)

    Ou, Jinping

    2005-06-01

    The intelligent health monitoring systems more and more become a technique for ensuring the health and safety of civil infrastructures and also an important approach for research of the damage accumulation or even disaster evolving characteristics of civil infrastructures, and attracts prodigious research interests and active development interests of scientists and engineers since a great number of civil infrastructures are planning and building each year in mainland China. In this paper, some recent advances on research, development nad implementation of intelligent health monitoring systems for civil infrastructuresin mainland China, especially in Harbin Institute of Technology (HIT), P.R.China. The main contents include smart sensors such as optical fiber Bragg grating (OFBG) and polivinyllidene fluoride (PVDF) sensors, fatigue life gauges, self-sensing mortar and carbon fiber reinforced polymer (CFRP), wireless sensor networks and their implementation in practical infrastructures such as offshore platform structures, hydraulic engineering structures, large span bridges and large space structures. Finally, the relative research projects supported by the national foundation agencies of China are briefly introduced.

  18. 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.

  19. Acoustic richness modulates the neural networks supporting intelligible speech processing.

    PubMed

    Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E

    2016-03-01

    The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high.

  20. Development of an intelligent wireless sensor network with mobile nodes

    NASA Astrophysics Data System (ADS)

    St. Pierre, Joseph; Michel, Howard E.

    2009-05-01

    Wireless sensor networks have become viable solutions to many commercial and military applications. This research focuses on utilizing the I-TRM to develop an architecture which supports adaptive, self-healing, and self-aware intelligent wireless sensor networks capable of supporting mobile nodes. Sensor subsystems are crucial in the development of projects to test complex systems such as the Future Combat System, a multi-layered system consisting of soldiers and 18 subsystems connected by a network. The proposed architecture utilizes the Sensor Web Enablement (SWE), a standard for sensor networks being developed by the Open Geospatial Consortium (OGC), and the Integrated Technical Reference Model (I-TRM), a multi-layered technical reference model consisting of a behavior-centric technical reference model, information-centric technical reference model, and control technical reference model. The designed architecture has been implemented on MPR2400CA motes using the nesC programming language. Preliminary results show the architecture meets needs of systems such as the Future Combat System. The architecture supports standard and tailored sensors, mobile and immobile sensors nodes, and is scalable. Also, functionality was implemented which produces adaptive, self-healing, and self-aware behavior in the wireless sensor network.

  1. Intelligent communication systems sensor scheduling based on network information

    NASA Astrophysics Data System (ADS)

    Blasch, Erik P.; Hoff, Andrew

    2004-04-01

    Increased reliance on data communications has driven the need for a higher capacity solution to transmit data. Many decision making problems include various types of data (i.e. video, text), which require an intelligent way to transfer the data across a communication system. Data fusion can be performed at the transmitting end to reduce the dimensionality of the data transferred; however if there are errors, the receiving end would have no way to search through the pedigree of information to correct the problem. Thus, a desired analysis is to be able to transfer all the data types, while achieving the "Quality of Service" metrics of throughput, delay, delay variation, probability of error, and cost. One way to solve this problem is by using the Asynchronous Transfer Mode network data scheduling. An ATM network allows multiple types of data to be sent over the same system with dynamic bandwidth allocation. The following paper provides a description of an intelligent scheduling model to enhance the capability to transmit data for fusion analysis.

  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. Self-Learning Intelligent Agents for Dynamic Traffic Routing on Transportation Networks

    NASA Astrophysics Data System (ADS)

    Sadek, Add; Basha, Nagi

    Intelligent Transportation Systems (ITS) are designed to take advantage of recent advances in communications, electronics, and Information Technology in improving the efficiency and safety of transportation systems. Among the several ITS applications is the notion of Dynamic Traffic Routing (DTR), which involves generating "optimal" routing recommendations to drivers with the aim of maximizing network utilizing. In this paper, we demonstrate the feasibility of using a self-learning intelligent agent to solve the DTR problem to achieve traffic user equilibrium in a transportation network. The core idea is to deploy an agent to a simulation model of a highway. The agent then learns by itself by interacting with the simulation model. Once the agent reaches a satisfactory level of performance, it can then be deployed to the real-world, where it would continue to learn how to refine its control policies over time. To test this concept in this paper, the Cell Transmission Model (CTM) developed by Carlos Daganzo of the University of California at Berkeley is used to simulate a simple highway with two main alternative routes. With the model developed, a Reinforcement Learning Agent (RLA) is developed to learn how to best dynamically route traffic, so as to maximize the utilization of existing capacity. Preliminary results obtained from our experiments are promising. RL, being an adaptive online learning technique, appears to have a great potential for controlling a stochastic dynamic systems such as a transportation system. Furthermore, the approach is highly scalable and applicable to a variety of networks and roadways.

  4. Adaptive link-layer intelligence for enhanced ad hoc networking

    NASA Astrophysics Data System (ADS)

    MacLennan, James; Walburg, Bill; Nevins, Larry; Hartup, David

    2005-05-01

    Networked radio systems that utilize self-forming, fault tolerant techniques offer needed communication functions for Homeland Security and Law Enforcement agencies. The use of an ad hoc mesh network architecture solves some of the problems inherent to the wireless physical layer such as interferers, multi-path fading, shadowing, and loss of line-of-site. These effects severely limit the performance of current 802.11 wireless network implementations. This paper describes the use of Adaptive Link-layer Intelligence for Enhanced ad hoc Networking. This technology enhances recognition and characterization of sources of wireless channel perturbations and predicts their effects on wireless link quality. Identifying and predicting channel problems at the link level improves dynamic route discovery, circumvents channel disruptions before they cause a link failure, and increases communications reliability and data rate. First Responders, Homeland Security, and Law Enforcement agencies operating in locations lacking infrastructure, such as Urban Search and Rescue (USAR) operations, can benefit from increased communications reliability in highly impaired channels that are typical in disaster response scenarios.

  5. Knowledge Discovery Using Bayesian Network Framework for Intelligent Telecommunication Network Management

    NASA Astrophysics Data System (ADS)

    Bashar, Abul; Parr, Gerard; McClean, Sally; Scotney, Bryan; Nauck, Detlef

    The ever-evolving nature of telecommunication networks has put enormous pressure on contemporary Network Management Systems (NMSs) to come up with improved functionalities for efficient monitoring, control and management. In such a context, the rapid deployments of Next Generation Networks (NGN) and their management requires intelligent, autonomic and resilient mechanisms to guarantee Quality of Service (QoS) to the end users and at the same time to maximize revenue for the service/network providers. We present a framework for evaluating a Bayesian Networks (BN) based Decision Support System (DSS) for assisting and improving the performance of a Simple Network Management Protocol (SNMP) based NMS. More specifically, we describe our methodology through a case study which implements the function of Call Admission Control (CAC) in a multi-class video conferencing service scenario. Simulation results are presented for a proof of concept, followed by a critical analysis of our proposed approach and its application.

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

    PubMed

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

    2016-08-26

    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.

  7. 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.

  8. 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.

  9. The Application of Neural Networks with Artificial Intelligence Technique in the Modeling of Industrial Processes

    NASA Astrophysics Data System (ADS)

    Saini, K. K.; Saini, Sanju

    2008-10-01

    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.

  10. 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.

  11. 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).

  12. 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.

  13. 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…

  14. 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

  15. 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.

  16. 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

  17. Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

    DTIC Science & Technology

    1987-10-01

    This was an instrumentation grant to purchase equipment of support of research in neural networks, information science , artificial intelligence, and applied mathematics. Computer lab equipment, motor control and robotics lab equipment, speech analysis equipment and computational vision equipment were purchased.

  18. 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.

  19. Advanced Materials Intelligent Processing Center (AMIPC): Manufacturing for Multi-Functionality

    DTIC Science & Technology

    2005-12-31

    through the development and use of Resin Transfer Molding ( RTM ) and Vacuum Assisted Resin Transfer Molding ( VARTM ) to address processing, sensing, and...intelligent processing has been advanced through the development and use of Resin Transfer Molding VRTM) and Vacuum Assisted Resin Transfer Molding ( VARTm ...16 Task 4B: Process Developments: Resin Bleeding During VARTM Infusion ....................... _18 Task 5

  20. What Is the Relationship between Emotional Intelligence and Administrative Advancement in an Urban School Division?

    ERIC Educational Resources Information Center

    Roberson, Elizabeth W.

    2010-01-01

    The purpose of this research was to study the relationship between emotional intelligence and administrative advancement in one urban school division; however, data acquired in the course of study may have revealed areas that could be further developed in future studies to increase the efficacy of principals and, perhaps, to inform the selection…

  1. Advancing satellite operations with intelligent graphical monitoring systems

    NASA Technical Reports Server (NTRS)

    Hughes, Peter M.; Shirah, Gregory W.; Luczak, Edward C.

    1993-01-01

    For nearly twenty-five years, spacecraft missions have been operated in essentially the same manner: human operators monitor displays filled with alphanumeric text watching for limit violations or other indicators that signal a problem. The task is performed predominately by humans. Only in recent years have graphical user interfaces and expert systems been accepted within the control center environment to help reduce operator workloads. Unfortunately, the development of these systems is often time consuming and costly. At the NASA Goddard Space Flight Center (GSFC), a new domain specific expert system development tool called the Generic Spacecraft Analyst Assistant (GenSAA) has been developed. Through the use of a highly graphical user interface and point-and-click operation, GenSAA facilitates the rapid, 'programming-free' construction of intelligent graphical monitoring systems to serve as real-time, fault-isolation assistants for spacecraft analysts. Although specifically developed to support real-time satellite monitoring, GenSAA can support the development of intelligent graphical monitoring systems in a variety of space and commercial applications.

  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. 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.

  4. 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

  5. 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.

  6. 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

  7. 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…

  8. 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…

  9. 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.

  10. 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

  11. Advanced Material Intelligent Processing Center: Next Generation Scalable Lean Manufacturing

    DTIC Science & Technology

    2012-09-04

    machines and have made significant advances to automated tape laying (ATL) and automated fiber placement (AFP) technologies. Companies are moving...beyond standard thermoplastic and thermoset prepregs and are looking at placing 00A prepregs as well as dry fabrics. Today. Automated Tape Laying (ATL...References [1] Michael N. Grimshaw, " Automated Tape Laying ." in ASM Handbook Vol. 21 Composites.. ASM International, 2001. [2] Obaid Younossi. Michael

  12. Context-Driven Decision Making in Network-Centric Operations: Agent-Based Intelligent Support

    DTIC Science & Technology

    2006-01-01

    SPIIRAS CKM Workshop (MIT, Cambridge, MA; January 24, 2006 Context-Driven Decision Making in Network-Centric Operations: Agent- Based Intelligent...Operations: Agent- Based Intelligent Support 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK...Enterprise and Multi-Agent Systems (Engineering and Physical Sciences Research Council, UK, 2003-2005) Ontology- Based New Order Code Generation for

  13. Predictive Network-Centric Intelligence: Toward a Total-Systems Transformation of Analysis and Assessment

    DTIC Science & Technology

    2006-09-15

    data are required to bring it to full fruition and prove its superiority to the inevitable legions of doubters. As Galileo Galilei could attest...0 Predictive Network-Centric Intelligence: Toward a Total-Systems Transformation of Analysis and Assessment Winner, 2006 Galileo ...Two previous Galileo papers also have called for the application of scientific method to intelligence assessment: Bruce, James: “Dynamic Adaptation

  14. Intelligent composting assisted by a wireless sensing network.

    PubMed

    López, Marga; Martinez-Farre, Xavier; Casas, Oscar; Quilez, Marcos; Polo, Jose; Lopez, Oscar; Hornero, Gemma; Pinilla, Mirta R; Rovira, Carlos; Ramos, Pedro M; Borges, Beatriz; Marques, Hugo; Girão, Pedro Silva

    2014-04-01

    Monitoring of the moisture and temperature of composting process is a key factor to obtain a quality product beyond the quality of raw materials. Current methodologies for monitoring these two parameters are time consuming for workers, sometimes not sufficiently reliable to help decision-making and thus are ignored in some cases. This article describes an advance on monitoring of composting process through a Wireless Sensor Network (WSN) that allows measurement of temperature and moisture in real time in multiple points of the composting material, the Compo-ball system. To implement such measurement capabilities on-line, a WSN composed of multiple sensor nodes was designed and implemented to provide the staff with an efficient monitoring composting management tool. After framing the problem, the objectives and characteristics of the WSN are briefly discussed and a short description of the hardware and software of the network's components are presented. Presentation and discussion of practical issues and results obtained with the WSN during a demonstration stage that took place in several composting sites concludes the paper.

  15. 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.

  16. 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

  17. Associations between the Antioxidant Network and Emotional Intelligence: A Preliminary Study

    PubMed Central

    Pesce, Mirko; Sergi, Maria R.; Rizzuto, Alessia; Tatangelo, Raffaella; Tommasi, Marco; Picconi, Laura; Balsamo, Michela; Gatta, Valentina; Stuppia, Liborio; Siegling, Alexander B.; Gökçen, Elif; Grilli, Alfredo; Saggino, Aristide

    2014-01-01

    Background Emotional intelligence (EI) can be broadly defined as the ability to cope with environmental demands. In the scientific research, however, there is not a univocal precise definition of EI and recent articles have underlined the necessity to explore its biological basis to advance understanding of the construct. The aim of study was to investigate if the antioxidant network may be associated with typical-performance or trait EI. Methods The study group consisted of 50 women (age, M = 25.10, SD = 3.87). Super Oxide Dismutase (SOD), Catalase (CAT), Glutathione Reductase (GR), and Glutathione Peroxidase (GPx) activities were evaluated on proteins extracted from Peripheral Blood Mononuclear Cells. Participants completed the Italian version of the EQ-i (Bar-On, 1997) as a measure of trait EI. Results We observed positive and significant correlations between some biological variables and EQ-i scores, and a significant predictive effect of CAT activity when controlling for related biological variables, age, and smoking. Conclusions Our preliminary study suggests that the antioxidant network may constitute some of trait EI's biological basis. In particular, CAT and the SOD/CAT ratio could be two biological variables involved in some specific components of EI. PMID:24983620

  18. 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.

  19. 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.

  20. 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.

  1. 77 FR 3544 - Meeting and Webinar on the Active Traffic and Demand Management and Intelligent Network Flow...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-24

    ... Management and Intelligent Network Flow Optimization Operational Concepts; Notice of Public Meeting AGENCY... Traffic and Demand Management (ADTM) and Intelligent Network Flow Optimization (INFLO) operational concepts. The ADTM meeting is scheduled for February 7, 2012, 8:30 a.m. to 4:30 p.m. followed by the...

  2. Advances in the Neuroscience of Intelligence: from Brain Connectivity to Brain Perturbation.

    PubMed

    Santarnecchi, Emiliano; Rossi, Simone

    2016-12-06

    Our view is that intelligence, as expression of the complexity of the human brain and of its evolutionary path, represents an intriguing example of "system level brain plasticity": tangible proofs of this assertion lie in the strong links intelligence has with vital brain capacities as information processing (i.e., pure, rough capacity to transfer information in an efficient way), resilience (i.e., the ability to cope with loss of efficiency and/or loss of physical elements in a network) and adaptability (i.e., being able to efficiently rearrange its dynamics in response to environmental demands). Current evidence supporting this view move from theoretical models correlating intelligence and individual response to systematic "lesions" of brain connectivity, as well as from the field of Noninvasive Brain Stimulation (NiBS). Perturbation-based approaches based on techniques as transcranial magnetic stimulation (TMS) and transcranial alternating current stimulation (tACS), are opening new in vivo scenarios which could allow to disclose more causal relationship between intelligence and brain plasticity, overcoming the limitations of brain-behavior correlational evidence.

  3. 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…

  4. Emerging Network Storage Management Standards for Intelligent Data Storage Subsystems

    NASA Technical Reports Server (NTRS)

    Podio, Fernando; Vollrath, William; Williams, Joel; Kobler, Ben; Crouse, Don

    1998-01-01

    This paper discusses the need for intelligent storage devices and subsystems that can provide data integrity metadata, the content of the existing data integrity standard for optical disks and techniques and metadata to verify stored data on optical tapes developed by the Association for Information and Image Management (AIIM) Optical Tape Committee.

  5. 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.

  6. 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

  7. 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.

  8. An Intelligent Control for the Distributed Flexible Network Photovoltaic System using Autonomous Control and Agent

    NASA Astrophysics Data System (ADS)

    Park, Sangsoo; Miura, Yushi; Ise, Toshifumi

    This paper proposes an intelligent control for the distributed flexible network photovoltaic system using autonomous control and agent. The distributed flexible network photovoltaic system is composed of a secondary battery bank and a number of subsystems which have a solar array, a dc/dc converter and a load. The control mode of dc/dc converter can be selected based on local information by autonomous control. However, if only autonomous control using local information is applied, there are some problems associated with several cases such as voltage drop on long power lines. To overcome these problems, the authors propose introducing agents to improve control characteristics. The autonomous control with agents is called as intelligent control in this paper. The intelligent control scheme that employs the communication between agents is applied for the model system and proved with simulation using PSCAD/EMTDC.

  9. Personal mobility and manipulation using robotics, artificial intelligence and advanced control.

    PubMed

    Cooper, Rory A; Ding, Dan; Grindle, Garrett G; Wang, Hongwu

    2007-01-01

    Recent advancements of technologies, including computation, robotics, machine learning, communication, and miniaturization technologies, bring us closer to futuristic visions of compassionate intelligent devices. The missing element is a basic understanding of how to relate human functions (physiological, physical, and cognitive) to the design of intelligent devices and systems that aid and interact with people. Our stakeholder and clinician consultants identified a number of mobility barriers that have been intransigent to traditional approaches. The most important physical obstacles are stairs, steps, curbs, doorways (doors), rough/uneven surfaces, weather hazards (snow, ice), crowded/cluttered spaces, and confined spaces. Focus group participants suggested a number of ways to make interaction simpler, including natural language interfaces such as the ability to say "I want a drink", a library of high level commands (open a door, park the wheelchair, ...), and a touchscreen interface with images so the user could point and use other gestures.

  10. 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.

  11. 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…

  12. 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.

  13. Intelligence Collection Targeting and Interdiction of Dark Networks

    DTIC Science & Technology

    2014-06-01

    means, dark network decision cycle , strategic interaction model. 15. NUMBER OF PAGES 83 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...analysis (Friedkin71), as well as spatial, longitudinal, and relation analysis of dark networks ( Krebs 2001; Bakker, Raab, Milward;72 Everton and

  14. 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.

  15. 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.

  16. 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.

  17. Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration

    PubMed Central

    Cole, Michael W.

    2016-01-01

    The human brain is able to exceed modern computers on multiple computational demands (e.g., language, planning) using a small fraction of the energy. The mystery of how the brain can be so efficient is compounded by recent evidence that all brain regions are constantly active as they interact in so-called resting-state networks (RSNs). To investigate the brain's ability to process complex cognitive demands efficiently, we compared functional connectivity (FC) during rest and multiple highly distinct tasks. We found previously that RSNs are present during a wide variety of tasks and that tasks only minimally modify FC patterns throughout the brain. Here, we tested the hypothesis that, although subtle, these task-evoked FC updates from rest nonetheless contribute strongly to behavioral performance. One might expect that larger changes in FC reflect optimization of networks for the task at hand, improving behavioral performance. Alternatively, smaller changes in FC could reflect optimization for efficient (i.e., small) network updates, reducing processing demands to improve behavioral performance. We found across three task domains that high-performing individuals exhibited more efficient brain connectivity updates in the form of smaller changes in functional network architecture between rest and task. These smaller changes suggest that individuals with an optimized intrinsic network configuration for domain-general task performance experience more efficient network updates generally. Confirming this, network update efficiency correlated with general intelligence. The brain's reconfiguration efficiency therefore appears to be a key feature contributing to both its network dynamics and general cognitive ability. SIGNIFICANCE STATEMENT The brain's network configuration varies based on current task demands. For example, functional brain connections are organized in one way when one is resting quietly but in another way if one is asked to make a decision. We found that

  18. 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.

  19. Relations between performance on the advance matrices and the EPI in high-intelligence subjects.

    PubMed

    Gibson, H B

    1975-11-01

    This study continues the investigation of the relationship between performance on tests of intelligence, and the personality parameters of the Eysenckian theoretical framework. Candidates for admission to an honours degree course (n = 281) were given the Advanced Progressive Matrices as a screening device. Those admitted to the course were on later occasions given both forms of the Eysenck Personality Inventory (EPI). In view of problems of test-retest on the EPI, scores were analysed in a novel fashion to give three groups: 'introverts', 'extraverts' and 'ambiverts'. The 'introverts' scored significantly highest on the Matrices, but the scores of the 'ambiverts' were lowest. Neuroticism showed little interaction with other variables. These results are discussed in terms of the theory of reactive inhibition. New data on the Advanced Progressive Matrices are given which are significantly higher than the published university norms.

  20. 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…

  1. 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.

  2. Intelligent segmentation of industrial radiographic images using neural networks

    NASA Astrophysics Data System (ADS)

    Lawson, Shaun W.; Parker, Graham A.

    1994-10-01

    An application of machine vision, incorporating neural networks, which aims to fully automate real-time radiographic inspection in welding process is described. The current methodology adopted comprises two distinct stages - the segmentation of the weld from the background content of the radiographic image, and the segmentation of suspect defect areas inside the weld region itself. In the first stage, a back propagation neural network has been employed to adaptively and accurately segment the weld region from a given image. The training of the network is achieved with a single image showing a typical weld in the run which is to be inspected, coupled with a very simple schematic weld 'template'. The second processing stage utilizes a further backpropagation network which is trained on a test set of image data previously segmented by a conventional adaptive threshold method. It is shown that the two techniques can be combined to fully segment radiographic weld images.

  3. 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

  4. 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.

  5. Recent advancements towards green optical networks

    NASA Astrophysics Data System (ADS)

    Davidson, Alan; Glesk, Ivan; Buis, Adrianus; Wang, Junjia; Chen, Lawrence

    2014-12-01

    Recent years have seen a rapid growth in demand for ultra high speed data transmission with end users expecting fast, high bandwidth network access. With this rapid growth in demand, data centres are under pressure to provide ever increasing data rates through their networks and at the same time improve the quality of data handling in terms of reduced latency, increased scalability and improved channel speed for users. However as data rates increase, present technology based on well-established CMOS technology is becoming increasingly difficult to scale and consequently data networks are struggling to satisfy current network demand. In this paper the interrelated issues of electronic scalability, power consumption, limited copper interconnect bandwidth and the limited speed of CMOS electronics will be explored alongside the tremendous bandwidth potential of optical fibre based photonic networks. Some applications of photonics to help alleviate the speed and latency in data networks will be discussed.

  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 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.

  8. 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.

  9. Advances in applications of spiking neuron networks

    NASA Astrophysics Data System (ADS)

    Cios, Krzysztof J.; Sala, Dorel M.

    2000-03-01

    In this paper, we present new findings in constructing and applications of artificial neural networks that use a biologically inspired spiking neuron model. The used model is a point neuron with the interaction between neurons described by postsynaptic potentials. The synaptic plasticity is achieved by using a temporal correlation learning rule, specified as a function of time difference between the firings of pre- and post-synaptic neurons. Using this rule we show how certain associations between neurons in a network of spiking neurons can be implemented. As an example we analyze the dynamic properties of networks of laterally connected spiking neurons and we show their capability to self-organize into topological maps in response to external stimulation. In another application we explore the capability networks of spiking neurons to solve graph algorithms by using temporal coding of distances in a given spatial configuration. The paper underlines the importance of temporal dimension in artificial neural network information processing.

  10. 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.

  11. 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.

  12. Advanced routing in interplanetary backbone network

    NASA Astrophysics Data System (ADS)

    Xu, Ge; Sheng, Min; Wu, Chengke

    2007-11-01

    Interplanetary (IPN) Internet is a communication infrastructure providing communication services for scientific data delivery and navigation services for the explorer spacecrafts and orbiters of the future deep space missions. The interplanetary backbone network has the unique characteristics hence routing through the backbone network present many challenges that are not presented in traditional networks. Some routing algorithms have been proposed, in which, LPDB integrates the shortest path algorithm and the directional broadcast method to guarantee fast and reliable message delivery. Through this mutipath routing strategy, unpredictable link failures is addressed, but additional network overhead is introduced. In this paper, we propose an improvement of the LPDB named ALPDB in which the source could adaptively decide the next-hop nodes according to the link condition, hence reduce the network overhead. We model this algorithm on the network simulation platform of OPNET and compare it with other applicable algorithms in data passing ratio, data delay and network overhead. The result indicates that the ALPDB algorithm could not only guarantee reliable message delivery, but also decrease the cost significantly.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Recent Research in Artificial Intelligence, Heuristic Programming, and Network Protocols

    DTIC Science & Technology

    1974-07-01

    and Joshua Lederberg , Co-principal Investigators NETWORK PROTOCOL DEVELOPMENT PROJECT Vinton Cerf, Principal Investigator ABSTRACT This is a...by Edward Feigenbaum, Professor of Computer Science, and Joshua Lederberg , Professor of Genetics, and was initially an element of the Artificial...Quam, J. Lederberg , E. Levinthal. R. Tucker, B. Eros». J. Pollack. Variable Features on Mars II: Mariner 9 Global Results, Journal of Geophysical

  18. Interaction and intelligence in living neuronal networks interfaced with moving robot

    NASA Astrophysics Data System (ADS)

    Kudoh, Suguru N.; Taguchi, Takahisa

    2006-01-01

    Neurons form complex networks and it seems that the living neuronal network can perform certain type of information processing. We are interested in intelligence autonomously formed in vitro. The most important features of the two-dimensional culture neural network are that it is a system in which the information processing is autonomously carries out. We reported previously that the functional connections were dynamically modified by synaptic potentiation and the process may be required for reorganization of the functional group of neurons. Such neuron assemblies are critical for information processing in brain. Certain types of feedback stimulation caused suppression of spontaneous network electrical activities and drastic re-organization of functional connections between neurons, when these activities are initially almost synchronized. The result suggests that neurons in dissociated culture autonomously re-organized their functional neuronal networks interacted with their environment. The spatio-temporal pattern of activity in the networks may be a reflection of their external environment. We also interfaced the cultured neuronal network with moving robot. The planar microelectrodes can be used for detecting neuronal electrical signals from the living neuronal network cultured on a 2-dimensional electrode array. The speed of actuators of moving robot was determined by these detected signals. Our goal is reconstruction of the neural network, which can process "thinking" in the dissociated culture system.

  19. The Deep Space Network Advanced Systems Program

    NASA Technical Reports Server (NTRS)

    Davarian, Faramaz

    2010-01-01

    The deep space network (DSN)--with its three complexes in Goldstone, California, Madrid, Spain, and Canberra, Australia--provides the resources to track and communicate with planetary and deep space missions. Each complex consists of an array of capabilities for tracking probes almost anywhere in the solar system. A number of innovative hardware, software and procedural tools are used for day-to-day operations at DSN complexes as well as at the network control at the Jet Propulsion Laboratory (JPL). Systems and technologies employed by the network include large-aperture antennas (34-m and 70-m), cryogenically cooled receivers, high-power transmitters, stable frequency and timing distribution assemblies, modulation and coding schemes, spacecraft transponders, radiometric tracking techniques, etc. The DSN operates at multiple frequencies, including the 2-GHz band, the 7/8-GHz band, and the 32/34-GHz band.

  20. 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.

  1. 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

  2. Self-Calibration and Optimal Response in Intelligent Sensors Design Based on Artificial Neural Networks

    PubMed Central

    Rivera, José; Carrillo, Mariano; Chacón, Mario; Herrera, Gilberto; Bojorquez, Gilberto

    2007-01-01

    The development of smart sensors involves the design of reconfigurable systems capable of working with different input sensors. Reconfigurable systems ideally should spend the least possible amount of time in their calibration. An autocalibration algorithm for intelligent sensors should be able to fix major problems such as offset, variation of gain and lack of linearity, as accurately as possible. This paper describes a new autocalibration methodology for nonlinear intelligent sensors based on artificial neural networks, ANN. The methodology involves analysis of several network topologies and training algorithms. The proposed method was compared against the piecewise and polynomial linearization methods. Method comparison was achieved using different number of calibration points, and several nonlinear levels of the input signal. This paper also shows that the proposed method turned out to have a better overall accuracy than the other two methods. Besides, experimentation results and analysis of the complete study, the paper describes the implementation of the ANN in a microcontroller unit, MCU. In order to illustrate the method capability to build autocalibration and reconfigurable systems, a temperature measurement system was designed and tested. The proposed method is an improvement over the classic autocalibration methodologies, because it impacts on the design process of intelligent sensors, autocalibration methodologies and their associated factors, like time and cost.

  3. 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.

  4. TALON: the telescope alert operation network system: intelligent linking of distributed autonomous robotic telescopes

    NASA Astrophysics Data System (ADS)

    White, Robert R.; Wren, James; Davis, Heath R.; Galassi, Mark; Starr, Daniel; Vestrand, W. T.; Wozniak, P.

    2004-09-01

    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 efficiently 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Cooperation and the evolution of intelligence.

    PubMed

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

    2012-08-07

    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.

  11. 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.

  12. 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

  13. 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.

  14. Advanced Plasma Diagnostic Analysis using Neural Networks

    NASA Astrophysics Data System (ADS)

    Tritz, Kevin; Reinke, Matt

    2016-10-01

    Machine learning techniques, specifically neural networks (NN), are used with sufficient internal complexity to develop an empirically weighted relationship between a set of filtered X-ray emission measurements and the electron temperature (Te) profile for a specific class of discharges on NSTX. The NN response matrix is used to calculate the Te profile directly from the filtered X-ray diode measurements which extends the electron temperature time response from the 60Hz Thomson Scattering profile measurements to fast timescales (>10kHz) and greatly expands the applicability of Te profile information to fast plasma phenomena, such as ELM dynamics. This process can be improved by providing additional information which helps the neural network refine the relationship between Te and the corresponding X-ray emission. NN supplement limited measurements of a particular quantity using related measurements with higher time or spatial resolution. For example, the radiated power (Prad) determined using resistive foil bolometers is related to similar measurements using AXUV diode arrays through a complex and slowly time-evolving quantum efficiency curve in the VUV spectral region. Results from a NN trained using Alcator C-Mod resistive foil bolometry and AXUV diodes are presented, working towards hybrid Prad measurements with the quantitative accuracy of resistive foil bolometers and with the enhanced temporal and spatial resolution of the unfiltered AXUV diode arrays. Work supported by Department of Energy Grant #: DE-FG02-09ER55012.

  15. 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

  16. 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.

  17. Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.

    PubMed

    Goehring, Tobias; Bolner, Federico; Monaghan, Jessica J M; van Dijk, Bas; Zarowski, Andrzej; Bleeck, Stefan

    2017-02-01

    Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices.

  18. 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.

  19. Fuzzy mobile-robot positioning in intelligent spaces using wireless sensor networks.

    PubMed

    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.

  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. Communications and Intelligent Systems Division Overview

    NASA Technical Reports Server (NTRS)

    Emerson, Dawn

    2017-01-01

    Provides expertise, and plans, conducts and directs research and engineering development in the competency fields of advanced communications and intelligent systems technologies for applications in current and future aeronautics and space systems.Advances communication systems engineering, development and analysis needed for Glenn Research Center's leadership in communications and intelligent systems technology. Focus areas include advanced high frequency devices, components, and antennas; optical communications, health monitoring and instrumentation; digital signal processing for communications and navigation, and cognitive radios; network architectures, protocols, standards and network-based applications; intelligent controls, dynamics and diagnostics; and smart micro- and nano-sensors and harsh environment electronics. Research and discipline engineering allow for the creation of innovative concepts and designs for aerospace communication systems with reduced size and weight, increased functionality and intelligence. Performs proof-of-concept studies and analyses to assess the impact of the new technologies.

  3. A uniform instrumentation, event, and adaptation framework for network-aware middleware and advanced network applications

    SciTech Connect

    Reed, Daniel A.

    2003-03-14

    Developers of advanced network applications such as remote instrument control, distributed data management, tele-immersion and collaboration, and distributed computing face a daunting challenge: sustaining robust application performance despite time-varying resource demands and dynamically changing resource availability. It is widely recognized that network-aware middleware is key to achieving performance robustness.

  4. A Survey of Geosensor Networks: Advances in Dynamic Environmental Monitoring

    PubMed Central

    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

  5. 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.

  6. Do Narcissism and Emotional Intelligence Win Us Friends? Modeling Dynamics of Peer Popularity Using Inferential Network Analysis.

    PubMed

    Czarna, Anna Z; Leifeld, Philip; Śmieja, Magdalena; Dufner, Michael; Salovey, Peter

    2016-09-27

    This research investigated effects of narcissism and emotional intelligence (EI) on popularity in social networks. In a longitudinal field study, we examined the dynamics of popularity in 15 peer groups in two waves (N = 273). We measured narcissism, ability EI, and explicit and implicit self-esteem. In addition, we measured popularity at zero acquaintance and 3 months later. We analyzed the data using inferential network analysis (temporal exponential random graph modeling, TERGM) accounting for self-organizing network forces. People high in narcissism were popular, but increased less in popularity over time than people lower in narcissism. In contrast, emotionally intelligent people increased more in popularity over time than less emotionally intelligent people. The effects held when we controlled for explicit and implicit self-esteem. These results suggest that narcissism is rather disadvantageous and that EI is rather advantageous for long-term popularity.

  7. 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.

  8. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    NASA Astrophysics Data System (ADS)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

  9. 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.

  10. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    PubMed Central

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model. PMID:28120889

  11. 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

  12. 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.

  13. Intelligent buildings.

    PubMed

    Williams, W E

    1987-01-01

    The maturing of technologies in computer capabilities, particularly direct digital signals, has provided an exciting variety of new communication and facility control opportunities. These include telecommunications, energy management systems, security systems, office automation systems, local area networks, and video conferencing. New applications are developing continuously. The so-called "intelligent" or "smart" building concept evolves from the development of this advanced technology in building environments. Automation has had a dramatic effect on facility planning. For decades, communications were limited to the telephone, the typewritten message, and copy machines. The office itself and its functions had been essentially unchanged for decades. Office automation systems began to surface during the energy crisis and, although their newer technology was timely, they were, for the most part, designed separately from other new building systems. For example, most mainframe computer systems were originally stand-alone, as were word processing installations. In the last five years, the advances in distributive systems, networking, and personal computer capabilities have provided opportunities to make such dramatic improvements in productivity that the Selectric typewriter has gone from being the most advanced piece of office equipment to nearly total obsolescence.

  14. 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…

  15. Advances, experiences, and prospects of the International Soil Moisture Network

    NASA Astrophysics Data System (ADS)

    Dorigo, W.; van Oevelen, P. J.; Drusch, M.; Wagner, W.; Scipal, K.; Mecklenburg, S.

    2012-12-01

    In 2009, the International Soil Moisture Network (ISMN; http:www.ipf.tuwien.ac.at) was initiated as a platform to support calibration and validation of soil moisture products from remote sensing and land surface models, and to advance studies on the behavior of soil moisture over space and time. This international initiative is fruit of continuing coordinative efforts of the Global Energy and Water Cycle Experiment (GEWEX) in cooperation with the Group of Earth Observation (GEO) and the Committee on Earth Observation Satellites (CEOS). The decisive financial incentive was given by the European Space Agency (ESA) who considered the establishment of the network critical for optimizing the soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. The ISMN collects and harmonizes ground-based soil moisture data sets from a large variety of individually operating networks and makes them available through a centralized data portal. Meanwhile, almost 6000 soil moisture data sets from over 1300 sites, distributed among 34 networks worldwide, are contained in the database. The steadily increasing number of organizations voluntarily contributing to the ISMN, and the rapidly increasing number of studies based on the network show that the portal has been successful in reaching its primary goal to promote easy data accessibility to a wide variety of users. Recently, several updates of the system were performed to keep up with the increasing data amount and traffic, and to meet the requirements of many advanced users. Many datasets from operational networks (e.g., SCAN, the US Climate Reference Network, COSMOS, and ARM) are now assimilated and processed in the ISMN on a fully automated basis in near-real time. In addition, a new enhanced quality control system is currently being implemented. This presentation gives an overview of these recent developments, presents some examples of important scientific results based on the ISMN, and sketches an outlook for

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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,…

  2. Experimental studies on intelligent fault detection and diagnosis using sensor networks on mechanical pneumatic systems

    NASA Astrophysics Data System (ADS)

    Zhang, Kunbo; Kao, Imin; Kambli, Sachin; Boehm, Christian

    2008-03-01

    Fault is a undesirable factor in any mechanical/pneumatic system. It affects the efficiency of system operation and reduces economic benefit in industry. The early detection and diagnosis of faults in a mechanical system becomes important for preventing failure of equipment and loss of productivity and profits. In this paper, we present our ongoing research results on intelligent fault detections and diagnosis (FDD) on mechanical/ pneumatic systems. Using data from sensors and sensor network in an integrated industrial system, our proposed FDD methodology provides the analysis of necessary sensory information (for example, flow rates and pressure, as well as other digital sensor data) for the detection and diagnosis of system fault. In this experimental study, the leakage of pneumatic cylinder was the "fault." It was shown that the FDD analysis was able to make diagnosis of leakage both in location and size of the fault. In addition, the systematic fault and localized faults can be detected separately. The proposed wavelet method gives rise to the fingerprint analysis to recognize the patterns of the flow rate and pressure data - a very useful tool in intelligent fault detection and diagnosis.

  3. 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.

  4. A novel electronic device for high speed WDM optical network operations capable of intelligent routing based on simulated electrical network approach

    NASA Astrophysics Data System (ADS)

    Sen, Soumya; Chaubey, V. K.

    2005-04-01

    In this paper, we propose the design of an electronic circuit that maps the whole optical system into the electronic domain and helps in intelligent routing by using simulated electrical network approach (SENA) method. The losses of a linear optical network due to the losses in propagation over the wavelengths and related optical components are modeled as resistances in order to simulate an equivalent electrical network. The concept used in SENA is that current flows in the path of least resistance, which provides a simulation tool to evaluate the optical path with a minimum loss. The developed model has been used to implement an intelligent routing algorithm to find the optimal path without going for time-consuming recursive algorithms for evaluating all possible path combinations. A novel modeling method incorporating some logic control circuitry and memory has been developed to achieve the best optimized path in WDM network.

  5. 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

    2016-08-15

    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.

  6. An intelligent load shedding scheme using neural networks and neuro-fuzzy.

    PubMed

    Haidar, Ahmed M A; Mohamed, Azah; Al-Dabbagh, Majid; Hussain, Aini; Masoum, Mohammad

    2009-12-01

    Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power supply. This was confirmed by the results obtained in this research of which sample results are given in this paper.

  7. Neural networks predict protein folding and structure: artificial intelligence faces biomolecular complexity.

    PubMed

    Casadio, R; Compiani, M; Fariselli, P; Jacoboni, I; Martelli, P L

    2000-01-01

    In the genomic era DNA sequencing is increasing our knowledge of the molecular structure of genetic codes from bacteria to man at a hyperbolic rate. Billions of nucleotides and millions of aminoacids are already filling the electronic files of the data bases presently available, which contain a tremendous amount of information on the most biologically relevant macromolecules, such as DNA, RNA and proteins. The most urgent problem originates from the need to single out the relevant information amidst a wealth of general features. Intelligent tools are therefore needed to optimise the search. Data mining for sequence analysis in biotechnology has been substantially aided by the development of new powerful methods borrowed from the machine learning approach. In this paper we discuss the application of artificial feedforward neural networks to deal with some fundamental problems tied with the folding process and the structure-function relationship in proteins.

  8. On the Need for Artificial Intelligence and Advanced Test and Evaluation Methods for Space Exploration

    NASA Astrophysics Data System (ADS)

    Scheidt, D. H.; Hibbitts, C. A.; Chen, M. H.; Paxton, L. J.; Bekker, D. L.

    2017-02-01

    Implementing mature artificial intelligence would create the ability to significantly increase the science return from a mission, while potentially saving costs in mission and instrument operations, and solving currently intractable problems.

  9. 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.

  10. 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

  11. A new efficient hybrid intelligent method for nonlinear dynamical systems identification: The Wavelet Kernel Fuzzy Neural Network

    NASA Astrophysics Data System (ADS)

    Loussifi, Hichem; Nouri, Khaled; Benhadj Braiek, Naceur

    2016-03-01

    In this paper a hybrid computational intelligent approach of combining kernel methods with wavelet Multi-resolution Analysis (MRA) is presented for fuzzy wavelet network construction and initialization. Mother wavelets are used as activation functions for the neural network structure, and as kernel functions in the machine learning process. By choosing precise values of scale parameters based on the windowed scalogram representation of the Continuous Wavelet Transform (CWT), a set of kernel parameters is taken to construct the proposed Wavelet Kernel based Fuzzy Neural Network (WK-FNN) with an efficient initialization technique based on the use of wavelet kernels in Support Vector Machine for Regression (SVMR). Simulation examples are given to test usability and effectiveness of the proposed hybrid intelligent method in the system identification of dynamic plants and in the prediction of a chaotic time series. It is seen that the proposed WK-FNN achieves higher accuracy and has good performance as compared to other methods.

  12. A Quantitative Methodology for Vetting Dark Network Intelligence Sources for Social Network Analysis

    DTIC Science & Technology

    2012-06-01

    introduced by Granovetter ( 1976 ) as a method to hurdle the requisite data collection efforts common to Social Network Analysis . His sampling method... 1976 ). Factor Regression Analysis : A New Method for Weighting Predictors. Defense Technical Information Center. de Leeuw, J., & Mair, P. (2009... ANALYSIS DISSERTATION James F. Morris AFIT/DS/ENS/12-05 The views expressed in this dissertation are those of the author and do not

  13. Processors, Pipelines, and Protocols for Advanced Modeling Networks

    NASA Technical Reports Server (NTRS)

    Coughlan, Joseph; Komar, George (Technical Monitor)

    2001-01-01

    Predictive capabilities arise from our understanding of natural processes and our ability to construct models that accurately reproduce these processes. Although our modeling state-of-the-art is primarily limited by existing computational capabilities, other technical areas will soon present obstacles to the development and deployment of future predictive capabilities. Advancement of our modeling capabilities will require not only faster processors, but new processing algorithms, high-speed data pipelines, and a common software engineering framework that allows networking of diverse models that represent the many components of Earth's climate and weather system. Development and integration of these new capabilities will pose serious challenges to the Information Systems (IS) technology community. Designers of future IS infrastructures must deal with issues that include performance, reliability, interoperability, portability of data and software, and ultimately, the full integration of various ES model systems into a unified ES modeling network.

  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. 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.

  16. 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

  17. 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.

  18. Advanced Scientific Computing Research Network Requirements: ASCR Network Requirements Review Final Report

    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.

  19. 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.

  20. 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.

  1. An Analysis of Collaborative Technology Advancements Achieved through the Center for Network Innovation and Experimentation

    DTIC Science & Technology

    2008-12-01

    COLLABORATIVE TECHNOLOGY ADVANCEMENTS ACHIEVED THROUGH THE CENTER FOR NETWORK INNOVATION AND EXPERIMENTATION by Eric L. Quarles December 2008...Advancements Achieved through the Center for Network Innovation and Experimentation 6. AUTHOR(S) Eric L. Quarles 5. FUNDING NUMBERS 7...cycles which the members of the Naval Postgraduate School Center for Network Innovation and Experimentation (CENETIX) participate. These experiments

  2. The Managing Epilepsy Well Network:: Advancing Epilepsy Self-Management.

    PubMed

    Sajatovic, Martha; Jobst, Barbara C; Shegog, Ross; Bamps, Yvan A; Begley, Charles E; Fraser, Robert T; Johnson, Erica K; Pandey, Dilip K; Quarells, Rakale C; Scal, Peter; Spruill, Tanya M; Thompson, Nancy J; Kobau, Rosemarie

    2017-03-01

    Epilepsy, a complex spectrum of disorders, affects about 2.9 million people in the U.S. Similar to other chronic disorders, people with epilepsy face challenges related to management of the disorder, its treatment, co-occurring depression, disability, social disadvantages, and stigma. Two national conferences on public health and epilepsy (1997, 2003) and a 2012 IOM report on the public health dimensions of epilepsy highlighted important knowledge gaps and emphasized the need for evidence-based, scalable epilepsy self-management programs. The Centers for Disease Control and Prevention translated recommendations on self-management research and dissemination into an applied research program through the Prevention Research Centers Managing Epilepsy Well (MEW) Network. MEW Network objectives are to advance epilepsy self-management research by developing effective interventions that can be broadly disseminated for use in people's homes, healthcare providers' offices, or in community settings. The aim of this report is to provide an update on the MEW Network research pipeline, which spans efficacy, effectiveness, and dissemination. Many of the interventions use e-health strategies to eliminate barriers to care (e.g., lack of transportation, functional limitations, and stigma). Strengths of this mature research network are the culture of collaboration, community-based partnerships, e-health methods, and its portfolio of prevention activities, which range from efficacy studies engaging hard-to-reach groups, to initiatives focused on provider training and knowledge translation. The MEW Network works with organizations across the country to expand its capacity, help leverage funding and other resources, and enhance the development, dissemination, and sustainability of MEW Network programs and tools. Guided by national initiatives targeting chronic disease or epilepsy burden since 2007, the MEW Network has been responsible for more than 43 scientific journal articles, two

  3. 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…

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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

    2015-11-11

    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.

  10. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    PubMed Central

    Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

  11. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend.

    PubMed

    Inthachot, Montri; Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

  12. 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

  13. 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

  14. 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.

  15. Advances in Ground Transmitters for the NASA Deep Space Network

    NASA Technical Reports Server (NTRS)

    Vodonos, Yakov I.; Conroy, Bruce L.; Losh, David L.; Silva, Arnold

    2007-01-01

    The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, is equipped with multiple microwave transmitters ranging in average radiated power from 200 W to 400 kW. The transmitters are used for routine or emergency communication with spacecraft, for navigation, and for radio science tasks. The latest advances in transmitter engineering were implemented in a new generation of 20-kW dual-band transmitters developed for the DSN 34-m beam waveguide antennas. Innovations include additional X-band communication capability for near Earth missions, new control algorithms, automated calibration, improved and expanded computerized monitoring and diagnostics, reduced cabling, and improved maintainability. The innovations were very beneficial for the DSN 'overload' during the Mars 2003/2004 missions and will benefit other missions throughout the next decade. This paper describes the current design of the new transmitters and possible future developments.

  16. 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

  17. 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.

  18. Advanced stoichiometric analysis of metabolic networks of mammalian systems.

    PubMed

    Orman, Mehmet A; Berthiaume, Francois; Androulakis, Ioannis P; Ierapetritou, Marianthi G

    2011-01-01

    Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted.

  19. 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.

  20. Northeast Artificial Intelligence Consortium annual report 1986. Volume 3. Distributed artificial intelligence for communication network management. Interim report, January-December 1986

    SciTech Connect

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

    1988-06-01

    The Northeast Consortium conducts pertinent research in artificial intelligence and performs activities ancillary to this research. This report describes progress made in the second year of the existence of the consortium 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 photo interpretation, 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. A new stochastic technique for Painlevé equation-I using neural network optimized with swarm intelligence.

    PubMed

    Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Ahmad, Siraj-ul-Islam; Qureshi, Ijaz Mansoor

    2012-01-01

    A methodology for solution of Painlevé equation-I is presented using computational intelligence technique based on neural networks and particle swarm optimization hybridized with active set algorithm. The mathematical model of the equation is developed with the help of linear combination of feed-forward artificial neural networks that define the unsupervised error of the model. This error is minimized subject to the availability of appropriate weights of the networks. The learning of the weights is carried out using particle swarm optimization algorithm used as a tool for viable global search method, hybridized with active set algorithm for rapid local convergence. The accuracy, convergence rate, and computational complexity of the scheme are analyzed based on large number of independents runs and their comprehensive statistical analysis. The comparative studies of the results obtained are made with MATHEMATICA solutions, as well as, with variational iteration method and homotopy perturbation method.

  6. A New Stochastic Technique for Painlevé Equation-I Using Neural Network Optimized with Swarm Intelligence

    PubMed Central

    Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Ahmad, Siraj-ul-Islam; Qureshi, Ijaz Mansoor

    2012-01-01

    A methodology for solution of Painlevé equation-I is presented using computational intelligence technique based on neural networks and particle swarm optimization hybridized with active set algorithm. The mathematical model of the equation is developed with the help of linear combination of feed-forward artificial neural networks that define the unsupervised error of the model. This error is minimized subject to the availability of appropriate weights of the networks. The learning of the weights is carried out using particle swarm optimization algorithm used as a tool for viable global search method, hybridized with active set algorithm for rapid local convergence. The accuracy, convergence rate, and computational complexity of the scheme are analyzed based on large number of independents runs and their comprehensive statistical analysis. The comparative studies of the results obtained are made with MATHEMATICA solutions, as well as, with variational iteration method and homotopy perturbation method. PMID:22919371

  7. A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment

    PubMed Central

    Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

    2016-01-01

    We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot’s performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks. PMID:27806074

  8. A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment.

    PubMed

    Li, Yongcheng; Sun, Rong; Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

    2016-01-01

    We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.

  9. 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…

  10. 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

  11. 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.

  12. INDIRECT INTELLIGENT SLIDING MODE CONTROL OF A SHAPE MEMORY ALLOY ACTUATED FLEXIBLE BEAM USING HYSTERETIC RECURRENT NEURAL NETWORKS

    PubMed Central

    Hannen, Jennifer C.; Crews, John H.; Buckner, Gregory D.

    2012-01-01

    This paper introduces an indirect intelligent sliding mode controller (IISMC) for shape memory alloy (SMA) actuators, specifically a flexible beam deflected by a single offset SMA tendon. The controller manipulates applied voltage, which alters SMA tendon temperature to track reference bending angles. A hysteretic recurrent neural network (HRNN) captures the nonlinear, hysteretic relationship between SMA temperature and bending angle. The variable structure control strategy provides robustness to model uncertainties and parameter variations, while effectively compensating for system nonlinearities, achieving superior tracking compared to an optimized PI controller. PMID:22962538

  13. 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.

  14. 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

  15. 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.

  16. 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…

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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…

  2. 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.

  3. Battlefield Acoustic Sensing, Multimodal Sensing, and Networked Sensing for Intelligence, Surveillance, and Reconnaissance (ISR) Applications

    DTIC Science & Technology

    2015-09-01

    Intelligence, Surveillance, and Reconnaissance (ISR) Applications by Latasha Solomon, Wesley Wang, and Miriam Häge...Surveillance, and Reconnaissance (ISR) Applications by Latasha Solomon Sensors and Electron Devices Directorate, ARL Wesley Wang...Latasha Solomon, Wesley Wang, and Miriam Hӓge 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S

  4. 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.

  5. Advanced Multiple In-Multiple Out (MIMO) Antenna Communications for Airborne Networks

    DTIC Science & Technology

    2015-03-01

    ADVANCED MULTIPLE IN-MULTIPLE OUT (MIMO) ANTENNA COMMUNICATIONS FOR AIRBORNE NETWORKS SYRACUSE UNIVERSITY MARCH 2015 FINAL TECHNICAL REPORT...TECHNICAL REPORT 3. DATES COVERED (From - To) OCT 2011 – SEP 2014 4. TITLE AND SUBTITLE ADVANCED MULTIPLE IN-MULTIPLE OUT (MIMO) ANTENNA ...MIMO system with over the air transmission. 15. SUBJECT TERMS Multiple In-Multiple Out (MIMO Antenna Communications, Airborne Networks, D-BLAST

  6. 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.

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

    SciTech Connect

    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 loose 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.

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

    DOE PAGES

    Li, Qiaoxi; Zhou, Jing; Vatankhah-Varnoosfaderani, Mohammad; ...

    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

  9. The 17th Annual Intelligent Ground Vehicle Competition: intelligent robots built by intelligent students

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.

    2010-01-01

    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 ground vehicle. Teams from around the world focus on developing a suite of dual-use technologies to equip their system of the future with intelligent driving capabilities. Over the past 17 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 70 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.

  10. The 16th annual intelligent ground vehicle competition: intelligent students creating intelligent vehicles

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.

    2009-01-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. 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 16 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 nearly 70 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.

  11. The 14 TH Annual Intelligent Ground Vehicle Competition: intelligent teams creating intelligent ground robots

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.; Nguyen, Dmitri

    2006-10-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. 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 14 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 50 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 three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

  12. The 13 th Annual Intelligent Ground Vehicle Competition: intelligent ground vehicles created by intelligent teams

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.

    2005-10-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. 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 13 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 50 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 three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

  13. The 15 TH annual intelligent ground vehicle competition: intelligent ground robots created by intelligent students

    NASA Astrophysics Data System (ADS)

    Theisen, Bernard L.

    2007-09-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. 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 15 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 50 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.

  14. 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.

  15. Advanced metrics for network-centric naval operations

    NASA Astrophysics Data System (ADS)

    Perry, Walter L.; Bowden, Fred D. J.

    2003-07-01

    Defense organizations around the world are formulating new visions, strategies, and concepts that utilize emerging information-age technologies. Central among these is network-based operations. Measures and metrics are needed that allow analysts to link the effects of alternative network structures, operating procedures and command and control arrangements to combat outcomes. This paper reports on measures and mathematical metrics that begin to address this problem. Networks are assessed in terms of their complexity, their ability to adapt, and the collaboration opportunity they afford. The metrics measure the contributions of complexity to information flow, and the deleterious effects of information overload and disconfirming reports to overall network performance. In addition, they measure the contributions of collaboration to shared situational awareness in terms of the accuracy and precision of the information produced and the costs associated with an imbalance of the two. We posit a fixed network connecting a Naval Task Force"s various platforms, and assess the ability of this network to support the range of missions required of the task force. The emphasis is not on connectivity, but rather on information flow and how well the network is able to adapt to alternative flow requirements. We assess the impact alternative network structures, operating procedures and command arrangements have on combat outcomes by applying the metrics to a cruise missile defense scenario.

  16. Advanced Neural Network Modeling of Synthetic Jet Flow Fields

    DTIC Science & Technology

    2006-03-01

    The purpose of this research was to continue development of a neural network -based, lumped deterministic source term (LDST) approximation module for...main exploration involved the grid sensitivity of the neural network model. A second task was originally planned on the portability of the approach to

  17. 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…

  18. 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

  19. 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.

  20. 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

  1. Statistical inference to advance network models in epidemiology.

    PubMed

    Welch, David; Bansal, Shweta; Hunter, David R

    2011-03-01

    Contact networks are playing an increasingly important role in the study of epidemiology. Most of the existing work in this area has focused on considering the effect of underlying network structure on epidemic dynamics by using tools from probability theory and computer simulation. This work has provided much insight on the role that heterogeneity in host contact patterns plays on infectious disease dynamics. Despite the important understanding afforded by the probability and simulation paradigm, this approach does not directly address important questions about the structure of contact networks such as what is the best network model for a particular mode of disease transmission, how parameter values of a given model should be estimated, or how precisely the data allow us to estimate these parameter values. We argue that these questions are best answered within a statistical framework and discuss the role of statistical inference in estimating contact networks from epidemiological data.

  2. Intelligence Networks and the Tri Border Area of South America: The Dilemma of Efficiency Versus Oversight

    DTIC Science & Technology

    2002-12-01

    Guzman of Sendero Luminoso, or Carlos the Jackal . One may not even exist. Therefore, past strategies that worked successfully against an...terrorist Carlos the Jackal . A paid informant who was instrumental in Carlos’ capture was a terrorist within his cell on the CIA’s payroll.40 The use of...p. 3 147 Golden , p. 2 148 The Economist (London) Nov 3, 2001 vol 361, issue 8246 pp. 44-46 68 Muslim community that the Brazilian intelligence

  3. Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

    DTIC Science & Technology

    1991-06-01

    Alto Research Center, August 1982. [82] Ernst W. Mayr . Well Structured Parallel Programs Are Not Easier to Schedule. Technical Report No. STAN-CS-81...articles on scheduling) [Dolev, 80; Graham, 69; Helmbold and Mayr , 84; Mayr , 81], in systems [Ackerman, 82] and in artificial intelligence [Rosenschein...Flight Control. NASA Technical Memorandum 58258, May 1984. [60] D. Helmbold and E. Mayr . Fast Scheduling Algorithms on Parallel Computers. Technical

  4. 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.

  5. 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

  6. Fast revelation of the motif mode for a yeast protein interaction network through intelligent agent-based distributed computing.

    PubMed

    Lee, Wei-Po; Tzou, Wen-Shyong

    2010-09-01

    In the yeast protein-protein interaction network, motif mode, a collection of motifs of special combinations of protein nodes annotated by the molecular function terms of the Gene Ontology, has revealed differences in the conservation constraints within the same topology. In this study, by employing an intelligent agent-based distributed computing method, we are able to discover motif modes in a fast and adaptive manner. Moreover, by focusing on the highly evolutionarily conserved motif modes belonging to the same biological function, we find a large downshift in the distance between nodes belonging to the same motif mode compared with the whole, suggesting that nodes with the same motif mode tend to congregate in a network. Several motif modes with a high conservation of the motif constituents were revealed, but from a new perspective, including that with a three-node motif mode engaged in the protein fate and that with three four-node motif modes involved in the genome maintenance, cellular organization, and transcription. The network motif modes discovered from this method can be linked to the wealth of biological data which require further elucidation with regard to biological functions.

  7. 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.

  8. 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.

  9. Psychiatric neural networks and neuropharmacology: Selected advances and novel implications

    PubMed Central

    Ghanemi, Abdelaziz

    2013-01-01

    Psychiatric disorders are often considered as simple imbalances between a limited number of cerebral neurotransmitters. In fact, it is more complicated than this “simple approach” and each psychiatric disorder constitutes network dysfunction within which several agents and factors are implicated. Thus, the therapeutical perspectives and implications are as vast and as numerous as the diversity of those network dysfunctions. Furthermore, the description of factors influencing diseases prognoses and treatment efficacy indicates new elements to consider both in therapies and drug researches. PMID:24648819

  10. 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.

  11. Advances in Integrating Autonomy with Acoustic Communications for Intelligent Networks of Marine Robots

    DTIC Science & Technology

    2013-02-01

    Front Seat Interface Robotic Marine Kayak +ship name : string Topside +name : string = Bobby Kayak +name : string = Dee Kayak #Tracking #Sonar Interface...Computer Bridge Display Computer «executable» Google Earth «executable» Google Earth «wired» ethernet Kayak (Elanor) MOOS Computer Kayak ASC (Dee) MOOS

  12. 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…

  13. 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.

  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. Internet2: Building and Deploying Advanced, Networked Applications.

    ERIC Educational Resources Information Center

    Hanss, Ted

    1997-01-01

    Internet2, a consortium effort of over 100 universities, is investing in upgrading campus and national computer network platforms for such applications as digital libraries, collaboration environments, tele-medicine, and distance-independent instruction. The project is described, issues the project intends to address are detailed, and ways in…

  16. 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.

  17. Congestion and flow control in signaling system No. 7: Impacts of intelligent networks and new services

    SciTech Connect

    Zepf, J.; Rufa, G. )

    1994-04-01

    This paper focuses on the transient performance analysis of the congestion and flow control mechanisms in CCITT Signaling System No. 7 (SS7). Special attention is directed to the impacts of the introduction of intelligent services and new applications, e.g., Freephone, credit card services, user-to-user signaling, etc. In particular, we show that signaling traffic characteristics like signaling scenarios or signaling message length as well as end-to-end signaling capabilities have a significant influence on the congestion and flow control and, therefore, on the real-time signaling performance. One important result of our performance studies is that if, e.g., intelligent services are introduced, the SS7 congestion and flow control does not work correctly. To solve this problem, some reinvestigations into these mechanisms would be necessary. Therefore, some approaches, e.g., modification of the Signaling Connection Control Part (SCCP) congestion control, usage of the SCCP relay function, or a redesign of the MTP flow control procedures are discussed in order to guarantee the efficacy of the congestion and flow control mechanisms also in the future. 16 refs.

  18. Congestion and flow control in signaling system no. 7: Impacts of intelligent networks and new services

    NASA Astrophysics Data System (ADS)

    Zepf, Joachim; Rufa, Gerhard

    1994-04-01

    This paper focuses on the transient performance analysis of the congestion and flow control mechanisms in CCITT Signaling System No. 7 (SS7). Special attention is directed to the impacts of the introduction of intelligent services and new applications, e.g., Freephone, credit card services, user-to-user signaling, etc. In particular, we show that signaling traffic characteristics like signaling scenarios or signaling message length as well as end-to-end signaling capabilities have a significant influence on the congestion and flow control and, therefore, on the real-time signaling performance. One important result of our performance studies is that if, e.g., intelligent services are introduced, the SS7 congestion and flow control does not work correctly. To solve this problem, some reinvestigations into these mechanisms would be necessary. Therefore, some approaches, e.g., modification of the Signaling Connection Control Part (SCCP) congestion control, usage of the SCCP relay function, or a redesign of the MTP flow control procedures are discussed in order to guarantee the efficacy of the congestion and flow control mechanisms also in the future.

  19. Multipoint sensing by intelligent collectives

    NASA Technical Reports Server (NTRS)

    Clare, L. P.

    2002-01-01

    Many remote sensing applications require that multiple sensors collect data simultaneously at spatially distributed locations and their information combined in order to characterize the phenomena of interest. Several basic classes of such multipoint measurement systems may be identified. For each, centralized methods exist for combining the raw data from the various sensors. However, recent advancements have given rise to small, integrated nodes comprised of one or more miniaturized sensors, processor, wireless communications capability and power supplies. Collections of these may be deployed and self-organized into intelligent sensor networks capable of performing cooperative signal processing locally, thereby providing substantial benefits.

  20. 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.

  1. THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

    DTIC Science & Technology

    COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

  2. 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)

  3. International Intelligence Forum 2002

    DTIC Science & Technology

    2002-01-01

    FORUM 39 Peavie, Barrett K . Intelligence Sharing in Bosnia. Fort Leavenworth, KS : U.S. Army Command and General Staff College, School of Advanced...Investigative Service, 2000. Jenssen, Lars Christian and Olav Riste. Intelligence in the Cold War: Organiza- tion, Role, International Cooperation. Oslo

  4. Charting epilepsy by searching for intelligence in network space with the help of evolving autonomous agents.

    PubMed

    Ohayon, Elan L; Kalitzin, Stiliyan; Suffczynski, Piotr; Jin, Frank Y; Tsang, Paul W; Borrett, Donald S; Burnham, W McIntyre; Kwan, Hon C

    2004-01-01

    The problem of demarcating neural network space is formidable. A simple fully connected recurrent network of five units (binary activations, synaptic weight resolution of 10) has 3.2 *10(26) possible initial states. The problem increases drastically with scaling. Here we consider three complementary approaches to help direct the exploration to distinguish epileptic from healthy networks. [1] First, we perform a gross mapping of the space of five-unit continuous recurrent networks using randomized weights and initial activations. The majority of weight patterns (>70%) were found to result in neural assemblies exhibiting periodic limit-cycle oscillatory behavior. [2] Next we examine the activation space of non-periodic networks demonstrating that the emergence of paroxysmal activity does not require changes in connectivity. [3] The next challenge is to focus the search of network space to identify networks with more complex dynamics. Here we rely on a major available indicator critical to clinical assessment but largely ignored by epilepsy modelers, namely: behavioral states. To this end, we connected the above network layout to an external robot in which interactive states were evolved. The first random generation showed a distribution in line with approach [1]. That is, the predominate phenotypes were fixed-point or oscillatory with seizure-like motor output. As evolution progressed the profile changed markedly. Within 20 generations the entire population was able to navigate a simple environment with all individuals exhibiting multiply-stable behaviors with no cases of default locked limit-cycle oscillatory motor behavior. The resultant population may thus afford us a view of the architectural principles demarcating healthy biological networks from the pathological. The approach has an advantage over other epilepsy modeling techniques in providing a way to clarify whether observed dynamics or suggested therapies are pointing to computational viability or dead

  5. 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.

  6. 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

  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.

  10. A Systems Engineering Survey of Artificial Intelligence and Smart Sensor Networks in a Network-Centric Environment

    DTIC Science & Technology

    2009-09-01

    system. The green dots show the senor locations and the red dot shows the estimated location of the sniper [35]. 63 Figure 29. ISIS Counter...Government Printing Office, Washington, D.C., 2005. [3] M. Fredriksson and R. Gustavsson , "Quality of service in network-centric warfare and

  11. 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.

  12. 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

  13. Neural networks for advanced control of robot manipulators.

    PubMed

    Patino, H D; Carelli, R; Kuchen, B R

    2002-01-01

    Presents an approach and a systematic design methodology to adaptive motion control based on neural networks (NNs) for high-performance robot manipulators, for which stability conditions and performance evaluation are given. The neurocontroller includes a linear combination of a set of off-line trained NNs, and an update law of the linear combination coefficients to adjust robot dynamics and payload uncertain parameters. A procedure is presented to select the learning conditions for each NN in the bank. The proposed scheme, based on fixed NNs, is computationally more efficient than the case of using the learning capabilities of the neural network to be adapted, as that used in feedback architectures that need to propagate back control errors through the model to adjust the neurocontroller. A practical stability result for the neurocontrol system is given. That is, we prove that the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the NN bank and the design parameters of the controller. In addition, a robust adaptive controller to NN learning errors is proposed, using a sign or saturation switching function in the control law, which leads to global asymptotic stability and zero convergence of control errors. Simulation results showing the practical feasibility and performance of the proposed approach to robotics are given.

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Advances in materials and current collecting networks for AMTEC electrodes

    NASA Technical Reports Server (NTRS)

    Ryan, M. A.; Jeffries-Nakamura, B.; Williams, R. M.; Underwood, M. L.; O'Connor, D.; Kikkert, S.

    1992-01-01

    Electrode materials for the Alkali Metal Thermal to Electric Converter (AMTEC) play a significant role in the efficiency of the device. RhW and PtW alloys have been studied to determine the best performing material. While RhW electrodes typically have power densities somewhat lower than PtW electrodes, PtW performance is strongly influenced by the Pt/W ratio. The best performing Pt/W ratio is about 3.4. RhW electrodes sinter more slowly than PtW and are predicted to have operating lifetimes up to 40 years; PtW electrodes are predicted to have lifetimes up to 7 years. Interaction with the current collection network can significantly decrease lifetime by inducing metal migration and segregation and by accelerating the sintering rate.

  1. 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...

  2. 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…

  3. 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.

  4. Temporally sequenced intelligent block-matching and motion-segmentation using locally coupled networks.

    PubMed

    Zhang, Xiaofu; Minai, A A

    2004-09-01

    Motion-based segmentation is a very important capability for computer vision and video analysis. It depends fundamentally on the system's ability to estimate optic flow using temporally proximate image frames. This is often done using block-matching. However, block-matching is sensitive to the presence of observational noise, which is inevitable in real images. Also, images often include regions of homogeneous intensity, where block-matching is problematic. A better method in this case is to estimate motion at the region level. In the approach described in this paper, we have attempted to address the noise-sensitivity and texture-insufficiency problems using a two-pathway system. The pixel-level pathway is a multilayer pulse-coupled neural network (PCNN)-like locally coupled network used to correct outliers in the block-matching motion estimates and produce improved estimates in regions with sufficient texture. In contrast, the region-level pathway is used to estimate the motion for regions with little intensity variation. In this pathway, a PCNN network first partitions intensity images into homogeneous regions, and a motion vector is then determined for the whole region. The optic flows from both pathways are fused together based on the estimated intensity variation. The fused optic flow is then segmented by a one-layer PCNN network. Results on synthetic and real images are presented to demonstrate that the accuracy of segmentation is improved significantly by taking advantage of the complementary strengths and weaknesses of the two pathways.

  5. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    NASA Astrophysics Data System (ADS)

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  6. Extraterrestrial intelligence? Not likely.

    PubMed

    DeVore, I

    2001-12-01

    The possibility that there exist extraterrestrial creatures with advanced intelligence is considered by examining major events in mammalian, primate, and human evolution on earth. The overwhelming evidence is that the evolution of intelligence in creatures elsewhere who have the capability to communicate with us is vanishingly small. The history of the evolution of advanced forms of life on this planet is so beset by adventitious, unpredictable events and multiple contingencies that the evolution of human-level intelligence is highly unlikely on any planet, including earth.

  7. 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.

  8. Plasma Cholesterol–Induced Lesion Networks Activated before Regression of Early, Mature, and Advanced Atherosclerosis

    PubMed Central

    Björkegren, Johan L. M.; Hägg, Sara; Jain, Rajeev K.; Cedergren, Cecilia; Shang, Ming-Mei; Rossignoli, Aránzazu; Takolander, Rabbe; Melander, Olle; Hamsten, Anders; Michoel, Tom; Skogsberg, Josefin

    2014-01-01

    Plasma cholesterol lowering (PCL) slows and sometimes prevents progression of atherosclerosis and may even lead to regression. Little is known about how molecular processes in the atherosclerotic arterial wall respond to PCL and modify responses to atherosclerosis regression. We studied atherosclerosis regression and global gene expression responses to PCL (≥80%) and to atherosclerosis regression itself in early, mature, and advanced lesions. In atherosclerotic aortic wall from Ldlr−/−Apob 100/100 Mttp flox/floxMx1-Cre mice, atherosclerosis regressed after PCL regardless of lesion stage. However, near-complete regression was observed only in mice with early lesions; mice with mature and advanced lesions were left with regression-resistant, relatively unstable plaque remnants. Atherosclerosis genes responding to PCL before regression, unlike those responding to the regression itself, were enriched in inherited risk for coronary artery disease and myocardial infarction, indicating causality. Inference of transcription factor (TF) regulatory networks of these PCL-responsive gene sets revealed largely different networks in early, mature, and advanced lesions. In early lesions, PPARG was identified as a specific master regulator of the PCL-responsive atherosclerosis TF-regulatory network, whereas in mature and advanced lesions, the specific master regulators were MLL5 and SRSF10/XRN2, respectively. In a THP-1 foam cell model of atherosclerosis regression, siRNA targeting of these master regulators activated the time-point-specific TF-regulatory networks and altered the accumulation of cholesterol esters. We conclude that PCL leads to complete atherosclerosis regression only in mice with early lesions. Identified master regulators and related PCL-responsive TF-regulatory networks will be interesting targets to enhance PCL-mediated regression of mature and advanced atherosclerotic lesions. PMID:24586211

  9. Plasma cholesterol-induced lesion networks activated before regression of early, mature, and advanced atherosclerosis.

    PubMed

    Björkegren, Johan L M; Hägg, Sara; Talukdar, Husain A; Foroughi Asl, Hassan; Jain, Rajeev K; Cedergren, Cecilia; Shang, Ming-Mei; Rossignoli, Aránzazu; Takolander, Rabbe; Melander, Olle; Hamsten, Anders; Michoel, Tom; Skogsberg, Josefin

    2014-02-01

    Plasma cholesterol lowering (PCL) slows and sometimes prevents progression of atherosclerosis and may even lead to regression. Little is known about how molecular processes in the atherosclerotic arterial wall respond to PCL and modify responses to atherosclerosis regression. We studied atherosclerosis regression and global gene expression responses to PCL (≥80%) and to atherosclerosis regression itself in early, mature, and advanced lesions. In atherosclerotic aortic wall from Ldlr(-/-)Apob (100/100) Mttp (flox/flox)Mx1-Cre mice, atherosclerosis regressed after PCL regardless of lesion stage. However, near-complete regression was observed only in mice with early lesions; mice with mature and advanced lesions were left with regression-resistant, relatively unstable plaque remnants. Atherosclerosis genes responding to PCL before regression, unlike those responding to the regression itself, were enriched in inherited risk for coronary artery disease and myocardial infarction, indicating causality. Inference of transcription factor (TF) regulatory networks of these PCL-responsive gene sets revealed largely different networks in early, mature, and advanced lesions. In early lesions, PPARG was identified as a specific master regulator of the PCL-responsive atherosclerosis TF-regulatory network, whereas in mature and advanced lesions, the specific master regulators were MLL5 and SRSF10/XRN2, respectively. In a THP-1 foam cell model of atherosclerosis regression, siRNA targeting of these master regulators activated the time-point-specific TF-regulatory networks and altered the accumulation of cholesterol esters. We conclude that PCL leads to complete atherosclerosis regression only in mice with early lesions. Identified master regulators and related PCL-responsive TF-regulatory networks will be interesting targets to enhance PCL-mediated regression of mature and advanced atherosclerotic lesions.

  10. 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.

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

    PubMed

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

    2002-09-01

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

  12. Intelligent Approaches in Improving In-vehicle Network Architecture and Minimizing Power Consumption in Combat Vehicles

    DTIC Science & Technology

    2011-01-01

    include washing machines , rice cookers, image processing applications , anti-lock brake controls , and steering controls . In general, fuzzy logic...its cognitive information to other in-vehicle network systems. In [58] a Fuzzy Logic Controller for Hybrid Electric Vehicle is proposed to maximize...provided to describe what is meant by ―optimal torque value‖. All the 121 rules in this fuzzy logic controller are static and have no flexibility to

  13. Intelligent detection and identification in fiber-optical perimeter intrusion monitoring system based on the FBG sensor network

    NASA Astrophysics Data System (ADS)

    Wu, Huijuan; Qian, Ya; Zhang, Wei; Li, Hanyu; Xie, Xin

    2015-12-01

    A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal's profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

  14. 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

  15. 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.

  16. Botanical drugs, synergy, and network pharmacology: forth and back to intelligent mixtures.

    PubMed

    Gertsch, Jürg

    2011-07-01

    For centuries the science of pharmacognosy has dominated rational drug development until it was gradually substituted by target-based drug discovery in the last fifty years. Pharmacognosy stems from the different systems of traditional herbal medicine and its "reverse pharmacology" approach has led to the discovery of numerous pharmacologically active molecules and drug leads for humankind. But do botanical drugs also provide effective mixtures? Nature has evolved distinct strategies to modulate biological processes, either by selectively targeting biological macromolecules or by creating molecular promiscuity or polypharmacology (one molecule binds to different targets). Widely claimed to be superior over monosubstances, mixtures of bioactive compounds in botanical drugs allegedly exert synergistic therapeutic effects. Despite evolutionary clues to molecular synergism in nature, sound experimental data are still widely lacking to support this assumption. In this short review, the emerging concept of network pharmacology is highlighted, and the importance of studying ligand-target networks for botanical drugs is emphasized. Furthermore, problems associated with studying mixtures of molecules with distinctly different pharmacodynamic properties are addressed. It is concluded that a better understanding of the polypharmacology and potential network pharmacology of botanical drugs is fundamental in the ongoing rationalization of phytotherapy.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Analysis and synthesis of networked control systems: A survey of recent advances and challenges.

    PubMed

    Zhang, Dan; Shi, Peng; Wang, Qing-Guo; Yu, Li

    2017-01-01

    A networked control system (NCS) is a control system which involves a communication network. In NCSs, the continuous-time measurement is usually sampled and quantized before transmission. Then, the measurement is transmitted to the remote controller via the communication channel, during which the signal may be delayed, lost or even sometimes not allowed for transmission due to the communication or energy constraints. In recent years, the modeling, analysis and synthesis of networked control systems (NCSs) have received great attention, which leads to a large number of publications. This paper attempts to present an overview of recent advances and unify them in a framework of network-induced issues such as signal sampling, data quantization, communication delay, packet dropouts, medium access constraints, channel fading and power constraint, and present respective solution approaches to each of these issues. We draw some conclusions and highlight future research directions in end.

  3. 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.

  4. 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.

  5. 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.

  6. MagIC: a textile system for vital signs monitoring. Advancement in design and embedded intelligence for daily life applications.

    PubMed

    Di Rienzo, Marco; Rizzo, Francesco; Meriggi, Paolo; Castiglioni, Paolo; Mazzoleni, Paolo; Ferrarin, Maurizio; Ferratini, Maurizio

    2007-01-01

    We recently developed a textile-based system for the unobtrusive assessment of vital signs. The system, named MagIC, was originally designed to collect data in elderly people and cardiac patients while living in a confined environment. Extending the area of application of MagIC from clinics to daily life meant to pay particular attention to the garment design and to the amount of intelligence embedded into the system. In this paper we addressed both these issues by illustrating 1) a new methodology we are developing to help the design of smart garments for daily life applications and 2) an example of embedded intelligence developed for an application of MagIC in ergonomics.

  7. 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

  8. Novel iterative P-cycle configure model in WDM intelligent optical network

    NASA Astrophysics Data System (ADS)

    Li, Bin; Huang, Shanguo; Zhang, Yongjun; Gu, Wanyi; Zu, Yunxiao

    2009-11-01

    In this paper, a p-cycle generation algorithm is proposed that can protect service of static traffic model in WDM network. As the basic p-cycle sets calculated by algorithm such as the straddle link algorithm (SLA) always contain a straddle link in it. That is why the protection efficiency is higher than bidirectional line switch ring (BLSR). Any idle resource can be used for traffic restoration. But if the resource is not configured carefully then not all the resource of idle state can be utilized efficiently. Some extensions of algorithms are brought into effect to improve the protection capability. Based on these extensions, a novel iterative expanding p-cycle is introduced. A platform is constructed in OPNET modeler to verify the performance of this algorithm. Simulation results show that after several expansions for the basic p-cycle sets, the efficiency is improved. The pre-configured resource is deployed before any requests come. Comparison between different network topologies is studied. Finally, the results are analyzed and some directivity is given for further research.

  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

    2016-01-08

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

    PubMed

    Moreland-Russell, Sarah; Carothers, Bobbi J

    2015-09-08

    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.

  11. 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

  12. An advanced distributed automated extraction of drainage network model on high-resolution DEM

    NASA Astrophysics Data System (ADS)

    Mao, Y.; Ye, A.; Xu, J.; Ma, F.; Deng, X.; Miao, C.; Gong, W.; Di, Z.

    2014-07-01

    A high-resolution and high-accuracy drainage network map is a prerequisite for simulating the water cycle in land surface hydrological models. The objective of this study was to develop a new automated extraction of drainage network model, which can get high-precision continuous drainage network on high-resolution DEM (Digital Elevation Model). The high-resolution DEM need too much computer resources to extract drainage network. The conventional GIS method often can not complete to calculate on high-resolution DEM of big basins, because the number of grids is too large. In order to decrease the computation time, an advanced distributed automated extraction of drainage network model (Adam) was proposed in the study. The Adam model has two features: (1) searching upward from outlet of basin instead of sink filling, (2) dividing sub-basins on low-resolution DEM, and then extracting drainage network on sub-basins of high-resolution DEM. The case study used elevation data of the Shuttle Radar Topography Mission (SRTM) at 3 arc-second resolution in Zhujiang River basin, China. The results show Adam model can dramatically reduce the computation time. The extracting drainage network was continuous and more accurate than HydroSHEDS (Hydrological data and maps based on Shuttle Elevation Derivatives at multiple Scales).

  13. 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.

  14. 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.

  15. 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.

  16. [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.

  17. An intelligent ballistocardiographic chair using a novel SF-ART neural network and Biorthogonal wavelets.

    PubMed

    Akhbardeh, Alireza; Junnila, Sakari; Koivistoinen, Teemu; Värri, Alpo

    2007-02-01

    This paper presents a comparative analysis of novel supervised fuzzy adaptive resonance theory (SF-ART), multilayer perceptron (MLP) and Multi Layer Perceptrons (MLP) neural networks over Ballistocardiogram (BCG) signal recognition. To extract essential features of the BCG signal, we applied Biorthogonal wavelets. SF-ART performs classification on two levels. At first level, pre-classifier which is self-organized fuzzy ART tuned for fast learning classifies the input data roughly to arbitrary (M) classes. At the second level, post-classification level, a special array called Affine Look-up Table (ALT) with M elements stores the labels of corresponding input samples in the address equal to the index of fuzzy ART winner. However, in running (testing) mode, the content of an ALT cell with address equal to the index of fuzzy ART winner output will be read. The read value declares the final class that input data belongs to. In this paper, we used two well-known patterns (IRIS and Vowel data) and a medical application (Ballistocardiogram data) to evaluate and check SF-ART stability, reliability, learning speed and computational load. Initial tests with BCG from six subjects (both healthy and unhealthy people) indicate that the SF-ART is capable to perform with a high classification performance, high learning speed (elapsed time for learning around half second), and very low computational load compared to the well-known neural networks such as MLP which needs minutes to learn the training material. Moreover, to extract essential features of the BCG signal, we applied Biorthogonal wavelets. The applied wavelet transform requires no prior knowledge of the statistical distribution of data samples.

  18. 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

  19. Study on the idity fuzzy neural network controller based on improved genetic algorithm of intelligent temperature control system in vegetable greenhouse

    NASA Astrophysics Data System (ADS)

    Zhang, Su; Yuan, Hongbo; Zhou, Yuhong; Wang, Nan

    2009-07-01

    In order to create the environment that the suitable crop grows, direct against the characteristic of the system of the greenhouse. The aim of the research was to study the intelligent temperature control system in vegetable greenhouse. Based on computer automatic control ,a kind of intelligent temperature control system in vegetable greenhouse was designed. The design thought of systematic hardwares such as temperature collection system, temperature display, control system, heater control circuit in the heater were expounded in detail The control algorithm of the system was improved and system simulation was made by using MATLAB finally. The control algorithm of the system was improved by a new fuzzy neural network controller. The stimulation curve showed that the system had better controlling and tracking performances ,higher accuracy of controlling the temperature. And this system and host epigyny computer could constitute the secondary computer control system which was favorable for realizing the centralized management of the production.

  20. Northeast Artificial Intelligence Consortium annual report - 1988. Volume 4. Distributed AI for communications network management. Interim report, January-December 1988

    SciTech Connect

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

    1989-10-01

    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 is to conduct pertinent research in artificial intelligence and to perform activities ancillary to this research. This report describes progress that has been made in the fourth year of 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-based reasoning and planning, knowledge base maintenance, hardware architectures for very large systems, 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.

  1. Neighbor Selection in Peer-to-Peer Overlay Networks: A Swarm Intelligence Approach

    NASA Astrophysics Data System (ADS)

    Liu, Hongbo; Abraham, Ajith; Badr, Youakim

    Peer-to-peer (P2P) topology has a significant influence on the performance, search efficiency and functionality, and scalability of the application. In this chapter, we investigate a multi-swarm approach to the problem of neighbor selection in P2P networks. Particle swarm share some common characteristics with P2P in the dynamic socially environment. Each particle encodes the upper half of the peer-connection matrix through the undirected graph, which reduces the search space dimension. The portion of the adjustment to the velocity influenced by the individual’s cognition, the group cognition from multi-swarms, and the social cognition from the whole swarm, makes an important influence on the particles’ ergodic and synergetic performance. We also attempt to theoretically prove that the multi-swarm optimization algorithm converges with a probability of 1 towards the global optima. The performance of our approach is evaluated and compared with other two different algorithms. The results indicate that it usually required shorter time to obtain better results than the other considered methods, specially for large scale problems.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. The processing of information from sensors in intelligent systems

    NASA Astrophysics Data System (ADS)

    Kokovin, V. A.; Sytin, A. N.

    2017-01-01

    The article describes the processing of information obtained from sensors in intelligent systems. The paper analyzes the need of advanced treatment for a paralleling operation calculator which reduces the time of response to input events. A realization of a speculative processing algorithm in the FPGA by streaming control is based on a data flow model. This solution can be used in applications related to telecommunications networks of distributed control systems.

  12. 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.

  13. 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).

  14. 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.

  15. Target-based optimization of advanced gravitational-wave detector network operations

    NASA Astrophysics Data System (ADS)

    Szölgyén, Á.; Dálya, G.; Gondán, L.; Raffai, P.

    2017-04-01

    We introduce two novel time-dependent figures of merit for both online and offline optimizations of advanced gravitational-wave (GW) detector network operations with respect to (i) detecting continuous signals from known source locations and (ii) detecting GWs of neutron star binary coalescences from known local galaxies, which thereby have the highest potential for electromagnetic counterpart detection. For each of these scientific goals, we characterize an N-detector network, and all its (N  ‑  1)-detector subnetworks, to identify subnetworks and individual detectors (key contributors) that contribute the most to achieving the scientific goal. Our results show that aLIGO-Hanford is expected to be the key contributor in 2017 to the goal of detecting GWs from the Crab pulsar within the network of LIGO and Virgo detectors. For the same time period and for the same network, both LIGO detectors are key contributors to the goal of detecting GWs from the Vela pulsar, as well as to detecting signals from 10 high interest pulsars. Key contributors to detecting continuous GWs from the Galactic Center can only be identified for finite time intervals within each sidereal day with either the 3-detector network of the LIGO and Virgo detectors in 2017, or the 4-detector network of the LIGO, Virgo, and KAGRA detectors in 2019–2020. Characterization of the LIGO-Virgo detectors with respect to goal (ii) identified the two LIGO detectors as key contributors. Additionally, for all analyses, we identify time periods within a day when lock losses or scheduled service operations could result with the least amount of signal-to-noise or transient detection probability loss for a detector network.

  16. 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.

  17. 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.

  18. 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.

  19. Translating biobehavioral research advances into improvements in health care-a "network of networks" approach to multimorbidity.

    PubMed

    Rohleder, Nicolas

    2017-02-01

    Biobehavioral research has made great advances in past decades, allowing researchers to paint an ever-improving picture of interactions between the central nervous system and the systems in the periphery of the body. This knowledge allows us, from a researcher's perspective, to better understand diseases and disease symptoms that are not explainable with a narrow view on organ-specific biomedical processes. However, what is lacking is the translation of this knowledge into clinical practice. In their commentary, Sturmberg et al pointed out these shortcomings and proposed a model connecting the different networks in the human body, and the importance of their connectedness, and drew conclusions for necessary changes in patient care. While doing so, Sturmberg et al also created the basis of what could be considered a new and all-encompassing stress model. This work therefore not only calls for changes in clinical practice but also provides a basis for further steps in biobehavioral research.

  20. The meaning and validation of social support networks for close family of persons with advanced cancer

    PubMed Central

    2012-01-01

    Background To strengthen the mental well-being of close family of persons newly diagnosed as having cancer, it is necessary to acquire a greater understanding of their experiences of social support networks, so as to better assess what resources are available to them from such networks and what professional measures are required. The main aim of the present study was to explore the meaning of these networks for close family of adult persons in the early stage of treatment for advanced lung or gastrointestinal cancer. An additional aim was to validate the study’s empirical findings by means of the Finfgeld-Connett conceptual model for social support. The intention was to investigate whether these findings were in accordance with previous research in nursing. Methods Seventeen family members with a relative who 8–14 weeks earlier had been diagnosed as having lung or gastrointestinal cancer were interviewed. The data were subjected to qualitative latent content analysis and validated by means of identifying antecedents and critical attributes. Results The meaning or main attribute of the social support network was expressed by the theme Confirmation through togetherness, based on six subthemes covering emotional and, to a lesser extent, instrumental support. Confirmation through togetherness derived principally from information, understanding, encouragement, involvement and spiritual community. Three subthemes were identified as the antecedents to social support: Need of support, Desire for a deeper relationship with relatives, Network to turn to. Social support involves reciprocal exchange of verbal and non-verbal information provided mainly by lay persons. Conclusions The study provides knowledge of the antecedents and attributes of social support networks, particularly from the perspective of close family of adult persons with advanced lung or gastrointestinal cancer. There is a need for measurement instruments that could encourage nurses and other health

  1. Intelligent algorithms for persistent and pervasive sensing in systems comprised of wireless ad hoc networks of ground-based sensors and mobile infrastructures

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2007-04-01

    With the development of low-cost, durable unmanned aerial vehicles (UAVs), it is now practical to perform persistent sensing and target tracking autonomously over broad surveillance areas. These vehicles can sense the environment directly through onboard active sensors, or indirectly when aimed toward ground targets in a mission environment by ground-based passive sensors operating wirelessly as an ad hoc network in the environment. The combination of the swarm intelligence of the airborne infrastructure comprised of UAVs with the ant-like collaborative behavior of the unattended ground sensors creates a system capable of both persistent and pervasive sensing of mission environment, such that, the continuous collection, analysis and tracking of targets from sensor data received from the ground can be achieved. Mobile software agents are used to implement intelligent algorithms for the communications, formation control and sensor data processing in this composite configuration. The enabling mobile agents are organized in a hierarchy for the three stages of processing in the distributed system: target detection, location and recognition from the collaborative data processing among active ground-sensor nodes; transfer of the target information processed on the ground to the UAV swarm overhead; and formation control and sensor activation of the UAV swarm for sustained ground-target surveillance and tracking. Intelligent algorithms are presented that can adapt to the operation of the composite system to target dynamics and system resources. Established routines, appropriate to the processing needs of each stage, are selected as preferred based on their published use in similar scenarios, ability to be distributively implemented over the set of processors at system nodes, and ability to conserve the limited resources at the ground nodes to extend the lifetime of the pervasive network. In this paper, the performance of this distributed, collaborative system concept for

  2. Robotics and Intelligent Systems Program

    SciTech Connect

    Not Available

    1987-06-01

    This report gives brief descriptions of the projects associated with the Robotics and Intelligent Systems Program (RISP). Projects included in the report are (1) Remote Operations Demonstration Facility; (2) M-2 Servomanipulator; (3) The Advanced Servomanipulator; (4) Hostile Environment Robotic Machine Intelligence Experiment Series robots); and (5) Telerobotic Concepts. These devices have application in nuclear industry and space environments. (JDH)

  3. 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…

  4. Advanced modularity-specialized label propagation algorithm for detecting communities in networks

    NASA Astrophysics Data System (ADS)

    Liu, X.; Murata, T.

    2010-04-01

    A modularity-specialized label propagation algorithm (LPAm) for detecting network communities was recently proposed. This promising algorithm offers some desirable qualities. However, LPAm favors community divisions where all communities are similar in total degree and thus it is prone to get stuck in poor local maxima in the modularity space. To escape local maxima, we employ a multistep greedy agglomerative algorithm (MSG) that can merge multiple pairs of communities at a time. Combining LPAm and MSG, we propose an advanced modularity-specialized label propagation algorithm (LPAm+). Experiments show that LPAm+ successfully detects communities with higher modularity values than ever reported in two commonly used real-world networks. Moreover, LPAm+ offers a fair compromise between accuracy and speed.

  5. 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.

  6. 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

  7. Recent Advance on Mesoporous Silica Nanoparticles-Based Controlled Release System: Intelligent Switches Open up New Horizon

    PubMed Central

    Sun, Ruijuan; Wang, Wenqian; Wen, Yongqiang; Zhang, Xueji

    2015-01-01

    Mesoporous silica nanoparticle (MSN)-based intelligent transport systems have attracted many researchers’ attention due to the characteristics of uniform pore and particle size distribution, good biocompatibility, high surface area, and versatile functionalization, which have led to their widespread application in diverse areas. In the past two decades, many kinds of smart controlled release systems were prepared with the development of brilliant nano-switches. This article reviews and discusses the advantages of MSN-based controlled release systems. Meanwhile, the switching mechanisms based on different types of stimulus response are systematically analyzed and summarized. Additionally, the application fields of these devices are further discussed. Obviously, the recent evolution of smart nano-switches promoted the upgrading of the controlled release system from the simple “separated” switch to the reversible, multifunctional, complicated logical switches and selective switches. Especially the free-blockage switches, which are based on hydrophobic/hydrophilic conversion, have been proposed and designed in the last two years. The prospects and directions of this research field are also briefly addressed, which could be better used to promote the further development of this field to meet the needs of mankind. PMID:28347110

  8. An Architecture for Intelligent Systems Based on Smart Sensors

    NASA Technical Reports Server (NTRS)

    Schmalzel, John; Figueroa, Fernando; Morris, Jon; Mandayam, Shreekanth; Polikar, Robi

    2004-01-01

    Based on requirements for a next-generation rocket test facility, elements of a prototype Intelligent Rocket Test Facility (IRTF) have been implemented. A key component is distributed smart sensor elements integrated using a knowledgeware environment. One of the specific goals is to imbue sensors with the intelligence needed to perform self diagnosis of health and to participate in a hierarchy of health determination at sensor, process, and system levels. The preliminary results provide the basis for future advanced development and validation using rocket test stand facilities at Stennis Space Center (SSC). We have identified issues important to further development of health-enabled networks, which should be of interest to others working with smart sensors and intelligent health management systems.

  9. Some Steps towards Intelligent Computer Tutoring Systems.

    ERIC Educational Resources Information Center

    Tchogovadze, Gotcha G.

    1986-01-01

    Describes one way of structuring an intelligent tutoring system (ITS) in light of developments in artificial intelligence. A specialized intelligent operating system (SIOS) is proposed for software for a network of microcomputers, and it is postulated that a general learning system must be used as a basic framework for the SIOS. (Author/LRW)

  10. The Quake-Catcher Network: A Community-Led, Strong-Motion Network with Implications for Earthquake Advanced Alert

    NASA Astrophysics Data System (ADS)

    Cochran, E. S.; Lawrence, J. F.; Christensen, C. M.; Jakka, R. S.; Chung, A. I.

    2009-12-01

    The goal of the Quake-Catcher Network (QCN) is to dramatically increase the number of strong-motion observations by exploiting recent advances in sensing technologies and cyberinfrastructure. Micro-Electro-Mechanical Systems (MEMS) triaxial accelerometers are very low cost (50-100), interface to any desktop computer via USB cable, and provide high-quality acceleration data. Preliminary shake table tests show the MEMS accelerometers can record high-fidelity seismic data and provide linear phase and amplitude response over a wide frequency range. Volunteer computing provides a mechanism to expand strong-motion seismology with minimal infrastructure costs, while promoting community participation in science. Volunteer computing also allows for rapid transfer of metadata, such as that used to rapidly determine the magnitude and location of an earthquake, from participating stations. QCN began distributing sensors and software to K-12 schools and the general public in April 2008 and has grown to roughly 1000 stations. Initial analysis shows metadata are received within 1-14 seconds from the observation of a trigger; the larger data latencies are correlated with greater server-station distances. Currently, we are testing a series of triggering algorithms to maximize the number of earthquakes captured while minimizing false triggers. We are also testing algorithms to automatically detect P- and S-wave arrivals in real time. Trigger times, wave amplitude, and station information are currently uploaded to the server for each trigger. Future work will identify additional metadata useful for quickly determining earthquake location and magnitude. The increased strong-motion observations made possible by QCN will greatly augment the capability of seismic networks to quickly estimate the location and magnitude of an earthquake for advanced alert to the public. In addition, the dense waveform observations will provide improved source imaging of a rupture in near-real-time. These

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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…

  16. 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…

  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…

  19. 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…

  20. Department of the Navy Supporting Data for Fiscal Year 1984 Budget Estimates Descriptive Summaries Submitted to Congress January 1983. Research, Development, Test & Evaluation, Navy. Book 3. Tactical Programs, Intelligence, & Communications Management & Support

    DTIC Science & Technology

    1983-01-01

    490 25670N TACTICAL INTELLIGENCE PROCESSING...SYSTEMS) ------------------------------------------------- 510 26625M MARINE CORPS INTELLIGENCE /ELECTRONIC WARFARE SYSTEMS (OPERATIONAL SYSTEMS...737 637304 MARINE CORPS INTELLIGENCE /ELECTRONIC WARFARE SYSTEM (ADVANCED

  1. 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

  2. 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.

  3. A Multi-layer, Data-driven Advanced Reasoning Tool for Intelligent Data Mining and Analysis for Smart Grids

    SciTech Connect

    Lu, Ning; Du, Pengwei; Greitzer, Frank L.; Guo, Xinxin; Hohimer, Ryan E.; Pomiak, Yekaterina G.

    2012-12-31

    This paper presents the multi-layer, data-driven advanced reasoning tool (M-DART), a proof-of-principle decision support tool for improved power system operation. M-DART will cross-correlate and examine different data sources to assess anomalies, infer root causes, and anneal data into actionable information. By performing higher-level reasoning “triage” of diverse data sources, M-DART focuses on early detection of emerging power system events and identifies highest priority actions for the human decision maker. M-DART represents a significant advancement over today’s grid monitoring technologies that apply offline analyses to derive model-based guidelines for online real-time operations and use isolated data processing mechanisms focusing on individual data domains. The development of the M-DART will bridge these gaps by reasoning about results obtained from multiple data sources that are enabled by the smart grid infrastructure. This hybrid approach integrates a knowledge base that is trained offline but tuned online to capture model-based relationships while revealing complex causal relationships among data from different domains.

  4. 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.

  5. Intelligent inspection system

    NASA Astrophysics Data System (ADS)

    May, Jeniece; Dale, Ken; Holloway, Mike; Gaby, Willard

    1997-01-01

    The intelligent inspection system is an advanced controller and analysis system for dimensional measuring machines dedicated to measuring surface of revolution mechanical parts. IIS was developed by the Lockheed Martin Energy Systems, Inc. Oak Ridge Y-12 plant because no commercial product was available to replace the obsolete computing systems on these important machines.

  6. 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…

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Advancing environmental health surveillance in the US through a national human biomonitoring network.

    PubMed

    Latshaw, Megan Weil; Degeberg, Ruhiyyih; Patel, Surili Sutaria; Rhodes, Blaine; King, Ewa; Chaudhuri, Sanwat; Nassif, Julianne

    2016-09-17

    The United States lacks a comprehensive, nationally-coordinated, state-based environmental health surveillance system. This lack of infrastructure leads to: • varying levels of understanding of chemical exposures at the state & local levels • often inefficient public health responses to chemical exposure emergencies (such as those that occurred in the Flint drinking water crisis, the Gold King mine spill, the Elk river spill and the Gulf Coast oil spill) • reduced ability to measure the impact of public health interventions or environmental policies • less efficient use of resources for cleaning up environmental contamination Establishing the National Biomonitoring Network serves as a step toward building a national, state-based environmental health surveillance system. The Network builds upon CDC investments in emergency preparedness and environmental public health tracking, which have created advanced chemical analysis and information sharing capabilities in the state public health systems. The short-term goal of the network is to harmonize approaches to human biomonitoring in the US, thus increasing the comparability of human biomonitoring data across states and communities. The long-term goal is to compile baseline data on exposures at the state level, similar to data found in CDC's National Report on Human Exposure to Environmental Chemicals. Barriers to success for this network include: available resources, effective risk communication strategies, data comparability & sharing, and political will. Anticipated benefits include high quality data on which to base public health and environmental decisions, data with which to assess the success of public health interventions, improved risk assessments for chemicals, and new ways to prioritize environmental health research.

  13. 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.

  14. Informatics and Nursing in a Post-Nursing Informatics World: Future Directions for Nurses in an Automated, Artificially Intelligent, Social-Networked Healthcare Environment.

    PubMed

    Booth, Richard G

    2016-01-01

    The increased adoption and use of technology within healthcare and society has influenced the nursing informatics specialty in a multitude of fashions. Namely, the nursing informatics specialty currently faces a range of important decisions related to its knowledge base, established values and future directions - all of which are in need of development and future-proofing. In light of the increased use of automation, artificial intelligence and big data in healthcare, the specialty must also reconceptualize the roles of both nurses and informaticians to ensure that the nursing profession is ready to operate within future digitalized healthcare ecosystems. To explore these goals, the author of this manuscript outlines an examination of technological advancements currently taking place within healthcare, and also proposes implications for the nursing role and the nursing informatics specialty. Finally, recommendations and insights towards how the roles of nurses and informaticians might evolve or be shaped in the growing post-nursing informatics era are presented.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Decreased resting-state connections within the visuospatial attention-related network in advanced aging.

    PubMed

    Li, Yujie; Li, Chunlin; Wu, Qiong; Xu, Zhihan; Kurata, Tomoko; Ohno, Seiichiro; Kanazawa, Susumu; Abe, Koji; Wu, Jinglong

    2015-06-15

    Advanced aging is accompanied by a decline in visuospatial attention. Previous neuroimaging and electrophysiological studies have demonstrated dysfunction in specific brain areas related to visuospatial attention. However, it is still unclear how the functional connectivity between brain regions causes the decline of visuospatial attention. Here, we combined task and rest functional magnetic resonance imaging (fMRI) to investigate the age-dependent alterations of resting-state functional connectivity within the task-related network. Twenty-three young subjects and nineteen elderly subjects participated in this study, and a modified Posner paradigm was used to define the region of interest (ROI). Our results showed that a marked reduction in the number of connections occurred with age, but this effect was not uniform throughout the brain: while there was a significant loss of communication in the anterior portion of the brain and between the anterior and posterior cerebral cortices, communication in the posterior portion of the brain was preserved. Moreover, the older adults exhibited weakened resting-state functional connectivity between the supplementary motor area and left anterior insular cortex. These findings suggest that, the disrupted functional connectivity of the brain network for visuospatial attention that occurs during normal aging may underlie the decline in cognitive performance.

  1. 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.

  2. 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

  3. Artificial Intelligence,

    DTIC Science & Technology

    PATTERN RECOGNITION, * ARTIFICIAL INTELLIGENCE , *TEXTBOOKS, COMPUTER PROGRAMMING, MATHEMATICAL LOGIC, ROBOTS, PROBLEM SOLVING, STATISTICAL ANALYSIS, GAME THEORY, NATURAL LANGUAGE, SELF ORGANIZING SYSTEMS.

  4. Advances in optical power budgets and bandwidth capacity of broadband networks

    NASA Astrophysics Data System (ADS)

    Mysore, Sudhesh M.

    determined to be 40 channels. A twenty-channel DWDM system using more than 650 km of optical fiber is tested that provides twice the number of DWDM channels and ten times more bandwidth per subscriber as commercial systems. Detailed tests are performed on both the analog video signals and 256-QAM digital signals transported over the network Measurements of fiber nonlinear effects such as SRS, four-wave-mixing, and cross-phase-modulation reveal that our modeling of linear and nonlinear fiber effects in broadband networks is accurate. The technologies and architectures investigated here will prove to be the building blocks for advanced broadband networks that will provide high-speed, interactive broadband services to subscribers in the near future. Our research has furthered the goal of developing reliable broadband networks that are similar to passive optical networks and provide very large bandwidth to subscribers.

  5. 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.

  6. 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.

  7. 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…

  8. 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

  9. Illusory Intelligences?

    ERIC Educational Resources Information Center

    White, John

    2008-01-01

    Howard Gardner's theory of Multiple Intelligences has had a huge influence on school education. But its credentials lack justification, as the first section of this paper shows via a detailed philosophical analysis of how the intelligences are identified. If we want to make sense of the theory, we need to turn from a philosophical to a historical…

  10. 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.

  11. 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.

  12. 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'.

  13. 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.

  14. 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

  15. 2009 Biospecimen research network symposium: advancing cancer research through biospecimen science.

    PubMed

    Moore, Helen M; Compton, Carolyn C; Lim, Mark D; Vaught, Jimmie; Christiansen, Katerina N; Alper, Joe

    2009-09-01

    This report details the proceedings of the 2009 Biospecimen Research Network (BRN) Symposium that took place on March 16 to 18, 2009, the second in a series of annual symposia sponsored by the National Cancer Institute Office of Biorepositories and Biospecimen Research. The BRN Symposium is a public forum addressing the relevance of biospecimen quality to progress in cancer research and the systematic investigation needed to understand how different methods of collection, processing, and storage of human biospecimens affect subsequent molecular research results. More than 300 participants from industry, academia, and government attended the symposium, which featured both formal presentations and a day of workshops aimed at addressing several key issues in biospecimen science. An additional 100 individuals participated via a live webcast (archived at http://brnsymposium.com). The BRN Symposium is part of a larger program designed as a networked, multidisciplinary research approach to increase the knowledge base for biospecimen science. Biospecimens are generally understood to represent an accurate representation of a patient's disease biology, but can instead reflect a combination of disease biology and the biospecimen's response to a wide range of biological stresses. The molecular signatures of disease can thus be confounded by the signatures of biospecimen biological stress, with the potential to affect clinical and research outcomes through incorrect diagnosis of disease, improper use of a given therapy, and irreproducible research results that can lead to misinterpretation of artifacts as biomarkers. Biospecimen research represents the kind of bricks-and-mortar research that provides a solid scientific foundation for future advances that will directly help patients.

  16. 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.

  17. Making Intelligent Systems Adaptive. (Revision)

    DTIC Science & Technology

    1988-10-01

    eventually produce solutions. BY contrast, human beinge and other intelligent animls continuously adapt to the demands and opportunities presented by a...such as monitoring critically ill medical patients or controlling a manufacturing process. Following the model set by human intelligence, we define...signs probabilistically, using a belief network, as well as from first principles, using explicit models of system structure and function. Concurrent

  18. Intelligent distributed medical image management

    NASA Astrophysics Data System (ADS)

    Garcia, Hong-Mei C.; Yun, David Y.

    1995-05-01

    The rapid advancements in high performance global communication have accelerated cooperative image-based medical services to a new frontier. Traditional image-based medical services such as radiology and diagnostic consultation can now fully utilize multimedia technologies in order to provide novel services, including remote cooperative medical triage, distributed virtual simulation of operations, as well as cross-country collaborative medical research and training. Fast (efficient) and easy (flexible) retrieval of relevant images remains a critical requirement for the provision of remote medical services. This paper describes the database system requirements, identifies technological building blocks for meeting the requirements, and presents a system architecture for our target image database system, MISSION-DBS, which has been designed to fulfill the goals of Project MISSION (medical imaging support via satellite integrated optical network) -- an experimental high performance gigabit satellite communication network with access to remote supercomputing power, medical image databases, and 3D visualization capabilities in addition to medical expertise anywhere and anytime around the country. The MISSION-DBS design employs a synergistic fusion of techniques in distributed databases (DDB) and artificial intelligence (AI) for storing, migrating, accessing, and exploring images. The efficient storage and retrieval of voluminous image information is achieved by integrating DDB modeling and AI techniques for image processing while the flexible retrieval mechanisms are accomplished by combining attribute- based and content-based retrievals.

  19. Computationally intelligent pulsed photoacoustics

    NASA Astrophysics Data System (ADS)

    Lukić, Mladena; Ćojbašić, Žarko; Rabasović, Mihailo D.; Markushev, Dragan D.

    2014-12-01

    In this paper, the application of computational intelligence in pulsed photoacoustics is discussed. Feedforward multilayer perception networks are applied for real-time simultaneous determination of the laser beam spatial profile and vibrational-to-translational relaxation time of the polyatomic molecules in gases. Networks are trained and tested with theoretical data adjusted for a given experimental set-up. Genetic optimization has been used for calculation of the same parameters, fitting the photoacoustic signals with a different number of generations. Observed benefits from the application of computational intelligence in pulsed photoacoustics and advantages over previously developed methods are discussed, such as real-time operation, high precision and the possibility of finding solutions in a wide range of parameters, similar to in experimental conditions. In addition, the applicability for practical uses, such as the real-time in situ measurements of atmospheric pollutants, along with possible further developments of obtained results, is argued.

  20. 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.

  1. Advancements of data anomaly detection research in wireless sensor networks: a survey and open issues.

    PubMed

    Rassam, Murad A; Zainal, Anazida; Maarof, Mohd Aizaini

    2013-08-07

    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.

  2. 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

  3. Design of Intelligent Cross-Layer Routing Protocols for Airborne Wireless Networks Under Dynamic Spectrum Access Paradigm

    DTIC Science & Technology

    2011-05-01

    manet-aodv-11.txt 107 17. D. Johnson, D. A. Maltz, and J. Broch , “The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks,” IETF Internet...multipath distance vector routing,” Wireless Communications And Mobile Computing, vol. 6, pp. 969–988, 2006. 51. J. Broch , D. Maltz, D. Johnson, Y. Hu...wireless networks,” Proc. INFOCOM’97, pp. 1405–1413, April 1997. 55. J. Broch , D. Johnson, and D.Maltz, “The dynamic source routing protocol for mobile ad

  4. 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…

  5. Synthetic biology routes to bio-artificial intelligence.

    PubMed

    Nesbeth, Darren N; Zaikin, Alexey; Saka, Yasushi; Romano, M Carmen; Giuraniuc, Claudiu V; Kanakov, Oleg; Laptyeva, Tetyana

    2016-11-30

    The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular 'teachers' and 'students' is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI).

  6. Synthetic biology routes to bio-artificial intelligence

    PubMed Central

    Zaikin, Alexey; Saka, Yasushi; Romano, M. Carmen; Giuraniuc, Claudiu V.; Kanakov, Oleg; Laptyeva, Tetyana

    2016-01-01

    The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular ‘teachers’ and ‘students’ is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI). PMID:27903825

  7. Intelligent foreign particle inspection machine for injection liquid examination based on modified pulse-coupled neural networks.

    PubMed

    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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. Combining advanced networked technology and pedagogical methods to improve collaborative distance learning.

    PubMed

    Staccini, Pascal; Dufour, Jean-Charles; Raps, Hervé; Fieschi, Marius

    2005-01-01

    Making educational material be available on a network cannot be reduced to merely implementing hypermedia and interactive resources on a server. A pedagogical schema has to be defined to guide students for learning and to provide teachers with guidelines to prepare valuable and upgradeable resources. Components of a learning environment, as well as interactions between students and other roles such as author, tutor and manager, can be deduced from cognitive foundations of learning, such as the constructivist approach. Scripting the way a student will to navigate among information nodes and interact with tools to build his/her own knowledge can be a good way of deducing the features of the graphic interface related to the management of the objects. We defined a typology of pedagogical resources, their data model and their logic of use. We implemented a generic and web-based authoring and publishing platform (called J@LON for Join And Learn On the Net) within an object-oriented and open-source programming environment (called Zope) embedding a content management system (called Plone). Workflow features have been used to mark the progress of students and to trace the life cycle of resources shared by the teaching staff. The platform integrated advanced on line authoring features to create interactive exercises and support live courses diffusion. The platform engine has been generalized to the whole curriculum of medical studies in our faculty; it also supports an international master of risk management in health care and will be extent to all other continuous training diploma.

  14. 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.

  15. Advancing the State of the Art in Applying Network Science to C2

    DTIC Science & Technology

    2014-06-01

    research into effective mixed-sector ER network governance. In the third contribution, Networked Operations: Taking into Account the Principles of...relationship between the number of nodes and network effectiveness , arguing that near-decomposability is an important organizational design parameter. He makes...as elaborating on the effect of structural holes in organizational networks . The second group consists of the three contributions on modelling

  16. General expressions for downlink signal to interference and noise ratio in homogeneous and heterogeneous LTE-Advanced networks.

    PubMed

    Ali, Nora A; Mourad, Hebat-Allah M; ElSayed, Hany M; El-Soudani, Magdy; Amer, Hassanein H; Daoud, Ramez M

    2016-11-01

    The interference is the most important problem in LTE or LTE-Advanced networks. In this paper, the interference was investigated in terms of the downlink signal to interference and noise ratio (SINR). In order to compare the different frequency reuse methods that were developed to enhance the SINR, it would be helpful to have a generalized expression to study the performance of the different methods. Therefore, this paper introduces general expressions for the SINR in homogeneous and in heterogeneous networks. In homogeneous networks, the expression was applied for the most common types of frequency reuse techniques: soft frequency reuse (SFR) and fractional frequency reuse (FFR). The expression was examined by comparing it with previously developed ones in the literature and the comparison showed that the expression is valid for any type of frequency reuse scheme and any network topology. Furthermore, the expression was extended to include the heterogeneous network; the expression includes the problem of co-tier and cross-tier interference in heterogeneous networks (HetNet) and it was examined by the same method of the homogeneous one.

  17. 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.

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

    DTIC Science & Technology

    2011-09-30

    channel interference mitigation for underwater acoustic MIMO-OFDM. 3) Turbo equalization for OFDM modulated physical layer network coding. 4) Blind CFO...Localization and tracking of underwater physical systems. 7) NAMS: A networked acoustic modem system for underwater applications . 8) OFDM receiver design in...3) Turbo Equalization for OFDM Modulated Physical Layer Network Coding. We have investigated a practical orthogonal frequency division multiplexing

  19. 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…

  20. Genome-Wide Association Mapping for Intelligence in Military Working Dogs: Development of Advanced Classification Algorithm for Genome-Wide Single Nucleotide Polymorphism (SNP) Data Analysis

    DTIC Science & Technology

    2011-04-01

    distribution unlimited. QC – quality control QTL – quantitative trait loci SNP – single nucleotide polymorphism TE – Tris + EDTA TBE – Tris + Boric Acid + EDTA WGSA – whole genome sampling assay ...canine intelligence testing protocol EDTA – ethylenediaminetetraacetic acid GWAS – genome-wide association study LD – linkage disequilibrium MWD

  1. Advancing the Public Interest through Knowledge and Distributed Intelligence. Summary Report of the Leadership Colloquium (Washington, D.C., September 25-26, 1997, December 12, 1997).

    ERIC Educational Resources Information Center

    National Academy of Sciences - National Research Council, Washington, DC. Computer Science and Telecommunications Board.

    The relationship between research on information technologies and efforts to meet societal needs is the underlying theme of this summary document, which synthesizes the proceedings of the Leadership Colloquium on Knowledge and Distributed Intelligence (KDI). The Colloquium (which comprised one meeting in September and one meeting in December 1997)…

  2. 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…

  3. Incidental Learning, Intelligence, and Verbal Ability.

    ERIC Educational Resources Information Center

    Necka, Edward; And Others

    1992-01-01

    The effects of incidental learning were assessed in 2 experiments involving 201 seventh graders in Poland through an experimental paradigm based on the levels of processing theory. Data suggest that an important aspect of intelligence is "opportunistic" learning (learning in advance). Intelligent people take cognitive advantage of…

  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. 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

  6. Engineering robust intelligent robots

    NASA Astrophysics Data System (ADS)

    Hall, E. L.; Ali, S. M. Alhaj; Ghaffari, M.; Liao, X.; Cao, M.

    2010-01-01

    The purpose of this paper is to discuss the challenge of engineering robust intelligent robots. Robust intelligent robots may be considered as ones that not only work in one environment but rather in all types of situations and conditions. Our past work has described sensors for intelligent robots that permit adaptation to changes in the environment. We have also described the combination of these sensors with a "creative controller" that permits adaptive critic, neural network learning, and a dynamic database that permits task selection and criteria adjustment. However, the emphasis of this paper is on engineering solutions which are designed for robust operations and worst case situations such as day night cameras or rain and snow solutions. This ideal model may be compared to various approaches that have been implemented on "production vehicles and equipment" using Ethernet, CAN Bus and JAUS architectures and to modern, embedded, mobile computing architectures. Many prototype intelligent robots have been developed and demonstrated in terms of scientific feasibility but few have reached the stage of a robust engineering solution. Continual innovation and improvement are still required. The significance of this comparison is that it provides some insights that may be useful in designing future robots for various manufacturing, medical, and defense applications where robust and reliable performance is essential.

  7. 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

  8. 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.

  9. Emerging systems and machine intelligence

    SciTech Connect

    Glasgow, J.C. II.

    1989-01-01

    A theory of mind or intelligence that derives from elements of philosophical, biological, linguistic, and psychological thought as well as of physics and information theory is presented. The hypothesis is defended that intelligence is not a thing but a composite of activities and attributes that must be described in terms of the evolution and interactions of systems, emerging into the environments in which they are embedded. It is proposed that a machine intelligence that emulates human intelligence must conform to certain restrictions that derive from accepting this hypothesis. In particular an implication is that for machine intelligence to be accepted as human-like intelligence it must be produced by a machine that functions in a manner substantially similar to a man and that interacts, grows or learns in and with an environment similar to that in which a man grows and learns. It is proposed that it should be possible to create machines and programs capable of this and that they can achieve intelligence with a large, but not arbitrarily large, degree of human-like characteristics. One system (of many possible systems), in development, based on grammars, and that satisfies some of those requirements is described. It consists of an artificial environment in which a grammar like program based on augmented transition networks, interacts with a human teacher. The purpose of KARA is to learn about the environment by being told and by imitation.

  10. 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…

  11. 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…

  12. 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.

  13. Strong Artificial Intelligence and National Security: Operational and Strategic Implications

    DTIC Science & Technology

    2015-05-18

    FINAL 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE Strong Artificial Intelligence and National Security 5a...Prominent business and science leaders believe that technological advances will soon allow humankind to develop artificial intelligence (AI) that...its potential strategic pitfalls. 15. SUBJECT TERMS Artificial Intelligence 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT

  14. Attention and Working Memory as Predictors of Intelligence

    ERIC Educational Resources Information Center

    Schweizer, Karl; Moosbrugger, Helfried

    2004-01-01

    The paper reports on an investigation of attention and working memory as sources of intelligence. The investigation was concentrated on the relatedness of attention and working memory as predictors of intelligence and on the structure underlying the prediction. In a sample of 120 participants, intelligence was assessed by the Advanced Progressive…

  15. 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.

  16. Effect of Noise in Intelligent Cellular Decision Making

    PubMed Central

    Bates, Russell; Blyuss, Oleg; Alsaedi, Ahmed; Zaikin, Alexey

    2015-01-01

    Similar to intelligent multicellular neural networks controlling human brains, even single cells, surprisingly, are able to make intelligent decisions to classify several external stimuli or to associate them. This happens because of the fact that gene regulatory networks can perform as perceptrons, simple intelligent schemes known from studies on Artificial Intelligence. We study the role of genetic noise in intelligent decision making at the genetic level and show that noise can play a constructive role helping cells to make a proper decision. We show this using the example of a simple genetic classifier able to classify two external stimuli. PMID:25965584

  17. Advanced WDM CATV technologies and development issues for improved network performance

    NASA Astrophysics Data System (ADS)

    Schweitzer, Eric

    2003-08-01

    CATV (Community Antenna Television) networks were developed several decades ago to deliver a few channels of analog television to a fraction of the homes in a small area. Over the intervening years, these networks have evolved into true communications networks supporting digital video and the delivery of different targeted services to homes and business covering a much larger area. Supporting targeted services and spanning the longer distances has required the application of several technologies and the development of new network architectures. These new services require the use of technologies such as WDM. First, the unique characteristics of CATV networks are discussed. Examples of WDM-based network architectures that can support targeted data services via CATV cable modems and Video-on-Demand (VOD) are also presented.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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…

  5. 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.

  6. Developing an Intelligent Language Tutor

    ERIC Educational Resources Information Center

    Heift, Trude

    2010-01-01

    This article discusses the development and functionalities of an intelligent computer-assisted language learning (ICALL) system. By way of example, we describe "E-Tutor", an ICALL system for L2 learners of German that has been in use for a decade. Based on advancements in technology, user studies with L2 learners of German as well as feedback…

  7. 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

  8. Multiple Intelligences.

    ERIC Educational Resources Information Center

    Laughlin, Janet

    1999-01-01

    Details the characteristics of Howard Gardner's seven multiple intelligences (MI): linguistic, logical-mathematical, bodily-kinesthetic, spatial, musical, interpersonal, and intrapersonal. Discusses the implications of MI for instruction. Explores how students can study using their preferred learning style - visual, auditory, and physical study…

  9. 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…

  10. Intelligent Intervention.

    ERIC Educational Resources Information Center

    Scarr, Sandra

    Research has shown that differences among ordinary people in intelligence and personality depend equally on individual genetic variability and on differences in the environments that siblings experience within the same family, not differences in the neighborhood, school, and community environments. As of yet, there are no adequate theories to…

  11. 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.

  12. Intelligent Mobile Health Monitoring System (IMHMS)

    NASA Astrophysics Data System (ADS)

    Shahriyar, Rifat; Bari, Md. Faizul; Kundu, Gourab; Ahamed, Sheikh Iqbal; Akbar, Md. Mostofa

    Health monitoring is repeatedly mentioned as one of the main application areas for Pervasive computing. Mobile Health Care is the integration of mobile computing and health monitoring. It is the application of mobile computing technologies for improving communication among patients, physicians, and other health care workers. As mobile devices have become an inseparable part of our life it can integrate health care more seamlessly to our everyday life. It enables the delivery of accurate medical information anytime anywhere by means of mobile devices. Recent technological advances in sensors, low-power integrated circuits, and wireless communications have enabled the design of low-cost, miniature, lightweight and intelligent bio-sensor nodes. These nodes, capable of sensing, processing, and communicating one or more vital signs, can be seamlessly integrated into wireless personal or body area networks for mobile health monitoring. In this paper we present Intelligent Mobile Health Monitoring System (IMHMS), which can provide medical feedback to the patients through mobile devices based on the biomedical and environmental data collected by deployed sensors.

  13. 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.

  14. 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

  15. 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.

  16. An intercomparison of artificial intelligence approaches for polar scene identification

    NASA Astrophysics Data System (ADS)

    Tovinkere, V. R.; Penaloza, M.; Logar, A.; Lee, J.; Weger, R. C.; Berendes, T. A.; Welch, R. M.

    1993-03-01

    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 "don't care" perceptron network; (5) the "don't care" 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 "don't care" 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 (≥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.

  17. 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.

  18. 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,…

  19. Adaptive Probabilistic Protocols for Advanced Networks/Assuring the Integrity of Highly Decentralized Communications Systems

    DTIC Science & Technology

    2005-03-01

    on work done in our effort, and the IPTO Situation-Aware Protocols In Edge Network Technologies ( SAPIENT ) program, under Jonathan Smith, seeks to...of our work: The IPTO SRS program, under Lee Badger, builds 3 on work done in our effort, and the IPTO SAPIENT program, under Jonathan Smith, seeks...Jonathan Smith’s SAPIENT program reflects some of the ideas and successes of our compositional networking approach. SAPIENT will apply similar 11

  20. 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.

  1. 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.

  2. 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.

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

    PubMed

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

    2012-09-01

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

  4. Intelligence Sharing in Bosnia

    DTIC Science & Technology

    2007-11-02

    increases with the demands of near real time accurate intelligence for operational decision-making. Given this environment, intelligence-sharing...operating system providing actionable near-real- time intelligence to commanders for coalition synchronization and the requirement to protect national...real time accurate intelligence for operational decision-making. Given this environment, intelligence-sharing requirements across an ad hoc coalition

  5. 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…

  6. 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.

  7. 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.

  8. Intelligent Transformer: Possibilities and Challenges

    NASA Astrophysics Data System (ADS)

    Viktor, Beldjajev; Indrek, Roasto; Tõnu, Lehtla

    2011-01-01

    This paper covers the concept of an intelligent transformer that is a good candidate to replace a conventional low frequency transformer in the microgrids. As the power production and consumption can vary in a wide range, the new substations have to meet many requirements to guarantee reliable energy management in the autonomous networks. Different topologies of intelligent transformers can be used to meet these requirements. Therefore the advantages and disadvantages of the existing topologies were analyzed. The future trends and challenges are also discussed.

  9. 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.

  10. Advancing the boundaries of high-connectivity network simulation with distributed computing.

    PubMed

    Morrison, Abigail; Mehring, Carsten; Geisel, Theo; Aertsen, A D; Diesmann, Markus

    2005-08-01

    The availability of efficient and reliable simulation tools is one of the mission-critical technologies in the fast-moving field of computational neuroscience. Research indicates that higher brain functions emerge from large and complex cortical networks and their interactions. The large number of elements (neurons) combined with the high connectivity (synapses) of the biological network and the specific type of interactions impose severe constraints on the explorable system size that previously have been hard to overcome. Here we present a collection of new techniques combined to a coherent simulation tool removing the fundamental obstacle in the computational study of biological neural networks: the enormous number of synaptic contacts per neuron. Distributing an individual simulation over multiple computers enables the investigation of networks orders of magnitude larger than previously possible. The software scales excellently on a wide range of tested hardware, so it can be used in an interactive and iterative fashion for the development of ideas, and results can be produced quickly even for very large networks. In contrast to earlier approaches, a wide class of neuron models and synaptic dynamics can be represented.

  11. Intelligence Revisited

    DTIC Science & Technology

    2005-05-01

    reasoning, rote memory , and the like.” Standardized tests also fall short in terms of assessing other important aspects of intelligence such as creativity...ipEngine made by BrightStar Engineering. Then in 2004 we further evolved to a Compulab 686 CORE with 128 megabytes of memory running at 266 mHz...driver runs in a continuous loop, timing sonar echoes on each pass, storing the resulting range values in memory for on-demand access by other

  12. International experience on the use of artificial neural networks in gastroenterology.

    PubMed

    Grossi, E; Mancini, A; Buscema, M

    2007-03-01

    In this paper, we reconsider the scientific background for the use of artificial intelligence tools in medicine. A review of some recent significant papers shows that artificial neural networks, the more advanced and effective artificial intelligence technique, can improve the classification accuracy and survival prediction of a number of gastrointestinal diseases. We discuss the 'added value' the use of artificial neural networks-based tools can bring in the field of gastroenterology, both at research and clinical application level, when compared with traditional statistical or clinical-pathological methods.

  13. Increasing the coverage area through relay node deployment in long term evolution advanced cellular networks

    NASA Astrophysics Data System (ADS)

    Aldhaibani, Jaafar A.; Ahmad, R. B.; Yahya, A.; Azeez, Suzan A.

    2015-05-01

    Wireless multi-hop relay networks have become very important technologies in mobile communications. These networks ensure high throughput and coverage extension with a low cost. The poor capacity at cell edges is not enough to meet with growing demand of high capacity and throughput irrespective of user's placement in the cellular network. In this paper we propose optimal placement of relay node that provides maximum achievable rate at users and enhances the throughput and coverage at cell edge region. The proposed scheme is based on the outage probability at users and taken on account the interference between nodes. Numerical analyses along with simulation results indicated there are an improvement in capacity for users at the cell edge is 40% increment from all cell capacity.

  14. 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

  15. 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. The neural network technique works well not only as an interpolating device but also as an extrapolating device to achieve blade designs from a given database. Two validating test cases are discussed.

  16. 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.

  17. 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.

  18. 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.

  19. 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)

  20. A Comparison of Adolescents' Friendship Networks by Advanced Coursework Participation Status

    ERIC Educational Resources Information Center

    Barber, Carolyn; Wasson, Jillian Woodford

    2015-01-01

    Friendships serve as a source of support and as a context for developing social competence. Although advanced coursework may provide a unique context for the development of friendships, more research is needed to explore exactly what differences exist. Using the National Longitudinal Study of Adolescent Health and the Adolescent Health and…