Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

A new type of intelligent wireless sensing network for health monitoring of large-size structures

Science.gov (United States)

Lei, Ying; Liu, Ch.; Wu, D. T.; Tang, Y. L.; Wang, J. X.; Wu, L. J.; Jiang, X. D.

2009-07-01

In recent years, some innovative wireless sensing systems have been proposed. However, more exploration and research on wireless sensing systems are required before wireless systems can substitute for the traditional wire-based systems. In this paper, a new type of intelligent wireless sensing network is proposed for the heath monitoring of large-size structures. Hardware design of the new wireless sensing units is first studied. The wireless sensing unit mainly consists of functional modules of: sensing interface, signal conditioning, signal digitization, computational core, wireless communication and battery management. Then, software architecture of the unit is introduced. The sensing network has a two-level cluster-tree architecture with Zigbee communication protocol. Important issues such as power saving and fault tolerance are considered in the designs of the new wireless sensing units and sensing network. Each cluster head in the network is characterized by its computational capabilities that can be used to implement the computational methodologies of structural health monitoring; making the wireless sensing units and sensing network have "intelligent" characteristics. Primary tests on the measurement data collected by the wireless system are performed. The distributed computational capacity of the intelligent sensing network is also demonstrated. It is shown that the new type of intelligent wireless sensing network provides an efficient tool for structural health monitoring of large-size structures.

A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

Science.gov (United States)

2017-12-05

A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

Ecological Design of Cooperative Human-Machine Interfaces for Safety of Intelligent Transport Systems

Directory of Open Access Journals (Sweden)

Orekhov Aleksandr

2016-01-01

Full Text Available The paper describes research results in the domain of cooperative intelligent transport systems. The requirements for human-machine interface considering safety issue of for intelligent transport systems (ITSare analyzed. Profiling of the requirements to cooperative human-machine interface (CHMI for such systems including requirements to usability and safety is based on a set of standards for ITSs. An approach and design technique of cooperative human-machine interface for ITSs are suggested. The architecture of cloud-based CHMI for intelligent transport systems has been developed. The prototype of software system CHMI4ITSis described.

Intelligent Wireless Sensor Networks for System Health Monitoring

Science.gov (United States)

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

Efficient Networks Communication Routing Using Swarm Intelligence

OpenAIRE

Koushal Kumar

2012-01-01

As demonstrated by natural biological swarm’s collective intelligence has an abundance of desirable properties for problem-solving like in network routing. The focus of this paper is in the applications of swarm based intelligence in information routing for communication networks. As we know networks are growing and adopting new platforms as new technologies comes. Also according to new demands and requirements networks topologies and its complexity is increasing with time. Thus it is becomin...

Multiple network interface core apparatus and method

Science.gov (United States)

Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

2011-04-26

A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

A Framework for Function Allocation in Intelligent Driver Interface Design for Comfort and Safety

Directory of Open Access Journals (Sweden)

Wuhong Wang

2010-11-01

Full Text Available This paper presents a conceptual framework for ecological function allocation and optimization matching solution for a human-machine interface with intelligent characteristics by lwho does what and when and howr consideration. As a highlighted example in nature-social system, intelligent transportation system has been playing increasingly role in keeping traffic safety, our research is concerned with identifying human factors problem of In-vehicle Support Systems (ISSs and revealing the consequence of the effects of ISSs on driver cognitive interface. The primary objective is to explore some new ergonomics principals that will be able to use to design an intelligent driver interface for comfort and safety, which will address the impact of driver interfaces layouts, traffic information types, and driving behavioral factors on the advanced vehicles safety design.

Intelligent Human Machine Interface Design for Advanced Product Life Cycle Management Systems

OpenAIRE

Ahmed, Zeeshan

2010-01-01

Designing and implementing an intelligent and user friendly human machine interface for any kind of software or hardware oriented application is always be a challenging task for the designers and developers because it is very difficult to understand the psychology of the user, nature of the work and best suit of the environment. This research paper is basically about to propose an intelligent, flexible and user friendly machine interface for Product Life Cycle Management products or PDM Syste...

Robot Advanced Intelligent Control developed through Versatile ...

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... environments of human life exposed to great dangers such as support and repair in .... intelligent control interfaces, network quality of service, shared resources and ..... Artificial Intelligence series, volume 6556, p. 336-349 ...

Humans, Intelligent Technology, and Their Interface: A Study of Brown’s Point

Science.gov (United States)

2017-12-01

INTELLIGENT TECHNOLOGY , AND THEIR INTERFACE: A STUDY OF BROWN’S POINT by Jackie L. J. White December 2017 Thesis Advisor: Carolyn Halladay...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE HUMANS, INTELLIGENT TECHNOLOGY , AND THEIR INTERFACE: A STUDY OF BROWN’S POINT...with the technology before and during the accident. I combined the findings from the accident investigation with various heuristics regarding the human

Network device interface for digitally interfacing data channels to a controller via a network

Science.gov (United States)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor)

2009-01-01

A communications system and method are provided for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. Network device interfaces associated with different data channels can coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

The desktop interface in intelligent tutoring systems

Science.gov (United States)

Baudendistel, Stephen; Hua, Grace

1987-01-01

The interface between an Intelligent Tutoring System (ITS) and the person being tutored is critical to the success of the learning process. If the interface to the ITS is confusing or non-supportive of the tutored domain, the effectiveness of the instruction will be diminished or lost entirely. Consequently, the interface to an ITS should be highly integrated with the domain to provide a robust and semantically rich learning environment. In building an ITS for ZetaLISP on a LISP Machine, a Desktop Interface was designed to support a programming learning environment. Using the bitmapped display, windows, and mouse, three desktops were designed to support self-study and tutoring of ZetaLISP. Through organization, well-defined boundaries, and domain support facilities, the desktops provide substantial flexibility and power for the student and facilitate learning ZetaLISP programming while screening the student from the complex LISP Machine environment. The student can concentrate on learning ZetaLISP programming and not on how to operate the interface or a LISP Machine.

Eye gaze in intelligent user interfaces gaze-based analyses, models and applications

CERN Document Server

Nakano, Yukiko I; Bader, Thomas

2013-01-01

Remarkable progress in eye-tracking technologies opened the way to design novel attention-based intelligent user interfaces, and highlighted the importance of better understanding of eye-gaze in human-computer interaction and human-human communication. For instance, a user's focus of attention is useful in interpreting the user's intentions, their understanding of the conversation, and their attitude towards the conversation. In human face-to-face communication, eye gaze plays an important role in floor management, grounding, and engagement in conversation.Eye Gaze in Intelligent User Interfac

Advanced Applications of Neural Networks and Artificial Intelligence: A Review

OpenAIRE

Koushal Kumar; Gour Sundar Mitra Thakur

2012-01-01

Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

CATO: a CAD tool for intelligent design of optical networks and interconnects

Science.gov (United States)

Chlamtac, Imrich; Ciesielski, Maciej; Fumagalli, Andrea F.; Ruszczyk, Chester; Wedzinga, Gosse

1997-10-01

Increasing communication speed requirements have created a great interest in very high speed optical and all-optical networks and interconnects. The design of these optical systems is a highly complex task, requiring the simultaneous optimization of various parts of the system, ranging from optical components' characteristics to access protocol techniques. Currently there are no computer aided design (CAD) tools on the market to support the interrelated design of all parts of optical communication systems, thus the designer has to rely on costly and time consuming testbed evaluations. The objective of the CATO (CAD tool for optical networks and interconnects) project is to develop a prototype of an intelligent CAD tool for the specification, design, simulation and optimization of optical communication networks. CATO allows the user to build an abstract, possible incomplete, model of the system, and determine its expected performance. Based on design constraints provided by the user, CATO will automatically complete an optimum design, using mathematical programming techniques, intelligent search methods and artificial intelligence (AI). Initial design and testing of a CATO prototype (CATO-1) has been completed recently. The objective was to prove the feasibility of combining AI techniques, simulation techniques, an optical device library and a graphical user interface into a flexible CAD tool for obtaining optimal communication network designs in terms of system cost and performance. CATO-1 is an experimental tool for designing packet-switching wavelength division multiplexing all-optical communication systems using a LAN/MAN ring topology as the underlying network. The two specific AI algorithms incorporated are simulated annealing and a genetic algorithm. CATO-1 finds the optimal number of transceivers for each network node, using an objective function that includes the cost of the devices and the overall system performance.

Collective intelligent wireless sensor networks

NARCIS (Netherlands)

Mihaylov, M.; Nowe, A.; Tuyls, K.P.; Nijholt, A.; Pantic, M.

2008-01-01

In this paper we apply the COllective INtelligence (COIN) framework ofWolpert et al. toWireless Sensor Networks (WSNs) with the aim to increase the autonomous lifetime of the network in a decentralized manner. COIN describes how selfish agents can learn to optimize their own performance, so that the

Wireless intelligent network: infrastructure before services?

Science.gov (United States)

Chu, Narisa N.

1996-01-01

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

Constructing an Intelligent Patent Network Analysis Method

Directory of Open Access Journals (Sweden)

Chao-Chan Wu

2012-11-01

Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

A Proposed Intelligent Policy-Based Interface for a Mobile eHealth Environment

Science.gov (United States)

Tavasoli, Amir; Archer, Norm

Users of mobile eHealth systems are often novices, and the learning process for them may be very time consuming. In order for systems to be attractive to potential adopters, it is important that the interface should be very convenient and easy to learn. However, the community of potential users of a mobile eHealth system may be quite varied in their requirements, so the system must be able to adapt easily to suit user preferences. One way to accomplish this is to have the interface driven by intelligent policies. These policies can be refined gradually, using inputs from potential users, through intelligent agents. This paper develops a framework for policy refinement for eHealth mobile interfaces, based on dynamic learning from user interactions.

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

Directory of Open Access Journals (Sweden)

Florian U Fischer

Full Text Available 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.

Association of Structural Global Brain Network Properties with Intelligence in Normal Aging

Science.gov (United States)

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. PMID:24465994

Preparation of heterogeneous networks for ambient intelligence

NARCIS (Netherlands)

Stok, van der P.D.V.; Basten, A.A.; Geilen, M.C.W.; Groot, de H.W.H.

2003-01-01

Ambient Intelligence assumes the existence of ubiquitous networked computing. Networking is supported in the home by a so-called home network. Currently, the home network emerges from the purchase of a second PC in the home. Extending the home network confronts the prospective buyer with a multitude

Service creation and deployment on an intelligent network

OpenAIRE

Collins, Michael

1999-01-01

Active competition in the telecommunications industry has caused a dramatic shift in focus for public network operators. Service designers need to be able to easily and rapidly create services according to the customer’s requirements. This is achievable by using Intelligent Networks (INs). Two primary goals of service development under the Intelligent Network paradigm are rapid service crcation using new software technologies and the minimisation of service development costs through switch ve...

i-Car: An Intelligent and Interactive Interface for Driver Assistance ...

African Journals Online (AJOL)

i-Car: An Intelligent and Interactive Interface for Driver Assistance System. ... techniques with pattern recognition, feature extraction, machine learning, object recognition, ... The system uses eye closure based decision algorithm to detect driver ...

Advantages of Intelligent SDH/SONET Networks

Indian Academy of Sciences (India)

First page Back Continue Last page Overview Graphics. Advantages of Intelligent SDH/SONET Networks. GMPLS simplifies network management, thus reducing operating expenses (“staff”) and minimizing errors. Same benefits as computerization of banking, accounts, etc. Auto-discovery simplifies equipment installation ...

Intelligent Network in the Republic of Croatia

Directory of Open Access Journals (Sweden)

Slavko Šarić

2012-10-01

Full Text Available The introduction of intelligence into the telecommunicationnetwork of Croatia is becoming one of the key elements ofthe future development of the network. The paper describes there-organisation of the telecommunication network in Croatia,the process of creating and managing the intelligent services,the initial situation and the feasible plan of introducing the INconcepts. The paper is concluded with a list of IN services thatare being introduced in the initial phase of the Croatian telecommunicationnetwork.

An Intelligent Alternative Approach to the efficient Network Management

Directory of Open Access Journals (Sweden)

MARTÍN, A.

2012-12-01

Full Text Available Due to the increasing complexity and heterogeneity of networks and services, many efforts have been made to develop intelligent techniques for management. Network intelligent management is a key technology for operating large heterogeneous data transmission networks. This paper presents a proposal for an architecture that integrates management object specifications and the knowledge of expert systems. We present a new approach named Integrated Expert Management, for learning objects based on expert management rules and describe the design and implementation of an integrated intelligent management platform based on OSI and Internet management models. The main contributions of our approach is the integration of both expert system and managed models, so we can make use of them to construct more flexible intelligent management network. The prototype SONAP (Software for Network Assistant and Performance is accuracy-aware since it can control and manage a network. We have tested our system on real data to the fault diagnostic in a telecommunication system of a power utility. The results validate the model and show a significant improvement with respect to the number of rules and the error rate in others systems.

An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

Science.gov (United States)

1996-01-01

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 appli...

Social networks a framework of computational intelligence

CERN Document Server

Chen, Shyi-Ming

2014-01-01

This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

A theory of intelligence: networked problem solving in animal societies

OpenAIRE

Shour, Robert

2009-01-01

A society's single emergent, increasing intelligence arises partly from the thermodynamic advantages of networking the innate intelligence of different individuals, and partly from the accumulation of solved problems. Economic growth is proportional to the square of the network entropy of a society's population times the network entropy of the number of the society's solved problems.

The Cyber Intelligence Challenge of Asyngnotic Networks

Directory of Open Access Journals (Sweden)

Edward M. Roche

2015-09-01

Full Text Available The intelligence community is facing a new type of organization, one enabled by the world’s information and communications infrastructure. These asyngnotic networks operate without leadership and are self-organizing in nature. They pose a threat to national security because they are difficult to detect in time for intelligence to provide adequate warning. Social network analysis and link analysis are important tools but can be supplemented by application of neuroscience principles to understand the forces that drive asyngnotic self-organization and triggering of terrorist events. Applying Living Systems Theory (LST to a terrorist attack provides a useful framework to identify hidden asyngnotic networks. There is some antecedent work in propaganda analysis that may help uncover hidden asyngnotic networks, but computerized SIGINT methods face a number of challenges.

Cultural intelligence and network organizations in society: Case of Tehran neighborhood councils

Directory of Open Access Journals (Sweden)

Salamzadeh Yashar

2016-01-01

Full Text Available Network communications is one of the modern ideas in the field of organizational behavior. On the other hand, the ability to communicate with employees and understand the cultural differences between them in a multicultural environment is one of the key skills that managers and employees need them in the nowadays organizations. These skills are introduced as cultural intelligence in organizations that have ability to respond to many challenges in multicultural environments. This article was aimed to analysis the relationship between cultural intelligence and network communication. These questionnaires were distributed between 134 members at the Tehran neighborhood councils. In order to analyzing data and concluding results, SPSS, and then Pearson correlation test were used. The research was done based on structural equation modeling (SEM. The result indicated that there was significant positive relationship between cultural intelligence and network communication. Also there was significant positive relationship between each dimension of cultural intelligence and network communication. Findings show that cultural intelligence is a basic factor in network communication and confirm the main hypothesis of this study which represents the existence of a positive and meaningful relation between cultural intelligence and network communication. Furthermore, the results show that considering this kind of intelligence, especially in network organizations which has a high ethnic and cultural variety, could be very useful for improve employees and managers communications.

The role of trait emotional intelligence in predicting networking behavior

Directory of Open Access Journals (Sweden)

Teresa Torres-Coronas

2017-02-01

Full Text Available Objective – The purpose of this paper is to obtain evidence of the relation between entrepreneur proactive networking behavior and trait emotional intelligence to support transition towards entrepreneurial careers. Design/methodology/approach – The Trait Emotional Intelligence Questionnaire-Short form (TEIQue-SF, developed by Cooper and Petrides (2010, was used to test hypotheses on the factors that define a proactive use of a professional network and their relationship with the individual level of trait emotional intelligence and its four components (well-being, self-control, emotionality and sociability. A questionnaire was sent to local entrepreneurs to verify whether trait emotional intelligence act as a predictor of proactive networking behavior. Theoretical foundation – We will be using Petrides and Furnham’s (2001 trait EI definition and EI will be studied within a personality framework (Petrides, 2001, Petrides & Furnham, 2001, 2006, 2014. Findings – Final findings partially confirms research hypothesis, with some components of EI (well-being and self-control factors showing a significant positive correlation with proactive networking behavior. This indicates that entrepreneurs’ ability to regulate emotions influences their networking behavior helping them to succeed in their business relationships. Practical implications – The present study provides a clear direction for further research by focusing on how trait emotional intelligence affects social networking behavior amongst entrepreneurs, thus demonstrating the utility of using trait EI to evaluate high potential entrepreneurs.

A Visualized Message Interface (VMI) for intelligent messaging services

International Nuclear Information System (INIS)

Endo, T.; Kasahara, H.; Nakagawa, T.

1984-01-01

In CCITT, Message Handling Systems (MHS) have been studied from the viewpoint of communications protocol standardization. In addition to MHS services, Message Processing (MP) services, such as image processing, filing and retrieving services, will come into increasing demand in office automation field. These messaging services, including MHS services, can be thought of as Intelligent Messaging (IM) services. IM services include many basic services, optional user facilities and service parameters. Accordingly, it is necessary to deal with these parameters and MP procedures in as systematic and user-friendly a manner as possible. As one step towards realizing a user-friendly IM services interface, the characteristics of IM service parameters are studied and a Visualized Message Interface (VMI) which resembles a conventional letter exchange format is presented. The concept of VMI formation is discussed using the generic document structure concept as well as a Screen Interface and Protocol Interface conversion package

Techniques for Intelligence Analysis of Networks

National Research Council Canada - National Science Library

Cares, Jeffrey R

2005-01-01

...) there are significant intelligence analysis manifestations of these properties; and (4) a more satisfying theory of Networked Competition than currently exists for NCW/NCO is emerging from this research...

Nuclear spectrum data acquisition intelligent interface based on MCS-51 single chip microcomputer

International Nuclear Information System (INIS)

Xia Songjiang; Su Qin

1991-01-01

The intelligent interface consists of multichannel buffer and communication interface. It can acquire 4096 channels nuclear spectrum data. By connecting to a main computer, the data acquisition system has high resolution and foreground, background operating functions. The system features simple structure, reliable communication, convenient operation and high cost performance

Inter-cooperative collective intelligence techniques and applications

CERN Document Server

Bessis, Nik

2014-01-01

This book covers the latest advances in the rapid growing field of inter-cooperative collective intelligence aiming the integration and cooperation of various computational resources, networks and intelligent processing paradigms to collectively build intelligence and advanced decision support and interfaces for end-users. The book brings a comprehensive view of the state-of-the-art in the field of integration of sensor networks, IoT and Cloud computing, massive and intelligent querying and processing of data. As a result, the book presents lessons learned so far and identifies new research issues, challenges and opportunities for further research and development agendas. Emerging areas of applications are also identified and usefulness of inter-cooperative collective intelligence is envisaged.   Researchers, software developers, practitioners and students interested in the field of inter-cooperative collective intelligence will find the comprehensive coverage of this book useful for their research, academic...

Intelligence is associated with the modular structure of intrinsic brain networks.

Science.gov (United States)

Hilger, Kirsten; Ekman, Matthias; Fiebach, Christian J; Basten, Ulrike

2017-11-22

General intelligence is a psychological construct that captures in a single metric the overall level of behavioural and cognitive performance in an individual. While previous research has attempted to localise intelligence in circumscribed brain regions, more recent work focuses on functional interactions between regions. However, even though brain networks are characterised by substantial modularity, it is unclear whether and how the brain's modular organisation is associated with general intelligence. Modelling subject-specific brain network graphs from functional MRI resting-state data (N = 309), we found that intelligence was not associated with global modularity features (e.g., number or size of modules) or the whole-brain proportions of different node types (e.g., connector hubs or provincial hubs). In contrast, we observed characteristic associations between intelligence and node-specific measures of within- and between-module connectivity, particularly in frontal and parietal brain regions that have previously been linked to intelligence. We propose that the connectivity profile of these regions may shape intelligence-relevant aspects of information processing. Our data demonstrate that not only region-specific differences in brain structure and function, but also the network-topological embedding of fronto-parietal as well as other cortical and subcortical brain regions is related to individual differences in higher cognitive abilities, i.e., intelligence.

Computational intelligence synergies of fuzzy logic, neural networks and evolutionary computing

CERN Document Server

Siddique, Nazmul

2013-01-01

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspect

Adaptive intelligent power systems: Active distribution networks

International Nuclear Information System (INIS)

McDonald, Jim

2008-01-01

Electricity networks are extensive and well established. They form a key part of the infrastructure that supports industrialised society. These networks are moving from a period of stability to a time of potentially major transition, driven by a need for old equipment to be replaced, by government policy commitments to cleaner and renewable sources of electricity generation, and by change in the power industry. This paper looks at moves towards active distribution networks. The novel transmission and distribution systems of the future will challenge today's system designs. They will cope with variable voltages and frequencies, and will offer more flexible, sustainable options. Intelligent power networks will need innovation in several key areas of information technology. Active control of flexible, large-scale electrical power systems is required. Protection and control systems will have to react to faults and unusual transient behaviour and ensure recovery after such events. Real-time network simulation and performance analysis will be needed to provide decision support for system operators, and the inputs to energy and distribution management systems. Advanced sensors and measurement will be used to achieve higher degrees of network automation and better system control, while pervasive communications will allow networks to be reconfigured by intelligent systems

Low Power Multi-Hop Networking Analysis in Intelligent Environments.

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-05-19

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

Internet-based intelligent information processing systems

CERN Document Server

Tonfoni, G; Ichalkaranje, N S

2003-01-01

The Internet/WWW has made it possible to easily access quantities of information never available before. However, both the amount of information and the variation in quality pose obstacles to the efficient use of the medium. Artificial intelligence techniques can be useful tools in this context. Intelligent systems can be applied to searching the Internet and data-mining, interpreting Internet-derived material, the human-Web interface, remote condition monitoring and many other areas. This volume presents the latest research on the interaction between intelligent systems (neural networks, adap

Utilising artificial intelligence in software defined wireless sensor network

CSIR Research Space (South Africa)

Matlou, OG

2017-10-01

Full Text Available Software Defined Wireless Sensor Network (SDWSN) is realised by infusing Software Defined Network (SDN) model in Wireless Sensor Network (WSN), Reason for that is to overcome the challenges of WSN. Artificial Intelligence (AI) and machine learning...

Brain computer interfaces as intelligent sensors for enhancing human-computer interaction

NARCIS (Netherlands)

Poel, M.; Nijboer, F.; Broek, E.L. van den; Fairclough, S.; Nijholt, A.

2012-01-01

BCIs are traditionally conceived as a way to control apparatus, an interface that allows you to act on" external devices as a form of input control. We propose an alternative use of BCIs, that of monitoring users as an additional intelligent sensor to enrich traditional means of interaction. This

Brain computer interfaces as intelligent sensors for enhancing human-computer interaction

NARCIS (Netherlands)

Poel, Mannes; Nijboer, Femke; van den Broek, Egon; Fairclough, Stephen; Morency, Louis-Philippe; Bohus, Dan; Aghajan, Hamid; Nijholt, Antinus; Cassell, Justine; Epps, Julien

2012-01-01

BCIs are traditionally conceived as a way to control apparatus, an interface that allows you to "act on" external devices as a form of input control. We propose an alternative use of BCIs, that of monitoring users as an additional intelligent sensor to enrich traditional means of interaction. This

Relationship between Social Networks Adoption and Social Intelligence

Science.gov (United States)

Gunduz, Semseddin

2017-01-01

The purpose of this study was to set forth the relationship between the individuals' states to adopt social networks and social intelligence and analyze both concepts according to various variables. Research data were collected from 1145 social network users in the online media by using the Adoption of Social Network Scale and Social Intelligence…

The role of trait emotional intelligence in predicting networking behavior

OpenAIRE

Teresa Torres-Coronas; María-Arántzazu Vidal-Blasco

2017-01-01

Objective – The purpose of this paper is to obtain evidence of the relation between entrepreneur proactive networking behavior and trait emotional intelligence to support transition towards entrepreneurial careers. Design/methodology/approach – The Trait Emotional Intelligence Questionnaire-Short form (TEIQue-SF), developed by Cooper and Petrides (2010), was used to test hypotheses on the factors that define a proactive use of a professional network and their relationship with the indivi...

Network resilience against intelligent attacks constrained by the degree-dependent node removal cost

International Nuclear Information System (INIS)

Annibale, A; Coolen, A C C; Bianconi, G

2010-01-01

We study the resilience of complex networks against attacks in which nodes are targeted intelligently, but where disabling a node has a cost to the attacker which depends on its degree. Attackers have to meet these costs with limited resources, which constrains their actions. A network's integrity is quantified in terms of the efficacy of the process that it supports. We calculate how the optimal attack strategy and the most attack-resistant network degree statistics depend on the node removal cost function and the attack resources. The resilience of networks against intelligent attacks is found to depend strongly on the node removal cost function faced by the attacker. In particular, if node removal costs increase sufficiently fast with the node degree, power law networks are found to be more resilient than Poissonian ones, even against optimized intelligent attacks. For cost functions increasing quadratically in the node degrees, intelligent attackers cannot damage the network more than random damages would.

THE COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR PREDICTIONS - ARTIFICIAL NEURAL NETWORKS

OpenAIRE

Mary Violeta Bar

2014-01-01

The computational intelligence techniques are used in problems which can not be solved by traditional techniques when there is insufficient data to develop a model problem or when they have errors.Computational intelligence, as he called Bezdek (Bezdek, 1992) aims at modeling of biological intelligence. Artificial Neural Networks( ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is solving problems that are too c...

An approach to efficient mobility management in intelligent networks

Science.gov (United States)

Murthy, K. M. S.

1995-01-01

Providing personal communication systems supporting full mobility require intelligent networks for tracking mobile users and facilitating outgoing and incoming calls over different physical and network environments. In realizing the intelligent network functionalities, databases play a major role. Currently proposed network architectures envision using the SS7-based signaling network for linking these DB's and also for interconnecting DB's with switches. If the network has to support ubiquitous, seamless mobile services, then it has to support additionally mobile application parts, viz., mobile origination calls, mobile destination calls, mobile location updates and inter-switch handovers. These functions will generate significant amount of data and require them to be transferred between databases (HLR, VLR) and switches (MSC's) very efficiently. In the future, the users (fixed or mobile) may use and communicate with sophisticated CPE's (e.g. multimedia, multipoint and multisession calls) which may require complex signaling functions. This will generate volumness service handling data and require efficient transfer of these message between databases and switches. Consequently, the network providers would be able to add new services and capabilities to their networks incrementally, quickly and cost-effectively.

Intelligence Constraints on Terrorist Network Plots

Science.gov (United States)

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.

Optimisation of Software-Defined Networks Performance Using a Hybrid Intelligent System

Directory of Open Access Journals (Sweden)

Ann Sabih

2017-06-01

Full Text Available This paper proposes a novel intelligent technique that has been designed to optimise the performance of Software Defined Networks (SDN. The proposed hybrid intelligent system has employed integration of intelligence-based optimisation approaches with the artificial neural network. These heuristic optimisation methods include Genetic Algorithms (GA and Particle Swarm Optimisation (PSO. These methods were utilised separately in order to select the best inputs to maximise SDN performance. In order to identify SDN behaviour, the neural network model is trained and applied. The maximal optimisation approach has been identified using an analytical approach that considered SDN performance and the computational time as objective functions. Initially, the general model of the neural network was tested with unseen data before implementing the model using GA and PSO to determine the optimal performance of SDN. The results showed that the SDN represented by Artificial Neural Network ANN, and optmised by PSO, generated a better configuration with regards to computational efficiency and performance index.

Designing distributed user interfaces for ambient intelligent environments using models and simulations

OpenAIRE

LUYTEN, Kris; VAN DEN BERGH, Jan; VANDERVELPEN, Chris; CONINX, Karin

2006-01-01

There is a growing demand for design support to create interactive systems that are deployed in ambient intelligent environments. Unlike traditional interactive systems, the wide diversity of situations these type of user interfaces need to work in require tool support that is close to the environment of the end-user on the one hand and provide a smooth integration with the application logic on the other hand. This paper shows how the model-based user interface development methodology can be ...

Smart Collision Avoidance and Hazard Routing Mechanism for Intelligent Transport Network

Science.gov (United States)

Singh, Gurpreet; Gupta, Pooja; Wahab, Mohd Helmy Abd

2017-08-01

The smart vehicular ad-hoc network is the network that consists of vehicles for smooth movement and better management of the vehicular connectivity across the given network. This research paper aims to propose a set of solution for the VANETs consisting of the automatic driven vehicles, also called as the autonomous car. Such vehicular networks are always prone to collision due to the natural or un-natural reasons which must be solved before the large-scale deployment of the autonomous transport systems. The newly designed intelligent transport movement control mechanism is based upon the intelligent data propagation along with the vehicle collision and traffic jam prevention schema [8], which may help the future designs of smart cities to become more robust and less error-prone. In the proposed model, the focus is on designing a new dynamic and robust hazard routing protocol for intelligent vehicular networks for improvement of the overall performance in various aspects. It is expected to improve the overall transmission delay as well as the number of collisions or adversaries across the vehicular network zone.

Internal Interface Diversification as a Security Measure in Sensor Networks

Directory of Open Access Journals (Sweden)

Sampsa Rauti

2018-03-01

Full Text Available More actuator and sensor devices are connected to the Internet of Things (IoT every day, and the network keeps growing, while software security of the devices is often incomplete. Sensor networks and the IoT in general currently cover a large number of devices with an identical internal interface structure. By diversifying the internal interfaces, the interfaces on each node of the network are made unique, and it is possible to break the software monoculture of easily exploitable identical systems. This paper proposes internal interface diversification as a security measure for sensor networks. We conduct a study on diversifiable internal interfaces in 20 IoT operating systems. We also present two proof-of-concept implementations and perform experiments to gauge the feasibility in the IoT environment. Internal interface diversification has practical limitations, and not all IoT operating systems have that many diversifiable interfaces. However, because of low resource requirements, compatibility with other security measures and wide applicability to several interfaces, we believe internal interface diversification is a promising and effective approach for securing nodes in sensor networks.

Integrated computer network high-speed parallel interface

International Nuclear Information System (INIS)

Frank, R.B.

1979-03-01

As the number and variety of computers within Los Alamos Scientific Laboratory's Central Computer Facility grows, the need for a standard, high-speed intercomputer interface has become more apparent. This report details the development of a High-Speed Parallel Interface from conceptual through implementation stages to meet current and future needs for large-scle network computing within the Integrated Computer Network. 4 figures

High-resolution method for evolving complex interface networks

Science.gov (United States)

Pan, Shucheng; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-04-01

In this paper we describe a high-resolution transport formulation of the regional level-set approach for an improved prediction of the evolution of complex interface networks. The novelty of this method is twofold: (i) construction of local level sets and reconstruction of a global level set, (ii) local transport of the interface network by employing high-order spatial discretization schemes for improved representation of complex topologies. Various numerical test cases of multi-region flow problems, including triple-point advection, single vortex flow, mean curvature flow, normal driven flow, dry foam dynamics and shock-bubble interaction show that the method is accurate and suitable for a wide range of complex interface-network evolutions. Its overall computational cost is comparable to the Semi-Lagrangian regional level-set method while the prediction accuracy is significantly improved. The approach thus offers a viable alternative to previous interface-network level-set method.

Neural-Network-Based Fuzzy Logic Navigation Control for Intelligent Vehicles

Directory of Open Access Journals (Sweden)

Ahcene Farah

2002-06-01

Full Text Available This paper proposes a Neural-Network-Based Fuzzy logic system for navigation control of intelligent vehicles. First, the use of Neural Networks and Fuzzy Logic to provide intelligent vehicles  with more autonomy and intelligence is discussed. Second, the system  for the obstacle avoidance behavior is developed. Fuzzy Logic improves Neural Networks (NN obstacle avoidance approach by handling imprecision and rule-based approximate reasoning. This system must make the vehicle able, after supervised learning, to achieve two tasks: 1- to make one’s way towards its target by a NN, and 2- to avoid static or dynamic obstacles by a Fuzzy NN capturing the behavior of a human expert. Afterwards, two association phases between each task and the appropriate actions are carried out by Trial and Error learning and their coordination allows to decide the appropriate action. Finally, the simulation results display the generalization and adaptation abilities of the system by testing it in new unexplored environments.

Capacity of Intelligent Underlay and Overlay Network

DEFF Research Database (Denmark)

Ling, Yim; Elling, Jan; Nielsen, Thomas Toftegaard

1996-01-01

traffic. The formulas of the model have been implemented with the use of MatLab. To verify the model, measurement methods have been developed to collect the teletraffic information in a real-live GSM network. The measured data indicates that the teletraffic model describes the capacity with high accuracy...... and therefore can be used to dimension the network. The model shows that the increase of capacity for a GSM network with 34 frequencies is about 30%. Further capacity enhancement can be achieved by intelligent frequency planning method which is currently being developed...

Artificial intelligence in diagnosis and supply restoration for a distribution network

Energy Technology Data Exchange (ETDEWEB)

Teo, C.Y.; Gooi, H.B. [Nanyang Technological University (Singapore). School of Electrical and Electronic Engineering

1998-07-01

The development of a PC-based integrated system, to illustrate the application of artificial intelligence in the fault diagnosis and supply restoration for an interconnected distribution network is described. The intelligent process utilises the post-fault network status, a list of the tripped breakers, main protection alarm, and the conventional event log. The fault diagnostic system is implemented by three independent mechanisms, namely the generic core rule, specific post-fault network matching, and generic relay inference rules. The intelligent restoration process is implemented by the switching check, the dynamic restoration algorithm and the mechanism for restoration by record matching and learning. By linking to a PC-based distribution simulator it has been demonstrated that the developed mechanisms enable the correct deduction of fault under different network configurations. The appropriate restoration plan can also be generated to restore supply to the entire restorable load for various post-fault networks. This system is currently used for undergraduate teaching and will be ideal for the training of network operation engineers. As the system developed is generic and can be used for a general network, it can be further developed for practical operation in a subtransmission system or an urban distribution system operated in any configuration. (author)

System Interface for an Integrated Intelligent Safety System (ISS for Vehicle Applications

Directory of Open Access Journals (Sweden)

Mahammad A. Hannan

2010-01-01

Full Text Available This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS that includes an airbag deployment decision system (ADDS and a tire pressure monitoring system (TPMS. A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications.

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

Science.gov (United States)

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

Interfaces for a simple local network

International Nuclear Information System (INIS)

Nekhanevich, Eh.L.; Yasenev, M.V.

1988-01-01

A system of communication and interfaces for a simple local network of computers is described. The data on technical parameters, fields of application and operation features of the interfaces developed are presented. The data indispensable for the development of software are given. The experience in operation of the subsystem of software for remote terminal computers which makes use of the above interfaces is briefly presented. 7 refs.; 3 figs

Detection of Intelligent Intruders in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Yun Wang

2016-01-01

Full Text Available Most of the existing research works on the intrusion detection problem in a wireless sensor network (WSN assume linear or random mobility patterns in abstracting intruders’ models in traversing the WSN field. However, in real-life WSN applications, an intruder is usually an intelligent mobile robot with environment learning and detection avoidance capability (i.e., the capability to avoid surrounding sensors. Due to this, the literature results based on the linear or random mobility models may not be applied to the real-life WSN design and deployment for efficient and effective intrusion detection in practice. This motivates us to investigate the impact of intruder’s intelligence on the intrusion detection problem in a WSN for various applications. To be specific, we propose two intrusion algorithms, the pinball and flood-fill algorithms, to mimic the intelligent motion and behaviors of a mobile intruder in detecting and circumventing nearby sensors for detection avoidance while heading for its destination. The two proposed algorithms are integrated into a WSN framework for intrusion detection analysis in various circumstances. Monte Carlo simulations are conducted, and the results indicate that: (1 the performance of a WSN drastically changes as a result of the intruder’s intelligence in avoiding sensor detections and intrusion algorithms; (2 network parameters, including node density, sensing range and communication range, play a crucial part in the effectiveness of the intruder’s intrusion algorithms; and (3 it is imperative to integrate intruder’s intelligence in the WSN research for intruder detection problems under various application circumstances.

Fluid and flexible minds: Intelligence reflects synchrony in the brain’s intrinsic network architecture

Directory of Open Access Journals (Sweden)

Michael A. Ferguson

2017-06-01

Full Text Available Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830, we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease. In our study, we aimed to understand how individual differences in intellectual functioning are reflected in the intrinsic network architecture of the human brain. We applied statistical methods, known as spectral decompositions, in order to identify individual differences in the synchronous patterns of spontaneous brain activity that reliably predict core aspects of human intelligence. The synchrony of brain activity at rest across multiple discrete neural networks demonstrated positive relationships with fluid intelligence. In contrast, global synchrony within the brain’s network architecture reliably, and inversely, predicted mental flexibility, a core facet of intellectual functioning. The multinetwork systems approach described here represents a methodological and conceptual extension of earlier efforts that related differences in

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

An intelligent and networking solution of radiation monitoring system for LHC

International Nuclear Information System (INIS)

Shao Beibei; Gong Guanghua

2001-01-01

The LHC (the Large Hadron Collider), the largest accelerator in the world, is under designing and construction at CERN. It shares the 27 km LEP tunnel and is expected to be on the air in 2005. The Radiation Monitoring System of LEP was a central system with non-intelligent detectors. While as the proposed new RMS for LHC is a distributing intelligent networked system. Around 350 detectors will be employed. To save the cost, the design should make the old LEP's non-intelligent detectors reusable. To allow the detector controller automatic reports the detector database and net location through the world Fip bus, 1 wire components are embedded into the detectors and the network sockets. The radiation tolerance and the reliability of the communication of the wire components have been tested in a strong radiation field at CERN. The low cost components based position detection technique is valuable for most networked control system

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

Energy Technology Data Exchange (ETDEWEB)

Zhu, Michelle M. [Southern Illinois Univ., Carbondale, IL (United States); Wu, Chase Q. [Univ. of Memphis, TN (United States)

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.

Interfacing An Intelligent Decision-Maker To A Real-Time Control System

Science.gov (United States)

Evers, D. C.; Smith, D. M.; Staros, C. J.

1984-06-01

This paper discusses some of the practical aspects of implementing expert systems in a real-time environment. There is a conflict between the needs of a process control system and the computational load imposed by intelligent decision-making software. The computation required to manage a real-time control problem is primarily concerned with routine calculations which must be executed in real time. On most current hardware, non-trivial AI software should not be forced to operate under real-time constraints. In order for the system to work efficiently, the two processes must be separated by a well-defined interface. Although the precise nature of the task separation will vary with the application, the definition of the interface will need to follow certain fundamental principles in order to provide functional separation. This interface was successfully implemented in the expert scheduling software currently running the automated chemical processing facility at Lockheed-Georgia. Potential applications of this concept in the areas of airborne avionics and robotics will be discussed.

Fundamentals of computational intelligence neural networks, fuzzy systems, and evolutionary computation

CERN Document Server

Keller, James M; Fogel, David B

2016-01-01

This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basi function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzz...

Interface Design Concepts in the Development of ELSA, an Intelligent Electronic Library Search Assistant.

Science.gov (United States)

Denning, Rebecca; Smith, Philip J.

1994-01-01

Describes issues and advances in the design of appropriate inference engines and knowledge structures needed by commercially feasible intelligent intermediary systems for information retrieval. Issues associated with the design of interfaces to such functions are discussed in detail. Design principles for guiding implementation of these interfaces…

On-line Configuration of Network Emulator for Intelligent Energy System Testbed Applications

DEFF Research Database (Denmark)

Kemal, Mohammed Seifu; Iov, Florin; Olsen, Rasmus Løvenstein

2015-01-01

Intelligent energy networks (or Smart Grids) provide efficient solutions for a grid integrated with near-real-time communication technologies between various grid assets in power generation, transmission and distribution systems. The design of a communication network associated with intelligent...... power system involves detailed analysis of its communication requirements, a proposal of the appropriate protocol architecture, the choice of appropriate communication technologies for each case study, and a means to support heterogeneous communication technology management system. This paper discuses...

Driving the brain towards creativity and intelligence: A network control theory analysis.

Science.gov (United States)

Kenett, Yoed N; Medaglia, John D; Beaty, Roger E; Chen, Qunlin; Betzel, Richard F; Thompson-Schill, Sharon L; Qiu, Jiang

2018-01-04

High-level cognitive constructs, such as creativity and intelligence, entail complex and multiple processes, including cognitive control processes. Recent neurocognitive research on these constructs highlight the importance of dynamic interaction across neural network systems and the role of cognitive control processes in guiding such a dynamic interaction. How can we quantitatively examine the extent and ways in which cognitive control contributes to creativity and intelligence? To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how NCT relates to individual differences in distinct measures of creative ability and intelligence. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that intelligence is related to the ability to "drive" the brain system into easy to reach neural states by the right inferior parietal lobe and lower integration abilities in the left retrosplenial cortex. We also find that creativity is related to the ability to "drive" the brain system into difficult to reach states by the right dorsolateral prefrontal cortex (inferior frontal junction) and higher integration abilities in sensorimotor areas. Furthermore, we found that different facets of creativity-fluency, flexibility, and originality-relate to generally similar but not identical network controllability processes. We relate our findings to general theories on intelligence and creativity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Intelligent Network Flow Optimization (INFLO) prototype acceptance test summary.

Science.gov (United States)

2015-05-01

This report summarizes the results of System Acceptance Testing for the implementation of the Intelligent Network : Flow Optimization (INFLO) Prototype bundle within the Dynamic Mobility Applications (DMA) portion of the Connected : Vehicle Program. ...

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

Science.gov (United States)

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

The Portals 4.0 network programming interface.

Energy Technology Data Exchange (ETDEWEB)

Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin; Wheeler, Kyle Bruce; Hemmert, Karl Scott; Riesen, Rolf E.; Underwood, Keith Douglas; Maccabe, Arthur Bernard; Hudson, Trammell B.

2012-11-01

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

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

Science.gov (United States)

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

2009-12-01

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

Intelligent Packet Shaper to Avoid Network Congestion for Improved Streaming Video Quality at Clients

DEFF Research Database (Denmark)

Kaul, Manohar; Khosla, Rajiv; Mitsukura, Y

2003-01-01

of this intelligent traffic-shaping algorithm on the underlying network real time packet traffic and the eradication of unwanted abruption in the streaming video qualiy. This paper concluded from the end results of the simulation that neural networks are a very superior means of modeling real-time traffic......This paper proposes a traffic shaping algorithm based on neural networks, which adapts to a network over which streaming video is being transmitted. The purpose of this intelligent shaper is to eradicate all traffic congestion and improve the end-user's video quality. It possesses the capability...

Tomorrow's energy needs require intelligent networks

International Nuclear Information System (INIS)

Bitsch, R.

1998-01-01

With the European wide move towards increased competition and greater deregulation of the energy industry, has come a thrust for greater efficiency and understanding customer needs and external constraints such as the environment. This, in turn, has led to solutions which take advantage of the tremendous developments in information technology and on-line control systems which are described in this paper. Topics include intelligent networks, decentralised energy supplies and decentralised energy management. (UK)

Real-time distributed simulation using the Modular Modeling System interfaced to a Bailey NETWORK 90 system

International Nuclear Information System (INIS)

Edwards, R.M.; Turso, J.A.; Garcia, H.E.; Ghie, M.H.; Dharap, S.; Lee, S.

1991-01-01

The Modular Modeling System was adapted for real-time simulation testing of diagnostic expert systems in 1987. The early approach utilized an available general purpose mainframe computer which operated the simulation and diagnostic program in the multitasking environment of the mainframe. That research program was subsequently expanded to intelligent distributed control applications incorporating microprocessor based controllers with the aid of an equipment grant from the National Science Foundation (NSF). The Bailey NETWORK 90 microprocessor-based control system, acquired with the NSF grant, has been operational since April of 1990 and has been interfaced to both VAX mainframe and PC simulations of power plant processes in order to test and demonstrate advanced control and diagnostic concepts. This paper discusses the variety of techniques that have been used and which are under development to interface simulations and other distributed control functions to the Penn State Bailey system

Designing a holistic end-to-end intelligent network analysis and security platform

Science.gov (United States)

Alzahrani, M.

2018-03-01

Firewall protects a network from outside attacks, however, once an attack entering a network, it is difficult to detect. Recent significance accidents happened. i.e.: millions of Yahoo email account were stolen and crucial data from institutions are held for ransom. Within two year Yahoo’s system administrators were not aware that there are intruder inside the network. This happened due to the lack of intelligent tools to monitor user behaviour in internal network. This paper discusses a design of an intelligent anomaly/malware detection system with proper proactive actions. The aim is to equip the system administrator with a proper tool to battle the insider attackers. The proposed system adopts machine learning to analyse user’s behaviour through the runtime behaviour of each node in the network. The machine learning techniques include: deep learning, evolving machine learning perceptron, hybrid of Neural Network and Fuzzy, as well as predictive memory techniques. The proposed system is expanded to deal with larger network using agent techniques.

Intelligent Interfaces to Empower People with Disabilities

Science.gov (United States)

Betke, Margrit

Severe motion impairments can result from non-progressive disorders, such as cerebral palsy, or degenerative neurological diseases, such as Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), or muscular dystrophy (MD). They can be due to traumatic brain injuries, for example, due to a traffic accident, or to brainstem strokes [9, 84]. Worldwide, these disorders affect millions of individuals of all races and ethnic backgrounds [4, 75, 52]. Because disease onset of MS and ALS typically occurs in adulthood, afflicted people are usually computer literate. Intelligent interfaces can immensely improve their daily lives by allowing them to communicate and participate in the information society, for example, by browsing the web, posting messages, or emailing friends. However, people with advanced ALS, MS, or MD may reach a point when they cannot control the keyboard and mouse anymore and also cannot rely on automated voice recognition because their speech has become slurred.

Semantic Network and Frame Knowledge Representation Formalisms in Artificial Intelligence

OpenAIRE

Rashid, Pshtiwan Qader

2015-01-01

ABSTRACT: Choosing a suitable method to represent the knowledge concerning the real world is one of the major issues involved in Artificial Intelligence. The purpose of this research is to consider the important beneficial roles of semantic network and frame formalisms for knowledge representation in Artificial Intelligence. The basic properties of the above methods for appropriate structuring and arranging the knowledge are presented. Some types of relationships, the conceptual graph...

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

Science.gov (United States)

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.

Neural network-based control of an intelligent solar Stirling pump

International Nuclear Information System (INIS)

Tavakolpour-Saleh, A.R.; Jokar, H.

2016-01-01

In this paper, an ANN (artificial neural network) control system is applied to a novel solar-powered active LTD (low temperature differential) Stirling pump. First, a mathematical description of the proposed Stirling pump is presented. Then, optimum operating frequencies of the converter corresponding to different operating conditions (i.e. different sink and source temperatures and water heads) are investigated using the proposed mathematical framework. It is found that the proposed complex mathematical scheme has a very slow convergence and thus, is not appropriate for real-time implementation of the model-based controller. Consequently, a NN (neural network) model with a lower complexity is proposed to learn the simulation data obtained from the mathematical model. The designed neural network controller is thus applied to a digital processor to effectively tune the converter frequency so that a maximum output power is acquired. Finally, the performance of the proposed mechatronic system is evaluated experimentally. The experimental results clearly demonstrate the feasibility of pumping water at low temperature difference under variable operating conditions using the proposed intelligent Stirling converter. - Highlights: • A novel intelligent solar-powered active LTD Stirling pump was introduced. • A neural network controller was used to tune the converter speed. • The intelligent converter was able to adapt itself to different operating conditions. • It was possible to excite the water column with its resonance mode. • Experimental results showed the effectiveness of the proposed converter.

A Cross-Layer Routing Design for Multi-Interface Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Tzu-Chieh Tsai

2009-01-01

Full Text Available In recent years, Wireless Mesh Networks (WMNs technologies have received significant attentions. WMNs not only accede to the advantages of ad hoc networks but also provide hierarchical multi-interface architecture. Transmission power control and routing path selections are critical issues in the past researches of multihop networks. Variable transmission power levels lead to different network connectivity and interference. Further, routing path selections among different radio interfaces will also produce different intra-/interflow interference. These features tightly affect the network performance. Most of the related works on the routing protocol design do not consider transmission power control and multi-interface environment simultaneously. In this paper, we proposed a cross-layer routing protocol called M2iRi2 which coordinates transmission power control and intra-/interflow interference considerations as routing metrics. Each radio interface calculates the potential tolerable-added transmission interference in the physical layer. When the route discovery starts, the M2iRi2 will adopt the appropriate power level to evaluate each interface quality along paths. The simulation results demonstrate that our design can enhance both network throughput and end-to-end delay.

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

Science.gov (United States)

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

2014-12-01

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

Information, intelligence, and interface: the pillars of a successful medical information system.

Science.gov (United States)

Hadzikadic, M; Harrington, A L; Bohren, B F

1995-01-01

This paper addresses three key issues facing developers of clinical and/or research medical information systems. 1. INFORMATION. The basic function of every database is to store information about the phenomenon under investigation. There are many ways to organize information in a computer; however only a few will prove optimal for any real life situation. Computer Science theory has developed several approaches to database structure, with relational theory leading in popularity among end users [8]. Strict conformance to the rules of relational database design rewards the user with consistent data and flexible access to that data. A properly defined database structure minimizes redundancy i.e.,multiple storage of the same information. Redundancy introduces problems when updating a database, since the repeated value has to be updated in all locations--missing even a single value corrupts the whole database, and incorrect reports are produced [8]. To avoid such problems, relational theory offers a formal mechanism for determining the number and content of data files. These files not only preserve the conceptual schema of the application domain, but allow a virtually unlimited number of reports to be efficiently generated. 2. INTELLIGENCE. Flexible access enables the user to harvest additional value from collected data. This value is usually gained via reports defined at the time of database design. Although these reports are indispensable, with proper tools more information can be extracted from the database. For example, machine learning, a sub-discipline of artificial intelligence, has been successfully used to extract knowledge from databases of varying size by uncovering a correlation among fields and records[1-6, 9]. This knowledge, represented in the form of decision trees, production rules, and probabilistic networks, clearly adds a flavor of intelligence to the data collection and manipulation system. 3. INTERFACE. Despite the obvious importance of collecting

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 ampersand 2

International Nuclear Information System (INIS)

Johnson, J.R.

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks

A generic service interfacing approach for home networking

NARCIS (Netherlands)

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

2010-01-01

This paper presents a generic service interfacing approach which enables the interoperability of networked devices and the reusability of services. Services are specified through a set of interfaces which are language and deployment platform independent. External service orchestration is applied to

Supporting tactical intelligence using collaborative environments and social networking

Science.gov (United States)

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.

Service offerings and interfaces for the ACTS network of earth stations

Science.gov (United States)

Coney, T. A.; Dobyns, T. R.; Chitre, D. M.; Lindstrom, R.

1988-01-01

The NASA Advanced Communications Technology Satellite (ACTS) will use a network of about 20 earth stations to operate as a Mode 1 network. This network will support two ACTS program objectives: to verify the technical performance of ACTS Mode 1 operation in GEO and to demonstrate the types and quality of services that can be provided by an ACTS Mode 1 communications system. The terrestrial interface design is a critical element in assuring that these network earth stations will meet the objectives. In this paper, the applicable terrestrial interface design requirements, the resulting interface specifications, and the associated terrestrial input/output hardware are discussed. A functional block diagram of a network earth station is shown.

Intelligent networks recent approaches and applications in medical systems

CERN Document Server

Ahamed, Syed V

2013-01-01

This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear

Optical label-controlled transparent metro-access network interface

DEFF Research Database (Denmark)

Osadchiy, Alexey Vladimirovich

This thesis presents results obtained during the course of my PhD research on optical signal routing and interfacing between the metropolitan and access segments of optical networks. Due to both increasing capacity demands and variety of emerging services types, new technological challenges...... control. Highlights of my research include my proposal and experimental proof of principle of an optical coherent detection based optical access network architecture providing support for a large number of users over a single distribution fiber; a spectral amplitude encoded label detection technique...... are arising for seamlessly interfacing metropolitan and access networks. Therefore, in this PhD project, I have analyzed those technological challenges and identified the key aspects to be addressed. I have also proposed and experimentally verified a number of solutions to metropolitan and access networks...

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

International Nuclear Information System (INIS)

Saini, K. K.; Saini, Sanju

2008-01-01

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.

An Intelligent Handover Management System for Future Generation Wireless Networks

Directory of Open Access Journals (Sweden)

Kassar Meriem

2008-01-01

Full Text Available Abstract Future generation wireless networks should provide to mobile users the best connectivity to services anywhere at anytime. The most challenging problem is the seamless intersystem/vertical mobility across heterogeneous wireless networks. In order to answer it, a vertical handover management system is needed. In our paper, we propose an intelligent solution answering user requirements and ensuring service continuity. We focus on a vertical handover decision strategy based on the context-awareness concept. The given strategy chooses the appropriate time and the most suitable access network among those available to perform a handover. It uses advanced decision algorithms (for more efficiency and intelligence and it is governed by handover policies as decision rules (for more flexibility and optimization. To maintain a seamless service continuity, handover execution is based on mobile IP functionalities. We study our decision system in a case of a 3G/UMTS-WLAN scenario and we discuss all the handover decision issues in our solution.

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

Science.gov (United States)

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…

An Intelligent Monitoring Network for Detection of Cracks in Anvils of High-Press Apparatus.

Science.gov (United States)

Tian, Hao; Yan, Zhaoli; Yang, Jun

2018-04-09

Due to the endurance of alternating high pressure and temperature, the carbide anvils of the high-press apparatus, which are widely used in the synthetic diamond industry, are prone to crack. In this paper, an acoustic method is used to monitor the crack events, and the intelligent monitoring network is proposed to classify the sound samples. The pulse sound signals produced by such cracking are first extracted based on a short-time energy threshold. Then, the signals are processed with the proposed intelligent monitoring network to identify the operation condition of the anvil of the high-pressure apparatus. The monitoring network is an improved convolutional neural network that solves the problems that may occur in practice. The length of pulse sound excited by the crack growth is variable, so a spatial pyramid pooling layer is adopted to solve the variable-length input problem. An adaptive weighted algorithm for loss function is proposed in this method to handle the class imbalance problem. The good performance regarding the accuracy and balance of the proposed intelligent monitoring network is validated through the experiments finally.

Soft optics in intelligent optical networks

Science.gov (United States)

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.

An Object-Oriented Graphical User Interface for a Reusable Rocket Engine Intelligent Control System

Science.gov (United States)

Litt, Jonathan S.; Musgrave, Jeffrey L.; Guo, Ten-Huei; Paxson, Daniel E.; Wong, Edmond; Saus, Joseph R.; Merrill, Walter C.

1994-01-01

An intelligent control system for reusable rocket engines under development at NASA Lewis Research Center requires a graphical user interface to allow observation of the closed-loop system in operation. The simulation testbed consists of a real-time engine simulation computer, a controls computer, and several auxiliary computers for diagnostics and coordination. The system is set up so that the simulation computer could be replaced by the real engine and the change would be transparent to the control system. Because of the hard real-time requirement of the control computer, putting a graphical user interface on it was not an option. Thus, a separate computer used strictly for the graphical user interface was warranted. An object-oriented LISP-based graphical user interface has been developed on a Texas Instruments Explorer 2+ to indicate the condition of the engine to the observer through plots, animation, interactive graphics, and text.

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

Energy Technology Data Exchange (ETDEWEB)

Lehman, Tom; Yang, Xi

2018-01-16

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyberinfrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum of compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyberinfrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate

Network traffic intelligence using a low interaction honeypot

Science.gov (United States)

Nyamugudza, Tendai; Rajasekar, Venkatesh; Sen, Prasad; Nirmala, M.; Madhu Viswanatham, V.

2017-11-01

Advancements in networking technology have seen more and more devices becoming connected day by day. This has given organizations capacity to extend their networks beyond their boundaries to remote offices and remote employees. However as the network grows security becomes a major challenge since the attack surface also increases. There is need to guard the network against different types of attacks like intrusion and malware through using different tools at different networking levels. This paper describes how network intelligence can be acquired through implementing a low-interaction honeypot which detects and track network intrusion. Honeypot allows an organization to interact and gather information about an attack earlier before it compromises the network. This process is important because it allows the organization to learn about future attacks of the same nature and allows them to develop counter measures. The paper further shows how honeypot-honey net based model for interruption detection system (IDS) can be used to get the best valuable information about the attacker and prevent unexpected harm to the network.

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

Science.gov (United States)

2012-01-24

... Intelligent Network Flow Optimization Operational Concepts; Notice of Public Meeting AGENCY: Research and... Demand Management (ADTM) and Intelligent Network Flow Optimization (INFLO) operational concepts. The ADTM... infrastructure. The vision for ATDM research is to allow transportation agencies to increase traffic flow...

Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks.

Science.gov (United States)

Wang, Zhijun; Mirdamadi, Reza; Wang, Qing

2016-01-01

Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building.

An Intelligent Approach to Observability of Distribution Networks

DEFF Research Database (Denmark)

Pokhrel, Basanta Raj; Nainar, Karthikeyan; Bak-Jensen, Birgitte

2018-01-01

This paper presents a novel intelligent observability approach for active distribution systems. Observability assessment of the measured power system network, which is a preliminary task in state estimation, is handled via an algebraic method that uses the triangular factors of singular, symmetric...... gain matrix accompanied by a minimum meter placement technique. In available literature, large numbers of pseudo measurements are used to cover the scarcity of sufficient real measurements in distribution systems; the values of these virtual meters are calculated value based on the available real...... measurements, network topology, and network parameters. However, since there are large margin of errors exist in the calculation phase, estimated states may be significantly differed from the actual values though network is classified as observable. Hence, an approach based on numerical observability analysis...

Dynamic Intelligent Feedback Scheduling in Networked Control Systems

Directory of Open Access Journals (Sweden)

Hui-ying Chen

2013-01-01

Full Text Available For the networked control system with limited bandwidth and flexible workload, a dynamic intelligent feedback scheduling strategy is proposed. Firstly, a monitor is used to acquire the current available network bandwidth. Then, the new available bandwidth in the next interval is predicted by using LS_SVM approach. At the same time, the dynamic performance indices of all control loops are obtained with a two-dimensional fuzzy logic modulator. Finally, the predicted network bandwidth is dynamically allocated by the bandwidth manager and the priority allocator in terms of the loops' dynamic performance indices. Simulation results show that the sampling periods and priorities of control loops are adjusted timely according to the network workload condition and the dynamic performance of control loops, which make the system running in the optimal state all the time.

The portals 4.0.1 network programming interface.

Energy Technology Data Exchange (ETDEWEB)

Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin; Wheeler, Kyle Bruce; Hemmert, Karl Scott; Riesen, Rolf E.; Underwood, Keith Douglas; Maccabe, Arthur Bernard; Hudson, Trammell B.

2013-04-01

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

A framework for the intelligent control of nuclear rockets

International Nuclear Information System (INIS)

Parlos, A.G.; Metzger, J.D.

1993-01-01

An intelligent control system architecture is proposed for nuclear rockets, and its various components are briefly described. The objective of the intelligent controller is the satisfaction of performance, robustness, fault-tolerance and reliability design specifications. The proposed hierarchical architecture consists of three levels: hardware, signal processing, and knowledge processing. The functionality of the intelligent controller is implemented utilizing advanced information processing technologies such as artificial neutral networks and fuzzy expert systems. The feasibility of a number of the controller architecture components have been independently validated using computer simulations. Preliminary results are presented demonstrating some of the signal processing capabilities of the intelligent nuclear rocket controller. Further work, currently in progress, is attempting to implement a number of the knowledge processing capabilities of the controller and their interface with the lower levels of the proposed architecture

Realization of Intelligent Household Appliance Wireless Monitoring Network Based on LEACH Protocol

Directory of Open Access Journals (Sweden)

Weilong ZHOU

2014-06-01

Full Text Available The intelligent household appliance wireless monitoring network can real-time monitor the apparent power and power factor of various household appliances in different indoor regions, and can realize the real-time monitoring on the household appliance working status and performance. The household appliance wireless monitoring network based on LEACH protocol is designed in the paper. Firstly, the basic idea of LEACH routing algorithm is proposed. Aiming at the node-distribution feature of intelligent home, the selection of cluster head in the routing algorithm and the data transmission method at the stable communication phase is modified. Moreover, the hardware circuit of power acquisition and power factor measurement is designed. The realization of wireless monitoring network based on CC2530 is described, each module and the whole system were conducted the on-line debugging. Finally, the system is proved to meet the practical requirement through the networking test.

On the synergy of network science and artificial intelligence

NARCIS (Netherlands)

Mocanu, D.C.

2016-01-01

Traditionally science is done using the reductionism paradigm. Artificial intelligence does not make an exception and it follows the same strategy. At the same time, network science tries to study complex systems as a whole. This Ph.D. research takes an alternative approach to the reductionism

An intelligent human-machine system based on an ecological interface design concept

International Nuclear Information System (INIS)

Naito, N.

1995-01-01

It seems both necessary and promising to develop an intelligent human-machine system, considering the objective of the human-machine system and the recent advance in cognitive engineering and artificial intelligence together with the ever-increasing importance of human factor issues in nuclear power plant operation and maintenance. It should support human operators in their knowledge-based behaviour and allow them to cope with unanticipated abnormal events, including recovery from erroneous human actions. A top-down design approach has been adopted based on cognitive work analysis, and (1) an ecological interface, (2) a cognitive model-based advisor and (3) a robust automatic sequence controller have been established. These functions have been integrated into an experimental control room. A validation test was carried out by the participation of experienced operators and engineers. The results showed the usefulness of this system in supporting the operator's supervisory plant control tasks. ((orig.))

Flexible Transport Network Expansion via Open WDM Interfaces

DEFF Research Database (Denmark)

Fagertun, Anna Manolova; Skjoldstrup, Bjarke

2013-01-01

This paper presents a successful test-bed implementation of a multi-vendor transport network interconnection via open WDM interfaces. The concept of applying Alien Wavelengths (AWs) for network expansion was successfully illustrated via deployment of multi-domain/multi-vendor end-to-end OTN servi...

The Portals 4.1 Network Programming Interface

Energy Technology Data Exchange (ETDEWEB)

Barrett, Brian; Brightwell, Ronald B.; Grant, Ryan; Hemmert, Karl Scott; Pedretti, Kevin; Wheeler, Kyle; Underwood, Keith D; Riesen, Rolf; Maccabe, Arthur B.; Hudson, Trammel

2017-04-01

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

Intelligent systems and soft computing for nuclear science and industry

International Nuclear Information System (INIS)

Ruan, D.; D'hondt, P.; Govaerts, P.; Kerre, E.E.

1996-01-01

The second international workshop on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS) addresses topics related to intelligent systems and soft computing for nuclear science and industry. The proceedings contain 52 papers in different fields such as radiation protection, nuclear safety (human factors and reliability), safeguards, nuclear reactor control, production processes in the fuel cycle, dismantling, waste and disposal, decision making, and nuclear reactor control. A clear link is made between theory and applications of fuzzy logic such as neural networks, expert systems, robotics, man-machine interfaces, and decision-support techniques by using modern and advanced technologies and tools. The papers are grouped in three sections. The first section (Soft computing techniques) deals with basic tools to treat fuzzy logic, neural networks, genetic algorithms, decision-making, and software used for general soft-computing aspects. The second section (Intelligent engineering systems) includes contributions on engineering problems such as knowledge-based engineering, expert systems, process control integration, diagnosis, measurements, and interpretation by soft computing. The third section (Nuclear applications) focusses on the application of soft computing and intelligent systems in nuclear science and industry

Development of intelligent interface for simulation execution by module-based simulation system

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu; Mizutani, Naoki; Shimoda, Hiroshi; Wakabayashi, Jiro

1988-01-01

An intelligent user support for the two phases of simulation execution was newly developed for Module-based Simulation System (MSS). The MSS has been in development as a flexible simulation environment to improve software productivity in complex, large-scale dynamic simulation of nuclear power plant. The AI programing by Smalltalk-80 was applied to materialize the two user-interface programs for (i) semantic diagnosis of the simulation program generated automatically by MSS, and (ii) consultation system by which user can set up consistent numerical input data files necessary for executing a MSS-generated program. Frame theory was utilized in those interface programs to represent the four knowledge bases, which are (i) usage information on module library in MSS and MSS-generated program, and (ii) expertise knowledge on nuclear power plant analysis such as material properties and reactor system configuration. Capabilities of those interface programs were confirmed by some example practice on LMFBR reactor dynamic calculation, and it was demonstrated that the knowledge-based systemization was effective to improve software work environment. (author)

Network Interface Specification for the T1 Microprocessor

Science.gov (United States)

1994-05-01

details of the data transfer functional units, interconnect structure, and network operation. Application Layer Communication Model Communication...use of the communication resources. 3.6 Network Virtualisation The CNS-1 is designed for single-user, batch-style processing; no timesharing or space...matches the count register (both the timer and count register are in the network interface and are user-accessible). Although this function is not strictly

Macroeconomic potentials of intelligent networks in Germany. Abstract; Gesamtwirtschaftliche Potenziale intelligenter Netze in Deutschland. Kurzfassung

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

Within the contribution under consideration the Fraunhofer Institute for Systems and Innovation Research ISI (Karlsruhe, Federal Republic of Germany) determines the total economic effects of intelligent networks for the German economy. For the first time, the contributions of the different areas (energy, health, traffic, education, administration) are shown detailed. On the whole, it arises a societal total benefit of intelligent networks of 55.7 billion Euro per year.

Web-Based Interface for Command and Control of Network Sensors

Science.gov (United States)

Wallick, Michael N.; Doubleday, Joshua R.; Shams, Khawaja S.

2010-01-01

This software allows for the visualization and control of a network of sensors through a Web browser interface. It is currently being deployed for a network of sensors monitoring Mt. Saint Helen s volcano; however, this innovation is generic enough that it can be deployed for any type of sensor Web. From this interface, the user is able to fully control and monitor the sensor Web. This includes, but is not limited to, sending "test" commands to individual sensors in the network, monitoring for real-world events, and reacting to those events

An architecture for human-network interfaces

DEFF Research Database (Denmark)

Sonnenwald, Diane H.

1990-01-01

Some of the issues (and their consequences) that arise when human-network interfaces (HNIs) are viewed from the perspective of people who use and develop them are examined. Target attributes of HNI architecture are presented. A high-level architecture model that supports the attributes is discussed...

Introducing AI into MEMS can lead us to brain-computer interfaces and super-human intelligence

OpenAIRE

Sanders, David

2009-01-01

Last year, I spoke about the progress being made in machine intelligence (Sanders, 2008c) and with sensors and networks of sensors (Sanders, 2008b). Earlier this year (in this journal) I spoke about ambient-intelligence, rapid-prototyping and the role of humans in the factories of the future (Sanders, 2009a). I addressed new applications and technologies such as merging machines with human beings, micro-electromechanics, electro-mechanical systems that can be personalized, smarter than human ...

SNMS: an intelligent transportation system network architecture based on WSN and P2P network

Institute of Scientific and Technical Information of China (English)

LI Li; LIU Yuan-an; TANG Bi-hua

2007-01-01

With the development of city road networks, the question of how to obtain information about the roads is becoming more and more important. In this article, sensor network with mobile station (SNMS), a novel two-tiered intelligent transportation system (ITS) network architecture based on wireless sensor network (WSN) and peer-to-peer (P2P) network, is proposed to provide significant traffic information about the road and thereby, assist travelers to take optimum decisions when they are driving. A detailed explanation with regard to the strategy of each level as well as the design of two main components in the network, sensor unit (SU) and mobile station (MS), is presented. Finally, a representative scenario is described to display the operation of the system.

Highly reliable computer network for real time system

International Nuclear Information System (INIS)

Mohammed, F.A.; Omar, A.A.; Ayad, N.M.A.; Madkour, M.A.I.; Ibrahim, M.K.

1988-01-01

Many of computer networks have been studied different trends regarding the network architecture and the various protocols that govern data transfers and guarantee a reliable communication among all a hierarchical network structure has been proposed to provide a simple and inexpensive way for the realization of a reliable real-time computer network. In such architecture all computers in the same level are connected to a common serial channel through intelligent nodes that collectively control data transfers over the serial channel. This level of computer network can be considered as a local area computer network (LACN) that can be used in nuclear power plant control system since it has geographically dispersed subsystems. network expansion would be straight the common channel for each added computer (HOST). All the nodes are designed around a microprocessor chip to provide the required intelligence. The node can be divided into two sections namely a common section that interfaces with serial data channel and a private section to interface with the host computer. This part would naturally tend to have some variations in the hardware details to match the requirements of individual host computers. fig 7

Interface Assignment-Based AODV Routing Protocol to Improve Reliability in Multi-Interface Multichannel Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Won-Suk Kim

2015-01-01

Full Text Available The utilization of wireless mesh networks (WMNs has greatly increased, and the multi-interface multichannel (MIMC technic has been widely used for the backbone network. Unfortunately, the ad hoc on-demand distance vector (AODV routing protocol defined in the IEEE 802.11s standard was designed for WMNs using the single-interface single-channel technic. So, we define a problem that happens when the legacy AODV is used in MIMC WMNs and propose an interface assignment-based AODV (IA-AODV in order to resolve that problem. IA-AODV, which is based on multitarget path request, consists of the PREQ prediction scheme, the PREQ loss recovery scheme, and the PREQ sender assignment scheme. A detailed operation according to various network conditions and services is introduced, and the routing efficiency and network reliability of a network using IA-AODV are analyzed over the presented system model. Finally, after a real-world test-bed for MIMC WMNs using the IA-AODV routing protocol is implemented, the various indicators of the network are evaluated through experiments. When the proposed routing protocol is compared with the existing AODV routing protocol, it performs the path update using only 14.33% of the management frames, completely removes the routing malfunction, and reduces the UDP packet loss ratio by 0.0012%.

A Low Energy Intelligent Clustering Protocol for Wireless Sensor Network

DEFF Research Database (Denmark)

Li, Qiao; Cui, Lingguo; Zhang, Baihai

2010-01-01

LEACH (low-energy adaptive clustering hierarchy) is a well-known self-organizing, adaptive clustering protocol of wireless sensor networks. However it has some shortcomings when it faces such problems as the cluster construction and energy management. In this paper, LEICP (low energy intelligent...

Intelligent IPv6 based iot network monitoring and altering system on ...

African Journals Online (AJOL)

Intelligent IPv6 based iot network monitoring and altering system on Cooja framework. ... Journal of Fundamental and Applied Sciences. Journal Home · ABOUT THIS ... Keywords: IoT; Cooja framework; Contiki OS; packet monitoring.

Intelligent battery energy management and control for vehicle-to-grid via cloud computing network

International Nuclear Information System (INIS)

Khayyam, Hamid; Abawajy, Jemal; Javadi, Bahman; Goscinski, Andrzej; Stojcevski, Alex; Bab-Hadiashar, Alireza

2013-01-01

Highlights: • The intelligent battery energy management substantially reduces the interactions of PEV with parking lots. • The intelligent battery energy management improves the energy efficiency. • The intelligent battery energy management predicts the road load demand for vehicles. - Abstract: Plug-in Electric Vehicles (PEVs) provide new opportunities to reduce fuel consumption and exhaust emission. PEVs need to draw and store energy from an electrical grid to supply propulsive energy for the vehicle. As a result, it is important to know when PEVs batteries are available for charging and discharging. Furthermore, battery energy management and control is imperative for PEVs as the vehicle operation and even the safety of passengers depend on the battery system. Thus, scheduling the grid power electricity with parking lots would be needed for efficient charging and discharging of PEV batteries. This paper aims to propose a new intelligent battery energy management and control scheduling service charging that utilize Cloud computing networks. The proposed intelligent vehicle-to-grid scheduling service offers the computational scalability required to make decisions necessary to allow PEVs battery energy management systems to operate efficiently when the number of PEVs and charging devices are large. Experimental analyses of the proposed scheduling service as compared to a traditional scheduling service are conducted through simulations. The results show that the proposed intelligent battery energy management scheduling service substantially reduces the required number of interactions of PEV with parking lots and grid as well as predicting the load demand calculated in advance with regards to their limitations. Also it shows that the intelligent scheduling service charging using Cloud computing network is more efficient than the traditional scheduling service network for battery energy management and control

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

Science.gov (United States)

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…

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

Energy Technology Data Exchange (ETDEWEB)

Dasari, Venkat [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Sadlier, Ronald J [ORNL; Geerhart, Mr. Billy [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Snow, Nikolai [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Williams, Brian P [ORNL; Humble, Travis S [ORNL

2017-01-01

Well-defined and stable quantum networks are essential to realize functional quantum applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. We develop new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

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

Science.gov (United States)

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…

Design of intelligent house system based on Yeelink

Directory of Open Access Journals (Sweden)

Lin Zhi-Huang

2016-01-01

Full Text Available In order to monitor the security situation of house in real time, an intelligent house remote monitoring system is designed based on Yeelink cloud services and ZigBee wireless communication technology. This system includes three parts, ZigBee wireless sensor networks, intelligent house gateway and Yeelink Cloud Services. Users can access Yeelink website or APP to get real time information in the house, receiving information including gas concentration, temperature. Also, remote commands can be sent from mobile devices to control the household appliances. The user who can monitor and control the house effectively through a simple and convenient user interface, will feel much more safe and comfortable.

Digital intelligent booster for DCC miniature train networks

Science.gov (United States)

Ursu, M. P.; Condruz, D. A.

2017-08-01

Modern miniature trains are now driven by means of the DCC (Digital Command and Control) system, which allows the human operator or a personal computer to launch commands to each individual train or even to control different features of the same train. The digital command station encodes these commands and sends them to the trains by means of electrical pulses via the rails of the railway network. Due to the development of the miniature railway network, it may happen that the power requirement of the increasing number of digital locomotives, carriages and accessories exceeds the nominal output power of the digital command station. This digital intelligent booster relieves the digital command station from powering the entire railway network all by itself, and it automatically handles the multiple powered sections of the network. This electronic device is also able to detect and process short-circuits and overload conditions, without the intervention of the digital command station.

Fluid intelligence allows flexible recruitment of the parieto-frontal network in analogical reasoning.

Science.gov (United States)

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

2011-01-01

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

Fluid intelligence allows flexible recruitment of the parieto-frontal network in analogical reasoning.

Directory of Open Access Journals (Sweden)

Franziska ePreusse

2011-03-01

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

Resource Optimization of Mobile Intelligent System with heart MPLS network

Directory of Open Access Journals (Sweden)

Mohammed Elkoutbi

2009-10-01

Full Text Available In this paper, we introduce the original Mobile Intelligent System (MIS in embeded FPGA architecture. This node will allow the construction of autonomous mobile network units which can move in unknowns, inaccessible or hostile environnement for human being, in order to collect data by various sensors and transmits them by routing to a unit of distant process. In the sake of improving the performance of transmission, we propose a global schema of QoS management using DiffServ/MPLS backbones. We provide an evaluation of several scenarios for combining QoS IP networks with MIS access network. We conclude with a study on interoperability between QoS patterns in access and backbone networks.

VAR control in distribution systems by using artificial intelligence techniques

Energy Technology Data Exchange (ETDEWEB)

Golkar, M.A. [Curtin Univ. of Technology, Sarawak (Malaysia). School of Engineering and Science

2005-07-01

This paper reviewed artificial intelligence techniques used in VAR control systems. Reactive power controls in distribution systems were also reviewed. While artificial intelligence methods are widely used in power control systems, the techniques require extensive human knowledge bases and experiences in order to operate correctly. Expert systems use knowledge and interface procedures to solve problems that often require human expertise. Expert systems often cause knowledge bottlenecks as they are unable to learn or adopt to new situations. While neural networks possess learning ability, they are computationally expensive. However, test results in recent neural network studies have demonstrated that they work well in a variety of loading conditions. Fuzzy logic techniques are used to accurately represent the operational constraints of power systems. Fuzzy logic has an advantage over other artificial intelligence techniques as it is able to remedy uncertainties in data. Evolutionary computing algorithms use probabilistic transition rules which can search complicated data to determine optimal constraints and parameters. Over 95 per cent of all papers published on power systems use genetic algorithms. It was concluded that hybrid systems using various artificial intelligence techniques are now being used by researchers. 69 refs.

INTELLIGENT TRAFFIC-SAFETY MIRROR BY USING WIRELESS SENSOR NETWORK

Directory of Open Access Journals (Sweden)

Peter Danišovič

2014-03-01

Full Text Available This article is focused on the problematic of traffic safety, dealing with the problem of car intersections with blocked view crossing by a special wireless sensor network (WSN proposed for the traffic monitoring, concretely for vehicle’s detection at places, where it is necessary. Some ultra-low-power TI products were developed due to this reason: microcontroller MSP430F2232, 868MHz RF transceiver CC1101 and LDO voltage regulator TPS7033. The WSN consist of four network nodes supplied with the special safety lightings which serve the function of intelligent traffic safety mirror.

Intelligent condition monitoring of railway catenary systems : A Bayesian Network approach

NARCIS (Netherlands)

Wang, H.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Liu, Zhigang; Chen, Junwen; Spiryagin, Maksym; Gordon, Timothy; Cole, Colin; McSweeney, Tim

2017-01-01

This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of railway catenary systems. It combines five types of measurements related to catenary condition, namely the contact wire stagger, contact wire height, pantograph head displacement, pantograph head

The artificial neural networks: An approach to artificial intelligence; Un approccio ``biologico`` all`intelligenza artificiale

Energy Technology Data Exchange (ETDEWEB)

Taraglio, Sergio; Zanela, Andrea [ENEA, Casaccia (Italy). Dipt. Innovazione

1997-05-01

The artificial neural networks try to simulate the functionalities of the nervous system through a complex network of simple computing elements. In this work is presented an introduction to the neural networks and some of their possible applications, especially in the field of Artificial Intelligence.

Dynamic mobility applications policy analysis : policy and institutional issues for intelligent network flow optimization (INFLO).

Science.gov (United States)

2014-12-01

The report documents policy considerations for the Intelligent Network Flow Optimization (INFLO) connected vehicle applications : bundle. INFLO aims to optimize network flow on freeways and arterials by informing motorists of existing and impen...

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

Science.gov (United States)

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.

Trends in ambient intelligent systems the role of computational intelligence

CERN Document Server

Khan, Mohammad; Abraham, Ajith

2016-01-01

This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

Graphical user interface for wireless sensor networks simulator

Science.gov (United States)

Paczesny, Tomasz; Paczesny, Daniel; Weremczuk, Jerzy

2008-01-01

Wireless Sensor Networks (WSN) are currently very popular area of development. It can be suited in many applications form military through environment monitoring, healthcare, home automation and others. Those networks, when working in dynamic, ad-hoc model, need effective protocols which must differ from common computer networks algorithms. Research on those protocols would be difficult without simulation tool, because real applications often use many nodes and tests on such a big networks take much effort and costs. The paper presents Graphical User Interface (GUI) for simulator which is dedicated for WSN studies, especially in routing and data link protocols evaluation.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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

1986-01-01

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

Using Wireless Sensor Networks to Achieve Intelligent Monitoring for High-Temperature Gas-Cooled Reactor

Directory of Open Access Journals (Sweden)

Jianghai Li

2017-01-01

Full Text Available High-temperature gas-cooled reactors (HTGR can incorporate wireless sensor network (WSN technology to improve safety and economic competitiveness. WSN has great potential in monitoring the equipment and processes within nuclear power plants (NPPs. This technology not only reduces the cost of regular monitoring but also enables intelligent monitoring. In intelligent monitoring, large sets of heterogeneous data collected by the WSN can be used to optimize the operation and maintenance of the HTGR. In this paper, WSN-based intelligent monitoring schemes that are specific for applications of HTGR are proposed. Three major concerns regarding wireless technology in HTGR are addressed: wireless devices interference, cybersecurity of wireless networks, and wireless standards selected for wireless platform. To process nonlinear and non-Gaussian data obtained by WSN for fault diagnosis, novel algorithms combining Kernel Entropy Component Analysis (KECA and support vector machine (SVM are developed.

STIMULUS: End-System Network Interface Controller for 100 Gb/s Wide Area Networks

Energy Technology Data Exchange (ETDEWEB)

Zarkesh-Ha, Payman [University of New Mexico

2014-09-12

The main goal of this research grant is to develop a system-level solution leveraging novel technologies that enable network communications at 100 Gb/s or beyond. University of New Mexico in collaboration with Acadia Optronics LLC has been working on this project to develop the 100 Gb/s Network Interface Controller (NIC) under this Department of Energy (DOE) grant.

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

OpenAIRE

Ajay Kumar Saxena; S. 0. Bhatnagar; P. K Saxena

2002-01-01

Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives p...

DATA MAYHEM VERSUS NIMBLE INFORMATION: TRANSFORMING HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS

Science.gov (United States)

2017-10-01

organized intelligence with a comprehensive account of the information derived, validated by intelligence requirements tasking. Third Phase...AU/ACSC/MORALES/AY17 AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY DATA MAYHEM VERSUS NIMBLE INFORMATION : TRANSFORMING...HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS by Luis A. Morales, Major, USAF A Research

Middleware Architecture for Ambient Intelligence in the Networked Home

Science.gov (United States)

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

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

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

Science.gov (United States)

Kentzoglanakis, Kyriakos; Poole, Matthew

2012-01-01

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

Intelligent Resource Management for Local Area Networks: Approach and Evolution

Science.gov (United States)

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.

An Intelligent Network Proposed for Assessing Seismic Vulnerability Index of Sewerage Networks within a GIS Framework (A Case Study of Shahr-e-Kord

Directory of Open Access Journals (Sweden)

Mohamadali Rahgozar

2016-01-01

Full Text Available Due to their vast spread, sewerage networks are exposed to considerable damages during severe earthquakes, which may lead to catastrophic environmental contamination. Multiple repairs in the pipelines, including pipe and joint fractures, could be costly and time-consuming. In seismic risk management, it is of utmost importance to have an intelligent tool for assessing seismic vulnerability index at any given point in time for such important utilities as sewerage networks. This study uses a weight-factor methodology and proposes an online GIS-based intelligent algorithm to evaluate the seismic vulnerability index (VI for metropolitan sewerage networks. The proposed intelligent tool is capable of updating VI as the sewerage network conditions may change with time and at different locations. The city of Shahr-e-Kord located on the high risk seismic belt is selected for a case study to which the proposed methodology is applied for zoning the vulnerability index in GIS. Results show that the overall seismic vulnerability index for the selected study area ranges from low to medium but that it increases in the southern parts of the city, especially in the old town where brittle pipes have been laid

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

Science.gov (United States)

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.

Inversion of Density Interfaces Using the Pseudo-Backpropagation Neural Network Method

Science.gov (United States)

Chen, Xiaohong; Du, Yukun; Liu, Zhan; Zhao, Wenju; Chen, Xiaocheng

2018-05-01

This paper presents a new pseudo-backpropagation (BP) neural network method that can invert multi-density interfaces at one time. The new method is based on the conventional forward modeling and inverse modeling theories in addition to conventional pseudo-BP neural network arithmetic. A 3D inversion model for gravity anomalies of multi-density interfaces using the pseudo-BP neural network method is constructed after analyzing the structure and function of the artificial neural network. The corresponding iterative inverse formula of the space field is presented at the same time. Based on trials of gravity anomalies and density noise, the influence of the two kinds of noise on the inverse result is discussed and the scale of noise requested for the stability of the arithmetic is analyzed. The effects of the initial model on the reduction of the ambiguity of the result and improvement of the precision of inversion are discussed. The correctness and validity of the method were verified by the 3D model of the three interfaces. 3D inversion was performed on the observed gravity anomaly data of the Okinawa trough using the program presented herein. The Tertiary basement and Moho depth were obtained from the inversion results, which also testify the adaptability of the method. This study has made a useful attempt for the inversion of gravity density interfaces.

U-Net/SLE: A Java-Based User-Customizable Virtual Network Interface

Directory of Open Access Journals (Sweden)

Matt Welsh

1999-01-01

Full Text Available We describe U‐Net/SLE (Safe Language Extensions, a user‐level network interface architecture which enables per‐application customization of communication semantics through downloading of user extension applets, implemented as Java classfiles, to the network interface. This architecture permits applications to safely specify code to be executed within the NI on message transmission and reception. By leveraging the existing U‐Net model, applications may implement protocol code at the user level, within the NI, or using some combination of the two. Our current implementation, using the Myricom Myrinet interface and a small Java Virtual Machine subset, allows host communication overhead to be reduced and improves the overlap of communication and computation during protocol processing.

iSpike: a spiking neural interface for the iCub robot

International Nuclear Information System (INIS)

Gamez, D; Fidjeland, A K; Lazdins, E

2012-01-01

This paper presents iSpike: a C++ library that interfaces between spiking neural network simulators and the iCub humanoid robot. It uses a biologically inspired approach to convert the robot’s sensory information into spikes that are passed to the neural network simulator, and it decodes output spikes from the network into motor signals that are sent to control the robot. Applications of iSpike range from embodied models of the brain to the development of intelligent robots using biologically inspired spiking neural networks. iSpike is an open source library that is available for free download under the terms of the GPL. (paper)

Effects of Prior Knowledge in Mathematics on Learner-Interface Interactions in a Learning-by-Teaching Intelligent Tutoring System

Science.gov (United States)

Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T.

2016-01-01

This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…

Automatic figure ranking and user interfacing for intelligent figure search.

Directory of Open Access Journals (Sweden)

Hong Yu

2010-10-01

Full Text Available Figures are important experimental results that are typically reported in full-text bioscience articles. Bioscience researchers need to access figures to validate research facts and to formulate or to test novel research hypotheses. On the other hand, the sheer volume of bioscience literature has made it difficult to access figures. Therefore, we are developing an intelligent figure search engine (http://figuresearch.askhermes.org. Existing research in figure search treats each figure equally, but we introduce a novel concept of "figure ranking": figures appearing in a full-text biomedical article can be ranked by their contribution to the knowledge discovery.We empirically validated the hypothesis of figure ranking with over 100 bioscience researchers, and then developed unsupervised natural language processing (NLP approaches to automatically rank figures. Evaluating on a collection of 202 full-text articles in which authors have ranked the figures based on importance, our best system achieved a weighted error rate of 0.2, which is significantly better than several other baseline systems we explored. We further explored a user interfacing application in which we built novel user interfaces (UIs incorporating figure ranking, allowing bioscience researchers to efficiently access important figures. Our evaluation results show that 92% of the bioscience researchers prefer as the top two choices the user interfaces in which the most important figures are enlarged. With our automatic figure ranking NLP system, bioscience researchers preferred the UIs in which the most important figures were predicted by our NLP system than the UIs in which the most important figures were randomly assigned. In addition, our results show that there was no statistical difference in bioscience researchers' preference in the UIs generated by automatic figure ranking and UIs by human ranking annotation.The evaluation results conclude that automatic figure ranking and user

Design and implementation of interface units for high speed fiber optics local area networks and broadband integrated services digital networks

Science.gov (United States)

Tobagi, Fouad A.; Dalgic, Ismail; Pang, Joseph

1990-01-01

The design and implementation of interface units for high speed Fiber Optic Local Area Networks and Broadband Integrated Services Digital Networks are discussed. During the last years, a number of network adapters that are designed to support high speed communications have emerged. This approach to the design of a high speed network interface unit was to implement package processing functions in hardware, using VLSI technology. The VLSI hardware implementation of a buffer management unit, which is required in such architectures, is described.

Intelligible Artificial Intelligence

OpenAIRE

Weld, Daniel S.; Bansal, Gagan

2018-01-01

Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

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

International Nuclear Information System (INIS)

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

1986-01-01

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

Vision based interface system for hands free control of an intelligent wheelchair

Directory of Open Access Journals (Sweden)

Kim Eun

2009-08-01

Full Text Available Abstract Background Due to the shift of the age structure in today's populations, the necessities for developing the devices or technologies to support them have been increasing. Traditionally, the wheelchair, including powered and manual ones, is the most popular and important rehabilitation/assistive device for the disabled and the elderly. However, it is still highly restricted especially for severely disabled. As a solution to this, the Intelligent Wheelchairs (IWs have received considerable attention as mobility aids. The purpose of this work is to develop the IW interface for providing more convenient and efficient interface to the people the disability in their limbs. Methods This paper proposes an intelligent wheelchair (IW control system for the people with various disabilities. To facilitate a wide variety of user abilities, the proposed system involves the use of face-inclination and mouth-shape information, where the direction of an IW is determined by the inclination of the user's face, while proceeding and stopping are determined by the shapes of the user's mouth. Our system is composed of electric powered wheelchair, data acquisition board, ultrasonic/infra-red sensors, a PC camera, and vision system. Then the vision system to analyze user's gestures is performed by three stages: detector, recognizer, and converter. In the detector, the facial region of the intended user is first obtained using Adaboost, thereafter the mouth region is detected based on edge information. The extracted features are sent to the recognizer, which recognizes the face inclination and mouth shape using statistical analysis and K-means clustering, respectively. These recognition results are then delivered to the converter to control the wheelchair. Result & conclusion The advantages of the proposed system include 1 accurate recognition of user's intention with minimal user motion and 2 robustness to a cluttered background and the time-varying illumination

Integration of an intelligent systems behavior simulator and a scalable soldier-machine interface

Science.gov (United States)

Johnson, Tony; Manteuffel, Chris; Brewster, Benjamin; Tierney, Terry

2007-04-01

As the Army's Future Combat Systems (FCS) introduce emerging technologies and new force structures to the battlefield, soldiers will increasingly face new challenges in workload management. The next generation warfighter will be responsible for effectively managing robotic assets in addition to performing other missions. Studies of future battlefield operational scenarios involving the use of automation, including the specification of existing and proposed technologies, will provide significant insight into potential problem areas regarding soldier workload. The US Army Tank Automotive Research, Development, and Engineering Center (TARDEC) is currently executing an Army technology objective program to analyze and evaluate the effect of automated technologies and their associated control devices with respect to soldier workload. The Human-Robotic Interface (HRI) Intelligent Systems Behavior Simulator (ISBS) is a human performance measurement simulation system that allows modelers to develop constructive simulations of military scenarios with various deployments of interface technologies in order to evaluate operator effectiveness. One such interface is TARDEC's Scalable Soldier-Machine Interface (SMI). The scalable SMI provides a configurable machine interface application that is capable of adapting to several hardware platforms by recognizing the physical space limitations of the display device. This paper describes the integration of the ISBS and Scalable SMI applications, which will ultimately benefit both systems. The ISBS will be able to use the Scalable SMI to visualize the behaviors of virtual soldiers performing HRI tasks, such as route planning, and the scalable SMI will benefit from stimuli provided by the ISBS simulation environment. The paper describes the background of each system and details of the system integration approach.

Network Edge Intelligence for the Emerging Next-Generation Internet

Directory of Open Access Journals (Sweden)

Salekul Islam

2010-11-01

Full Text Available The success of the Content Delivery Networks (CDN in the recent years has demonstrated the increased benefits of the deployment of some form of “intelligence” within the network. Cloud computing, on the other hand, has shown the benefits of economies of scale and the use of a generic infrastructure to support a variety of services. Following that trend, we propose to move away from the smart terminal-dumb network dichotomy to a model where some degree of intelligence is put back into the network, specifically at the edge, with the support of Cloud technology. In this paper, we propose the deployment of an Edge Cloud, which integrates a variety of user-side and server-side services. On the user side, surrogate, an application running on top of the Cloud, supports a virtual client. The surrogate hides the underlying network infrastructure from the user, thus allowing for simpler, more easily managed terminals. Network side services supporting delivery of and exploiting content are also deployed on this infrastructure, giving the Internet Service Providers (ISP many opportunities to become directly involved in content and service delivery.

Artificial Intelligence--Applications in Education.

Science.gov (United States)

Poirot, James L.; Norris, Cathleen A.

1987-01-01

This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

Design of Fault Tolerant Network Interfaces for NoCs

DEFF Research Database (Denmark)

Fiorin, Leandro; Micconi, Laura; Sami, Mariagiovanna

2011-01-01

Networks-on-Chip (NoCs) appeared as a strategy to deal with the communication requirements of complex IP-based System-on-Chips. As the complexity of designs increases and the technology scales down into the deep-submicron domain, the probability of malfunctions and failures in the NoC components...... increases. This paper focuses on the study and evaluation of techniques for increasing reliability and resilience of Network Interfaces (NIs). NIs act as interfaces between IP cores and the communication infrastructure; a faulty behavior in them could affect therefore the overall system. In this work, we...... of the NI, while saving up to 83% in area with respect to a standard Triple Modular Redundancy implementation, as well as a significant energy reduction....

A Lateral Control Method of Intelligent Vehicle Based on Fuzzy Neural Network

Directory of Open Access Journals (Sweden)

Linhui Li

2015-01-01

Full Text Available A lateral control method is proposed for intelligent vehicle to track the desired trajectory. Firstly, a lateral control model is established based on the visual preview and dynamic characteristics of intelligent vehicle. Then, the lateral error and orientation error are melded into an integrated error. Considering the system parameter perturbation and the external interference, a sliding model control is introduced in this paper. In order to design a sliding surface, the integrated error is chosen as the parameter of the sliding mode switching function. The sliding mode switching function and its derivative are selected as two inputs of the controller, and the front wheel angle is selected as the output. Next, a fuzzy neural network is established, and the self-learning functions of neural network is utilized to construct the fuzzy rules. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed method.

10th International Symposium on Intelligent Distributed Computing

CERN Document Server

Seghrouchni, Amal; Beynier, Aurélie; Camacho, David; Herpson, Cédric; Hindriks, Koen; Novais, Paulo

2017-01-01

This book presents the combined peer-reviewed proceedings of the tenth International Symposium on Intelligent Distributed Computing (IDC’2016), which was held in Paris, France from October 10th to 12th, 2016. The 23 contributions address a range of topics related to theory and application of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

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

Science.gov (United States)

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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

An intelligent switch with back-propagation neural network based hybrid power system

Science.gov (United States)

Perdana, R. H. Y.; Fibriana, F.

2018-03-01

The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

Intelligent Stale-Frame Discards for Real-Time Video Streaming over Wireless Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Sheu Tsang-Ling

2009-01-01

Full Text Available Abstract This paper presents intelligent early packet discards (I-EPD for real-time video streaming over a multihop wireless ad hoc network. In a multihop wireless ad hoc network, the quality of transferring real-time video streams could be seriously degraded, since every intermediate node (IN functionally like relay device does not possess large buffer and sufficient bandwidth. Even worse, a selected relay node could leave or power off unexpectedly, which breaks the route to destination. Thus, a stale video frame is useless even if it can reach destination after network traffic becomes smooth or failed route is reconfigured. In the proposed I-EPD, an IN can intelligently determine whether a buffered video packet should be early discarded. For the purpose of validation, we implement the I-EPD on Linux-based embedded systems. Via the comparisons of performance metrics (packet/frame discards ratios, PSNR, etc., we demonstrate that video quality over a wireless ad hoc network can be substantially improved and unnecessary bandwidth wastage is greatly reduced.

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

Science.gov (United States)

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. © 2016 by the Society for Personality and Social Psychology, Inc.

Automation of seismic network signal interpolation: an artificial intelligence approach

International Nuclear Information System (INIS)

Chiaruttini, C.; Roberto, V.

1988-01-01

After discussing the current status of the automation in signal interpretation from seismic networks, a new approach, based on artificial-intelligence tecniques, is proposed. The knowledge of the human expert analyst is examined, with emphasis on its objects, strategies and reasoning techniques. It is argued that knowledge-based systems (or expert systems) provide the most appropriate tools for designing an automatic system, modelled on the expert behaviour

Knowledge-based control of an adaptive interface

Science.gov (United States)

Lachman, Roy

1989-01-01

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

General, crystallized and fluid intelligence are not associated with functional global network efficiency: A replication study with the human connectome project 1200 data set.

Science.gov (United States)

Kruschwitz, J D; Waller, L; Daedelow, L S; Walter, H; Veer, I M

2018-05-01

One hallmark example of a link between global topological network properties of complex functional brain connectivity and cognitive performance is the finding that general intelligence may depend on the efficiency of the brain's intrinsic functional network architecture. However, although this association has been featured prominently over the course of the last decade, the empirical basis for this broad association of general intelligence and global functional network efficiency is quite limited. In the current study, we set out to replicate the previously reported association between general intelligence and global functional network efficiency using the large sample size and high quality data of the Human Connectome Project, and extended the original study by testing for separate association of crystallized and fluid intelligence with global efficiency, characteristic path length, and global clustering coefficient. We were unable to provide evidence for the proposed association between general intelligence and functional brain network efficiency, as was demonstrated by van den Heuvel et al. (2009), or for any other association with the global network measures employed. More specifically, across multiple network definition schemes, ranging from voxel-level networks to networks of only 100 nodes, no robust associations and only very weak non-significant effects with a maximal R 2 of 0.01 could be observed. Notably, the strongest (non-significant) effects were observed in voxel-level networks. We discuss the possibility that the low power of previous studies and publication bias may have led to false positive results fostering the widely accepted notion of general intelligence being associated to functional global network efficiency. Copyright © 2018 Elsevier Inc. All rights reserved.

Intelligent fault diagnosis of rolling bearings using an improved deep recurrent neural network

Science.gov (United States)

Jiang, Hongkai; Li, Xingqiu; Shao, Haidong; Zhao, Ke

2018-06-01

Traditional intelligent fault diagnosis methods for rolling bearings heavily depend on manual feature extraction and feature selection. For this purpose, an intelligent deep learning method, named the improved deep recurrent neural network (DRNN), is proposed in this paper. Firstly, frequency spectrum sequences are used as inputs to reduce the input size and ensure good robustness. Secondly, DRNN is constructed by the stacks of the recurrent hidden layer to automatically extract the features from the input spectrum sequences. Thirdly, an adaptive learning rate is adopted to improve the training performance of the constructed DRNN. The proposed method is verified with experimental rolling bearing data, and the results confirm that the proposed method is more effective than traditional intelligent fault diagnosis methods.

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

Science.gov (United States)

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.

9th International Symposium on Intelligent Distributed Computing

CERN Document Server

Camacho, David; Analide, Cesar; Seghrouchni, Amal; Badica, Costin

2016-01-01

This book represents the combined peer-reviewed proceedings of the ninth International Symposium on Intelligent Distributed Computing – IDC’2015, of the Workshop on Cyber Security and Resilience of Large-Scale Systems – WSRL’2015, and of the International Workshop on Future Internet and Smart Networks – FI&SN’2015. All the events were held in Guimarães, Portugal during October 7th-9th, 2015. The 46 contributions published in this book address many topics related to theory and applications of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

An Intelligent QoS Identification for Untrustworthy Web Services Via Two-phase Neural Networks

OpenAIRE

Wang, Weidong; Wang, Liqiang; Lu, Wei

2016-01-01

QoS identification for untrustworthy Web services is critical in QoS management in the service computing since the performance of untrustworthy Web services may result in QoS downgrade. The key issue is to intelligently learn the characteristics of trustworthy Web services from different QoS levels, then to identify the untrustworthy ones according to the characteristics of QoS metrics. As one of the intelligent identification approaches, deep neural network has emerged as a powerful techniqu...

Probabilistic reasoning in intelligent systems networks of plausible inference

CERN Document Server

Pearl, Judea

1988-01-01

Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provid

Acoustic richness modulates the neural networks supporting intelligible speech processing.

Science.gov (United States)

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. Copyright © 2015 Elsevier

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

Science.gov (United States)

Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

2015-01-01

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

BELIEF dashboard - a web-based curation interface to support generation of BEL networks

OpenAIRE

Madan, Sumit; Hodapp, Sven; Fluck, Juliane

2015-01-01

The relevance of network-based approaches in systems biology to achieve a better understanding of biological mechanisms has increased enormously. The Biological Expression Language (BEL) is well designed to collate findings from scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a free and user-friendly web-based curation interface called BELIEF Dashboard has been developed. The interface incorporates an information extraction...

Intelligent distributed computing

CERN Document Server

Thampi, Sabu

2015-01-01

This book contains a selection of refereed and revised papers of the Intelligent Distributed Computing Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India.  The papers selected for this Track cover several Distributed Computing and related topics including Peer-to-Peer Networks, Cloud Computing, Mobile Clouds, Wireless Sensor Networks, and their applications.

Concept development and needs identification for intelligent network flow optimization (INFLO) : concept of operations.

Science.gov (United States)

2012-06-01

The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...

Concept development and needs identification for intelligent network flow optimization (INFLO) : test readiness assessment.

Science.gov (United States)

2012-11-01

The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...

Prototype interface facility for intelligent handling and processing of medical image and data

Science.gov (United States)

Lymberopoulos, Dimitris C.; Garantziotis, Giannis; Spiropoulos, Kostas V.; Kotsopoulos, Stavros A.; Goutis, Costas E.

1993-06-01

This paper introduces an interface facility (IF) developed within the overall framework of RACE research project. Due to the nature of the project which it has been focused in the Remote Medical Expert Consultation, the involvement of distances, the versatile user advocation and familiarity with newly introduced methods of medical diagnosis, considerable deficiencies can arise. The aim was to intelligently assist the user/physician by providing an ergonomic environment which would contain operational and functional deficiencies to the lowest possible levels. IF, energizes and activates system and application level commands and procedures along with the necessary exemplified and instructional help facilities, in order to concisely allow the user to interact with the system safely and easily at all levels.

Ecological Interface Design for Computer Network Defense.

Science.gov (United States)

Bennett, Kevin B; Bryant, Adam; Sushereba, Christen

2018-05-01

A prototype ecological interface for computer network defense (CND) was developed. Concerns about CND run high. Although there is a vast literature on CND, there is some indication that this research is not being translated into operational contexts. Part of the reason may be that CND has historically been treated as a strictly technical problem, rather than as a socio-technical problem. The cognitive systems engineering (CSE)/ecological interface design (EID) framework was used in the analysis and design of the prototype interface. A brief overview of CSE/EID is provided. EID principles of design (i.e., direct perception, direct manipulation and visual momentum) are described and illustrated through concrete examples from the ecological interface. Key features of the ecological interface include (a) a wide variety of alternative visual displays, (b) controls that allow easy, dynamic reconfiguration of these displays, (c) visual highlighting of functionally related information across displays, (d) control mechanisms to selectively filter massive data sets, and (e) the capability for easy expansion. Cyber attacks from a well-known data set are illustrated through screen shots. CND support needs to be developed with a triadic focus (i.e., humans interacting with technology to accomplish work) if it is to be effective. Iterative design and formal evaluation is also required. The discipline of human factors has a long tradition of success on both counts; it is time that HF became fully involved in CND. Direct application in supporting cyber analysts.

The role of networks and artificial intelligence in nanotechnology design and analysis.

Science.gov (United States)

Hudson, D L; Cohen, M E

2004-05-01

Techniques with their origins in artificial intelligence have had a great impact on many areas of biomedicine. Expert-based systems have been used to develop computer-assisted decision aids. Neural networks have been used extensively in disease classification and more recently in many bioinformatics applications including genomics and drug design. Network theory in general has proved useful in modeling all aspects of biomedicine from healthcare organizational structure to biochemical pathways. These methods show promise in applications involving nanotechnology both in the design phase and in interpretation of system functioning.

Gestures in an Intelligent User Interface

Science.gov (United States)

Fikkert, Wim; van der Vet, Paul; Nijholt, Anton

In this chapter we investigated which hand gestures are intuitive to control a large display multimedia interface from a user's perspective. Over the course of two sequential user evaluations, we defined a simple gesture set that allows users to fully control a large display multimedia interface, intuitively. First, we evaluated numerous gesture possibilities for a set of commands that can be issued to the interface. These gestures were selected from literature, science fiction movies, and a previous exploratory study. Second, we implemented a working prototype with which the users could interact with both hands and the preferred hand gestures with 2D and 3D visualizations of biochemical structures. We found that the gestures are influenced to significant extent by the fast paced developments in multimedia interfaces such as the Apple iPhone and the Nintendo Wii and to no lesser degree by decades of experience with the more traditional WIMP-based interfaces.

Network and user interface for PAT DOME virtual motion environment system

Science.gov (United States)

Worthington, J. W.; Duncan, K. M.; Crosier, W. G.

1993-01-01

The Device for Orientation and Motion Environments Preflight Adaptation Trainer (DOME PAT) provides astronauts a virtual microgravity sensory environment designed to help alleviate tye symptoms of space motion sickness (SMS). The system consists of four microcomputers networked to provide real time control, and an image generator (IG) driving a wide angle video display inside a dome structure. The spherical display demands distortion correction. The system is currently being modified with a new graphical user interface (GUI) and a new Silicon Graphics IG. This paper will concentrate on the new GUI and the networking scheme. The new GUI eliminates proprietary graphics hardware and software, and instead makes use of standard and low cost PC video (CGA) and off the shelf software (Microsoft's Quick C). Mouse selection for user input is supported. The new Silicon Graphics IG requires an Ethernet interface. The microcomputer known as the Real Time Controller (RTC), which has overall control of the system and is written in Ada, was modified to use the free public domain NCSA Telnet software for Ethernet communications with the Silicon Graphics IG. The RTC also maintains the original ARCNET communications through Novell Netware IPX with the rest of the system. The Telnet TCP/IP protocol was first used for real-time communication, but because of buffering problems the Telnet datagram (UDP) protocol needed to be implemented. Since the Telnet modules are written in C, the Adap pragma 'Interface' was used to interface with the network calls.

Intelligent Information Retrieval: An Introduction.

Science.gov (United States)

Gauch, Susan

1992-01-01

Discusses the application of artificial intelligence to online information retrieval systems and describes several systems: (1) CANSEARCH, from MEDLINE; (2) Intelligent Interface for Information Retrieval (I3R); (3) Gausch's Query Reformulation; (4) Environmental Pollution Expert (EP-X); (5) PLEXUS (gardening); and (6) SCISOR (corporate…

A novel proton exchange membrane fuel cell based power conversion system for telecom supply with genetic algorithm assisted intelligent interfacing converter

International Nuclear Information System (INIS)

Kaur, Rajvir; Krishnasamy, Vijayakumar; Muthusamy, Kaleeswari; Chinnamuthan, Periasamy

2017-01-01

Highlights: • Proton exchange membrane fuel cell based telecom tower supply is proposed. • The use of diesel generator is eliminated and battery size is reduced. • Boost converter based intelligent interfacing unit is implemented. • The genetic algorithm assisted controller is proposed for effective interfacing. • The controller is robust against input and output disturbance rejection. - Abstract: This paper presents the fuel cell based simple electric energy conversion system for supplying the telecommunication towers to reduce the operation and maintenance cost of telecom companies. The telecom industry is at the boom and is penetrating deep into remote rural areas having unreliable or no grid supply. The telecom industry is getting heavily dependent on a diesel generator set and battery bank as a backup for continuously supplying a base transceiver station of telecom towers. This excessive usage of backup supply resulted in increased operational expenditure, the unreliability of power supply and had become a threat to the environment. A significant development and concern of clean energy sources, proton exchange membrane fuel cell based supply for base transceiver station is proposed with intelligent interfacing unit. The necessity of the battery bank capacity is significantly reduced as compared with the earlier solutions. Further, a simple closed loop and genetic algorithm assisted controller is proposed for intelligent interfacing unit which consists of power electronic boost converter for power conditioning. The proposed genetic algorithm assisted controller would ensure the tight voltage regulation at the DC distribution bus of the base transceiver station. Also, it will provide the robust performance of the base transceiver station under telecom load variation and proton exchange membrane fuel cell output voltage fluctuations. The complete electric energy conversion system along with telecom loads is simulated in MATLAB/Simulink platform and

Technical report on prototype intelligent network flow optimization (INFLO) dynamic speed harmonization and queue warning.

Science.gov (United States)

2015-06-01

This Technical Report on Prototype Intelligent Network Flow Optimization (INFLO) Dynamic Speed Harmonization and : Queue Warning is the final report for the project. It describes the prototyping, acceptance testing and small-scale : demonstration of ...

Intelligent environmental sensing

CERN Document Server

Mukhopadhyay, Subhas

2015-01-01

Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

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

1989-03-01

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

Artificial Intelligence.

Science.gov (United States)

Wash, Darrel Patrick

1989-01-01

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

Network Performance Evaluation of Abis Interface over DVB-S2 in the GSM over Satellite Network

Directory of Open Access Journals (Sweden)

S. B. Musabekov

2010-01-01

Full Text Available This paper deals with establishing a GSM link over Satellite. Abis interface, which is defined between Base Transceiver Station (BTS and Base Station Controller (BSC, in a GSM network is considered here to be routed over the Satellite. The satellite link enables a quick and cost-effective GSM link in meagerly populated areas. A different scenario comparison was done to understand the impact of Satellite environment on network availability comparing to terrestrial scenario. We have implemented an Abis interface over DVB S2 in NS2 and evaluated the performance over the high delay and loss satellite channel. Network performance was evaluated with respect to Satellite channel delay and DVB S2 encapsulation efficiency under different amount of user traffic and compared with the terrestrial scenario. The results clearly showed an increased amount of SDCCH and TCH channels required in the case of satellite scenario for the same amount of traffic in comparison to conventional terrestrial scenario. We have optimized the parameters based on the simulation results. Link budget estimation considering DVB-S2 platform was done to find satellite bandwidth and cost requirements for different network setups.

Secure data exchange between intelligent devices and computing centers

Science.gov (United States)

Naqvi, Syed; Riguidel, Michel

2005-03-01

The advent of reliable spontaneous networking technologies (commonly known as wireless ad-hoc networks) has ostensibly raised stakes for the conception of computing intensive environments using intelligent devices as their interface with the external world. These smart devices are used as data gateways for the computing units. These devices are employed in highly volatile environments where the secure exchange of data between these devices and their computing centers is of paramount importance. Moreover, their mission critical applications require dependable measures against the attacks like denial of service (DoS), eavesdropping, masquerading, etc. In this paper, we propose a mechanism to assure reliable data exchange between an intelligent environment composed of smart devices and distributed computing units collectively called 'computational grid'. The notion of infosphere is used to define a digital space made up of a persistent and a volatile asset in an often indefinite geographical space. We study different infospheres and present general evolutions and issues in the security of such technology-rich and intelligent environments. It is beyond any doubt that these environments will likely face a proliferation of users, applications, networked devices, and their interactions on a scale never experienced before. It would be better to build in the ability to uniformly deal with these systems. As a solution, we propose a concept of virtualization of security services. We try to solve the difficult problems of implementation and maintenance of trust on the one hand, and those of security management in heterogeneous infrastructure on the other hand.

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

Directory of Open Access Journals (Sweden)

Gilberto Bojorquez

2007-08-01

Full Text Available The development of smart sensors involves the design of reconfigurable systemscapable of working with different input sensors. Reconfigurable systems ideally shouldspend the least possible amount of time in their calibration. An autocalibration algorithmfor intelligent sensors should be able to fix major problems such as offset, variation of gainand lack of linearity, as accurately as possible. This paper describes a new autocalibrationmethodology 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 linearizationmethods. Method comparison was achieved using different number of calibration points,and several nonlinear levels of the input signal. This paper also shows that the proposedmethod 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 theimplementation of the ANN in a microcontroller unit, MCU. In order to illustrate themethod capability to build autocalibration and reconfigurable systems, a temperaturemeasurement 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.

An Intelligent Cooperative Visual Sensor Network for Urban Mobility.

Science.gov (United States)

Leone, Giuseppe Riccardo; Moroni, Davide; Pieri, Gabriele; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea; Marino, Francesco

2017-11-10

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.

IC design challenges for ambient intelligence

NARCIS (Netherlands)

Aarts, E.H.L.; Roovers, R.L.J.

2003-01-01

The vision of ambient intelligence opens a world of unprecedented experiences: the interaction of people with electronic devices is changed as contextual awareness, natural interfaces and ubiquitous availability of information are realized. We analyze the consequences of the ambient intelligence

Machine learning based Intelligent cognitive network using fog computing

Science.gov (United States)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

Local computer network of the JINR Neutron Physics Laboratory

International Nuclear Information System (INIS)

Alfimenkov, A.V.; Vagov, V.A.; Vajdkhadze, F.

1988-01-01

New high-speed local computer network, where intelligent network adapter (NA) is used as hardware base, is developed in the JINR Neutron Physics Laboratory to increase operation efficiency and data transfer rate. NA consists of computer bus interface, cable former, microcomputer segment designed for both program realization of channel-level protocol and organization of bidirectional transfer of information through direct access channel between monochannel and computer memory with or witout buffering in NA operation memory device

Uncertainty management using bayesian networks in student knowledge diagnosis

Directory of Open Access Journals (Sweden)

Adina COCU

2005-12-01

Full Text Available In intelligent tutoring systems, student or user modeling implies dealing with imperfect and uncertain knowledge. One of the artificial intelligence techniques used for uncertainty management is that of Bayesian networks. This paradigm is recommended in the situation when exist dependencies between data and qualitative information about these data. In this work we present a student knowledge diagnosis model based on representation with Bayesian networks. The educational system incorporate a multimedia interface for accomplishes the testing tools. The results of testing sessions are represented and interpreted with probability theory in order to ensure an adapted support for the student. The aims of the computer assisted application that contains this diagnose module are to support the student in personalized learning process and errors explanation.

Recent Advances in Intelligent Engineering Systems

CERN Document Server

Klempous, Ryszard; Araujo, Carmen

2012-01-01

This volume is a collection of 19 chapters on intelligent engineering systems written by respectable experts of the fields. The book consists of three parts. The first part is devoted to the foundational aspects of computational intelligence. It consists of 8 chapters that include studies in genetic algorithms, fuzzy logic connectives, enhanced intelligence in product models, nature-inspired optimization technologies, particle swarm optimization, evolution algorithms, model complexity of neural networks, and fitness landscape analysis. The second part contains contributions to intelligent computation in networks, presented in 5 chapters. The covered subjects include the application of self-organizing maps for early detection of denial of service attacks, combating security threats via immunity and adaptability in cognitive radio networks, novel modifications in WSN network design for improved SNR and reliability, a conceptual framework for the design of audio based cognitive infocommunication channels, and a ...

FPGA implementation of advanced FEC schemes for intelligent aggregation networks

Science.gov (United States)

Zou, Ding; Djordjevic, Ivan B.

2016-02-01

In state-of-the-art fiber-optics communication systems the fixed forward error correction (FEC) and constellation size are employed. While it is important to closely approach the Shannon limit by using turbo product codes (TPC) and low-density parity-check (LDPC) codes with soft-decision decoding (SDD) algorithm; rate-adaptive techniques, which enable increased information rates over short links and reliable transmission over long links, are likely to become more important with ever-increasing network traffic demands. In this invited paper, we describe a rate adaptive non-binary LDPC coding technique, and demonstrate its flexibility and good performance exhibiting no error floor at BER down to 10-15 in entire code rate range, by FPGA-based emulation, making it a viable solution in the next-generation high-speed intelligent aggregation networks.

Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

International Nuclear Information System (INIS)

Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

2017-01-01

Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

Integration of multi-interface conversion channel using FPGA for modular photonic network

Science.gov (United States)

Janicki, Tomasz; Pozniak, Krzysztof T.; Romaniuk, Ryszard S.

2010-09-01

The article discusses the integration of different types of interfaces with FPGA circuits using a reconfigurable communication platform. The solution has been implemented in practice in a single node of a distributed measurement system. Construction of communication platform has been presented with its selected hardware modules, described in VHDL and implemented in FPGA circuits. The graphical user interface (GUI) has been described that allows a user to control the operation of the system. In the final part of the article selected practical solutions have been introduced. The whole measurement system resides on multi-gigabit optical network. The optical network construction is highly modular, reconfigurable and scalable.

An intelligent multi-media human-computer dialogue system

Science.gov (United States)

Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.

1988-01-01

Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.

An Intelligent Pinger Network for Solid Glacier Environments

Science.gov (United States)

Schönitz, S.; Reuter, S.; Henke, C.; Jeschke, S.; Ewert, D.; Eliseev, D.; Heinen, D.; Linder, P.; Scholz, F.; Weinstock, L.; Wickmann, S.; Wiebusch, C.; Zierke, S.

2016-12-01

This talk presents a novel approach for an intelligent, agent-based pinger network in an extraterrestrial glacier environment. Because of recent findings of the Cassini spacecraft, a mission to Saturn's moon Enceladus is planned in order search for extraterrestrial life within the ocean beneath Enceladus' ice crust. Therefore, a maneuverable melting probe, the EnEx probe, was developed to melt into Enceladus' ice and take liquid samples from water-filled crevasses. Hence, the probe collecting the samples has to be able to navigate in ice which is a hard problem, because neither visual nor gravitational methods can be used. To enhance the navigability of the probe, a network of autonomous pinger units (APU) is in development that is able to extract a map of the ice environment via ultrasonic soundwaves. A network of these APUs will be deployed on the surface of Enceladus, melt into the ice and form a network to help guide the probe safely to its destination. The APU network is able to form itself fully autonomously and to compensate system failures of individual APUs. The agents controlling the single APU are realized by rule-based expert systems implemented in CLIPS. The rule-based expert system evaluates available information of the environment, decides for actions to take to achieve the desired goal (e.g. a specific network topology), and executes and monitors such actions. In general, it encodes certain situations that are evaluated whenever an APU is currently idle, and then decides for a next action to take. It bases this decision on its internal world model that is shared with the other APUs. The optimal network topology that defines each agents position is iteratively determined by mixed-integer nonlinear programming. Extensive simulations studies show that the proposed agent design enables the APUs to form a robust network topology that is suited to create a reliable 3D map of the ice environment.

Distributed intelligence in CAMAC

International Nuclear Information System (INIS)

Kunz, P.F.

1977-01-01

The CAMAC digital interface standard has served us well since 1969. During this time there have been enormous advances in digital electronics. In particular, low cost microprocessors now make it feasible to consider use of distributed intelligence even in simple data acquisition systems. This paper describes a simple extension of the CAMAC standard which allows distributed intelligence at the crate level

DESIGN OF AN INTELLIGENT SYSTEM TO DETECT TYPE OF PAIN USING ARTIFICIAL NEURAL NETWORK FOR PATIENTS WITH SPINAL CORD INJURY IN SHEFA NEUROSCIENCE RESEARCH CENTER

OpenAIRE

Nasrolah Nasr HeidarAbadi, Reza Safdari, Peirhossein Kolivand, Amir Javadi, Azimeh Danesh Shahraki1, Marjan Ghazi Saeidi*

2017-01-01

Using artificial intelligence in computerized clinical systems helps physicians diagnose disease or choose treatment. Intelligent methods are constantly changed to be more effective and accurate for quick medical diagnosis. Neural networks are a powerful tool to help physicians. The tools can process a high number of data and minimize errors in ignoring patients' information. Intelligent system design based on artificial neural network was performed in 3 phases. Phase1: Designing the data rec...

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

Science.gov (United States)

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-05-30

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

Directory of Open Access Journals (Sweden)

Gaining Han

2017-05-01

Full Text Available The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS, the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

Classification of user interfaces for graph-based online analytical processing

Science.gov (United States)

Michaelis, James R.

2016-05-01

In the domain of business intelligence, user-oriented software for conducting multidimensional analysis via Online- Analytical Processing (OLAP) is now commonplace. In this setting, datasets commonly have well-defined sets of dimensions and measures around which analysis tasks can be conducted. However, many forms of data used in intelligence operations - deriving from social networks, online communications, and text corpora - will consist of graphs with varying forms of potential dimensional structure. Hence, enabling OLAP over such data collections requires explicit definition and extraction of supporting dimensions and measures. Further, as Graph OLAP remains an emerging technique, limited research has been done on its user interface requirements. Namely, on effective pairing of interface designs to different types of graph-derived dimensions and measures. This paper presents a novel technique for pairing of user interface designs to Graph OLAP datasets, rooted in Analytic Hierarchy Process (AHP) driven comparisons. Attributes of the classification strategy are encoded through an AHP ontology, developed in our alternate work and extended to support pairwise comparison of interfaces. Specifically, according to their ability, as perceived by Subject Matter Experts, to support dimensions and measures corresponding to Graph OLAP dataset attributes. To frame this discussion, a survey is provided both on existing variations of Graph OLAP, as well as existing interface designs previously applied in multidimensional analysis settings. Following this, a review of our AHP ontology is provided, along with a listing of corresponding dataset and interface attributes applicable toward SME recommendation structuring. A walkthrough of AHP-based recommendation encoding via the ontology-based approach is then provided. The paper concludes with a short summary of proposed future directions seen as essential for this research area.

Advanced intelligent systems

CERN Document Server

Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

2014-01-01

Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

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

Science.gov (United States)

Hortos, William S.

2006-05-01

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

The intelligent data recorder

International Nuclear Information System (INIS)

Kojima, Mamoru; Hidekuma, Sigeru.

1985-01-01

The intelligent data recorder has been developed to data acquisition for a microwave interferometer. The 'RS-232C' which is the standard interface is used for data transmission to the host computer. Then, it's easy to connect with any computer which has general purpose serial port. In this report, the charcteristics of the intelligent data recorder and the way of developing the software are described. (author)

Freedom and privacy in ambient intelligence

NARCIS (Netherlands)

Brey, Philip A.E.

2006-01-01

This paper analyzes ethical aspects of the new paradigm of Ambient Intelligence, which is a combination of Ubiquitous Computing and Intelligent User Interfaces (IUI’s). After an introduction to the approach, two key ethical dimensions will be analyzed: freedom and privacy. It is argued that Ambient

Prediction of interface residue based on the features of residue interaction network.

Science.gov (United States)

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Intelligent Cooperative Visual Sensor Network for Urban Mobility

Science.gov (United States)

Leone, Giuseppe Riccardo; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea

2017-01-01

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities. PMID:29125535

An Intelligent Cooperative Visual Sensor Network for Urban Mobility

Directory of Open Access Journals (Sweden)

Giuseppe Riccardo Leone

2017-11-01

Full Text Available Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.

Information for the user in design of intelligent systems

Science.gov (United States)

Malin, Jane T.; Schreckenghost, Debra L.

1993-01-01

Recommendations are made for improving intelligent system reliability and usability based on the use of information requirements in system development. Information requirements define the task-relevant messages exchanged between the intelligent system and the user by means of the user interface medium. Thus, these requirements affect the design of both the intelligent system and its user interface. Many difficulties that users have in interacting with intelligent systems are caused by information problems. These information problems result from the following: (1) not providing the right information to support domain tasks; and (2) not recognizing that using an intelligent system introduces new user supervisory tasks that require new types of information. These problems are especially prevalent in intelligent systems used for real-time space operations, where data problems and unexpected situations are common. Information problems can be solved by deriving information requirements from a description of user tasks. Using information requirements embeds human-computer interaction design into intelligent system prototyping, resulting in intelligent systems that are more robust and easier to use.

A replica exchange transition interface sampling method with multiple interface sets for investigating networks of rare events

Science.gov (United States)

Swenson, David W. H.; Bolhuis, Peter G.

2014-07-01

The multiple state transition interface sampling (TIS) framework in principle allows the simulation of a large network of complex rare event transitions, but in practice suffers from convergence problems. To improve convergence, we combine multiple state TIS [J. Rogal and P. G. Bolhuis, J. Chem. Phys. 129, 224107 (2008)] with replica exchange TIS [T. S. van Erp, Phys. Rev. Lett. 98, 268301 (2007)]. In addition, we introduce multiple interface sets, which allow more than one order parameter to be defined for each state. We illustrate the methodology on a model system of multiple independent dimers, each with two states. For reaction networks with up to 64 microstates, we determine the kinetics in the microcanonical ensemble, and discuss the convergence properties of the sampling scheme. For this model, we find that the kinetics depend on the instantaneous composition of the system. We explain this dependence in terms of the system's potential and kinetic energy.

Intelligent control and automation technology for nuclear applications

International Nuclear Information System (INIS)

Kim, Jae Hee; Kim, Ko Ryeo; Lee, Jae Cheol; Eom, Heung Seop; Lee, Jang Soo

1994-01-01

Using recently established intelligent mobile robot theory and high technologies in computer science, we have designed an inspection automation system for welded parts of the reactor vessel, and we intend to establish basic technologies. The recent status of those technologies is surveyed for various application areas, and the characteristics and availability of those techniques such as intelligent mobile robot, digital computer control, intelligent user interface, realtime data processing, ultrasonic signal processing, intelligent user interface, intelligent defect recognition, are studied and examined at first. The high performance and compact size inspection system is designed, and if implemented, it is expected to be very efficient in economic point of view. In addition, the use of integrated SW system leads to the reduction of human errors. Through the analysis results and experiences, we investigated the further feasibility of basic technology applications to the various similar operation systems in NPP. (Author)

Embedded systems design issues in ambient intelligence

NARCIS (Netherlands)

Aarts, E.H.L.; Roovers, R.L.J.; Basten, A.A.; Geilen, M.C.W.; Groot, de H.W.H.

2003-01-01

The vision of ambient intelligence opens a world of unprecedented ex.periences: the interaction of people with electronic devices is changed as context awareness, natural interfaces and ubiquitous availability of information are realized. We analyze the consequences of the ambient intelligence

Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

Directory of Open Access Journals (Sweden)

Yuanpeng Tan

2018-01-01

Full Text Available Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

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

Science.gov (United States)

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.

Artificial intelligence. Application of the Statistical Neural Networks computer program in nuclear medicine

International Nuclear Information System (INIS)

Stefaniak, B.; Cholewinski, W.; Tarkowska, A.

2005-01-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer application of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. In this paper practical aspects of scientific application of ANN in medicine using the Statistical Neural Networks Computer program, were presented. Several steps of data analysis with the above ANN software package were discussed shortly, from material selection and its dividing into groups to the types of obtained results. The typical problems connected with assessing scintigrams by ANN were also described. (author)

Design and implementation of an inter-agency, multi-mission space flight operations network interface

Science.gov (United States)

Byrne, R.; Scharf, M.; Doan, D.; Liu, J.; Willems, A.

2004-01-01

An advanced network interface was designed and implemented by a team from the Jet Propulsion Lab with support from the European Space Operations Center. This poster shows the requirements for the interface, the design, the topology, the testing and lessons learned from the whole implementation.

BWR shutdown analyzer using artificial intelligence (AI) techniques

International Nuclear Information System (INIS)

Cain, D.G.

1986-01-01

A prototype alarm system for detecting abnormal reactor shutdowns based on artificial intelligence technology is described. The system incorporates knowledge about Boiling Water Reactor (BWR) plant design and component behavior, as well as knowledge required to distinguish normal, abnormal, and ATWS accident conditions. The system was developed using a software tool environment for creating knowledge-based applications on a LISP machine. To facilitate prototype implementation and evaluation, a casual simulation of BWR shutdown sequences was developed and interfaced with the alarm system. An intelligent graphics interface for execution and control is described. System performance considerations and general observations relating to artificial intelligence application to nuclear power plant problems are provided

An intensive insulinotherapy mobile phone application built on artificial intelligence techniques.

Science.gov (United States)

Curran, Kevin; Nichols, Eric; Xie, Ermai; Harper, Roy

2010-01-01

Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use "flat" computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial confirmed to a large degree that

Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

Science.gov (United States)

Qiu, Feng; Dai, Guang; Zhang, Ying

According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.

Intelligence Control System for Landfills Based on Wireless Sensor Network

Science.gov (United States)

Zhang, Qian; Huang, Chuan; Gong, Jian

2018-06-01

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

ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

Institute of Scientific and Technical Information of China (English)

X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

2003-01-01

An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

Intelligent routing protocol for ad hoc wireless network

Science.gov (United States)

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

Intelligent Performance Analysis with a Natural Language Interface

Science.gov (United States)

Juuso, Esko K.

2017-09-01

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.

Intelligent mechatronics; Intelligent mechatronics

Energy Technology Data Exchange (ETDEWEB)

Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

1995-10-01

Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

OMNI: An optoelectronic multichannel network interface based on hybrid CMOS-SEED technology

Science.gov (United States)

Pinkston, Timothy M.

1996-11-01

This paper presents a hybrid CMOS-SEED multiprocessor network interface smart pixel design that implements a reservation-based channel control protocol for collisionless concurrent access to multiple optical interprocessor communication channels. An asynchronous optical token is used as the arbitration mechanism for reservation control instead of slotted access. This work demonstrates that complex network protocol functions can be implemented using optoelectronic smart pixel technology.

Universal Intelligent Small Cell (UnISCell for next generation cellular networks

Directory of Open Access Journals (Sweden)

Mohammad Patwary

2016-11-01

Full Text Available Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations.

Ubiquitous fuzzy computing in open ambient intelligence environments

NARCIS (Netherlands)

Acampora, G.; Loia, V.

2006-01-01

Ambient intelligence (AmI) is considered as the composition of three emergent technologies: ubiquitous computing, ubiquitous communication and intelligent user interfaces. The aim of integration of aforesaid technologies is to make wider the interaction between human beings and information

A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems

Directory of Open Access Journals (Sweden)

Yiming Jiang

2016-01-01

Full Text Available Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC and neural network (NN control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area.

2nd International Conference on Intelligent Computing, Communication & Devices

CERN Document Server

Popentiu-Vladicescu, Florin

2017-01-01

The book presents high quality papers presented at 2nd International Conference on Intelligent Computing, Communication & Devices (ICCD 2016) organized by Interscience Institute of Management and Technology (IIMT), Bhubaneswar, Odisha, India, during 13 and 14 August, 2016. The book covers all dimensions of intelligent sciences in its three tracks, namely, intelligent computing, intelligent communication and intelligent devices. intelligent computing track covers areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication covers communication and network technologies, including mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. This covers communication hardware, soft...

User interface on networked workstations for MFTF plasma diagnostic instruments

International Nuclear Information System (INIS)

Renbarger, V.L.; Balch, T.R.

1985-01-01

A network of Sun-2/170 workstations is used to provide an interface to the MFTF-B Plasma Diagnostics System at Lawrence Livermore National Laboratory. The Plasma Diagnostics System (PDS) is responsible for control of MFTF-B plasma diagnostic instrumentation. An EtherNet Local Area Network links the workstations to a central multiprocessing system which furnishes data processing, data storage and control services for PDS. These workstations permit a physicist to command data acquisition, data processing, instrument control, and display of results. The interface is implemented as a metaphorical desktop, which helps the operator form a mental model of how the system works. As on a real desktop, functions are provided by sheets of paper (windows on a CRT screen) called worksheets. The worksheets may be invoked by pop-up menus and may be manipulated with a mouse. These worksheets are actually tasks that communicate with other tasks running in the central computer system. By making entries in the appropriate worksheet, a physicist may specify data acquisition or processing, control a diagnostic, or view a result

Artificial Intelligence Techniques: Applications for Courseware Development.

Science.gov (United States)

Dear, Brian L.

1986-01-01

Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

Directory of Open Access Journals (Sweden)

Ufa Ruslan A.

2015-01-01

Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

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

Directory of Open Access Journals (Sweden)

Hongzhi Hu

2015-01-01

Full Text Available 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.

An intelligent medical system for diagnosis of bone diseases

International Nuclear Information System (INIS)

Hatzilygeroudis, I.; Vassilakos, P.J.; Tsakalidis, A.

1994-01-01

In this paper, aspects of the design of an intelligent medical system for diagnosis of bone diseases that can be detected by scintigraphic images are presented. The system comprises three major parts: a user interface (UI), a database management system (DBMS), and an expert system (ES). The DBMS is used for manipulation of various patient data. A number of patient cases are selected as prototype and stored in separate database. Diagnosis is performed via the ES, called XBONE, based on patient data. Knowledge is represented via an integrated formalism that combines production rules and a neural network. This results in better representation, and facilitates knowledge acquisition and maintenance. (authors)

Event detection intelligent camera development

International Nuclear Information System (INIS)

Szappanos, A.; Kocsis, G.; Molnar, A.; Sarkozi, J.; Zoletnik, S.

2008-01-01

A new camera system 'event detection intelligent camera' (EDICAM) is being developed for the video diagnostics of W-7X stellarator, which consists of 10 distinct and standalone measurement channels each holding a camera. Different operation modes will be implemented for continuous and for triggered readout as well. Hardware level trigger signals will be generated from real time image processing algorithms optimized for digital signal processor (DSP) and field programmable gate array (FPGA) architectures. At full resolution a camera sends 12 bit sampled 1280 x 1024 pixels with 444 fps which means 1.43 Terabyte over half an hour. To analyse such a huge amount of data is time consuming and has a high computational complexity. We plan to overcome this problem by EDICAM's preprocessing concepts. EDICAM camera system integrates all the advantages of CMOS sensor chip technology and fast network connections. EDICAM is built up from three different modules with two interfaces. A sensor module (SM) with reduced hardware and functional elements to reach a small and compact size and robust action in harmful environment as well. An image processing and control unit (IPCU) module handles the entire user predefined events and runs image processing algorithms to generate trigger signals. Finally a 10 Gigabit Ethernet compatible image readout card functions as the network interface for the PC. In this contribution all the concepts of EDICAM and the functions of the distinct modules are described

Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network

Directory of Open Access Journals (Sweden)

Widodo Budiharto

2015-01-01

Full Text Available 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.

Intelligence Control System for Landfills Based on Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Zhang Qian

2018-01-01

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

On user behaviour adaptation under interface change

CSIR Research Space (South Africa)

Rosman, Benjamin S

2014-02-01

Full Text Available International Conference on Intelligent User Interfaces, Haifa, Israel, 24-27 February 2014 On User Behaviour Adaptation Under Interface Change Benjamin Rosman_ Subramanian Ramamoorthy M. M. Hassan Mahmud School of Informatics University of Edinburgh...

How does network governance affect social-ecological fit across the land-sea interface? An empirical assessment from the Lesser Antilles

Directory of Open Access Journals (Sweden)

Jeremy Pittman

2017-12-01

Full Text Available Governance across the land-sea interface presents many challenges related to (1 the engagement of diverse actors and systems of knowledge, (2 the coordinated management of shared ecological resources, and (3 the development of mechanisms to address or account for biogeochemical (e.g., nutrient flows and ecological (e.g., species movements interdependencies between marine and terrestrial systems. If left unaddressed, these challenges can lead to multiple problems of social-ecological fit stemming from governance fragmentation or inattention to various components of land-sea systems. Network governance is hypothesized to address these multiple challenges, yet its specific role in affecting social-ecological fit across the land-sea interface is not well understood. We aim to improve this understanding by examining how network governance affects social-ecological fit across the land-sea interface in two empirical case studies from the Lesser Antilles: Dominica and Saint Lucia. We found that network governance plays a clear role in coordinating management of shared resources and providing capacity to address interactions between ecological entities. Yet, its potential role in engaging diverse actors and addressing, specifically, biogeochemical interactions across the land-sea interface has not been fully realized. Our research suggests that network governance is beneficial, but not sufficient, to improve social-ecological fit across the land-sea interface. Strategically leveraging the network processes (e.g., triadic closure leading to the existing governance networks could prove useful in addressing the current deficiencies in the networks. Additionally, the interplay between hierarchical and networked modes of governance appears to be a critical issue in determining social-ecological fit at the land-sea interface.

Intelligence is differentially related to neural effort in the task-positive and the task-negative brain network

NARCIS (Netherlands)

Basten, U.; Stelzel, C.; Fiebach, C.J.

2013-01-01

Previous studies on individual differences in intelligence and brain activation during cognitive processing focused on brain regions where activation increases with task demands (task-positive network, TPN). Our study additionally considers brain regions where activation decreases with task demands

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

Science.gov (United States)

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.

Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

International Nuclear Information System (INIS)

Laghari, J.A.; Mokhlis, H.; Karimi, M.; Bakar, A.H.A.; Mohamad, Hasmaini

2014-01-01

Highlights: • Unintentional and intentional islanding, their causes, and solutions are presented. • Remote, passive, active and hybrid islanding detection techniques are discussed. • The limitation of these techniques in accurately detect islanding are discussed. • Computational intelligence techniques ability in detecting islanding is discussed. • Review of ANN, fuzzy logic control, ANFIS, Decision tree techniques is provided. - Abstract: Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system

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

International Nuclear Information System (INIS)

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

1992-01-01

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

Intelligent Mobile Sensing and Analysis Research Network in South Africa – Building a base at the CSIR

CSIR Research Space (South Africa)

Mekuria, F

2010-09-01

Full Text Available Intelligent capturing and secure communication of physiological and environmental data to central point of presence in large magnitude is crucial in the design of accurate models of natural and man-made systems or processes. The research network...

MRI correlates of general intelligence in neurotypical adults.

Science.gov (United States)

Malpas, Charles B; Genc, Sila; Saling, Michael M; Velakoulis, Dennis; Desmond, Patricia M; O'Brien, Terence J

2016-02-01

There is growing interest in the neurobiological substrate of general intelligence. Psychometric estimates of general intelligence are reduced in a range of neurological disorders, leading to practical application as sensitive, but non-specific, markers of cerebral disorder. This study examined estimates of general intelligence in neurotypical adults using diffusion tensor imaging and resting-state functional connectivity analysis. General intelligence was related to white matter organisation across multiple brain regions, confirming previous work in older healthy adults. We also found that variation in general intelligence was related to a large functional sub-network involving all cortical lobes of the brain. These findings confirm that individual variance in general intelligence is related to diffusely represented brain networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Smart thermal networks for smart cities - Introduction of concepts and measures

Science.gov (United States)

Schmidt, R. R.; Pol, O.; Basciotti, D.; Page, J.

2012-10-01

In order to contribute to high living standards, climate mitigation and energy supply security, future urban energy systems require a holistic approach. In particular an intelligent integration of thermal networks is necessary. This paper will briefly present the "smart city" concept and introduce an associated definition for smart thermal networks defined on three levels: 1. the interaction with urban planning processes and the interface to the overall urban energy system, 2. the adaptation of the temperature level and 3. supply and demand-side management strategies.

Use of artificial intelligence in nuclear power plants

International Nuclear Information System (INIS)

Uhrig, R.E.

1990-01-01

The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, there are a large number of non-operating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) in which artificial intelligence can increase the efficiency and effectiveness of overall plant and corporate operations. This paper reviews the state-of-the-art of artificial intelligence techniques, specifically, expert systems and neural networks, to nuclear power plants. This paper has reviewed the state-of-the-art of artificial intelligence, specifically expert systems and neural networks that are applied to problems in nuclear power plants

Intelligent Electric Vehicle Integration - Domain Interfaces and Supporting Informatics

DEFF Research Database (Denmark)

Andersen, Peter Bach

This thesis seeks to apply the field of informatics to the intelligent integration of electric vehicles into the power system. The main goal is to release the potential of electric vehicles in relation to a reliable, economically efficient power system based on renewables. To make intelligent EV...... and services in which the electric vehicle may be best suited to participate. The next stakeholder investigated is the distribution system operator representing the low voltage grid. The challenge is assessed by considering a number of grid impacts studies. Next, a set of grid congestion mitigation strategies...

Fixed Point Learning Based Intelligent Traffic Control System

Science.gov (United States)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

Intelligent fiber optic sensor for solution concentration examination

Science.gov (United States)

Borecki, Michal; Kruszewski, Jerzy

2003-09-01

This paper presents the working principles of intelligent fiber-optic intensity sensor used for solution concentration examination. The sensor head is the ending of the large core polymer optical fiber. The head works on the reflection intensity basis. The reflected signal level depends on Fresnel reflection and reflection on suspended matter when the head is submersed in solution. The sensor head is mounted on a lift. For detection purposes the signal includes head submerging, submersion, emerging and emergence is measured. This way the viscosity turbidity and refraction coefficient has an effect on measured signal. The signal forthcoming from head is processed electrically in opto-electronic interface. Then it is feed to neural network. The novelty of presented sensor is implementation of neural network that works in generalization mode. The sensor resolution depends on opto-electronic signal conversion precision and neural network learning accuracy. Therefore, the number and quality of points used for learning process is very important. The example sensor application for examination of liquid soap concentration in water is presented in the paper.

A proposal of ubiquitous fuzzy computing for ambient Intelligence

NARCIS (Netherlands)

Acampora, G.; Loia, V.

2008-01-01

Ambient Intelligence is considered as the composition of three emergent technologies: Ubiquitous Computing, Ubiquitous Communication and Intelligent User Interfaces. The aim of integration of aforesaid technologies is to make wider the interaction between human beings and information technology

Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

Science.gov (United States)

Niewoehner, Kevin R.; Carter, John (Technical Monitor)

2001-01-01

The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

Science.gov (United States)

Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

2017-02-01

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

Use of artificial intelligence in analytical systems for the clinical laboratory.

Science.gov (United States)

Place, J F; Truchaud, A; Ozawa, K; Pardue, H; Schnipelsky, P

1995-01-01

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

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

Science.gov (United States)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

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

Science.gov (United States)

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

Do narcissism and emotional intelligence win us friends? : modeling dynamics of peer popularity using inferential network analysis

OpenAIRE

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

2016-01-01

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...

Distributed neural system for emotional intelligence revealed by lesion mapping.

Science.gov (United States)

Barbey, Aron K; Colom, Roberto; Grafman, Jordan

2014-03-01

Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease.

Distributed neural system for emotional intelligence revealed by lesion mapping

Science.gov (United States)

Colom, Roberto; Grafman, Jordan

2014-01-01

Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease. PMID:23171618

Research and Development of a Network-Based Intelligent Maintenance Information System

Institute of Scientific and Technical Information of China (English)

ZANG Tie-gang; YANG Ming-zhong; GUO Shun-sheng

2003-01-01

A maintenance information system is an important part of equipment management. An intelli gent maintenance information system ( IMIS) is a synthesis of network technology, information technology and intelligent technology. The IMIS is used to finish flexible maintenance decision-making and fast maintenance planning, which helps enterprises to effectively reduce maintenance cost and increase working efficiency. Because the IMIS integrates advanced technologies, its performance is better than a traditional one.The difference between an IMIS and a traditional maintenance information system, and the functions, structure, important realizations, and application of an IMIS are discussed in this paper.

Computational intelligence in wireless sensor networks recent advances and future challenges

CERN Document Server

Falcon, Rafael; Koeppen, Mario

2017-01-01

This book emphasizes the increasingly important role that Computational Intelligence (CI) methods are playing in solving a myriad of entangled Wireless Sensor Networks (WSN) related problems. The book serves as a guide for surveying several state-of-the-art WSN scenarios in which CI approaches have been employed. The reader finds in this book how CI has contributed to solve a wide range of challenging problems, ranging from balancing the cost and accuracy of heterogeneous sensor deployments to recovering from real-time sensor failures to detecting attacks launched by malicious sensor nodes and enacting CI-based security schemes. Network managers, industry experts, academicians and practitioners alike (mostly in computer engineering, computer science or applied mathematics) benefit from the spectrum of successful applications reported in this book. Senior undergraduate or graduate students may discover in this book some problems well suited for their own research endeavors. USP: Presents recent advances and fu...

Advance in study of intelligent diagnostic method for nuclear power plant

International Nuclear Information System (INIS)

Zhou Gang; Yang Li

2008-01-01

The advance of research on the application of three types of intelligent diagnostic approach based on neural network (ANN), fuzzy logic and expert system to the operation status monitoring and fault diagnosis of nuclear power plant (NPP) was reviewed. The research status and characters on status monitoring and fault diagnosis approaches based on neural network, fuzzy logic and expert system for nuclear power plant were analyzed. The development trend of applied research on intelligent diagnostic approaches for nuclear power plant was explored. The analysis results show that the research achievements on intelligent diagnostic approaches based on fuzzy logic and expert system for nuclear power plant are not much relatively. The research of intelligent diagnostic approaches for nuclear power plant concentrate on the aspect of operation status monitoring and fault diagnosis based on neural networks for nuclear power plant. The advancing tendency of intelligent diagnostic approaches for nuclear power plant is the combination of various intelligent diagnostic approaches, the combination of neural network diagnostic approaches and other diagnostic approaches as well as multiple neural network diagnostic approaches. (authors)

Double network bacterial cellulose hydrogel to build a biology-device interface

Science.gov (United States)

Shi, Zhijun; Li, Ying; Chen, Xiuli; Han, Hongwei; Yang, Guang

2013-12-01

Establishing a biology-device interface might enable the interaction between microelectronics and biotechnology. In this study, electroactive hydrogels have been produced using bacterial cellulose (BC) and conducting polymer (CP) deposited on the BC hydrogel surface to cover the BC fibers. The structures of these composites thus have double networks, one of which is a layer of electroactive hydrogels combined with BC and CP. The electroconductivity provides the composites with capabilities for voltage and current response, and the BC hydrogel layer provides good biocompatibility, biodegradability, bioadhesion and mass transport properties. Such a system might allow selective biological functions such as molecular recognition and specific catalysis and also for probing the detailed genetic and molecular mechanisms of life. A BC-CP composite hydrogel could then lead to a biology-device interface. Cyclic voltammetry and electrochemical impedance spectroscopy (EIS) are used here to study the composite hydrogels' electroactive property. BC-PAni and BC-PPy respond to voltage changes. This provides a mechanism to amplify electrochemical signals for analysis or detection. BC hydrogels were found to be able to support the growth, spreading and migration of human normal skin fibroblasts without causing any cytotoxic effect on the cells in the cell culture. These double network BC-CP hydrogels are biphasic Janus hydrogels which integrate electroactivity with biocompatibility, and might provide a biology-device interface to produce implantable devices for personalized and regenerative medicine.

End-System Network Interface Controller for 100 Gb/s Wide Area Networks: Final Report

Energy Technology Data Exchange (ETDEWEB)

Wen, Jesse [Acadia Optronics LLC, Rockville, MD (United States)

2013-08-30

In recent years, network bandwidth requirements have scaled multiple folds, pushing the need for the development of data exchange mechanisms at 100 Gb/s and beyond. High performance computing, climate modeling, large-scale storage, and collaborative scientific research are examples of applications that can greatly benefit by leveraging high bandwidth capabilities of the order of 100 Gb/s. Such requirements and advances in IEEE Ethernet standards, Optical Transport Unit4 (OTU4), and host-system interconnects demand a network infrastructure supporting throughput rates of the order of 100 Gb/s with a single wavelength. To address such a demand Acadia Optronics in collaboration with the University of New Mexico, proposed and developed a end-system Network Interface Controller (NIC) for the 100Gbps WANs. Acadia’s 100G NIC employs an FPGA based system with a high-performance processor interconnect (PCIe 3.0) and a high capacity optical transmission link (CXP) to provide data transmission at the rate of 100 Gbps.

1st International Conference on Intelligent Communication, Control and Devices

CERN Document Server

Choudhury, Sushabhan

2017-01-01

The book presents high-quality research papers presented at the first international conference, ICICCD 2016, organised by the Department of Electronics, Instrumentation and Control Engineering of University of Petroleum and Energy Studies, Dehradun on 2nd and 3rd April, 2016. The book is broadly divided into three sections: Intelligent Communication, Intelligent Control and Intelligent Devices. The areas covered under these sections are wireless communication and radio technologies, optical communication, communication hardware evolution, machine-to-machine communication networks, routing techniques, network analytics, network applications and services, satellite and space communications, technologies for e-communication, wireless Ad-Hoc and sensor networks, communications and information security, signal processing for communications, communication software, microwave informatics, robotics and automation, optimization techniques and algorithms, intelligent transport, mechatronics system, guidance and navigat...

Cost/worth assessment of reliability improvement in distribution networks by means of artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Bouhouras, Aggelos S.; Labridis, Dimitris P.; Bakirtzis, Anastasios G. [Power Systems Laboratory, Aristotle University of Thessaloniki, Dept. of Electrical and Computer Engineering, 54124 Thessaloniki (Greece)

2010-06-15

A major challenge for the power utilities today is to ensure a high level of reliability of supply to customers. Two main factors determine the feasibility of a project that improves the reliability of supply: the project cost (investment and operational) and the benefits that result from the implementation of the project. This paper examines the implementation of an Artificial Intelligence System in an urban distribution network, capable to locate and isolate short circuit faults in the feeder, thus accomplishing immediate restoration of electric supply to the customers. The paper describes the benefits of the project, which are supply reliability improvement and distribution network loss reduction through network reconfigurations. By comparison of the project benefits and costs the economic feasibility of such a project for an underground distribution feeder in Greece is demonstrated. (author)

Communications interface for plant monitoring system

International Nuclear Information System (INIS)

Lee, K.L.; Morgan, F.A.

1988-01-01

This paper presents the communications interface for an intelligent color graphic system which PSE and G developed as part of a plant monitoring system. The intelligent graphic system is designed to off-load traditional host functions such as dynamic graphic updates, keyboard handling and alarm display. The distributed system's data and synchronization problems and their solutions are discussed

Reconfigurable intelligent sensors for health monitoring: a case study of pulse oximeter sensor.

Science.gov (United States)

Jovanov, E; Milenkovic, A; Basham, S; Clark, D; Kelley, D

2004-01-01

Design of low-cost, miniature, lightweight, ultra low-power, intelligent sensors capable of customization and seamless integration into a body area network for health monitoring applications presents one of the most challenging tasks for system designers. To answer this challenge we propose a reconfigurable intelligent sensor platform featuring a low-power microcontroller, a low-power programmable logic device, a communication interface, and a signal conditioning circuit. The proposed solution promises a cost-effective, flexible platform that allows easy customization, run-time reconfiguration, and energy-efficient computation and communication. The development of a common platform for multiple physical sensors and a repository of both software procedures and soft intellectual property cores for hardware acceleration will increase reuse and alleviate costs of transition to a new generation of sensors. As a case study, we present an implementation of a reconfigurable pulse oximeter sensor.

Combinatorial Nano-Bio Interfaces.

Science.gov (United States)

Cai, Pingqiang; Zhang, Xiaoqian; Wang, Ming; Wu, Yun-Long; Chen, Xiaodong

2018-06-08

Nano-bio interfaces are emerging from the convergence of engineered nanomaterials and biological entities. Despite rapid growth, clinical translation of biomedical nanomaterials is heavily compromised by the lack of comprehensive understanding of biophysicochemical interactions at nano-bio interfaces. In the past decade, a few investigations have adopted a combinatorial approach toward decoding nano-bio interfaces. Combinatorial nano-bio interfaces comprise the design of nanocombinatorial libraries and high-throughput bioevaluation. In this Perspective, we address challenges in combinatorial nano-bio interfaces and call for multiparametric nanocombinatorics (composition, morphology, mechanics, surface chemistry), multiscale bioevaluation (biomolecules, organelles, cells, tissues/organs), and the recruitment of computational modeling and artificial intelligence. Leveraging combinatorial nano-bio interfaces will shed light on precision nanomedicine and its potential applications.

Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

Science.gov (United States)

Wei, Yawei; Venayagamoorthy, Ganesh Kumar

2017-09-01

To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

A graphical user-interface control system at SRRC

International Nuclear Information System (INIS)

Chen, J.S.; Wang, C.J.; Chen, S.J.; Jan, G.J.

1993-01-01

A graphical user interface control system of 1.3 GeV synchrotron radiation light source was designed and implemented for the beam transport line (BTL) and storage ring (SR). A modern control technique has been used to implement and control the third generation synchrotron light source. Two level computer hardware configuration, that includes process and console computers as a top level and VME based intelligent local controller as a bottom level, was setup and tested. Both level computers are linked by high speed Ethernet data communication network. A database includes static and dynamic databases as well as access routines were developed. In order to commission and operate the machine friendly, the graphical man machine interface was designed and coded. The graphical user interface (GUI) software was installed on VAX workstations for the BTL and SR at the Synchrotron Radiation Research Center (SRRC). The over all performance has been evaluated at 10Hz update rate. The results showed that the graphical operator interface control system is versatile system and can be implemented into the control system of the accelerator. It will provide the tool to control and monitor the equipments of the radiation light source especially for machine commissioning and operation

Profiling nonhuman intelligence: An exercise in developing unbiased tools for describing other "types" of intelligence on earth

Science.gov (United States)

Herzing, Denise L.

2014-02-01

Intelligence has historically been studied by comparing nonhuman cognitive and language abilities with human abilities. Primate-like species, which show human-like anatomy and share evolutionary lineage, have been the most studied. However, when comparing animals of non-primate origins our abilities to profile the potential for intelligence remains inadequate. Historically our measures for nonhuman intelligence have included a variety of tools: (1) physical measurements - brain to body ratio, brain structure/convolution/neural density, presence of artifacts and physical tools, (2) observational and sensory measurements - sensory signals, complexity of signals, cross-modal abilities, social complexity, (3) data mining - information theory, signal/noise, pattern recognition, (4) experimentation - memory, cognition, language comprehension/use, theory of mind, (5) direct interfaces - one way and two way interfaces with primates, dolphins, birds and (6) accidental interactions - human/animal symbiosis, cross-species enculturation. Because humans tend to focus on "human-like" attributes and measures and scientists are often unwilling to consider other "types" of intelligence that may not be human equated, our abilities to profile "types" of intelligence that differ on a variety of scales is weak. Just as biologists stretch their definitions of life to look at extremophiles in unusual conditions, so must we stretch our descriptions of types of minds and begin profiling, rather than equating, other life forms we may encounter.

An intelligent medical system for diagnosis of bone diseases

Energy Technology Data Exchange (ETDEWEB)

Hatzilygeroudis, I [University of Patras, School of Engineering, Department of Computer Engineering and Informatics, 26500 Patras, Greece (Greece); Vassilakos, P J [Regional University Hospital of Patras, Department of Nuclear Medicine, Patras Greece (Greece); Tsakalidis, A [Computer Technology Institute, P.O. Box 1122, 26110 Patras, Greece (Greece)

1994-12-31

In this paper, aspects of the design of an intelligent medical system for diagnosis of bone diseases that can be detected by scintigraphic images are presented. The system comprises three major parts: a user interface (UI), a database management system (DBMS), and an expert system (ES). The DBMS is used for manipulation of various patient data. A number of patient cases are selected as prototype and stored in separate database. Diagnosis is performed via the ES, called XBONE, based on patient data. Knowledge is represented via an integrated formalism that combines production rules and a neural network. This results in better representation, and facilitates knowledge acquisition and maintenance. (authors). 10 refs., 2 figs.

Modelling intelligent behavior

Science.gov (United States)

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.

HIGH: A Hexagon-based Intelligent Grouping Approach in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

FAN, C.-S.

2016-02-01

Full Text Available In a random deployment or uniform deployment strategy, sensor nodes are scattered randomly or uniformly in the sensing field, respectively. Hence, the coverage ratio cannot be guaranteed. The coverage ratio of uniform deployment, in general, is larger than that of the random deployment strategy. However, a random deployment or uniform deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs. Therefore, cluster heads (CHs around the sink have larger loads than those farther away from the sink. That is, CHs close to the sink exhaust their energy earlier. In order to overcome the above problem, we propose a Hexagon-based Intelligent Grouping approacH in WSNs (called HIGH. The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed HIGH scheme. The simulation results validate our theoretical analysis and show that the proposed HIGH scheme achieves a satisfactory coverage ratio, balances the energy consumption among sensor nodes, and extends network lifetime significantly.

Computational Intelligence in Intelligent Data Analysis

CERN Document Server

Nürnberger, Andreas

2013-01-01

Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

System for intelligent teleoperation research

International Nuclear Information System (INIS)

Orlando, N.E.

1983-01-01

The Automation Technology Branch of NASA Langley Research Center is developing a research capability in the field of artificial intelligence, particularly as applicable in teleoperator/robotics development for remote space operations. As a testbed for experimentation in these areas, a system concept has been developed and is being implemented. This system, termed DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), interfaces the key processes of perception, reasoning, and manipulation by linking hardware sensors and manipulators to a modular artificial intelligence (AI) software system in a hierarchical control structure. Verification experiments have been performed: one experiment used a blocksworld database and planner embedded in the DAISIE system to intelligently manipulate a simple physical environment; the other experiment implemented a joint-space collision avoidance algorithm. Continued system development is planned

Bayesian artificial intelligence

CERN Document Server

Korb, Kevin B

2010-01-01

Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente

A network-based Macintosh serial host interface program

International Nuclear Information System (INIS)

Wight, J.

1991-03-01

A program has been written for the Apple Macintosh to replace conventional host RS232 terminals with customizable user interfaces. Serial port NuBus cards in the Macintosh allow many simultaneous sessions to be maintained. A powerful system is attained by connecting multiple Macintoshes on a network, each running this program. Each is then able to share incoming data from any of its serial ports with any other Macintosh, as well as accept data from any other Macintosh for output to any of its serial ports. The program has been used to eliminate multiple host terminals, modernize the user interface, and to centralize operation of a complex control system. Minimal changes to host software have been required. By making extensive use of Macintosh resources, the same executable code serves in a variety of roles. An object oriented C language with a class library made the development straightforward and easy to modify. This program is used to control a 2 MW neutral beam system on the DIII-D magnetic fusion tokamak. 7 figs

Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks

Directory of Open Access Journals (Sweden)

Ramanpreet Kaur

2017-02-01

Full Text Available Intelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many factors such as underlying user’s online behavior, geographical position, time of the day, day of the week etc. as reported in many applications. We can exploit these characteristics for efficient maintenance of structured overlay networks by implementing an intelligent predictive framework for setting stabilization parameters appropriately. Considering the fact that human driven behavior usually goes beyond intermittent availability patterns, we use a hybrid Neuro-fuzzy based predictor to enhance the accuracy of the predictions. In this paper, we discuss our predictive stabilization approach, implement Neuro-fuzzy based prediction in MATLAB simulation and apply this predictive stabilization model in a chord based overlay network using OverSim as a simulation tool. The MATLAB simulation results present that the behavior of neighboring nodes is predictable to a large extent as indicated by the very small RMSE. The OverSim based simulation results also observe significant improvements in the performance of chord based overlay network in terms of lookup success ratio, lookup hop count and maintenance overhead as compared to periodic stabilization approach.

An Interfacing System for Radiation Surveillance Using a Radio Communication Network

International Nuclear Information System (INIS)

Arunsiri, T.; Punnachaiya, S.; Pattarasumun, A.

1998-01-01

The development of an interfacing system for environmental radiation surveillance using radio communication network is aimed to improve a way by which environmental radiation measurement is transmitted and reported from the regional area monitoring station network. This also includes an automatic warning of beacon status via the radio link network to the center of environmental radiation control when an abnormal radiation level is detected. The interfacing system was developed by simulating the EGAT radio link network, the NT 2612, and can be separated into two parts. The first part was for a mobile station which can manage the output data from the radiation measurement system in the standard form of RS-232, IEEE-488, BCD and analog signal. This was accomplished by modulating the signal in selected baud rates ranging from 150 to 9600 bps using an economical radio packet capable of identifying and recalling the station code number. The other part is the linking system between the output data and the microcomputer equipped with a software to manage and evaluate the data from 10 surveillance stations for convenient handing of data output, statistical analysis and transmitting warning signal. Data transmission was tested using a baud rate of 1200 bps and was found to contain no detectable error when digital signal was transmitted while analog signal transmission resulted in deviations of less than ± 0.003%. The development of this radio link system provides a future trend for the environmental radiation monitoring network for countries with nuclear power plants or neighboring countries needed to continuously monitor for any abnormal radiation level in the environment. In case that the radiation surveillance system detects a high level of radiation, a warning signal will be transmitted and appropriate actions may be immediately exercised to control impacts of radiation on environment and living things according to international guidelines

Intelligent PV Power Smoothing Control Using Probabilistic Fuzzy Neural Network with Asymmetric Membership Function

Directory of Open Access Journals (Sweden)

Faa-Jeng Lin

2017-01-01

Full Text Available An intelligent PV power smoothing control using probabilistic fuzzy neural network with asymmetric membership function (PFNN-AMF is proposed in this study. First, a photovoltaic (PV power plant with a battery energy storage system (BESS is introduced. The BESS consisted of a bidirectional DC/AC 3-phase inverter and LiFePO4 batteries. Then, the difference of the actual PV power and smoothed power is supplied by the BESS. Moreover, the network structure of the PFNN-AMF and its online learning algorithms are described in detail. Furthermore, the three-phase output currents of the PV power plant are converted to the dq-axis current components. The resulted q-axis current is the input of the PFNN-AMF power smoothing control, and the output is a smoothing PV power curve to achieve the effect of PV power smoothing. Comparing to the other smoothing methods, a minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the PV power smoothing control using PFNN-AMF. In addition, a personal computer- (PC- based PV power plant emulator and BESS are built for the experimentation. From the experimental results of various irradiance variation conditions, the effectiveness of the proposed intelligent PV power smoothing control can be verified.

Intelligent community management system based on the devicenet fieldbus

Science.gov (United States)

Wang, Yulan; Wang, Jianxiong; Liu, Jiwen

2013-03-01

With the rapid development of the national economy and the improvement of people's living standards, people are making higher demands on the living environment. And the estate management content, management efficiency and service quality have been higher required. This paper in-depth analyzes about the intelligent community of the structure and composition. According to the users' requirements and related specifications, it achieves the district management systems, which includes Basic Information Management: the management level of housing, household information management, administrator-level management, password management, etc. Service Management: standard property costs, property charges collecting, the history of arrears and other property expenses. Security Management: household gas, water, electricity and security and other security management, security management district and other public places. Systems Management: backup database, restore database, log management. This article also carries out on the Intelligent Community System analysis, proposes an architecture which is based on B / S technology system. And it has achieved a global network device management with friendly, easy to use, unified human - machine interface.

SME Internationalization Intelligence Information and Knowledge on International Opportunities

Directory of Open Access Journals (Sweden)

Zizah Che Senik

2014-12-01

Full Text Available Small and medium enterprises (SMEs internationalization intelligence, referring to the process of gathering information and knowledge on international opportunities, is crucial to initiate SMEs’ internationalization. The literature has stressed organizational resources, networks and information sharing as means to acquire internationalization intelligence, suggesting that the resource-based, network and social capital perspectives can be adopted to explore this issue. However, previous literature still lacks evidence on how SMEs acquire relevant intelligence, and who or what are involved with the process. To address this lack of evidence, we interviewed 54 SME owners/key personnel in the manufacturing sector to: identify sources of internationalization intelligence; examine how those sources assist SMEs to internationalize; and develop propositions on internationalization intelligence. Analyzing the data using NVivo, four themes emerged including institutions, business associates, personal efforts, and other means. The analysis suggests internationalization intelligence occurs mainly through the networks of the SME owners/key personnel, built on their firm’s resources through their internal and external information sharing activities, indicating the need of the SMEs to position themselves in their environments. These findings are developed into propositions. The study indicates multiple perspectives in conceptualizing the process of internationalization intelligence. This study advances a conceptualization of internationalization intelligence, and offers avenues for future research.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

An intelligent nuclear reactor core controller for load following operations, using recurrent neural networks and fuzzy systems

International Nuclear Information System (INIS)

Boroushaki, M.; Ghofrani, M.B.; Lucas, C.; Yazdanpanah, M.J.

2003-01-01

In the last decade, the intelligent control community has paid great attention to the topic of intelligent control systems for nuclear plants (core, steam generator...). Papers mostly used approximate and simple mathematical SISO (single-input-single-output) model of nuclear plants for testing and/or tuning of the control systems. They also tried to generalize theses models to a real MIMO (multi-input-multi-output) plant, while nuclear plants are typically of complex nonlinear and multivariable nature with high interactions between their state variables and therefore, many of these proposed intelligent control systems are not appropriate for real cases. In this paper, we designed an on-line intelligent core controller for load following operations, based on a heuristic control algorithm, using a valid and updatable recurrent neural network (RNN). We have used an accurate 3-dimensional core calculation code to represent the real plant and to train the RNN. The results of simulation show that this intelligent controller can control the reactor core during load following operations, using optimum control rod groups manoeuvre and variable overlapping strategy. This methodology represents a simple and reliable procedure for controlling other complex nonlinear MIMO plants, and may improve the responses, comparing to other control systems

Intelligent Networks Data Fusion Web-based Services for Ad-hoc Integrated WSNs-RFID

Directory of Open Access Journals (Sweden)

Falah Alshahrany

2016-01-01

Full Text Available The use of variety of data fusion tools and techniques for big data processing poses the problem of the data and information integration called data fusion having objectives which can differ from one application to another. The design of network data fusion systems aimed at meeting these objectives, need to take into account of the necessary synergy that can result from distributed data processing within the data networks and data centres, involving increased computation and communication. This papers reports on how this processing distribution is functionally structured as configurable integrated web-based support services, in the context of an ad-hoc wireless sensor network used for sensing and tracking, in the context of distributed detection based on complete observations to support real rime decision making. The interrelated functional and hardware RFID-WSN integration is an essential aspect of the data fusion framework that focuses on multi-sensor collaboration as an innovative approach to extend the heterogeneity of the devices and sensor nodes of ad-hoc networks generating a huge amount of heterogeneous soft and hard raw data. The deployment and configuration of these networks require data fusion processing that includes network and service management and enhances the performance and reliability of networks data fusion support systems providing intelligent capabilities for real-time control access and fire detection.

Smart thermal networks for smart cities – Introduction of concepts and measures

Directory of Open Access Journals (Sweden)

Basciotti D.

2012-10-01

Full Text Available In order to contribute to high living standards, climate mitigation and energy supply security, future urban energy systems require a holistic approach. In particular an intelligent integration of thermal networks is necessary. This paper will briefly present the “smart city” concept and introduce an associated definition for smart thermal networks defined on three levels: 1. the interaction with urban planning processes and the interface to the overall urban energy system, 2. the adaptation of the temperature level and 3. supply and demand-side management strategies.

Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

Science.gov (United States)

Piao, Chunhui; Han, Xufang; Wu, Harris

2010-08-01

We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.

2015 Chinese Intelligent Automation Conference

CERN Document Server

Li, Hongbo

2015-01-01

Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.

Field Trial of 40 Gb/s Optical Transport Network using Open WDM Interfaces

DEFF Research Database (Denmark)

Fagertun, Anna Manolova; Ruepp, Sarah Renée; Petersen, Martin Nordal

2013-01-01

An experimental field-trail deployment of a 40Gb/s open WDM interface in an operational network is presented, in cross-carrier interconnection scenario. Practical challenges of integration and performance measures for both native and alien channels are outlined....

Employing the intelligence cycle process model within the Homeland Security Enterprise

OpenAIRE

Stokes, Roger L.

2013-01-01

CHDS State/Local The purpose of this thesis was to examine the employment and adherence of the intelligence cycle process model within the National Network of Fusion Centers and the greater Homeland Security Enterprise by exploring the customary intelligence cycle process model established by the United States Intelligence Community (USIC). This thesis revealed there are various intelligence cycle process models used by the USIC and taught to the National Network. Given the numerous differ...

Target-Centric Network Modeling

DEFF Research Database (Denmark)

Mitchell, Dr. William L.; Clark, Dr. Robert M.

In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...

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

Science.gov (United States)

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.

Distributed intelligent sensor network for the rehabilitation of Parkinson's patients.

Science.gov (United States)

Ying, Hong; Schlösser, Mario; Schnitzer, Andreas; Schäfer, Thorsten; Schläfke, Marianne E; Leonhardt, Steffen; Schiek, Michael

2011-03-01

The coordination between locomotion and respiration of Parkinson's disease (PD) patients is reduced or even absent. The degree of this disturbance is assumed to be associated with the disease severity [S. Schiermeier, D. Schäfer, T. Schäfer, W. Greulich, and M. E. Schläfke, "Breathing and locomotion in patients with Parkinson's disease," Eur. J. Physiol., vol. 443, No. 1, pp. 67-71, Jul. 2001]. To enable a long-term and online analysis of the locomotion-respiration coordination for scientific purpose, we have developed a distributed wireless communicating network. We aim to integrate biofeedback protocols with the real-time analysis of the locomotion-respiration coordination in the system to aid rehabilitation of PD patients. The network of sensor nodes is composed of intelligent network operating devices (iNODEs). The miniaturized iNODE contains a continuous data acquisition system based on microcontroller, local data storage, capability of on-sensor digital signal processing in real time, and wireless communication based on IEEE 802.15.4. Force sensing resistors and respiratory inductive plethysmography are applied for motion and respiration sensing, respectively. A number of experiments have been undertaken in clinic and laboratory to test the system. It shall facilitate identification of therapeutic effects on PD, allowing to measure the patients' health status, and to aid in the rehabilitation of PD patients.

Artificial intelligence and engineering curricula - are changes needed?

International Nuclear Information System (INIS)

Jenkins, J.P.

1988-01-01

The purpose of this paper is to identify the expected impact of artificial intelligence (AI) on curricula and training courses. From this examination, new elements are proposed for the academic preparation and training of engineers who will evaluate and use these systems and capabilities. Artificial intelligence, from an operational viewpoint, begins with a set of rules governing the operation of logic, implemented via computer software and userware. These systems apply logic and experience to handling problems in an intelligent approach, especially when the number of alternatives to problem solution is beyond the scope of the human user. Usually, AI applications take the form of expert systems. An expert system embodies in the computer the knowledge-based component of an expert, such as domain knowledge and reasoning techniques, in such a form that the system can offer intelligent advice and, on demand, justify its own line of reasoning. Two languages predominate, LISP and Prolog. The AI user may interface with the knowledge base via one of these languages or by means of menu displays, cursor selections, or other conventional user interface methods

1st International Conference on Intelligent Computing, Communication and Devices

CERN Document Server

Patnaik, Srikanta; Ichalkaranje, Nikhil

2015-01-01

In the history of mankind, three revolutions which impact the human life are the tool-making revolution, agricultural revolution and industrial revolution. They have transformed not only the economy and civilization but the overall development of the society. Probably, intelligence revolution is the next revolution, which the society will perceive in the next 10 years. ICCD-2014 covers all dimensions of intelligent sciences, i.e. Intelligent Computing, Intelligent Communication and Intelligent Devices. This volume covers contributions from Intelligent Communication which are from the areas such as Communications and Wireless Ad Hoc & Sensor Networks, Speech & Natural Language Processing, including Signal, Image and Video Processing and Mobile broadband and Optical networks, which are the key to the ground-breaking inventions to intelligent communication technologies. Secondly, Intelligent Device is any type of equipment, instrument, or machine that has its own computing capability. Contributions from ...

The new competitive intelligence agents: "Programming" competitive intelligence ethics into corporate cultures

OpenAIRE

Betsy Van der Veer Martens; Emilie Steele Giustozzi

2011-01-01

This article examines some of the ethical issues involved in competitive intelligence activities on the Internet. We discuss the importance of an ethical framework for the performance of competitive intelligence, especially the Code of Ethics of SCIP (the leading professional association for strategic and competitive professionals), in the context of today's networked global environment. The virtual borderlines separating national economic and military territories online are becoming increasi...

Some Steps towards Intelligent Computer Tutoring Systems.

Science.gov (United States)

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)

NEPHRUS: model of intelligent multilayers expert system for evaluation of the renal system based on scintigraphic images analysis

International Nuclear Information System (INIS)

Silva, Jose W.E. da; Schirru, Roberto; Boasquevisque, Edson M.

1997-01-01

This work develops a prototype for the system model based on Artificial Intelligence devices able to perform functions related to scintigraphic image analysis of the urinary system. Criteria used by medical experts for analysis images obtained with 99m Tc+DTPA and/or 99m Tc+DMSA were modeled and a multi resolution diagnosis technique was implemented. Special attention was given to the programs user interface design. Human Factor Engineering techniques were considered so as to ally friendliness and robustness. Results obtained using Artificial Neural Networks for the qualitative image analysis and the knowledge model constructed shows the feasibility of Artificial Intelligence implementation that use 'inherent' abilities of each technique in the resolution of diagnosis image analysis problems. (author). 12 refs., 2 figs., 2 tabs

Where value lives in a networked world.

Science.gov (United States)

Sawhney, M; Parikh, D

2001-01-01

While many management thinkers proclaim an era of radical uncertainty, authors Sawhney and Parikh assert that the seemingly endless upheavals of the digital age are more predictable than that: today's changes have a common root, and that root lies in the nature of intelligence in networks. Understanding the patterns of intelligence migration can help companies decipher and plan for the inevitable disruptions in today's business environment. Two patterns in network intelligence are reshaping industries and organizations. First, intelligence is decoupling--that is, modern high-speed networks are pushing back-end intelligence and front-end intelligence toward opposite ends of the network, making the ends the two major sources of potential profits. Second, intelligence is becoming more fluid and modular. Small units of intelligence now float freely like molecules in the ether, coalescing into temporary bundles whenever and wherever necessary to solve problems. The authors present four strategies that companies can use to profit from these patterns: arbitrage allows companies to move intelligence to new regions or countries where the cost of maintaining intelligence is lower; aggregation combines formerly isolated pieces of infrastructure intelligence into a large pool of shared infrastructure provided over a network; rewiring allows companies to connect islands of intelligence by creating common information backbones; and reassembly allows businesses to reorganize pieces of intelligence into coherent, personalized packages for customers. By being aware of patterns in network intelligence and by acting rather than reacting, companies can turn chaos into opportunity, say the authors.

Planning pesticides usage for herbal and animal pests based on intelligent classification system with image processing and neural networks

Directory of Open Access Journals (Sweden)

Dimililer Kamil

2018-01-01

Full Text Available Pests are divided into two as herbal and animal pests in agriculture, and detection and use of minimum pesticides are quite challenging task. Last three decades, researchers have been improving their studies on these manners. Therefore, effective, efficient, and as well as intelligent systems are designed and modelled. In this paper, an intelligent classification system is designed for detecting pests as herbal or animal to use of proper pesticides accordingly. The designed system suggests two main stages. Firstly, images are processed using different image processing techniques that images have specific distinguishing geometric patterns. The second stage is neural network phase for classification. A backpropagation neural network is used for training and testing with processed images. System is tested, and experiment results show efficiency and effective classification rate. Autonomy and time efficiency within the pesticide usage are also discussed.

Location Prediction-Based Data Dissemination Using Swarm Intelligence in Opportunistic Cognitive Networks

Directory of Open Access Journals (Sweden)

Jie Li

2014-01-01

Full Text Available Swarm intelligence is widely used in the application of communication networks. In this paper we adopt a biologically inspired strategy to investigate the data dissemination problem in the opportunistic cognitive networks (OCNs. We model the system as a centralized and distributed hybrid system including a location prediction server and a pervasive environment deploying the large-scale human-centric devices. To exploit such environment, data gathering and dissemination are fundamentally based on the contact opportunities. To tackle the lack of contemporaneous end-to-end connectivity in opportunistic networks, we apply ant colony optimization as a cognitive heuristic technology to formulate a self-adaptive dissemination-based routing scheme in opportunistic cognitive networks. This routing strategy has attempted to find the most appropriate nodes conveying messages to the destination node based on the location prediction information and intimacy between nodes, which uses the online unsupervised learning on geographical locations and the biologically inspired algorithm on the relationship of nodes to estimate the delivery probability. Extensive simulation is carried out on the real-world traces to evaluate the accuracy of the location prediction and the proposed scheme in terms of transmission cost, delivery ratio, average hops, and delivery latency, which achieves better routing performances compared to the typical routing schemes in OCNs.

Natural language interface for nuclear data bases

International Nuclear Information System (INIS)

Heger, A.S.; Koen, B.V.

1987-01-01

A natural language interface has been developed for access to information from a data base, simulating a nuclear plant reliability data system (NPRDS), one of the several existing data bases serving the nuclear industry. In the last decade, the importance of information has been demonstrated by the impressive diffusion of data base management systems. The present methods that are employed to access data bases fall into two main categories of menu-driven systems and use of data base manipulation languages. Both of these methods are currently used by NPRDS. These methods have proven to be tedious, however, and require extensive training by the user for effective utilization of the data base. Artificial intelligence techniques have been used in the development of several intelligent front ends for data bases in nonnuclear domains. Lunar is a natural language program for interface to a data base describing moon rock samples brought back by Apollo. Intellect is one of the first data base question-answering systems that was commercially available in the financial area. Ladder is an intelligent data base interface that was developed as a management aid to Navy decision makers. A natural language interface for nuclear data bases that can be used by nonprogrammers with little or no training provides a means for achieving this goal for this industry

Intelligent systems

CERN Document Server

Irwin, J David

2011-01-01

Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

An Effective Wormhole Attack Defence Method for a Smart Meter Mesh Network in an Intelligent Power Grid

Directory of Open Access Journals (Sweden)

Jungtaek Seo

2012-08-01

Full Text Available Smart meters are one of the key components of intelligent power grids. Wireless mesh networks based on smart meters could provide customer-oriented information on electricity use to the operational control systems, which monitor power grid status and estimate electric power demand. Using this information, an operational control system could regulate devices within the smart grid in order to provide electricity in a cost-efficient manner. Ensuring the availability of the smart meter mesh network is therefore a critical factor in securing the soundness of an intelligent power system. Wormhole attacks can be one of the most difficult-to-address threats to the availability of mesh networks, and although many methods to nullify wormhole attacks have been tried, these have been limited by high computational resource requirements and unnecessary overhead, as well as by the lack of ability of such methods to respond to attacks. In this paper, an effective defense mechanism that both detects and responds to wormhole attacks is proposed. In the proposed system, each device maintains information on its neighbors, allowing each node to identify replayed packets. The effectiveness and efficiency of the proposed method is analyzed in light of additional computational message and memory complexities.

Using FML and fuzzy technology in adaptive ambient intelligent environments

NARCIS (Netherlands)

Acampora, G.; Loia, V.

2005-01-01

Ambient Intelligence (AmI, shortly) gathers best re-sults from three key technologies, Ubiquitous Computing, Ubiq-uitous Communication, and Intelligent User Friendly Inter-faces. The functional and spatial distribution of tasks is a natu-ral thrust to employ multi-agent paradigm to design and

A control strategy for DC-link voltage control containing PV generation and energy storage — An intelligent approach

OpenAIRE

Rouzbehi, Kumars; Miranian, Arash; Candela García, José Ignacio; Luna Alloza, Álvaro; Rodríguez Cortés, Pedro

2014-01-01

In this paper, DC-link voltage control in DC microgrids with photovoltaic (PV) generation and battery, is addressed based on an intelligent approach. The proposed strategy is based on the modeling of the power interface, i.e. power electronic converter, located between the PV array, battery and DC bus, by use of measurement data. For this purpose, a local model network (LMN) is developed to model the converter and then a local linear control (LLC) strategy is designed based on the LMN. Simula...

Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches

Directory of Open Access Journals (Sweden)

Hanning Chen

2014-01-01

Full Text Available The development of radio frequency identification (RFID technology generates the most challenging RFID network planning (RNP problem, which needs to be solved in order to operate the large-scale RFID network in an optimal fashion. RNP involves many objectives and constraints and has been proven to be a NP-hard multi-objective problem. The application of evolutionary algorithm (EA and swarm intelligence (SI for solving multiobjective RNP (MORNP has gained significant attention in the literature, but these algorithms always transform multiple objectives into a single objective by weighted coefficient approach. In this paper, we use multiobjective EA and SI algorithms to find all the Pareto optimal solutions and to achieve the optimal planning solutions by simultaneously optimizing four conflicting objectives in MORNP, instead of transforming multiobjective functions into a single objective function. The experiment presents an exhaustive comparison of three successful multiobjective EA and SI, namely, the recently developed multiobjective artificial bee colony algorithm (MOABC, the nondominated sorting genetic algorithm II (NSGA-II, and the multiobjective particle swarm optimization (MOPSO, on MORNP instances of different nature, namely, the two-objective and three-objective MORNP. Simulation results show that MOABC proves to be more superior for planning RFID networks than NSGA-II and MOPSO in terms of optimization accuracy and computation robustness.

Building an intelligence-led security program

CERN Document Server

Liska, Allan

2014-01-01

As recently as five years ago, securing a network meant putting in a firewall, intrusion detection system, and installing antivirus software on the desktop. Unfortunately, attackers have grown more nimble and effective, meaning that traditional security programs are no longer effective. Today's effective cyber security programs take these best practices and overlay them with intelligence. Adding cyber threat intelligence can help security teams uncover events not detected by traditional security platforms and correlate seemingly disparate events across the network. Properly-implemented inte

Data transfer based on intelligent ethernet card

International Nuclear Information System (INIS)

Zhu Haitao; Chinese Academy of Sciences, Beijing; Chu Yuanping; Zhao Jingwei

2007-01-01

Intelligent Ethernet Cards are widely used in systems where the network throughout is very large, such as the DAQ systems for modern high energy physics experiments, web service. With the example of a commercial intelligent Ethernet card, this paper introduces the architecture, the principle and the process of intelligent Ethernet cards. In addition, the results of several experiments showing the differences between intelligent Ethernet cards and general ones are also presented. (authors)

Artificial Intelligence in Astronomy

Science.gov (United States)

Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

2010-12-01

From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

Training Software in Artificial-Intelligence Computing Techniques

Science.gov (United States)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Intelligent engineering and technology for nuclear power plant operation

International Nuclear Information System (INIS)

Wang, P.P.; Gu, X.

1996-01-01

The Three-Mile-Island accident has drawn considerable attention by the engineering, scientific, management, financial, and political communities as well as society at large. This paper surveys possible causes of the accident studied by various groups. Research continues in this area with many projects aimed at specifically improving the performance and operation of a nuclear power plant using the contemporary technologies available. In addition to the known cause of the accident and suggest a strategy for coping with these problems in the future. With the increased use of intelligent methodologies called computational intelligence or soft-computing, a substantially larger collection of powerful tools are now available for our designers to use in order to tackle these sensitive and difficult issues. These intelligent methodologies consists of fuzzy logic, genetic algorithms, neural networks, artificial intelligence and expert systems, pattern recognition, machine intelligence, and fuzzy constraint networks. Using the Three-Mile-Island experience, this paper offers a set of specific recommendations for future designers to take advantage of the powerful tools of intelligent technologies that we are now able to master and encourages the adoption of a novel methodology called fuzzy constraint network

A Fuzzy Preprocessing Module for Optimizing the Access Network Selection in Wireless Networks

Directory of Open Access Journals (Sweden)

Faisal Kaleem

2013-01-01

Full Text Available A heterogeneous wireless network is characterized by the presence of different wireless access technologies that coexist in an overlay fashion. These wireless access technologies usually differ in terms of their operating parameters. On the other hand, Mobile Stations (MSs in a heterogeneous wireless network are equipped with multiple interfaces to access different types of services from these wireless access technologies. The ultimate goal of these heterogeneous wireless networks is to provide global connectivity with efficient ubiquitous computing to these MSs based on the Always Best Connected (ABC principle. This is where the need for intelligent and efficient Vertical Handoffs (VHOs between wireless technologies in a heterogeneous environment becomes apparent. This paper presents the design and implementation of a fuzzy multicriteria based Vertical Handoff Necessity Estimation (VHONE scheme that determines the proper time for VHO, while considering the continuity and quality of the currently utilized service, and the end-users' satisfaction.

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

Directory of Open Access Journals (Sweden)

David Herrero

2011-11-01

Full Text Available 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.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Directory of Open Access Journals (Sweden)

Yipeng Yu

Full Text Available Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs. They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg has great potential in various applications, such as search and rescue in complex terrains.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Science.gov (United States)

Yu, Yipeng; Pan, Gang; Gong, Yongyue; Xu, Kedi; Zheng, Nenggan; Hua, Weidong; Zheng, Xiaoxiang; Wu, Zhaohui

2016-01-01

Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs). They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg) has great potential in various applications, such as search and rescue in complex terrains.

Intelligent Smoke Alarm System with Wireless Sensor Network Using ZigBee

Directory of Open Access Journals (Sweden)

Qin Wu

2018-01-01

Full Text Available The conflagration of fire is still a serious problem caused by humans, and houses are at a high risk of fire. Recently, people have used smoke alarms which only have one sensor to detect fire. Smoke is emitted in several forms in daily life. A single sensor is not a reliable way to detect fire. With the rapid advancement in Internet technology, people can monitor their houses remotely to determine the current condition of the house. This paper introduces an intelligent smoke alarm system that uses ZigBee transmission technology to build a wireless network, uses random forest to identify smoke, and uses E-charts for data visualization. By combining the real-time dynamic changes of various environmental factors, compared to the traditional smoke alarm, the accuracy and controllability of the fire warning are increased, and the visualization of the data enables users to monitor the room environment more intuitively. The proposed system consists of a smoke detection module, a wireless communication module, and intelligent identification and data visualization module. At present, the collected environmental data can be classified into four statuses, that is, normal air, water mist, kitchen cooking, and fire smoke. Reducing the frequency of miscalculations also means improving the safety of the person and property of the user.

Adding intelligence to scientific data management

Science.gov (United States)

Campbell, William J.; Short, Nicholas M., Jr.; Treinish, Lloyd A.

1989-01-01

NASA plans to solve some of the problems of handling large-scale scientific data bases by turning to artificial intelligence (AI) are discussed. The growth of the information glut and the ways that AI can help alleviate the resulting problems are reviewed. The employment of the Intelligent User Interface prototype, where the user will generate his own natural language query with the assistance of the system, is examined. Spatial data management, scientific data visualization, and data fusion are discussed.

Designing an information search interface for younger and older adults.

Science.gov (United States)

Pak, Richard; Price, Margaux M

2008-08-01

The present study examined Web-based information retrieval as a function of age for two information organization schemes: hierarchical organization and one organized around tags or keywords. Older adults' performance in information retrieval tasks has traditionally been lower compared with younger adults'. The current study examined the degree to which information organization moderated age-related performance differences on an information retrieval task. The theory of fluid and crystallized intelligence may provide insight into different kinds of information architectures that may reduce age-related differences in computer-based information retrieval performance. Fifty younger (18-23 years of age) and 50 older (55-76 years of age) participants browsed a Web site for answers to specific questions. Half of the participants browsed the hierarchically organized system (taxonomy), which maintained a one-to-one relationship between menu link and page, whereas the other half browsed the tag-based interface, with a many-to-one relationship between menu and page. This difference was expected to interact with age-related differences in fluid and crystallized intelligence. Age-related differences in information retrieval performance persisted; however, a tag-based retrieval interface reduced age-related differences, as compared with a taxonomical interface. Cognitive aging theory can lead to interface interventions that reduce age-related differences in performance with technology. In an information retrieval paradigm, older adults may be able to leverage their increased crystallized intelligence to offset fluid intelligence declines in a computer-based information search task. More research is necessary, but the results suggest that information retrieval interfaces organized around keywords may reduce age-related differences in performance.

PENINGKATAN KUALITAS JARINGAN KOMUNIKASI SEKTOR INDUSTRI DENGAN INTELLIGENT NETWORK SEBAGAI UPAYA PERLUASAN DAERAH PEMASARAN

Directory of Open Access Journals (Sweden)

Haryanto Haryanto

2005-08-01

Full Text Available Satu hal yang paling penting dalam upaya peningkatan profit adalah dengan penambahan dan perluasan daerah pemasaran, serta adanya sistem informasi yang terpadu dari pusat ke tiap unit yang dimiliki. Perluasan daerah pemasaran dapat diwujudkan dengan adanya sistem telekomunikasi yang lancar dan dapat menjangkau di tiap daerah yang akan dijadikan sebagai daerah pemasaran. Sehingga hal ini diharapkan tidak akan menghambat proses pendistribusian produk maupun informasi dari tiap daerah tujuan. Intelligent Network (Jaringan Cerdas adalah suatu arsitektur jaringan telekomunikasi yang memiliki tujuan untuk memberikan framework sehingga kerja dari jaringan untuk implementasi, kontrol, dan management menjadi lebih efektif serta lebih ekonomis, dan lebih cepat proses kerjanya dibandingkan arsitektur jaringan yang digunakan saat ini. Untuk meningkatkan kualitas jaringan komunikasi memerlukan infrastruktur yang memadai. Tidak luput dari standar mengenai spesifikasi yang menyangkut mobile system yang akan digunakan. Sehingga perkembangan suatu teknologi akan dapat berefek terjangkaunya komunikasi di daerah-daerah yang terisolasi, sehingga meningkatkan perkembangan daerah tersebut, bahkan tidak menutup kemungkinan dengan adanya peningkatan jaringan komunikasi di daerah maka akan memunculkan daerah-daerah sentra produksi di bidang industri. Peningkatan mobilitas komponen usaha yang tidak diperkirakan sebelumnya, semakin menuntut kemampuan sistem jaringan komunikasi dan data, serta pengembangan jenis-jenis pelanggan baru. Dengan adanya peranan Intelligent Network sebagai konsep arsitektur jaringan, maka akan mendapatkan solusi yang lebih baik untuk memenuhi segala kebutuhan.

Research and implementation of intelligent gateway driver layer based on Linux bus

Directory of Open Access Journals (Sweden)

ZHANG Jian

2016-10-01

Full Text Available Currently,in the field of smart home,there is no relevant organization that yet has proposed an unified protocol standard.It increases the complexity and limitations of heterogeneous gateway software framework design that different vendor′s devices have different communication mode and protocol standards.In this paper,a serial of interfaces are provided by Linux kernel,and a virtual bus is registered under Linux.The physical device drivers are able to connect to the virtual bus.The detailed designs of the communication protocol are placed in the underlying adapters,making the integration of heterogeneous networks more natural.At the same time,designing the intelligent gateway system driver layer based on Linux bus can let the application layer be more unified and clear logical.And it also let the hardware access network become more convenient and distinct.

CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

Energy Technology Data Exchange (ETDEWEB)

Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G. [ECN Energy in the Built Environment and Networks, Petten (Netherlands); Carlsson, P [EnerSearch, Malmoe (Sweden); Fontela, M. [Laboratory of Electrical Engineering LEG, Grenoble (France); Gustavsson, R. [Blekinge Institute of Technology BTH, Karlskrona (Sweden)

2003-10-15

This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4.

CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

International Nuclear Information System (INIS)

Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G.; Carlsson, P; Fontela, M.; Gustavsson, R.

2003-10-01

This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4

A user interface on networked workstations for MFTF-B plasma diagnostic instruments

International Nuclear Information System (INIS)

Balch, T.R.; Renbarger, V.L.

1986-01-01

A network of Sun-2/170 workstations is used to provide an interface to the MFTF-B Plasma Diagnostics System at Lawrence Livermore National Laboratory. The Plasma Diagnostics System (PDS) is responsible for control of MFTF-B plasma diagnostic instrumentation. An EtherNet Local Area Network links the workstations to a central multiprocessing system which furnishes data processing, data storage and control services for PDS. These workstations permit a physicist to command data acquisition, data processing, instrument control, and display of results. The interface is implemented as a metaphorical desktop, which helps the operator form a mental model of how the system works. As on a real desktop, functions are provided by sheets of paper (windows on a CRT screen) called worksheets. The worksheets may be invoked by pop-up menus and may be manipulated with a mouse. These worksheets are actually tasks that communicate with other tasks running in the central computer system. By making entries in the appropriate worksheet, a physicist may specify data acquisition or processing, control a diagnostic, or view a result

Large-scale Intelligent Transporation Systems simulation

Energy Technology Data Exchange (ETDEWEB)

Ewing, T.; Canfield, T.; Hannebutte, U.; Levine, D.; Tentner, A.

1995-06-01

A prototype computer system has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS) capable of running on massively parallel computers and distributed (networked) computer systems. The prototype includes the modelling of instrumented ``smart`` vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces to support human-factors studies. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of our design is that vehicles will be represented by autonomus computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.

Hopfield neural network and optical fiber sensor as intelligent heart rate monitor

Science.gov (United States)

Mutter, Kussay Nugamesh

2018-01-01

This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors' heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.

New challenges in computational collective intelligence

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Ngoc Thanh; Katarzyniak, Radoslaw Piotr [Wroclaw Univ. of Technology (Poland). Inst. of Informatics; Janiak, Adam (eds.) [Wroclaw Univ. of Technology (Poland). Inst. of Computer Engineering, Control and Robotics

2009-07-01

The book consists of 29 chapters which have been selected and invited from the submissions to the 1{sup st} International Conference on Collective Intelligence - Semantic Web, Social Networks and Multiagent Systems (ICCCI 2009). All chapters in the book discuss various examples of applications of computational collective intelligence and related technologies to such fields as semantic web, information systems ontologies, social networks, agent and multiagent systems. The editors hope that the book can be useful for graduate and Ph.D. students in Computer Science, in particular participants to courses on Soft Computing, Multi-Agent Systems and Robotics. This book can also be useful for researchers working on the concept of computational collective intelligence in artificial populations. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to create new cases intelligent collectives. Many such challenges are suggested by particular approaches and models presented in particular chapters of this book. (orig.)

Intelligent system for control and automation of natural gas distribution operation; Sistema inteligente de controle e automacao da operacao de distribuicao de gas natural

Energy Technology Data Exchange (ETDEWEB)

Scucuglia, Jose W.; Souza, Celso C. [Universidade para o Desenvolvimento do Estado e da Regiao do Pantanal (UNIDERP), Campo Grande, MS (Brazil). Curso de Engenharia Eletrica; Patricio, Cristian M.M.M.; Cruz, Lauro C.; Reis, Antonio M.; Cortez, Marco A.A.; Maldonado, Waldemar; Rosa, Willian A. [Universidade para o Desenvolvimento do Estado e da Regiao do Pantanal (UNIDERP), Campo Grande, MS (Brazil). Nucleo de Energia, Automacao e Controle; Teixeira, Marcelo C.M. [UNESP, Ilha Solteira, SP (Brazil). Faculdade de Engenharia Eletrica; Carrasco, Benjamim [PETROBRAS, Rio de Janeiro, RJ (Brazil)

2004-07-01

The present work has as objective to present the development of a dedicated intelligent system to the operation of natural gas distribution. The system adds tools of project, simulation, supervision and control of the flow of natural gas in networks distribution, and is composed of hardware and intelligent software. The developed software possess friendly graphical interface, so that the operator composing visually the distribution network automatically, composes a mathematical model formed by a set of differential equations, being solved by the Newton-Raphson method. This tool of simulation allows, in function of network topology, to get through simulation the conditions gas flow in each point of the loop flow. The micro controlled hardware for acquisition of the data in real time and control of valves was developed. The hardware possesses flexible communication (Radio Frequency, Ethernet and Optical Fiber), intelligence for decision taking and auto test of its proper functioning, so that guarantee security in the operations. An implanted neural system in software propitiates the control monitoring of the characteristics operation and conditions of leak with loss of load, identifying inclusive the place of this leak along of the duct. A system with national technology was gotten, of low cost and high added technological value. (author)

Intelligent networked teleoperation control

CERN Document Server

Li, Zhijun; Su, Chun-Yi

2015-01-01

This book describes a unified framework for networked teleoperation systems involving multiple research fields: networked control systems for linear and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral teleoperation and cooperative teleoperation. It closely examines networked control as a field at the intersection of systems & control and robotics and presents a number of experimental case studies on testbeds for robotic systems, including networked haptic devices, robotic network systems and sensor network systems. The concepts and results outlined are easy to understand, even for readers fairly new to the subject. As such, the book offers a valuable reference work for researchers and engineers in the fields of systems & control and robotics.

Reasoning about Users' Actions in a Graphical User Interface.

Science.gov (United States)

Virvou, Maria; Kabassi, Katerina

2002-01-01

Describes a graphical user interface called IFM (Intelligent File Manipulator) that provides intelligent help to users. Explains two underlying reasoning mechanisms, one an adaptation of human plausible reasoning and one that performs goal recognition based on the effects of users' commands; and presents results of an empirical study that…

Artificial intelligence in medicine.

OpenAIRE

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

2004-01-01

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

Intelligent Lighting Control System

OpenAIRE

García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

2014-01-01

This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

Application of artificial intelligence to the management of urological cancer.

Science.gov (United States)

Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

2007-10-01

Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

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

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Yongcheng Li

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

Artificial intelligence: Neural network model as the multidisciplinary team member in clinical decision support to avoid medical mistakes

Directory of Open Access Journals (Sweden)

Igor Vyacheslavovich Buzaev

2016-09-01

Full Text Available Objective: The continuous uninterrupted feedback system is the essential part of any well-organized system. We propose aLYNX concept that is a possibility to use an artificial intelligence algorithm or a neural network model in decision-making system so as to avoid possible mistakes and to remind the doctors to review tactics once more in selected cases. Method: aLYNX system includes: registry with significant factors, decisions and results; machine learning process based on this registry data; the use of the machine learning results as the adviser. We show a possibility to build a computer adviser with a neural network model for making a choice between coronary aortic bypass surgery (CABG and percutaneous coronary intervention (PCI in order to achieve a higher 5-year survival rate in patients with angina based on the experience of 5107 patients. Results: The neural network was trained by 4679 patients who achieved 5-year survival. Among them, 2390 patients underwent PCI and 2289 CABG. After training, the correlation coefficient (r of the network was 0.74 for training, 0.67 for validation, 0.71 for test and 0.73 for total. Simulation of the neural network function has been performed after training in the two groups of patients with known 5-year outcome. The disagreement rate was significantly higher in the dead patient group than that in the survivor group between neural network model and heart team [16.8% (787/4679 vs. 20.3% (87/428, P = 0.065]. Conclusion: The study shows the possibility to build a computer adviser with a neural network model for making a choice between CABG and PCI in order to achieve a higher 5-year survival rate in patients with angina. Keywords: Coronary artery bypass grafting, Percutaneous coronary intervention, Artificial intelligence, Decision making

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

Directory of Open Access Journals (Sweden)

Sanam Shahla Rizvi

2009-12-01

Full Text Available 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.

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

Science.gov (United States)

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.

Creative-Dynamics Approach To Neural Intelligence

Science.gov (United States)

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.

Wireless network interface energy consumption implications of popular streaming formats

Science.gov (United States)

Chandra, Surendar

2001-12-01

With the proliferation of mobile streaming multimedia, available battery capacity constrains the end-user experience. Since streaming applications tend to be long running, wireless network interface card's (WNIC) energy consumption is particularly an acute problem. In this work, we explore the WNIC energy consumption implications of popular multimedia streaming formats from Microsoft (Windows media), Real (Real media) and Apple (Quick Time). We investigate the energy consumption under varying stream bandwidth and network loss rates. We also explore history-based client-side strategies to reduce the energy consumed by transitioning the WNICs to a lower power consuming sleep state. We show that Microsoft media tends to transmit packets at regular intervals; streams optimized for 28.8 Kbps can save over 80% in energy consumption with 2% data loss. A high bandwidth stream (768 Kbps) can still save 57% in energy consumption with less than 0.3% data loss. For high bandwidth streams, Microsoft media exploits network-level packet fragmentation, which can lead to excessive packet loss (and wasted energy) in a lossy network. Real stream packets tend to be sent closer to each other, especially at higher bandwidths. Quicktime packets sometimes arrive in quick succession; most likely an application level fragmentation mechanism. Such packets are harder to predict at the network level without understanding the packet semantics.

A proposal of an open ubiquitous fuzzy computing system for Ambient Intelligence

NARCIS (Netherlands)

Acampora, G.; Loia, V.; Lee, R.S.T.; Lioa, V.

2007-01-01

Ambient Intelligence (AmI) is considered as the composition of three emergent technologies: Ubiquitous Computing, Ubiquitous Communication and Intelligent User Interfaces. The aim of integration of aforesaid technologies is to make wider the interaction between human beings and information

ZD-I intelligent scaler

International Nuclear Information System (INIS)

Zhen Zhihao; Zhou Weimin

1999-01-01

The ZD-I Intelligent Scaler is a new kind of high-powered scaler using high-speed CMOS96 series single chip processor. Besides the normal timing and counting functions, it can also supply 0-2000 V high voltage, store or print measuring data, communicate with PC by RS232 interface, and transfer measuring data. There is essential improvements on the panel. Keyboard without dialing switches and rheostats can perform all the operations, and the setting parameters would not lose when the scaler is switched off. So the ZD-I Intelligent Scaler is a perfect up-to-date production of the NIM-style scaler and the HV-generator

ZD-I intelligent scaler

International Nuclear Information System (INIS)

Chen Zhihao

2001-01-01

The ZD-I Intelligent Scaler is a new kind of high-powered scaler using high-speed CMOS96 series single chip processor. It not only has the normal timing, counting functions, but also can supply 0-2000 V high voltage, storage or print measuring data, communicate with PC by RS232 interface, transfer measuring data. And there is essentially improvement on the panel. Keyboard without dialing switches and rheostats can perform all the operations, and the setting parameters wouldn't lose when you shut down the scaler. So the ZE-I Intelligent Scaler is a perfect updating production of the NIM-style scaler and the HV-generator

Computational Foundations of Natural Intelligence.

Science.gov (United States)

van Gerven, Marcel

2017-01-01

New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

Nephrus: expert system model in intelligent multilayers for evaluation of urinary system based on scintigraphic image analysis

International Nuclear Information System (INIS)

Silva, Jorge Wagner Esteves da; Schirru, Roberto; Boasquevisque, Edson Mendes

1999-01-01

Renal function can be measured noninvasively with radionuclides in a extremely safe way compared to other diagnosis techniques. Nevertheless, due to the fact that radioactive materials are used in this procedure, it is necessary to maximize its benefits, therefore all efforts are justifiable in the development of data analysis support tools for this diagnosis modality. The objective of this work is to develop a prototype for a system model based on Artificial Intelligence devices able to perform functions related to cintilographic image analysis of the urinary system. Rules used by medical experts in the analysis of images obtained with 99m Tc+DTPA and /or 99m Tc+DMSA were modeled and a Neural Network diagnosis technique was implemented. Special attention was given for designing programs user-interface. Human Factor Engineering techniques were taking in account allowing friendliness and robustness. The image segmentation adopts a model based on Ideal ROIs, which represent the normal anatomic concept for urinary system organs. Results obtained using Artificial Neural Networks for qualitative image analysis and knowledge model constructed show the feasibility of Artificial Neural Networks for qualitative image analysis and knowledge model constructed show feasibility of Artificial Intelligence implementation that uses inherent abilities of each technique in the medical diagnosis image analysis. (author)

Artificial Intelligence in Civil Engineering

Directory of Open Access Journals (Sweden)

Pengzhen Lu

2012-01-01

Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

Application of Swarm Intelligence Based Routingprotocols for Wireless Adhoc Sensor Network

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Mrutyunjaya PANDA

2011-07-01

Full Text Available The enormous growth of wireless sensor network (WSN research has opined challenges about their ease in implementation and performance evaluation. Efficient swarm intelligence based routing protocols that can be used to obtain the application specific service guarantee are the key design issues in designing a WSN model. In this paper, an experimental testbed is designed with 100 sensor nodes deployed in a dense environment to address the scalability and performance issues of WSN. In this paper, we use Flooded Piggyback (FP and SC-MCBR ant colony based routing along with AODV and MCBR Tree in order to design an efficient WSN model. Finally, simulation results are presented with various performance measures to understand the efficacy of the proposed WSN design.

Soft computing in artificial intelligence

CERN Document Server

Matson, Eric

2014-01-01

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

Advances in Intelligence and Security Informatics

CERN Document Server

Mao, Wenji

2012-01-01

The Intelligent Systems Series comprises titles that present state of the art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. Traditionally, Intelligence and Security Informatics (ISI) research and applications have focused on information sharing and data mining, social network analysis, infrastructure protection and emergency responses for security informatics. With the continuous advance of IT technologies and the increasing sophistication of national and international securi

THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

Science.gov (United States)

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

Data flow methods for dynamic system simulation - A CSSL-IV microcomputer network interface

Science.gov (United States)

Makoui, A.; Karplus, W. J.

1983-01-01

A major problem in employing networks of microcomputers for the real-time simulation of complex systems is to allocate computational tasks to the various microcomputers in such a way that idle time and time lost in interprocess communication is minimized. The research reported in this paper is directed to the development of a software interface between a higher-level simulation language and a network of microcomputers. A CSSL-IV source program is translated to a data flow graph. This graph is then analyzed automatically so as to allocate computing tasks to the various processors.

1st International Conference on Computational Intelligence and Informatics

CERN Document Server

Prasad, V; Rani, B; Udgata, Siba; Raju, K

2017-01-01

The book covers a variety of topics which include data mining and data warehousing, high performance computing, parallel and distributed computing, computational intelligence, soft computing, big data, cloud computing, grid computing, cognitive computing, image processing, computer networks, wireless networks, social networks, wireless sensor networks, information and network security, web security, internet of things, bioinformatics and geoinformatics. The book is a collection of best papers submitted in the First International Conference on Computational Intelligence and Informatics (ICCII 2016) held during 28-30 May 2016 at JNTUH CEH, Hyderabad, India. It was hosted by Department of Computer Science and Engineering, JNTUH College of Engineering in association with Division V (Education & Research) CSI, India. .

Open Source Intelligence in a Networked World

CERN Document Server

Olcott, Anthony

2012-01-01

The amount of publicly and often freely available information is staggering. Yet, the intelligence community still continues to collect and use information in the same manner as during WWII, when the OSS set out to learn as much as possible about Nazi Germany and Imperial Japan by scrutinizing encyclopedias, guide books, and short-wave radio. Today, the supply of information is greater than any possible demand, and anyone can provide information. In effect, intelligence analysts are drowning in information. The book explains how to navigate this rising flood and make best use of these new, ric

International Conference on Computational Intelligence 2015

CERN Document Server

Saha, Sujan

2017-01-01

This volume comprises the proceedings of the International Conference on Computational Intelligence 2015 (ICCI15). This book aims to bring together work from leading academicians, scientists, researchers and research scholars from across the globe on all aspects of computational intelligence. The work is composed mainly of original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of computational intelligence. Specifically, the major topics covered include classical computational intelligence models and artificial intelligence, neural networks and deep learning, evolutionary swarm and particle algorithms, hybrid systems optimization, constraint programming, human-machine interaction, computational intelligence for the web analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, cross disciplinary topics and applications. The contents of this volume will be of use to researchers and professionals alike....

Service oriented network architecture for control and management of home appliances

Science.gov (United States)

Hayakawa, Hiroshi; Koita, Takahiro; Sato, Kenya

2005-12-01

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

Heterodox networks

DEFF Research Database (Denmark)

Lala, Purnima; Kumar, Ambuj

2016-01-01

It is imperative for the service providers to bring innovation in the network design to meet the exponential growth of mobile subscribers for multi-technology future wireless networks. As a matter of research, studies on providing services to moving subscriber groups aka ‘Place Time Capacity (PTC......)’ have not been considered much in the literature. In this article we present Heterodox networks as an innovative and alternate approach to handle the PTC congestion. We describe two different approaches to combat the PTC congestion where the traditional terrestrial infrastructure fails to provide......-Configurable Intelligent Distributed Antenna System (SCIDAS)’ that overlays intelligence over the conventional DAS architecture and latter is in the form of a swarm of intelligent hovering base stations working in a team to cooperatively resolve the PTC congestion at the Area of Event (AoE). A suitable network...

Intelligent Context-Aware and Adaptive Interface for Mobile LBS.

Science.gov (United States)

Feng, Jiangfan; Liu, Yanhong

2015-01-01

Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results.

Voltage Stability Control of Electrical Network Using Intelligent Load Shedding Strategy Based on Fuzzy Logic

Directory of Open Access Journals (Sweden)

Houda Jouini

2010-01-01

Full Text Available As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding strategy as a new approach based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to those injected at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a precalculated load shedding ratio in the purpose to reestablish the power balance and conduct the network to a new steady state.

Cooperation and the evolution of intelligence.

Science.gov (United States)

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.

Recent Advances on Hybrid Intelligent Systems

CERN Document Server

Melin, Patricia; Kacprzyk, Janusz

2013-01-01

This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

Distributed intelligent monitoring and reporting facilities

Science.gov (United States)

Pavlou, George; Mykoniatis, George; Sanchez-P, Jorge-A.

1996-06-01

Distributed intelligent monitoring and reporting facilities are of paramount importance in both service and network management as they provide the capability to monitor quality of service and utilization parameters and notify degradation so that corrective action can be taken. By intelligent, we refer to the capability of performing the monitoring tasks in a way that has the smallest possible impact on the managed network, facilitates the observation and summarization of information according to a number of criteria and in its most advanced form and permits the specification of these criteria dynamically to suit the particular policy in hand. In addition, intelligent monitoring facilities should minimize the design and implementation effort involved in such activities. The ISO/ITU Metric, Summarization and Performance management functions provide models that only partially satisfy the above requirements. This paper describes our extensions to the proposed models to support further capabilities, with the intention to eventually lead to fully dynamically defined monitoring policies. The concept of distributing intelligence is also discussed, including the consideration of security issues and the applicability of the model in ODP-based distributed processing environments.

The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility.

Science.gov (United States)

Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten

2018-01-01

Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.

Rendering Intelligence at Physical Layer for Smart Addressing and Multiple Access

DEFF Research Database (Denmark)

Sanyal, Rajarshi; Prasad, Ramjee; Cianca, Ernestina

2010-01-01

addressing of a node. For a typical closed user group type of network, we propose a multiple access mechanism and network topology which will not only eliminate the need of intelligent core network equipments in the network area , but to use this intelligent physical layer to directly reach any node over......The primary objective of this work is to propose a technique of wireless communication, where we render intelligence to the physical layer. We aim to realize a physical layer that can take part in some processes which is otherwise confined to higher layer signalling activities, like for example...... the fundamentals behind the proposed multiple access scheme and draws out the benefits compared to the existing multiple access processes based on cellular approach....

An intelligent simulation environment for control system design

International Nuclear Information System (INIS)

Robinson, J.T.

1989-01-01

The Oak Ridge National Laboratory is currently assisting in the development of advanced control systems for the next generation of nuclear power plants. This paper presents a prototype interactive and intelligent simulation environment being developed to support this effort. The environment combines tools from the field of Artificial Intelligence; in particular object-oriented programming, a LISP programming environment, and a direct manipulation user interface; with traditional numerical methods for simulating combined continuous/discrete processes. The resulting environment is highly interactive and easy to use. Models may be created and modified quickly through a window oriented direct manipulation interface. Models may be modified at any time, even as the simulation is running, and the results observed immediately via real-time graphics. 8 refs., 3 figs

FPGA implementation of a ZigBee wireless network control interface to transmit biomedical signals

International Nuclear Information System (INIS)

López, M A Gómez; Goy, C B; Bolognini, P C; Herrera, M C

2011-01-01

In recent years, cardiac hemodynamic monitors have incorporated new technologies based on wireless sensor networks which can implement different types of communication protocols. More precisely, a digital conductance catheter system recently developed adds a wireless ZigBee module (IEEE 802.15.4 standards) to transmit cardiac signals (ECG, intraventricular pressure and volume) which would allow the physicians to evaluate the patient's cardiac status in a noninvasively way. The aim of this paper is to describe a control interface, implemented in a FPGA device, to manage a ZigBee wireless network. ZigBee technology is used due to its excellent performance including simplicity, low-power consumption, short-range transmission and low cost. FPGA internal memory stores 8-bit signals with which the control interface prepares the information packets. These data were send to the ZigBee END DEVICE module that receives and transmits wirelessly to the external COORDINATOR module. Using an USB port, the COORDINATOR sends the signals to a personal computer for displaying. Each functional block of control interface was assessed by means of temporal diagrams. Three biological signals, organized in packets and converted to RS232 serial protocol, were successfully transmitted and displayed in a PC screen. For this purpose, a custom-made graphical software was designed using LabView.

FPGA implementation of a ZigBee wireless network control interface to transmit biomedical signals

Science.gov (United States)

Gómez López, M. A.; Goy, C. B.; Bolognini, P. C.; Herrera, M. C.

2011-12-01

In recent years, cardiac hemodynamic monitors have incorporated new technologies based on wireless sensor networks which can implement different types of communication protocols. More precisely, a digital conductance catheter system recently developed adds a wireless ZigBee module (IEEE 802.15.4 standards) to transmit cardiac signals (ECG, intraventricular pressure and volume) which would allow the physicians to evaluate the patient's cardiac status in a noninvasively way. The aim of this paper is to describe a control interface, implemented in a FPGA device, to manage a ZigBee wireless network. ZigBee technology is used due to its excellent performance including simplicity, low-power consumption, short-range transmission and low cost. FPGA internal memory stores 8-bit signals with which the control interface prepares the information packets. These data were send to the ZigBee END DEVICE module that receives and transmits wirelessly to the external COORDINATOR module. Using an USB port, the COORDINATOR sends the signals to a personal computer for displaying. Each functional block of control interface was assessed by means of temporal diagrams. Three biological signals, organized in packets and converted to RS232 serial protocol, were sucessfully transmitted and displayed in a PC screen. For this purpose, a custom-made graphical software was designed using LabView.

Interfacing a biosurveillance portal and an international network of institutional analysts to detect biological threats.

Science.gov (United States)

Riccardo, Flavia; Shigematsu, Mika; Chow, Catherine; McKnight, C Jason; Linge, Jens; Doherty, Brian; Dente, Maria Grazia; Declich, Silvia; Barker, Mike; Barboza, Philippe; Vaillant, Laetitia; Donachie, Alastair; Mawudeku, Abla; Blench, Michael; Arthur, Ray

2014-01-01

The Early Alerting and Reporting (EAR) project, launched in 2008, is aimed at improving global early alerting and risk assessment and evaluating the feasibility and opportunity of integrating the analysis of biological, chemical, radionuclear (CBRN), and pandemic influenza threats. At a time when no international collaborations existed in the field of event-based surveillance, EAR's innovative approach involved both epidemic intelligence experts and internet-based biosurveillance system providers in the framework of an international collaboration called the Global Health Security Initiative, which involved the ministries of health of the G7 countries and Mexico, the World Health Organization, and the European Commission. The EAR project pooled data from 7 major internet-based biosurveillance systems onto a common portal that was progressively optimized for biological threat detection under the guidance of epidemic intelligence experts from public health institutions in Canada, the European Centre for Disease Prevention and Control, France, Germany, Italy, Japan, the United Kingdom, and the United States. The group became the first end users of the EAR portal, constituting a network of analysts working with a common standard operating procedure and risk assessment tools on a rotation basis to constantly screen and assess public information on the web for events that could suggest an intentional release of biological agents. Following the first 2-year pilot phase, the EAR project was tested in its capacity to monitor biological threats, proving that its working model was feasible and demonstrating the high commitment of the countries and international institutions involved. During the testing period, analysts using the EAR platform did not miss intentional events of a biological nature and did not issue false alarms. Through the findings of this initial assessment, this article provides insights into how the field of epidemic intelligence can advance through an

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

Science.gov (United States)

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.

Development of intelligent supervisory control system

International Nuclear Information System (INIS)

Takizawa, Y.; Fukumoto, A.; Makino, M.; Takiguchi, S.

1994-01-01

The objective of the development of an intelligent supervisory control system for next generation plants is enhancement of the operational reliability by applying the recent outcome of artificial intelligence and computer technologies. This system consists of the supervisory control and monitoring for automatic operation, the equipment operation support for historical data management and for test scheduling, the operators' decision making support for accidental plant situations and the human-friendly interface of these support functions. The verification test results showed the validity of the functions realized by this system for the next generation control room. (author)

Active Probing Feedback based Self Configurable Intelligent Distributed Antenna System

DEFF Research Database (Denmark)

Kumar, Ambuj

collectively as Place Time Coverage & Capacity (PTC2). The dissertation proves through the concept of the PTC2 that the network performance can severely be degraded by the excessive and unrealistic site demands, the network management inefficiency, and the consequence of the accumulation of subscribers...... challenge through a viable solution that is based on injecting intelligence and services in parallel layers through a Distributed Antenna Systems (DAS) network. This approach would enable the remote sites to acquire intelligence and a resource pool at the same time, thereby managing the network dynamics...... promptly and aptly to absorb the PTC2 wobble. An Active Probing Management System (APMS) is proposed as a supporting architecture, to assist the intelligent system to keep a check on the variations at each and every site by either deploying the additional antenna or by utilising the service antenna...

Computational Foundations of Natural Intelligence

Directory of Open Access Journals (Sweden)

Marcel van Gerven

2017-12-01

Full Text Available New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation.   Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation. Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

GROWTH OF COLLECTIVE INTELLIGENCE BY LINKING KNOWLEDGE WORKERS THROUGH SOCIAL MEDIA

Directory of Open Access Journals (Sweden)

JAROSLAVA KUBÁTOVÁ

2012-05-01

Full Text Available Collective intelligence can be defined, very broadly, as groups of individuals that do things collectively, and that seem to be intelligent. Collective intelligence has existed for ages. Families, tribes, companies, countries, etc., are all groups of individuals doing things collectively, and that seem to be intelligent. However, over the past two decades, the rise of the Internet has given upturn to new types of collective intelligence. Companies can take advantage from the so-called Web-enabled collective intelligence. Web-enabled collective intelligence is based on linking knowledge workers through social media. That means that companies can hire geographically dispersed knowledge workers and create so-called virtual teams of these knowledge workers (members of the virtual teams are connected only via the Internet and do not meet face to face. By providing an online social network, the companies can achieve significant growth of collective intelligence. But to create and use an online social network within a company in a really efficient way, the managers need to have a deep understanding of how such a system works. Thus the purpose of this paper is to share the knowledge about effective use of social networks in companies. The main objectives of this paper are as follows: to introduce some good practices of the use of social media in companies, to analyze these practices and to generalize recommendations for a successful introduction and use of social media to increase collective intelligence of a company.

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

Directory of Open Access Journals (Sweden)

Jiangfan Feng

2015-01-01

Full Text Available Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users’ demands in a complicated environment and suggested the feasibility by the experimental results.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

Science.gov (United States)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

The role of the artificial intelligence within the context of the human factors in the nuclear safety

Energy Technology Data Exchange (ETDEWEB)

Bayout Alvarenga, M A [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil)

1994-12-31

The effective evaluation of a human-machine system depends heavily on a cognitive model of the human behaviour. The basic question is: How can we model the human cognition? The response should be found in the five disciplines that form the Cognitive Sciences: Artificial Intelligence, Cognitive Psychology, Neurophysiology, Linguistic, and Philosophy. Among them, the Artificial Intelligence appears as the catalyzer of the contributions and discoveries in the other four, trying to realize that cognitive model with the tools of the Computer Science. Sometimes, it seems as if these disciplines spoke different languages to describe the same ideas. It is necessary a holistic treatment of such questions that include the human cognition and its modelling. This becomes more clear when we observe that there are nowadays different methodologies that must be integrated in some way. This is the case of the symbolic approach (artificial intelligence), connectionist approach (neural networks) and the fuzzy logic. This paper makes a review of the available methodologies, showing the problems and the current solutions to answer the following question. How is possible to develop a human-machine system and an intelligent interface based on the Artificial Intelligence that fulfills the following characteristics: human-centered design, cognitive simulation of the human behaviour, and dynamic function allocation. This paper concludes with proposals of national projects to be applied to the Brazilian situation. (author). 28 refs.

The role of the artificial intelligence within the context of the human factors in the nuclear safety

International Nuclear Information System (INIS)

Bayout Alvarenga, M.A.

1994-01-01

The effective evaluation of a human-machine system depends heavily on a cognitive model of the human behaviour. The basic question is: How can we model the human cognition? The response should be found in the five disciplines that form the Cognitive Sciences: Artificial Intelligence, Cognitive Psychology, Neurophysiology, Linguistic, and Philosophy. Among them, the Artificial Intelligence appears as the catalyzer of the contributions and discoveries in the other four, trying to realize that cognitive model with the tools of the Computer Science. Sometimes, it seems as if these disciplines spoke different languages to describe the same ideas. It is necessary a holistic treatment of such questions that include the human cognition and its modelling. This becomes more clear when we observe that there are nowadays different methodologies that must be integrated in some way. This is the case of the symbolic approach (artificial intelligence), connectionist approach (neural networks) and the fuzzy logic. This paper makes a review of the available methodologies, showing the problems and the current solutions to answer the following question. How is possible to develop a human-machine system and an intelligent interface based on the Artificial Intelligence that fulfills the following characteristics: human-centered design, cognitive simulation of the human behaviour, and dynamic function allocation. This paper concludes with proposals of national projects to be applied to the Brazilian situation. (author). 28 refs

Defining a convergence network platform framework for smart grid and intelligent transport systems

International Nuclear Information System (INIS)

Coronado Mondragon, Adrian E.; Coronado, Etienne S.; Coronado Mondragon, Christian E.

2015-01-01

The challenges faced by electricity grids suggest smart grids will have to coordinate its operation with other important initiatives in areas such as transportation. The smart grid relies on the use of network platforms where meter readings and data can be transmitted. On the other hand, concerning transportation systems the need to achieve a reduction of road congestion and traffic accidents among the increasing use of electric vehicles has consolidated the importance of ITS (intelligent transport systems). Given the magnitude of the challenges faced by both the smart grid and ITS, the aim of this work is to identify the elements comprising a convergence platform capable of supporting future services for data traffic associated to smart grid operations as well as ITS-related commercial service applications and road traffic safety messaging. A seaport terminal scenario is used to present a convergence network platform incorporating WSN (wireless sensor network) theory. The results of the simulation of the proposed network confirms the suitability of WSN to be used in the transmission of data traffic associated to meter readings which is required for effective energy consumption and management policies in industrial environments comprising equipment with high energy demands. - Highlights: • Common needs/challenges of smart grid/ITS can be addressed by a convergence network platform. • VANETs are identified as key components of the smart grid/ITS convergence network platform. • WSN (Wireless Sensor Network) theory is suitable for the transmission of data traffic associated to meter readings. • The amount of energy supplied to the network is low but enough to support data traffic required in industrial environments. • WSN supports the steady exchange of packets as characterized in industrial environments like seaports

Concept development and needs identification for intelligent network flow optimization (INFLO) : functional and performance requirements, and high-level data and communication needs.

Science.gov (United States)

2012-11-01

The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...

Brain-Computer Interfacing Embedded in Intelligent and Affective Systems

NARCIS (Netherlands)

Nijholt, Antinus

In this talk we survey recent research views on non-traditional brain-computer interfaces (BCI). That is, interfaces that can process brain activity input, but that are designed for the ‘general population’, rather than for clinical purposes. Control of applications can be made more robust by fusing

Research and applications: Artificial intelligence

Science.gov (United States)

Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

1970-01-01

The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

Map Matching for Intelligent Speed Adaptation

DEFF Research Database (Denmark)

Tradisauskas, Nerius; Juhl, Jens; Lahrmann, Harry

2007-01-01

The availability of Global Navigation Satellite Systems enables sophisticated vehicle guidance and advisory systems such as Intelligent Speed Adaptation (ISA) systems. In ISA systems, it is essential to be able to position vehicles within a road network. Because digital road networks as well as G...

Ortho Image and DTM Generation with Intelligent Methods

Science.gov (United States)

Bagheri, H.; Sadeghian, S.

2013-10-01

Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse

Self-Adaptive Systems for Machine Intelligence

CERN Document Server

He, Haibo

2011-01-01

This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide application

A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Mohammad Nurul Afsar Shaon

2017-05-01

Full Text Available A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN. Most wormhole detection schemes reported in the literature assume the sensors are uniformly distributed in a network, and, furthermore, they use statistical and topological information and special hardware for their detection. However, these schemes may perform poorly in non-uniformly distributed networks, and, moreover, they may fail to defend against “out of band” and “in band” wormhole attacks. The aim of the proposed research is to develop a detection scheme that is able to detect all kinds of wormhole attacks in both uniformly and non-uniformly distributed sensor networks. Furthermore, the proposed research does not require any special hardware and causes no significant network overhead throughout the network. Most importantly, the probable location of the malicious nodes can be identified by the proposed ANN based detection scheme. We evaluate the efficacy of the proposed detection scheme in terms of detection accuracy, false positive rate, and false negative rate. The performance of the proposed algorithm is also compared with other machine learning techniques (i.e. SVM and regularized nonlinear logistic regression (LR based detection models. The simulation results show that proposed ANN based algorithm outperforms the SVM or LR based detection schemes in terms of detection accuracy, false positive rate, and false negative rates.

Intelligent Growth Automaton of Virtual Plant Based on Physiological Engine

Science.gov (United States)

Zhu, Qingsheng; Guo, Mingwei; Qu, Hongchun; Deng, Qingqing

In this paper, a novel intelligent growth automaton of virtual plant is proposed. Initially, this intelligent growth automaton analyzes the branching pattern which is controlled by genes and then builds plant; moreover, it stores the information of plant growth, provides the interface between virtual plant and environment, and controls the growth and development of plant on the basis of environment and the function of plant organs. This intelligent growth automaton can simulate that the plant growth is controlled by genetic information system, and the information of environment and the function of plant organs. The experimental results show that the intelligent growth automaton can simulate the growth of plant conveniently and vividly.

THE INTEREST OF GEOGRAPHICAL INFORMATION, ARTIFICIAL INTELLIGENCE AND VIRTUAL REALITY FOR THE UNDERGROUND NETWORK REPRESENTATION

Directory of Open Access Journals (Sweden)

M. Lacroix

2016-01-01

Full Text Available Two years ago, 63 people died and more than 150 were seriously injured in Beijing (China because of damage to a hydrocarbon pipeline. Urban networks are invisible because usually buried between 1 and 1,5 meters underground. They should be identified to prevent such accidents which involve workers as well as the public. Rural and urban districts, network concessionaries and contractors: everyone could benefit from their networks becoming safer. To prevent such accidents and protect workers and the public as well, some new regulations propose to identify and secure the buried networks. That’s why it is important to develop a software which deals with the risk management process and also about the risk visualization. This work is structured around three major sections:– the utility of the Geographical Information to determine the minimal distances and the topological relations between the networks themselves, and also with the other element in their vicinity;– the use of some Artificial Intelligence tools, and more particularly of Expert System, to take the current regulation into account and determine the accident risk probability;– the contribution of virtual reality to perceive the underground world.

The implementation of intelligent home controller

Science.gov (United States)

Li, Biqing; Li, Zhao

2018-04-01

This paper mainly talks about the working way of smart home terminal controller and the design of hardware and software. Controlling the lights and by simulating the lamp and the test of the curtain, destroy the light of lamp ON-OFF and the curtain's UP-DOWN by simulating the lamp and the test of the cuetain. Through the sensor collects the ambient information and sends to the network, such as light, temperature and humidity. Besides, it can realise the control of intelligent home control by PCS. Terminal controller of intelligent home which is based on ZiBee technology has into the intelligent home system, it provides people with convenient, safe and intelligent household experience.

Memory Based Machine Intelligence Techniques in VLSI hardware

OpenAIRE

James, Alex Pappachen

2012-01-01

We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

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

Science.gov (United States)

Kuljaca, Ognjen

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

Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program

Science.gov (United States)

Schallhorn, Paul; Popok, Daniel

1999-01-01

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.

TRACKING VEHICLE IN GSM NETWORK TO SUPPORT INTELLIGENT TRANSPORTATION SYSTEMS

Directory of Open Access Journals (Sweden)

Z. Koppanyi

2012-07-01

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

Behavior Analysis and the Quest for Machine Intelligence.

Science.gov (United States)

Stephens, Kenneth R.; Hutchison, William R.

1993-01-01

Discusses three approaches to building intelligent systems: artificial intelligence, neural networks, and behavior analysis. BANKET, an object-oriented software system, is explained; a commercial application of BANKET is described; and a collaborative effort between the academic and business communities for the use of BANKET is discussed.…

Natural-language processing applied to an ITS interface

OpenAIRE

Antonio Gisolfi; Enrico Fischetti

1994-01-01

The aim of this paper is to show that with a subset of a natural language, simple systems running on PCs can be developed that can nevertheless be an effective tool for interfacing purposes in the building of an Intelligent Tutoring System (ITS). After presenting the special characteristics of the Smalltalk/V language, which provides an appropriate environment for the development of an interface, the overall architecture of the interface module is discussed. We then show how sentences are par...

Toward New-Generation Intelligent Manufacturing

Directory of Open Access Journals (Sweden)

Ji Zhou

2018-02-01

Full Text Available Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and new-generation intelligent manufacturing. New-generation intelligent manufacturing represents an in-depth integration of new-generation artificial intelligence (AI technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for “parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China. Keywords: Advanced manufacturing, New-generation intelligent manufacturing, Human-cyber-physical system, New-generation AI, Basic paradigms, Parallel promotion, Integrated development