WorldWideScience

Sample records for networked intelligent luminaire

  1. LED roadway luminaires evaluation.

    Science.gov (United States)

    2012-02-01

    This research explores whether LED roadway luminaire technologies are a viable future solution to providing roadway lighting. Roadway lighting : enhances highway safety and traffic flow during limited lighting conditions. The purpose of this evaluati...

  2. High Flux Commercial Illumination Solution with Intelligent Controls

    Energy Technology Data Exchange (ETDEWEB)

    Camil Ghiu

    2012-04-30

    This report summarizes the work performed at OSRAM SYLVANIA under US Department of Energy contract DE-EE0003241 for developing a high efficiency LED-based luminaire. A novel light engine module (two versions: standard and super), power supply and luminaire mechanical parts were designed and tested. At steady-state, the luminaire luminous flux is 3156 lumens (lm), luminous efficacy 97.4 LPW and CRI (Ra) 88 at a correlated color temperature (CCT) of 3507K. When the luminaire is fitted with the super version of the light engine the efficacy reaches 130 LPW. In addition, the luminaire is provided with an intelligent control network capable of additional energy savings. The technology developed during the course of this project has been incorporated into a family of products. Recently, the first product in the family has been launched.

  3. The Luminaire Window

    DEFF Research Database (Denmark)

    Hansen, Ellen Kathrine

    2017-01-01

    they are seldom considered in a holistic lighting design. Natural daylight is not always sufficient - for instance on an overcast day, or on winter days. This paper explores a new universal design approach for supplementing the qualities of natural dynamic light by boosting the daylight with dynamic LED light...... integrated into the window. A qualitative experiment is carried out by integrating controllable LED in the frame of a façade window in a full-scale mock-up. It is examined how this set-up can support the colour spectrum and intensity of the daylight intake during the transmission time from daylight...... to darkness. The findings illustrate that a “luminaire window” has potentials of supporting circadian rhythm, stimulate peoples natural need for contact with nature and at the same time enhance the architectural potentials by using the window as the main (daylight and electrical) light source to create...

  4. 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.

  5. Advanced dimming strategy for solid state luminaires

    DEFF Research Database (Denmark)

    Beczkowski, Szymon

    2010-01-01

    Increased luminaire gamut as well as increase in luminous efficiency is found when the LED based luminaire is driven by a hybrid PWM/AM dimming technique. This technique is applicable to any n-chromaticity luminaire but it is especially suitable for trichromatic RGB luminaires that do not have in...... inherent degrees of freedom. Diodes' properties under the hybrid dimming method were measured and used in nonlinear optimization routine to find the driving conditions that yield e.g. the highest possible efficacy for a given color point....

  6. Macromolecular networks and intelligence in microorganisms

    Directory of Open Access Journals (Sweden)

    Hans V Westerhoff

    2014-07-01

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

  7. CALiPER Report 24: OLED Luminaires

    Energy Technology Data Exchange (ETDEWEB)

    Miller, N. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Leon, F. A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Davis, J. L. [RTI International, Research Triangle Park, NC (United States)

    2017-08-01

    This report documents an initial investigation of OLED luminaires and summarizes the key features of those products. In addition to photometric testing of four commercial products in independent laboratories, PNNL examined many of the products through teardown testing (disassemblies to identify parts and functionality) in PNNL laboratories. Results of these tests as well as results of stress testing of several OLED luminaires at RTI International have been included.

  8. 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...

  9. Luminaire layout: Design and implementation

    Science.gov (United States)

    Both, A. J.

    1994-01-01

    The information contained in this report was presented during the discussion regarding guidelines for PAR uniformity in greenhouses. The data shows a lighting uniformity analysis in a research greenhouse for rose production at the Cornell University campus. The luminaire layout was designed using the computer program Lumen-Micro. After implementation of the design, accurate measurements were taken in the greenhouse and the uniformity analysis for both the design and implementation were compared. A study of several supplemental lighting installations resulted in the following recommendations: include only the actual growing area in the lighting uniformity analysis; for growing areas up to 20 square meters, take four measurements per square meter; for growing areas above 20 square meters, take one measurement per square meter; use one of the uniformity criteria and frequency graphs to compare lighting uniformity amongst designs; and design for uniformity criterion of a least 0.75 and the fraction within +/- 15% of the average PAR value should be close to one.

  10. Capacity of Intelligent Underlay and Overlay Network

    DEFF Research Database (Denmark)

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

    1996-01-01

    This paper suggests a method of dimensioning the cell configuration of radio sites in a cellular network using the intelligent overlay and underlay (IOU) technique. The traffic capacity has been analysed by means of a teletraffic model, which is developed based on the classical theory of overflow...... 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...

  11. Network Neuroscience Theory of Human Intelligence.

    Science.gov (United States)

    Barbey, Aron K

    2018-01-01

    An enduring aim of research in the psychological and brain sciences is to understand the nature of individual differences in human intelligence, examining the stunning breadth and diversity of intellectual abilities and the remarkable neurobiological mechanisms from which they arise. This Opinion article surveys recent neuroscience evidence to elucidate how general intelligence, g, emerges from individual differences in the network architecture of the human brain. The reviewed findings motivate new insights about how network topology and dynamics account for individual differences in g, represented by the Network Neuroscience Theory. According to this framework, g emerges from the small-world topology of brain networks and the dynamic reorganization of its community structure in the service of system-wide flexibility and adaptation. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

  12. 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.

  13. 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.

  14. 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.

  15. Application of CAN-bus Network in Intelligent parking

    Science.gov (United States)

    Jianjun, WU; Juan, Hu

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

  16. Intelligent Classification and Visualization of Network Scans

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-03-01

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

  17. Next Generation Luminaires: Recognizing Innovative, Energy-Efficient Commercial Lighting Luminaires

    Energy Technology Data Exchange (ETDEWEB)

    None

    2013-04-01

    Fact sheet that describes the Next Generation Luminaires SSL lighting design competition, which recognizes excellence in technical innovation and design of high-quality, energy-efficient commercial lighting, both indoor and outdoor.

  18. Intelligent Communication Module for Wireless Biosensor Networks

    OpenAIRE

    Naik, R.; Singh, J.; Le, H. P.

    2010-01-01

    This chapter presented a new paradigm of biosensors which have processing capability with an intelligent and adaptive wireless communication module. The adaptive communication module efficiently reconfigures its hardware components according to the changes in operating environment in order to reduce system power consumption and optimally utilise resources. The chapter presented several significant applications of wireless biosensor networks which hold enormous potential to benefit the communi...

  19. Comparisons of luminaires: Efficacies and system design

    Energy Technology Data Exchange (ETDEWEB)

    Albright, L.D.; Both, A.J. [Cornell Univ., Ithaca, NY (United States)

    1994-12-31

    After reviewing basic information, three design examples have been presented to demonstrate a process of supplemental lighting design. The sequences of each example suggest careful thought and analysis are required to obtain supplemental lighting designs that provide both high levels of PAR and suitable uniformity. The end results should suggest how an analysis can evolve to achieve desired results, and the types of tools and adjustments required. It appears possible to design research greenhouses and plant growth chambers to achieve a {+-}10% PAR uniformity using HIPS luminaires. Further, HPS luminaires (and, by extension, NEHD, etc.) are required to achieve high PAR levels and have the decided advantage of providing the possibility of aiming, which reduces the region of the {open_quotes}edge effect{close_quotes}. Further, for designing plant lighting systems, a modification of the standard IES luminaire data file structure is potentially useful. Luminaire installation is an important factor to obtain PAR uniformity. Spacing and mounting height are critically important. Additionally, the mounting angle of each luminaire must be carefully adjusted to conform with design assumptions. This is true for both plant growth chambers and greenhouses. Surface reflectances are particularly important when designing for small lighted regions such as plant growth chambers and research greenhouses. It is not obvious, just from looking at a surface, what its reflectance is. It is suggested that an effort be mounted to develop valid surface reflectance data to be used by designers. The importance of the surfaces (particularly the walls) in achieving PAR uniformity suggests the importance of periodic cleaning/maintenance to retain initial reflectance values.

  20. OLED Luminaire with Panel Integrated Drivers and Advanced Controls

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Michael [Acuity Brands Lighting, Inc., Atlanta, GA (United States); Spindler, Jeff [OLEDWorks, Rochester, NY (United States)

    2017-01-31

    For this DOE award, Acuity Brands Lighting developed a novel OLED luminaire system featuring panel-integrated drivers at each individual OLED panel. The luminaire has a base station that receives user commands and performs AC/DC conversion. A power line communication (PLC) protocol is used to provide both power and digital control to each panel. A 66-panel CanvisTM luminaire using state-of-art OLED panels based on this system was successfully constructed. This is a first demonstration of such a luminaire architecture. It is also the first known implementation of this number of independently addressable nodes with a PLC protocol. This luminaire system architecture has added benefits in the flexibility of using multiple panel vendors for a given product, forward compatibility with future panels, and reduced luminaire wiring complexity and assembly time.

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

    Science.gov (United States)

    Büker, Engin

    2015-05-01

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

  2. Intelligent 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

  3. Nutritional status, brain network organization, and general intelligence.

    Science.gov (United States)

    Zamroziewicz, Marta K; Talukdar, M Tanveer; Zwilling, Chris E; Barbey, Aron K

    2017-11-01

    The high energy demands of the brain underscore the importance of nutrition in maintaining brain health and further indicate that aspects of nutrition may optimize brain health, in turn enhancing cognitive performance. General intelligence represents a critical cognitive ability that has been well characterized by cognitive neuroscientists and psychologists alike, but the extent to which a driver of brain health, namely nutritional status, impacts the neural mechanisms that underlie general intelligence is not understood. This study therefore examined the relationship between the intrinsic connectivity networks supporting general intelligence and nutritional status, focusing on nutrients known to impact the metabolic processes that drive brain function. We measured general intelligence, favorable connective architecture of seven intrinsic connectivity networks, and seventeen plasma phospholipid monounsaturated and saturated fatty acids in a sample of 99 healthy, older adults. A mediation analysis was implemented to investigate the relationship between empirically derived patterns of fatty acids, general intelligence, and underlying intrinsic connectivity networks. The mediation analysis revealed that small world propensity within one intrinsic connectivity network supporting general intelligence, the dorsal attention network, was promoted by a pattern of monounsaturated fatty acids. These results suggest that the efficiency of functional organization within a core network underlying general intelligence is influenced by nutritional status. This report provides a novel connection between nutritional status and functional network efficiency, and further supports the promise and utility of functional connectivity metrics in studying the impact of nutrition on cognitive and brain health. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Comparisons of luminaires: Efficacies and system design

    Science.gov (United States)

    Albright, L. D.; Both, A. J.

    1994-03-01

    Lighting designs for architectural (aesthetic) purposes, vision and safety, and plant growth have many features in common but several crucial ones that are not. The human eye is very sensitive to the color (wavelength) of light, whereas plants are less so. There are morphological reactions, particularly to the red and blue portions of the light spectrum but, in general, plants appear to accept and use light for photosynthesis everywhere over the PAR region of the spectrum. In contrast, the human eye interprets light intensity on a logarithmic scale, making people insensitive to significant differences of light intensity. As a rough rule, light intensity must change by 30 to 50% for the human eye to recognize the difference. Plants respond much more linearly to light energy, at least at intensities below photosynthetic saturation. Thus, intensity differences not noticeable to the human eye can have significant effects on total plant growth and yield, and crop timing. These factors make luminaire selection and lighting system design particularly important when designing supplemental lighting systems for plant growth. Supplemental lighting for plant growth on the scale of commercial greenhouses is a relatively expensive undertaking. Light intensities are often much higher than required for task (vision) lighting, which increases both installation and operating costs. However, and especially in the northern regions of the United States (and Canada, Europe, etc.), supplemental lighting during winter may be necessary to produce certain crops (e.g., tomatoes) and very useful to achieve full plant growth potential and crop timing with most other greenhouse crops. Operating costs over the life of a luminaire typically will exceed the initial investment, making lighting efficacy a major consideration. This report reviews tests completed to evaluate the efficiencies of various commercially-available High-Pressure Sodium luminaires, and then describes the results of using a

  5. 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…

  6. 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. ...

  7. Application of sensor networks to intelligent transportation systems.

    Science.gov (United States)

    2009-12-01

    The objective of the research performed is the application of wireless sensor networks to intelligent transportation infrastructures, with the aim of increasing their dependability and improving the efficacy of data collection and utilization. Exampl...

  8. Intelligent Servo Drives Control Based on a Single Fieldbus Network

    Directory of Open Access Journals (Sweden)

    D. Puiu

    2010-11-01

    Full Text Available Due to the quick evolution of manufacturing processes, the demand for more flexible automation systems is on the rise. To answer these requirements, distributed motion control architecture based on intelligent drives tends more and more to replace the traditional solutions. This paper presents the control of an articulated arm robot with two local intelligent servo drives connected on a CAN network to a motion controller which receives the trajectory of the robot from a computer. The control structure is based on a single CAN network where local intelligent servo drives, a motion controller and a computer are connected.

  9. High Performance OLED Panel and Luminaire

    Energy Technology Data Exchange (ETDEWEB)

    Spindler, Jeffrey [OLEDWorks LLC, Rochester, NY (United States)

    2017-02-20

    In this project, OLEDWorks developed and demonstrated the technology required to produce OLED lighting panels with high energy efficiency and excellent light quality. OLED panels developed in this program produce high quality warm white light with CRI greater than 85 and efficacy up to 80 lumens per watt (LPW). An OLED luminaire employing 24 of the high performance panels produces practical levels of illumination for general lighting, with a flux of over 2200 lumens at 60 LPW. This is a significant advance in the state of the art for OLED solid-state lighting (SSL), which is expected to be a complementary light source to the more advanced LED SSL technology that is rapidly replacing all other traditional forms of lighting.

  10. 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.

  11. 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.

  12. High-performance LED luminaire for sports hall

    Science.gov (United States)

    Lee, Xuan-Hao; Yang, Jin-Tsung; Chien, Wei-Ting; Chang, Jung-Hsuan; Lo, Yi-Chien; Lin, Che-Chu; Sun, Ching-Cherng

    2015-09-01

    In this paper, we present a luminaire design with anti-glare and energy-saving effects for sports hall. Compared with traditional lamps using in a badminton court, the average illuminance on the ground of the proposed LED luminaire is enhanced about 300%. Besides, the uniformity is obviously enhanced and improved. The switch-on speed of lighting in sports hall is greatly reduced from 5-10 minutes to 1 second. The simulation analysis and the corresponding experiment results are demonstrated.

  13. Neural Network Based Intelligent Sootblowing System

    Energy Technology Data Exchange (ETDEWEB)

    Mark Rhode

    2005-04-01

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

  14. 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

  15. Measurement of the light flux density patterns from luminaires proposed as photon sources for photosynthesis during space travel

    Science.gov (United States)

    Walker, Paul N.

    1989-01-01

    Two luminaires were evaluated to determine the light flux density pattern on a horizontal plane surface. NASA supplied both luminaires; one was made by NASA and the other is commercially available. Tests were made for three combinations of luminaire height and luminaire lens material using the NASA luminaire; only one configuration of the commercial luminaire was tested. Measurements were made using four sensors with different wavelength range capabilities. The data are presented in graphical and tabular formats.

  16. Developing an intelligence analysis process through social network analysis

    Science.gov (United States)

    Waskiewicz, Todd; LaMonica, Peter

    2008-04-01

    Intelligence analysts are tasked with making sense of enormous amounts of data and gaining an awareness of a situation that can be acted upon. This process can be extremely difficult and time consuming. Trying to differentiate between important pieces of information and extraneous data only complicates the problem. When dealing with data containing entities and relationships, social network analysis (SNA) techniques can be employed to make this job easier. Applying network measures to social network graphs can identify the most significant nodes (entities) and edges (relationships) and help the analyst further focus on key areas of concern. Strange developed a model that identifies high value targets such as centers of gravity and critical vulnerabilities. SNA lends itself to the discovery of these high value targets and the Air Force Research Laboratory (AFRL) has investigated several network measures such as centrality, betweenness, and grouping to identify centers of gravity and critical vulnerabilities. Using these network measures, a process for the intelligence analyst has been developed to aid analysts in identifying points of tactical emphasis. Organizational Risk Analyzer (ORA) and Terrorist Modus Operandi Discovery System (TMODS) are the two applications used to compute the network measures and identify the points to be acted upon. Therefore, the result of leveraging social network analysis techniques and applications will provide the analyst and the intelligence community with more focused and concentrated analysis results allowing them to more easily exploit key attributes of a network, thus saving time, money, and manpower.

  17. Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks

    OpenAIRE

    Chen, Mingzhe; Challita, Ursula; Saad, Walid; Yin, Changchuan; Debbah, Mérouane

    2017-01-01

    Next-generation wireless networks must support ultra-reliable, low-latency communication and intelligently manage a massive number of Internet of Things (IoT) devices in real-time, within a highly dynamic environment. This need for stringent communication quality-of-service (QoS) requirements as well as mobile edge and core intelligence can only be realized by integrating fundamental notions of artificial intelligence (AI) and machine learning across the wireless infrastructure and end-user d...

  18. Macromolecular networks and intelligence in microorganisms

    NARCIS (Netherlands)

    Westerhoff, H.V.; Brooks, A.N.; Simeonidis, E.; García-Contreras, R.; He, F.; Boogerd, F.C.; Jackson, V.J.; Goncharuk, V.; Kolodkin, A.

    2014-01-01

    Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from

  19. Advances in neural networks computational intelligence for ICT

    CERN Document Server

    Esposito, Anna; Morabito, Francesco; Pasero, Eros

    2016-01-01

    This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers’ peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in...

  20. AN INTELLIGENT VERTICAL HANDOVER DECISION ALGORITHM FOR WIRELESS HETEROGENEOUS NETWORKS

    OpenAIRE

    V. Anantha Narayanan; Rajeswari, A; Sureshkumar, V.

    2014-01-01

    The Next Generation Wireless Networks (NGWN) should be compatible with other communication technologies to offer the best connectivity to the mobile terminal which can access any IP based services at any time from any network without the knowledge of its user. It requires an intelligent vertical handover decision making algorithm to migrate between technologies that enable seamless mobility, always best connection and minimal terminal power consumption. Currently existing decision engines are...

  1. An Intelligent Handover Management System for Future Generation Wireless Networks

    OpenAIRE

    Kassar Meriem; Kervella Brigitte; Pujolle Guy

    2008-01-01

    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 contex...

  2. Developing intelligent sensor networks —a technological convergence approach

    OpenAIRE

    Vassev, Emil; Hinchey, Mike; Nixon, Paddy

    2010-01-01

    peer-reviewed We present a technological convergence approach to developing sensor networks capable of self-management. We use ASSL (Autonomic System Specification Language) to formally develop autonomous intelligent sensor nodes and DMF (Demand Migration Framework) to connect these nodes in a sensor network. ASSL provides constructs for modeling special self-management policies that drive the sensor nodes’ behavior and control the communication mechanism provided by DMF.

  3. Luminaires for Advanced Lighting in Education

    Energy Technology Data Exchange (ETDEWEB)

    Davis, J. Lynn [RTI International, Research Triangle Park, NC (United States)

    2017-06-29

    Evolving education methods and greater use of technology in the classroom are dictating the need to rethink facility designs, including classroom lighting. Advances in LED-based lighting technology have created the possibility of lighting systems that are not only cost effective and energy efficient, but also color-tunable and as durable as other facility infrastructures (a 20-30 year life expectancy). Thus, there is the opportunity that the modern lighting system can be used by educators as a tool in their teaching strategy. To meet this need, RTI International and Finelite, Inc. teamed to develop and test the Next Generation Integrated Classroom Lighting System (NICLS). The NICLS technology incorporates a high performance, color-tunable light engine into new luminaire designs (e.g., pendant, direct-indirect, downlight, troffers) that are acceptable for use in classrooms. During this project, we successfully demonstrated that the NICLS technology achieves exceptional performance and exceeds all DOE goals for the classroom of the future, including: Luminous efficacy value for NICLS luminaires in excess of 125 lpw at all CCT values; TWL range of 2,700 K to 6,500 K while maintaining a CRI of 82 or higher at all values; Capability for full-range dimming (100% to 1%) at all CCT values with flicker levels below industry guidelines; Performance of the lighting system in a classroom mock-up, incorporating daylight and occupancy sensing to provide automatic control of lighting zones to further reduce energy consumption; Rated lifetime on the system exceeding 50,000 hours with a lumen maintenance of at least 85% at 50,000 hours; and Teacher-focused UI located at the front of the classroom to operate the lighting system. A smartphone-based UI is also available to accommodate teacher movement in the classroom. A critical element of developing this technology is designing the user interface to be compatible with modern teaching methods, including increased use of icons and

  4. Intelligent Current Sensors as Part of Smart Grid Network

    Directory of Open Access Journals (Sweden)

    Andrzej Nowakowski

    2015-06-01

    Full Text Available The continuous development of the ITC systems, especially industrial Ethernet network using the IEC 61850 protocol allows to building a distributed sensor networks for control and monitor temporary states of the power infrastructure. In the paper the construction of the intelligent current sensors, Measurement Units (MU for the Smart Grid network has been presented. In the paper the circuit diagram of sensor and synchronization method of the analog to digital converter based on the UTC timestamps has been described. The presented method allows to synchronize intelligent current sensors with an accuracy better than 1 μs. The presented innovative synchronization method is characterized by a high level of resistance to disappearance and attack of the reference time signal. The measuring device MU design is based on the embedded Linux-platform and as a sensing element used air core current transducers based on Rogowski coil. The connection between the current transducers and the central unit is made using a fiber optic link. Built-in IEC-61850 server provides a real-time measurement value of the True RMS, harmonics spectrum and samples value. The intelligent current transducers in addition to being used in the MUs create also new possibilities in the substation construction like the possibility to place the Autonomous Sensors in large distance from Intelligent Electronic Devices that are located in the substation.

  5. 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

  6. Low Power Multi-Hop Networking Analysis in Intelligent Environments

    Directory of Open Access Journals (Sweden)

    Josu Etxaniz

    2017-05-01

    Full Text Available 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.

  7. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Vitela, J.E.; Hanebutte, U.R.; Reifman, J. [Argonne National Lab., IL (United States). Reactor Analysis Div.

    1996-04-01

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

  9. Constructing an Intelligent Patent Network Analysis Method

    OpenAIRE

    Chao-Chan Wu; Ching-Bang Yao

    2012-01-01

    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...

  10. Artificial neural network intelligent method for prediction

    Science.gov (United States)

    Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

    2017-09-01

    Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

  11. Intelligent Devices in Rural Wireless Networks

    Directory of Open Access Journals (Sweden)

    Daniel FUENTES

    2014-03-01

    Full Text Available The rural wireless networks are increasingly in demand by associations and autarchies to expand Internet access in this type of areas. The problem of such solutions centers not only in network deployment and its maintenance, but also in the equipment installation on clients, which always has big costs. This installation and configuration must be performed by a technician on site, so that the equipment can be integrated in the infrastructure. To try to mitigate this problem, it is presented a solution that allows the clients to install, with transparency, the device at home, reducing not only the cost for the management entity but also for the clients. This way, for info-excluded people or with new technology low experience level, it is the user that integrates himself in the network, making him part of the process, fostering the network usage.In this article are specified not only the system architecture but also the way that it works and how it obtains the desirable result. The tests made to the solution show the quickness, reliability and autonomy in the execution of the tasks, making it a benefit for rural wireless networks.This solution, by its robustness and simplicity, allowed an uptake to the IT by people who never thought to do it, namely an advanced age group (elderly who want to join the world of the new technologies

  12. Customer Intelligence Analytics on Social Networks

    Directory of Open Access Journals (Sweden)

    Brano MARKIĆ

    2016-08-01

    Full Text Available Discovering needs, habits and consumer behavior is the primary task of marketing analytics. It is necessary to integrate marketing and analytical skills with IT skills. Such knowledge integration allows access to data (structured and unstructured, their analysis and finding out information about the opinions, attitudes, needs and behavior of customers. In the paper is set the hypothesis that software tools can collect data (messages from social networks, analyze the content of messages and get to know the attitudes of customers about a product, service, tourist destination with the ultimate goal of improving customer relations. Experimental results are based on the analysis of the content of social network Facebook by using the package and function R language. This language showed a satisfactory application and development power in analysis of textual data on social networks for marketing analytics.

  13. Out of the shadow: Long term cost development of intelligent sensor networks

    NARCIS (Netherlands)

    Fledderus, E.R; Kester, L.J.H.M.; Kranenburg-Bruinsma, K. van

    2013-01-01

    The paper addresses intelligent sensor networks (ISNs) as a special version of networked wireless robotics. The success of these networks is partly explained by the technical advances, but as well by cutting down costs of these networks. Using a functional breakdown of intelligent ISNs, the trends

  14. Small Area Array-Based LED Luminaire Design

    Energy Technology Data Exchange (ETDEWEB)

    Thomas Yuan

    2008-01-09

    This report contains a summary of technical achievements during a three-year project to demonstrate high efficiency LED luminaire designs based on small area array-based gallium nitride diodes. Novel GaN-based LED array designs are described, specifically addressing the thermal, optical, electrical and mechanical requirements for the incorporation of such arrays into viable solid-state LED luminaires. This work resulted in the demonstration of an integrated luminaire prototype of 1000 lumens cool white light output with reflector shaped beams and efficacy of 89.4 lm/W at CCT of 6000oK and CRI of 73; and performance of 903 lumens warm white light output with reflector shaped beams and efficacy of 63.0 lm/W at CCT of 2800oK and CRI of 82. In addition, up to 1275 lumens cool white light output at 114.2 lm/W and 1156 lumens warm white light output at 76.5 lm/W were achieved if the reflector was not used. The success to integrate small area array-based LED designs and address thermal, optical, electrical and mechanical requirements was clearly achieved in these luminaire prototypes with outstanding performance and high efficiency.

  15. 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

  16. INTELLIGENT MULTI-AGENT PLATFORM WITHIN COLLABORATIVE NETWORKED ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Adina-Georgeta CREŢAN

    2016-06-01

    Full Text Available This paper proposes an agent-based intelligent platform to model and support parallel and concurrent negotiations among organizations acting in the same industrial market. The underlying complexity is to model the dynamic environment where multi-attribute and multi-participant negotiations are racing over a set of heterogeneous resources. The metaphor Interaction Abstract Machines (IAMs is used to model the parallelism and the non-deterministic aspects of the negotiation processes that occur in Collaborative Networked Environment.

  17. An intelligent management system for corporate information- calculating network development

    CERN Document Server

    Pirogov, V V; Khristenko, D V

    2001-01-01

    An approach to solving the problem of managerial control quality improvement corporate information-calculating networks (CICN) is proposed. The approach is based on the concept of a flexible toolkit. A macro-model, system-science and system-engineering models of an intelligent managerial control system (IMCS) for CICN development are considered as well as its dynamics. The practical opportunity of IMCS implementation is assessed. (5 refs).

  18. Evaluating neural networks and artificial intelligence systems

    Science.gov (United States)

    Alberts, David S.

    1994-02-01

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

  19. Intelligent Network Management and Functional Cerebellum Synthesis

    Science.gov (United States)

    Loebner, Egon E.

    1989-01-01

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

  20. Coordinated Sensing in Intelligent Camera Networks

    OpenAIRE

    Ding, Chong

    2013-01-01

    The cost and size of video sensors has led to camera networks becoming pervasive in our lives. However, the ability to analyze these images efficiently is very much a function of the quality of the acquired images. Human control of pan-tilt-zoom (PTZ) cameras is impractical and unreliable when high quality images are needed of multiple events distributed over a large area. This dissertation considers the problem of automatically controlling the fields of view of individual cameras in a camera...

  1. Intelligent reservoir operation system based on evolving artificial neural networks

    Science.gov (United States)

    Chaves, Paulo; Chang, Fi-John

    2008-06-01

    We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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......-head as the next hop for delivering the messages or to send the data to the base station directly, using Dijkstra algorithm to compute an optimal path. The performance of LEICP is compared with that of LEACH. Simulation results demonstrate that LEICP can prolong the lifetime of the sensor network by about 62...... clustering protocol), an improvement of the LEACH protocol is proposed to overcome the shortcomings of LEACH. LEICP aims at balancing the energy consumption in every cluster and prolonging the network lifetime. A fitness function is defined to balance the energy consumption in every cluster according...

  10. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo

    2014-01-01

    This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

  11. 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.

  12. Intelligent MV Switchgear as an Element of Smart Grid Network

    Directory of Open Access Journals (Sweden)

    Janusz Ropa

    2015-12-01

    Full Text Available In the paper the family of intelligent switchgears, developed by a consortium formed by Tele and Radio Research Institute, Transformex sp. o.o., Elektromontaż Lublin and Łódź University of Technology, has been presented as an element of a Smart Grid power network. The switchgear has been equipped with innovative, hybrid current-voltage transducers made using multilayer printed circuit board technology. In the paper the concept of the switchgear, the construction of the transducers and the electronic module integrating the transducer with protection relay input circuit have been described. The intelligent bay controller implemented in the switchgear contains several modules such as Smart Metering, Smart Control, Smart Communication (IEC 61850 and integrates easily with Smart Grid power networks. The bay controller is additionally equipped with a circuit breaker (CB diagnostics module (Smart Diagnostics, which analyses CB parameters during its operation. It generates early warning signals about imminent failure likely to happen between periodic inspections and in this way enhances the reliability and safety of network operation. The switchgear contains also the fault recorder and criterion recorder (Smart Recorder/Logger, that facilitates diagnosing the failure events.

  13. Development of High Efficacy, Low Cost Phosphorescent Oled Lightning Luminaire

    Energy Technology Data Exchange (ETDEWEB)

    Michael Hack

    2010-07-09

    In this two year program, UDC together with Armstrong World Industries, Professor Stephen Forrest (University of Michigan) and Professor Mark Thompson (University of Southern California) planned to develop and deliver high efficiency OLED lighting luminaires as part of an integrated ceiling illumination system that exceed the Department of Energy (DOE) 2010 performance projections. Specifically the UDC team in 2010 delivered two prototype OLED ceiling illumination systems, each consisting of four individual OLED lighting panels on glass integrated into Armstrong's novel TechZone open architecture ceiling systems, at an overall system efficacy of 51 lm/W, a CRI = 85 and a projected lifetime to 70% of initial luminance to exceed 10,000 hours. This accomplishment represents a 50% increase in luminaire efficacy and a factor of two in lifetime over that outlined in the solicitation. In addition, the team has also delivered one 15cm x 15cm lighting panel fabricated on a flexible metal foil substrate, demonstrating the possibility using OLEDs in a range of form factors. During this program, our Team has pursued the commercialization of these OLED based ceiling luminaires, with a goal to launch commercial products within the next three years. We have proven that our team is ideally suited to develop these highly novel and efficient solid state lighting luminaires, having both the technical experience and commercial strategy to leverage work performed under this contract. Our calculations show that the success of our program could lead to energy savings of more than 0.5 quads or 8 MMTC (million metric tons of carbon) per year by 2016.

  14. 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.

  15. Intelligent network video understanding modern video surveillance systems

    CERN Document Server

    Nilsson, Fredrik

    2008-01-01

    Offering ready access to the security industry's cutting-edge digital future, Intelligent Network Video provides the first complete reference for all those involved with developing, implementing, and maintaining the latest surveillance systems. Pioneering expert Fredrik Nilsson explains how IP-based video surveillance systems provide better image quality, and a more scalable and flexible system at lower cost. A complete and practical reference for all those in the field, this volume:Describes all components relevant to modern IP video surveillance systemsProvides in-depth information about ima

  16. 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.

  17. 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...

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. CALiPER Report 23: Photometric Testing of White Tunable LED Luminaires

    Energy Technology Data Exchange (ETDEWEB)

    None, None

    2016-01-01

    This report documents an initial investigation of photometric testing procedures for white-tunable LED luminaires and summarizes the key features of those products. Goals of the study include understanding the amount of testing required to characterize a white-tunable product, and documenting the performance of available color-tunable luminaires that are intended for architectural lighting.

  4. LOW-COST LED LUMINAIRE FOR GENERAL ILLUMINATION

    Energy Technology Data Exchange (ETDEWEB)

    Lowes, Ted

    2014-07-31

    During this two-year Solid-State Lighting (SSL) Manufacturing R&D project Cree developed novel light emitting diode (LED) technologies contributing to a cost-optimized, efficient LED troffer luminaire platform emitting at ~3500K correlated color temperature (CCT) at a color rendering index (CRI) of >90. To successfully achieve program goals, Cree used a comprehensive approach to address cost reduction of the various optical, thermal and electrical subsystems in the luminaire without impacting performance. These developments built on Cree’s high- brightness, low-cost LED platforms to design a novel LED component architecture that will enable low-cost troffer luminaire designs with high total system efficacy. The project scope included cost reductions to nearly all major troffer subsystems as well as assembly costs. For example, no thermal management components were included in the troffer, owing to the optimized distribution of compact low- to mid-power LEDs. It is estimated that a significant manufacturing cost savings will result relative to Cree’s conventional troffers at the start of the project. A chief project accomplishment was the successful development of a new compact, high-efficacy LED component geometry with a broad far-field intensity distribution and even color point vs. emission angle. After further optimization and testing for production, the Cree XQ series of LEDs resulted. XQ LEDs are currently utilized in Cree’s AR series troffers, and they are being considered for use in other platforms. The XQ lens geometry influenced the independent development of Cree’s XB-E and XB-G high-voltage LEDs, which also have a broad intensity distribution at high efficacy, and are finding wide implementation in Cree’s omnidirectional A-lamps.

  5. Intelligent systems II complete approximation by neural network operators

    CERN Document Server

    Anastassiou, George A

    2016-01-01

    This monograph is the continuation and completion of the monograph, “Intelligent Systems: Approximation by Artificial Neural Networks” written by the same author and published 2011 by Springer. The book you hold in hand presents the complete recent and original work of the author in approximation by neural networks. Chapters are written in a self-contained style and can be read independently. Advanced courses and seminars can be taught out of this brief book. All necessary background and motivations are given per chapter. A related list of references is given also per chapter. The book’s results are expected to find applications in many areas of applied mathematics, computer science and engineering. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also for all science and engineering libraries.  .

  6. 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.

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

    Science.gov (United States)

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

    2012-07-01

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

  8. Next Generation Luminaire (NGL) Downlight Demonstration Project, Hilton Columbus Downtown

    Energy Technology Data Exchange (ETDEWEB)

    Davis, R. G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Perrin, T. E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-09-30

    At the Hilton Columbus Downtown hotel in Ohio, DOE's Better Buildings Alliance conducted a demonstration of Next Generation Luminaires-winning downlights installed in all guest rooms and suites prior to the hotel's 2012 opening. After a post-occupancy assessment, the LED downlights not only provided the aesthetic appearance and dimming functionality desired, but also provided 50% energy savings relative to a comparable CFL downlight and enabled the lighting power to be more than 20% below that allowed by code.

  9. 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.

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

    Science.gov (United States)

    2017-10-01

    sensitive information. For tactical purposes, intelligence value is proportional to time, where the operational and strategic value is not as diminished...HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS by Luis A. Morales, Major, USAF A Research...PED) process does not satisfy the demands for intelligence to warfighters. Data production rate from Imagery Intelligence (IMINT) sensors far

  11. 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 ...

  12. 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.

  13. Final Report: System Reliability Model for Solid-State Lighting (SSL) Luminaires

    Energy Technology Data Exchange (ETDEWEB)

    Davis, J. Lynn [RTI International, Research Triangle Park, NC (United States)

    2017-05-31

    The primary objectives of this project was to develop and validate reliability models and accelerated stress testing (AST) methodologies for predicting the lifetime of integrated SSL luminaires. This study examined the likely failure modes for SSL luminaires including abrupt failure, excessive lumen depreciation, unacceptable color shifts, and increased power consumption. Data on the relative distribution of these failure modes were acquired through extensive accelerated stress tests and combined with industry data and other source of information on LED lighting. This data was compiled and utilized to build models of the aging behavior of key luminaire optical and electrical components.

  14. Life Prediction and Classification of Failure Modes in Solid State Luminaires Using Bayesian Probabilistic Models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-05-27

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  15. 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…

  16. 77 FR 3544 - Meeting and Webinar on the Active Traffic and Demand Management and Intelligent Network Flow...

    Science.gov (United States)

    2012-01-24

    ... Management and Intelligent Network Flow Optimization Operational Concepts; Notice of Public Meeting AGENCY... Traffic and Demand Management (ADTM) and Intelligent Network Flow Optimization (INFLO) operational... transportation network. Issued in Washington, DC, on the 18th day of January 2012. John Augustine, Managing...

  17. Fluid Intelligence Predicts Novel Rule Implementation in a Distributed Frontoparietal Control Network.

    Science.gov (United States)

    Tschentscher, Nadja; Mitchell, Daniel; Duncan, John

    2017-05-03

    Fluid intelligence has been associated with a distributed cognitive control or multiple-demand (MD) network, comprising regions of lateral frontal, insular, dorsomedial frontal, and parietal cortex. Human fluid intelligence is also intimately linked to task complexity, and the process of solving complex problems in a sequence of simpler, more focused parts. Here, a complex target detection task included multiple independent rules, applied one at a time in successive task epochs. Although only one rule was applied at a time, increasing task complexity (i.e., the number of rules) impaired performance in participants of lower fluid intelligence. Accompanying this loss of performance was reduced response to rule-critical events across the distributed MD network. The results link fluid intelligence and MD function to a process of attentional focus on the successive parts of complex behavior. SIGNIFICANCE STATEMENT Fluid intelligence is intimately linked to the ability to structure complex problems in a sequence of simpler, more focused parts. We examine the basis for this link in the functions of a distributed frontoparietal or multiple-demand (MD) network. With increased task complexity, participants of lower fluid intelligence showed reduced responses to task-critical events. Reduced responses in the MD system were accompanied by impaired behavioral performance. Low fluid intelligence is linked to poor foregrounding of task-critical information across a distributed MD system. Copyright © 2017 Tschentscher et al.

  18. An intelligent scheduling method based on improved particle swarm optimization algorithm for drainage pipe network

    Science.gov (United States)

    Luo, Yaqi; Zeng, Bi

    2017-08-01

    This paper researches the drainage routing problem in drainage pipe network, and propose an intelligent scheduling method. The method relates to the design of improved particle swarm optimization algorithm, the establishment of the corresponding model from the pipe network, and the process by using the algorithm based on improved particle swarm optimization to find the optimum drainage route in the current environment.

  19. Brain Network Architecture and Global Intelligence in Children with Focal Epilepsy.

    Science.gov (United States)

    Paldino, M J; Golriz, F; Chapieski, M L; Zhang, W; Chu, Z D

    2017-02-01

    The biologic basis for intelligence rests to a large degree on the capacity for efficient integration of information across the cerebral network. We aimed to measure the relationship between network architecture and intelligence in the pediatric, epileptic brain. Patients were retrospectively identified with the following: 1) focal epilepsy; 2) brain MR imaging at 3T, including resting-state functional MR imaging; and 3) full-scale intelligence quotient measured by a pediatric neuropsychologist. The cerebral cortex was parcellated into approximately 700 gray matter network "nodes." The strength of a connection between 2 nodes was defined by the correlation between their blood oxygen level-dependent time-series. We calculated the following topologic properties: clustering coefficient, transitivity, modularity, path length, and global efficiency. A machine learning algorithm was used to measure the independent contribution of each metric to the intelligence quotient after adjusting for all other metrics. Thirty patients met the criteria (4-18 years of age); 20 patients required anesthesia during MR imaging. After we accounted for age and sex, clustering coefficient and path length were independently associated with full-scale intelligence quotient. Neither motion parameters nor general anesthesia was an important variable with regard to accurate intelligence quotient prediction by the machine learning algorithm. A longer history of epilepsy was associated with shorter path lengths (P = .008), consistent with reorganization of the network on the basis of seizures. Considering only patients receiving anesthesia during machine learning did not alter the patterns of network architecture contributing to global intelligence. These findings support the physiologic relevance of imaging-based metrics of network architecture in the pathologic, developing brain. © 2017 by American Journal of Neuroradiology.

  20. Image recognition and neuronal networks: intelligent systems for the improvement of imaging information.

    Science.gov (United States)

    Karkanis, S; Magoulas, G D; Theofanous, N

    2000-01-01

    Intelligent computerised systems can provide useful assistance to the physician in the rapid identification of tissue abnormalities and accurate diagnosis in real-time. This paper reviews basic issues in medical imaging and neural network-based systems for medical image interpretation. In the framework of intelligent systems, a simple scheme that has been implemented is presented as an example of the use of intelligent systems to discriminate between normal and cancerous regions in colonoscopic images. Preliminary results indicate that this scheme is capable of high accuracy detection of abnormalities within the image. It can also be successfully applied to different types of images, to detect abnormalities that belong to different cancer types.

  1. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-09-01

    Intelligence is the ability to learn from past experience and, in general, to adapt to, shape, and select environments. Aspects of intelligence are measured by standardized tests of intelligence. Average raw (number-correct) scores on such tests vary across the life span and also across generations, as well as across ethnic and socioeconomic groups. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex. Measured values correlate with brain size, at least within humans. The heritability coefficient (ratio of genetic to phenotypic variation) is between 0.4 and 0.8. But genes always express themselves through environment. Heritability varies as a function of a number of factors, including socioeconomic status and range of environments. Racial-group differences in measured intelligence have been reported, but race is a socially constructed rather than biological variable. As a result, these differences are difficult to interpret. Different cultures have different conceptions of the nature of intelligence, and also require different skills in order to express intelligence in the environment. WIREs Cogn Sci 2012 doi: 10.1002/wcs.1193 For further resources related to this article, please visit the WIREs website. Copyright © 2012 John Wiley & Sons, Ltd.

  2. Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks

    OpenAIRE

    Nabil Ali Alrajeh; Lloret, J.

    2013-01-01

    Intrusion detection system (IDS) is regarded as the second line of defense against network anomalies and threats. IDS plays an important role in network security. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are widely used for threats detection. This paper presents a critical study on genetic algorithm, artificial immune, and artificial neural network (ANN) based IDSs techniques used in wireless sensor netw...

  3. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

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

  4. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

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

  5. 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...

  6. 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...... to predict, to a very high level of accuracy, a state of congestion based upon the training data collected about the network behaviour. Initially, the current traffic shaping technologies are discussed and later a simulation in a controlled environment is illustrated to exhibit the effects...

  7. Intelligent Joint Admission Control for Next Generation Wireless Networks

    OpenAIRE

    Abdulqader M. Mohsen; Al-Akwaa, Fadhl M.; Mohammed M. Alkhawlani

    2012-01-01

    The Heterogeneous Wireless Network (HWN) integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC) handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN) by the initia...

  8. Intelligent vertical handover management in heterogeneous wireless networks

    OpenAIRE

    Haider, Ammar

    2017-01-01

    The upcoming generation of wireless networks are characterized by seamless mobility across wireless access networks belonging to different radio access technologies. This requires the heterogeneous access networks to be integrated together, and the mobile terminals to be equipped with multiple radio interfaces allowing the users to roam across different networks. Vertical Handover (VHO) is the process of transparent switching from one access network to other. To achieve seamless heterogeneous...

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

    Science.gov (United States)

    Livingstone, Randall M.

    2012-01-01

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

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

    Science.gov (United States)

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

    1998-01-01

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

  11. Modeling the impact of thermal effects on luminous flux maintenance for SSL luminaires

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Lynn [RTI International, Research Triangle Park, NC (United States); Mills, Karmann [RTI International, Research Triangle Park, NC (United States); Lamvik, Michael [RTI International, Research Triangle Park, NC (United States); Solano, Eric [RTI International, Research Triangle Park, NC (United States); Bobashev, Georgiy [RTI International, Research Triangle Park, NC (United States); Perkins, Curtis [RTI International, Research Triangle Park, NC (United States)

    2017-05-30

    Meeting the longevity requirements of solid-state lighting (SSL) devices places extreme demands on the materials and designs that are used in SSL luminaires. Therefore, understanding the aging characteristics of lens, reflectors, and other materials is essential to projecting the long-term performance of LED-based lighting systems. Overlooking these factors at either the design or product specification stage can result in premature failure of the device due to poor luminous flux maintenance and/or excessive chromaticity shifts. This paper describes a methodology for performing accelerated stress testing (AST) on materials intended for use in SSL luminaires. This test methodology, which consists of elevated temperature and humidity conditions, produces accelerated aging data that can be correlated to expected performance under normal luminaire operating conditions. The correlations can then be leveraged to produce models of the changes in the optical properties of key materials including transmittance versus wavelength of lenses and reflectance versus wavelength for housings and other reflectors. This information has been collected into a lumen maintenance decision support tool (LM-DST) and together with user supplied inputs (e.g., expected operation conditions) can provide guidance on lifetime expectations of SSL luminaires. This approach has been applied to a variety of materials commonly found in SSL luminaires including acrylics, polycarbonates, and silicones used for lenses and paints, coatings, films, and composites used for reflectors.

  12. 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.

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

    Science.gov (United States)

    Ranganayaki, V.; Deepa, S. N.

    2016-01-01

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

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

    Science.gov (United States)

    Ranganayaki, V; Deepa, S N

    2016-01-01

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

  15. 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

  16. 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.

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

    Science.gov (United States)

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

    2011-01-01

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

  18. Amigo - Ambient Intelligence for the networked home environment

    NARCIS (Netherlands)

    Janse, M.D.

    2008-01-01

    The Amigo project develops open, standardized, interoperable middleware and attractive user services for the networked home environment. Fifteen of Europe's leading companies and research organizations in mobile and home networking, software development, consumer electronics and domestic appliances

  19. Artificial intelligence based event detection in wireless sensor networks

    NARCIS (Netherlands)

    Bahrepour, M.

    2013-01-01

    Wireless sensor networks (WSNs) are composed of large number of small, inexpensive devices, called sensor nodes, which are equipped with sensing, processing, and communication capabilities. While traditional applications of wireless sensor networks focused on periodic monitoring, the focus of more

  20. Demand Engineering: IP Network Optimisation Through Intelligent Demand Placement

    OpenAIRE

    Evans, John; Afrakteh, Arash; Xiu, Ruoyang

    2016-01-01

    Traffic engineering has been used in IP and MPLS networks for a number of years as a tool for making more efficient use of capacity by explicitly routing traffic demands where there is available network capacity that would otherwise be unused. Deployment of traffic engineering imposes an additional layer of complexity to network design and operations, however, which has constrained its adoption for capacity optimisation. The rise of Software Defined Networks has renewed interest in the use of...

  1. 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.

  2. 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.

  3. Design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization

    CERN Document Server

    Castillo, Oscar; Kacprzyk, Janusz

    2015-01-01

    This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in eight main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents div...

  4. Artificial intelligence-based 5G network capacity planning and operation

    OpenAIRE

    Pérez Romero, Jordi; Sallent Roig, José Oriol; Ferrús Ferré, Ramón Antonio; Agustí Comes, Ramon

    2015-01-01

    The highly demanding requirements envisaged for future 5G networks together with the required support of new customers from vertical industries (e.g. e-health, automotive, energy) pose a big challenge for operators in 5G on how to balance investments, user experience and profitability. There will be the need to revisit the actual methodologies of network planning and operation, fully exploiting cognitive capabilities that embrace knowledge and intelligence to achie...

  5. Effects of Personality on Social Network Disclosure: Do Emotionally Intelligent Individuals Post Inappropriate Content?

    OpenAIRE

    Chockalingam Viswesvaran; Kerry Newness; Jason Steinert

    2012-01-01

    The prevalence of individuals using social networking sites to stay connected has increased considerably in only a few years and the information posted is now being used by organizations for employee selection. The purpose of the current study was to investigating how differences on the Big Five Personality traits, honesty-integrity, and emotional intelligence influence whether individuals post inappropriate social network content. Participants were 506 college students from a large metropoli...

  6. Research on architecture of intelligent design platform for artificial neural network expert system

    Science.gov (United States)

    Gu, Honghong

    2017-09-01

    Based on the review of the development and current situation of CAD technology, the necessity of combination of artificial neural network and expert system, and then present an intelligent design system based on artificial neural network. Moreover, it discussed the feasibility of realization of a design-oriented expert system development tools on the basis of above combination. In addition, knowledge representation strategy and method and the solving process are given in this paper.

  7. 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.

  8. Artificial intelligence based event detection in wireless sensor networks

    OpenAIRE

    Bahrepour, M.

    2013-01-01

    Wireless sensor networks (WSNs) are composed of large number of small, inexpensive devices, called sensor nodes, which are equipped with sensing, processing, and communication capabilities. While traditional applications of wireless sensor networks focused on periodic monitoring, the focus of more recent applications is on fast and reliable identification of out-of-ordinary situations and events. This new functionality of wireless sensor networks is known as event detection. Due to the fact t...

  9. 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.

  10. Software implementation of artificial neural networks in automated intelligent systems

    Directory of Open Access Journals (Sweden)

    В.П. Харченко

    2009-02-01

    Full Text Available  Application of neural networks technologies effectively decides the task of synthesis of origin of accident risk and gives out the vector of managing signals of network on incomplete and distorted information about the phenomena, events and processes which influence on safety flights.

  11. Intelligent Control of Urban Road Networks: Algorithms, Systems and Communications

    Science.gov (United States)

    Smith, Mike

    This paper considers control in road networks. Using a simple example based on the well-known Braess network [1] the paper shows that reducing delay for traffic, assuming that the traffic distribution is fixed, may increase delay when travellers change their travel choices in light of changes in control settings and hence delays. It is shown that a similar effect occurs within signal controlled networks. In this case the effect appears at first sight to be much stronger: the overall capacity of a network may be substantially reduced by utilising standard responsive signal control algorithms. In seeking to reduce delays for existing flows, these policies do not allow properly for consequent routeing changes by travellers. Control methods for signal-controlled networks that do take proper account of the reactions of users are suggested; these require further research, development, and careful real-life trials.

  12. Intelligent Fault Diagnosis in a Power Distribution Network

    Directory of Open Access Journals (Sweden)

    Oluleke O. Babayomi

    2016-01-01

    Full Text Available This paper presents a novel method of fault diagnosis by the use of fuzzy logic and neural network-based techniques for electric power fault detection, classification, and location in a power distribution network. A real network was used as a case study. The ten different types of line faults including single line-to-ground, line-to-line, double line-to-ground, and three-phase faults were investigated. The designed system has 89% accuracy for fault type identification. It also has 93% accuracy for fault location. The results indicate that the proposed technique is effective in detecting, classifying, and locating low impedance faults.

  13. Social Networks and Collective Intelligence: A Return to the Agora

    DEFF Research Database (Denmark)

    Mazzara, Manuel; Biselli, Luca; Greco, Pier Paolo

    2013-01-01

    for bottom-up self-protection and social privacy. By presenting the Polidoxa solution, this work also describes the current state of traditional media as well as newer ones, providing an accurate analysis of major search engines such as Google and social network (e.g., Facebook). The advantages that Polidoxa......? credibility be fairly assessed? How can gatekeeping processes be found trustworthy when filtering out news and deciding ranking and priorities of traditional media? An Internet-based solution to a human-based ancient issue is being studied, and it is called Polidoxa, from Greek "poly", meaning "many...... backgrounds and institutes with significantly different agendas. Polidoxa aims at offering: 1) a trust-based search engine algorithm, which exploits stigmergic behaviours of users? network, 2) a trust-based social network, where the notion of trust derives from network activity and 3) a holonic system...

  14. INTELLIGENT VERTICAL HANDOVER FOR HETEROGONOUS NETWORKS USING FL AND ELECTRE

    OpenAIRE

    Mohammed M. Alkhawlani

    2011-01-01

    The future Heterogeneous Wireless Network (HWN) is composed of multiple Radio Access Technologies(RATs) and domains, therefore, new Radio Resource Management (RRM) schemes and mechanisms arenecessary to benefit from the individual characteristics of each RAT and to exploit the gain resultingfrom jointly considering the whole set of the available radio resources in each RAT. Vertical Handover(VHO) enables users to access several networks such as WLAN, WMAN, WPAN, and WWAN in parallel.It allows...

  15. Ubiquitous Sensor Networks in IMS: an Ambient Intelligence Telco Platform

    OpenAIRE

    Bernat Vercher, Jesús; Perez Marin, Santiago; Gonzalez Lucas, Agustin; Sorribas Mollon, Rafael; Villarrubia Grande, Luis; Campoy Cervera, Luis M.; Hernández Gómez, Luis Alfonso

    2008-01-01

    Ubiquitous Sensor Network (USN) concept describes the integration of heterogeneous and geographically dispersed Wireless Sensor and Actuator Networks (WS&AN) into rich information infrastructures for accurate representation and access to different dynamic user’s physical contexts. This relatively new concept envisions future Sensor-Based Services leading to market disruptive innovations in a broad range of application domains, mainly personal (lifestyle assistants), community (professional us...

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

    Directory of Open Access Journals (Sweden)

    Yongcheng Li

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

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

    Science.gov (United States)

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

    2015-01-01

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

  18. Association between resting-state coactivation in the parieto-frontal network and intelligence during late childhood and adolescence.

    Science.gov (United States)

    Li, C; Tian, L

    2014-06-01

    A number of studies have associated the adult intelligence quotient with the structure and function of the bilateral parieto-frontal networks, whereas the relationship between intelligence quotient and parieto-frontal network function has been found to be relatively weak in early childhood. Because both human intelligence and brain function undergo protracted development into adulthood, the purpose of the present study was to provide a better understanding of the development of the parieto-frontal network-intelligence quotient relationship. We performed independent component analysis of resting-state fMRI data of 84 children and 50 adolescents separately and then correlated full-scale intelligence quotient with the spatial maps of the bilateral parieto-frontal networks of each group. In children, significant positive spatial-map versus intelligence quotient correlations were detected in the right angular gyrus and inferior frontal gyrus in the right parieto-frontal network, and no significant correlation was observed in the left parieto-frontal network. In adolescents, significant positive correlation was detected in the left inferior frontal gyrus in the left parieto-frontal network, and the correlations in the frontal pole in the 2 parieto-frontal networks were only marginally significant. The present findings not only support the critical role of the parieto-frontal networks for intelligence but indicate that the relationship between intelligence quotient and the parieto-frontal network in the right hemisphere has been well established in late childhood, and that the relationship in the left hemisphere was also established in adolescence. © 2014 by American Journal of Neuroradiology.

  19. Development of constant-power driving control for light-emitting-diode (LED) luminaire

    KAUST Repository

    Huang, Bin-Juine

    2013-01-01

    The illumination of an LED may be affected by operating temperature even under constant-current condition. A constant-power driving technique is proposed in the present study for LED luminaire. A linear system dynamics model of LED luminaire is first derived and used in the design of the feedback control system. The PI controller was designed and tuned taking into account the control accuracy and robust properties with respect to plant uncertainty and variation of operating conditions. The control system was implemented on a microprocessor and used to control a 150W LED luminaire. The test result shows that the feedback system accurately controls the input power of LED luminaire to within 1.3 per cent error. As the ambient temperature changes from 0 to 40 °C, the LED illumination varies slightly (-1.7%) for constant-power driving, as compared to that of constant-current driving (-12%) and constant-voltage driving (+50%). The constant-power driving has revealed advantage in stabilizing the illumination of LED under large temperature variation. © 2012 Elsevier Ltd. All rights reserved.

  20. Exploiting Mobile Ad Hoc Networking and Knowledge Generation to Achieve Ambient Intelligence

    Directory of Open Access Journals (Sweden)

    Anna Lekova

    2012-01-01

    Full Text Available Ambient Intelligence (AmI joins together the fields of ubiquitous computing and communications, context awareness, and intelligent user interfaces. Energy, fault-tolerance, and mobility are newly added dimensions of AmI. Within the context of AmI the concept of mobile ad hoc networks (MANETs for “anytime and anywhere” is likely to play larger roles in the future in which people are surrounded and supported by small context-aware, cooperative, and nonobtrusive devices that will aid our everyday life. The connection between knowledge generation and communication ad hoc networking is symbiotic—knowledge generation utilizes ad hoc networking to perform their communication needs, and MANETs will utilize the knowledge generation to enhance their network services. The contribution of the present study is a distributed evolving fuzzy modeling framework (EFMF to observe and categorize relationships and activities in the user and application level and based on that social context to take intelligent decisions about MANETs service management. EFMF employs unsupervised online one-pass fuzzy clustering method to recognize nodes' mobility context from social scenario traces and ubiquitously learn “friends” and “strangers” indirectly and anonymously.

  1. Analysis and application of intelligence network based on FTTH

    Science.gov (United States)

    Feng, Xiancheng; Yun, Xiang

    2008-12-01

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

  2. Navigation Behaviors Based on Fuzzy ArtMap Neural Networks for Intelligent Autonomous Vehicles

    Directory of Open Access Journals (Sweden)

    Amine Chohra

    2011-01-01

    Full Text Available The use of hybrid intelligent systems (HISs is necessary to bring the behavior of intelligent autonomous vehicles (IAVs near the human one in recognition, learning, adaptation, generalization, decision making, and action. First, the necessity of HIS and some navigation approaches based on fuzzy ArtMap neural networks (FAMNNs are discussed. Indeed, such approaches can provide IAV with more autonomy, intelligence, and real-time processing capabilities. Second, an FAMNN-based navigation approach is suggested. Indeed, this approach must provide vehicles with capability, after supervised fast stable learning: simplified fuzzy ArtMap (SFAM, to recognize both target-location and obstacle-avoidance situations using FAMNN1 and FAMNN2, respectively. Afterwards, the decision making and action consist of two association stages, carried out by reinforcement trial and error learning, and their coordination using NN3. Then, NN3 allows to decide among the five (05 actions to move towards 30∘, 60∘, 90∘, 120∘, and 150∘. Third, simulation results display the ability of the FAMNN-based approach to provide IAV with intelligent behaviors allowing to intelligently navigate in partially structured environments. Finally, a discussion, dealing with the suggested approach and how its robustness would be if implemented on real vehicle, is given.

  3. Scalable Light Module for Low-Cost, High-Efficiency Light- Emitting Diode Luminaires

    Energy Technology Data Exchange (ETDEWEB)

    Tarsa, Eric [Cree, Inc., Goleta, CA (United States)

    2015-08-31

    During this two-year program Cree developed a scalable, modular optical architecture for low-cost, high-efficacy light emitting diode (LED) luminaires. Stated simply, the goal of this architecture was to efficiently and cost-effectively convey light from LEDs (point sources) to broad luminaire surfaces (area sources). By simultaneously developing warm-white LED components and low-cost, scalable optical elements, a high system optical efficiency resulted. To meet program goals, Cree evaluated novel approaches to improve LED component efficacy at high color quality while not sacrificing LED optical efficiency relative to conventional packages. Meanwhile, efficiently coupling light from LEDs into modular optical elements, followed by optimally distributing and extracting this light, were challenges that were addressed via novel optical design coupled with frequent experimental evaluations. Minimizing luminaire bill of materials and assembly costs were two guiding principles for all design work, in the effort to achieve luminaires with significantly lower normalized cost ($/klm) than existing LED fixtures. Chief project accomplishments included the achievement of >150 lm/W warm-white LEDs having primary optics compatible with low-cost modular optical elements. In addition, a prototype Light Module optical efficiency of over 90% was measured, demonstrating the potential of this scalable architecture for ultra-high-efficacy LED luminaires. Since the project ended, Cree has continued to evaluate optical element fabrication and assembly methods in an effort to rapidly transfer this scalable, cost-effective technology to Cree production development groups. The Light Module concept is likely to make a strong contribution to the development of new cost-effective, high-efficacy luminaries, thereby accelerating widespread adoption of energy-saving SSL in the U.S.

  4. Analysis of utility-theoretic heuristics for intelligent adaptive network routing

    Energy Technology Data Exchange (ETDEWEB)

    Mikler, A.R.; Honavar, V.; Wong, J.S.K. [Iowa State Univ., Ames, IA (United States)

    1996-12-31

    Utility theory offers an elegant and powerful theoretical framework for design and analysis of autonomous adaptive communication networks. Routing of messages in such networks presents a real-time instance of a multi-criterion optimization problem in a dynamic and uncertain environment. In this paper, we incrementally develop a set of heuristic decision functions that can be used to guide messages along a near-optimal (e.g., minimum delay) path in a large network. We present an analysis of properties of such heuristics under a set of simplifying assumptions about the network topology and load dynamics and identify the conditions under which they are guaranteed to route messages along an optimal path. The paper concludes with a discussion of the relevance of the theoretical results presented in the paper to the design of intelligent autonomous adaptive communication networks and an outline of some directions of future research.

  5. RBF neural network-based online intelligent management of a battery energy storage system for stand-alone microgrids

    National Research Council Canada - National Science Library

    Kerdphol, Thongchart; Qudaih, Yaser; Watanabe, Masayuki; Mitani, Yasunori

    2016-01-01

    ...) in a short period of time.This paper presents a new method for the intelligent online management of both active and reactive power of a BESS based on a radial basis function neural network (RBFNN...

  6. Intelligent networks and energy storage; Intelligente netten en energieopslag

    Energy Technology Data Exchange (ETDEWEB)

    Ongkiehong, O.; Van den Berg, P.

    2012-11-15

    The emergence of decentralized generators cause electricity networks to become more complex and technically difficult to control. This article highlights the role of ICT [Dutch] Door de opkomst van decentrale opwekkers worden elektriciteitsnetten steeds complexer en moeilijker om technisch te beheersen. In dit artikel wordt de rol van ICT belicht.

  7. Control of framed structures using intelligent monitoring networks

    Directory of Open Access Journals (Sweden)

    Foti Dora

    2017-01-01

    Full Text Available The paper proposes the integration of structural monitoring with Building Management Systems for electricity and gas distributions. To assess the state of damage of existing buildings the technics of Structural Health Monitoring (SHM is adopted. SHM as well as to record the occurrence of sudden structural damage resulting from exceptional events (earthquakes, explosions, shocks and collisions with vehicles, etc., allows the monitoring of the progressive damage and structural performance under operating conditions through the extraction of the modal parameters of the structure. This approach requires time to process acquired data that, depending on the size of the building and the number of monitored points, varies from minutes to hours. In this paper, an intelligent system is proposed to immediately communicate during an earthquake the overrun of a certain ground shaking threshold so that gas delivery and selected power loads are interrupted, as suggested by current national regulations on structures. The use of low-cost and reduced size accelerometric sensors integrated with Energy Monitoring Systems is proposed in both highrisk earthquake centers and in all “strategic” buildings that must ensure their operation use immediately after the earthquake. The procedure for calibrating the horizontal and vertical acceleration threshold is also sketched.

  8. Intelligent system to control electric power distribution networks

    Directory of Open Access Journals (Sweden)

    Pablo CHAMOSO

    2016-07-01

    Full Text Available The use of high voltage power lines transport involves some risks that may be avoided with periodic reviews as imposed by law in most countries. The objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. To reduce the number of transmission towers (TT to be reviewed, a virtual organization (VO based system of agents is proposed in conjunction with different artificial intelligence methods and algorithms. This system is able to propose a sample of TT from a selected set to be reviewed and to ensure that the whole set will have similar values without needing to review all the TT. As a result, the system provides a software solution to manage all the review processes and all the TT of Spain, allowing the review companies to use the application either when they initiate a new review process for a whole line or area of TT, or when they want to place an entirely new set of TT, in which case the system would recommend the best place and the best type of structure to use.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

    2017-01-01

    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. PMID:28556817

  14. 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.

  15. Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

    Science.gov (United States)

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

    2011-01-01

    Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This

  16. Designing an LED luminaire with balance between uniformity of luminance and illuminance for non-Lambertian road surfaces.

    Science.gov (United States)

    Teng, Tun-Chien; Sun, Wen-Shing; Lin, Jhih-Li

    2017-04-01

    We present a method of designing a light-emitting diode (LED) luminaire for non-Lambertian road surfaces, in which we optimized the overlap between the lighting areas of a luminaire and its adjacent luminaires to attain balance between uniformity of luminance and illuminance. The goal of the balance is to approach highly uniform luminance and raise illuminance uniformity as high as possible. The optimal illuminance rendered by a single luminaire and the corresponding far-field intensity were derived from the optimal overlap condition, and, thus, the optical model was established. The performance of the model is as follows: overall uniformity of luminance (UO) is 0.91, longitudinal uniformity of Luminance (UL) is 0.92, threshold increment (TI) is 1.64%, uniformity of horizontal illuminance (UHE) is 0.66, and surround ratio (SR) is 0.52. Finally, a compact freeform lens capping an LED was constructed to realize the optical model. The performance of the luminaire designed with arrayed units of an LED capped by the freeform lens is as follows: UO is 0.80, UL is 0.85, TI is 3.57%, UHE is 0.56, and SR is 0.51. In addition, the luminaire provides 19,600 lumens of luminous flux, of which 68% and 54% are projected on the target area and roadway alone, respectively, while 27% is absorbed by the surrounding materials.

  17. 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.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Yung-Shih Chi

    2009-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    Stottler, D.

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

  1. Bayesian probabilistic model for life prediction and fault mode classification of solid state luminaires

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep [Auburn Univ., Auburn, AL (United States); Wei, Junchao [Auburn Univ., Auburn, AL (United States); Sakalaukus, Peter [Auburn Univ., Auburn, AL (United States)

    2014-06-22

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminous flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2014-10-01

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

  4. Ambient intelligence context-based cross-layer design in wireless sensor networks.

    Science.gov (United States)

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

    2014-10-14

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

  5. ELiXIR—Solid-State Luminaire With Enhanced Light Extraction by Internal Reflection

    Science.gov (United States)

    Allen, Steven C.; Steckl, Andrew J.

    2007-06-01

    A phosphor-converted light-emitting diode (pcLED) luminaire featuring enhanced light extraction by internal reflection (ELiXIR) with efficacy of 60 lm/W producing 18 lumens of yellowish green light at 100 mA is presented. The luminaire consists of a commercial blue high power LED, a polymer hemispherical shell lens with interior phosphor coating, and planar aluminized reflector. High extraction efficiency of the phosphor-converted light is achieved by separating the phosphor from the LED and using internal reflection to steer the light away from lossy reflectors and the LED package and out of the device. At 10 and 500 mA, the luminaire produces 2.1 and 66 lumens with efficacies of 80 and 37 lm/W, respectively. Technological improvements over existing commercial LEDs, such as more efficient pcLED packages or, alternatively, higher efficiency green or yellow for color mixing, will be essential to achieving 150 200 lm/W solid-state lighting. Advances in both areas are demonstrated.

  6. 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.

  7. 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.

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

    Science.gov (United States)

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

    2017-02-01

    Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  9. Collective intelligence, social networks and social capital: searching for conceptual connections

    Directory of Open Access Journals (Sweden)

    Julia Bellia Margoto

    2015-04-01

    Full Text Available It is a theoretical essay whose goal was the search for conceptual similarities between the phenomena of collective intelligence, social networking and social capital within the context of the information society. Thereby, those elements are presented and discussed considering different authors. It appears that the concepts covered have numerous points of convergence and strong relations of proximity and complementarity. The conclusions point to the idea that the consideration of these relationships in the theoretical perspectives adopted in the research developed in the fields under consideration, could significantly enrich the results to be achieved.

  10. 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.

  11. 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.

  12. Intelligent Monitoring System on Prediction of Building Damage Index using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Reni Suryanita

    2012-03-01

    Full Text Available An earthquake potentially destroys a tall building. The building damage can be indexed by FEMA into three categories namely Immediate Occupancy (IO, Life Safety (LS, and Collapse Prevention (CP. To determine the damage index, the building model has been simulated into structure analysis software. Acceleration data has been analyzed using non linear method in structure analysis program. The earthquake load is time history at surface, PGA=0105g. This work proposes an intelligent monitoring system utilizing Artificial Neural Network to predict the building damage index. The system also provides an alert system and notification to inform the status of the damage. Data learning is trained on ANN utilizing feed forward and back propagation algorithm. The alert system is designed to be able to activate the alarm sound, view the alert bar or text, and send notification via email to the security or management. The system is tested using sample data represented in three conditions involving IO, LS, and CP. The results show that the proposed intelligent monitoring system could provide prediction of up to 92% rate of accuracy and activate the alert. Implementation of the system in building monitoring would allow for rapid, intelligent and accurate prediction of the building damage index due to earthquake.

  13. 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...

  14. Emotional intelligence is associated with connectivity within and between resting state networks.

    Science.gov (United States)

    Killgore, William D S; Smith, Ryan; Olson, Elizabeth A; Weber, Mareen; Rauch, Scott L; Nickerson, Lisa D

    2017-10-01

    Emotional intelligence (EI) is defined as an individual's capacity to accurately perceive, understand, reason about, and regulate emotions, and to apply that information to facilitate thought and achieve goals. Although EI plays an important role in mental health and success in academic, professional and social realms, the neurocircuitry underlying this capacity remains poorly characterized, and no study to date has yet examined the relationship between EI and intrinsic neural network function. Here, in a sample of 54 healthy individuals (28 women, 26 men), we apply independent components analysis (ICA) with dual regression to functional magnetic resonance imaging (fMRI) data acquired while subjects were resting in the scanner to investigate brain circuits (intrinsic resting state networks) whose activity is associated with greater self-reported (i.e. Trait) and objectively measured (i.e. Ability) EI. We show that higher Ability EI, but not Trait EI, is associated with stronger negatively correlated spontaneous fMRI signals between the basal ganglia/limbic network (BGN) and posterior default mode network (DMN), and regions involved in emotional processing and regulation. Importantly, these findings suggest that the functional connectivity within and between intrinsic networks associated with mentation, affective regulation, emotion processing, and reward are strongly related to ability EI. © The Author (2017). Published by Oxford University Press.

  15. 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.

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

    Science.gov (United States)

    Chiang, Kai-Wei; Chang, Hsiu-Wen

    2010-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  18. National Intelligence Systems as Networks: Power Distribution and Organizational Risk in Brazil, Russia, India, China, and South Africa

    Directory of Open Access Journals (Sweden)

    Marco Cepik

    2017-04-01

    Full Text Available This article compares the intelligence systems of Brazil, Russia, India, China, and South Africa. Three questions drive the research: How are the national intelligence systems organized? How is power distributed among organizations in each country? What are the organizational risks? By employing Network Analysis to publicly-available data on intelligence agencies, collegiate bodies, and supervising organizations, authority relations and information flows were mapped. Regarding organizational configuration, similarities were found between India and Russia, as well as between China and South Africa. Brazil differs from the four countries. As for the power distribution, in Russia, Brazil, and India intelligence is subordinated to the government, and shows more centrality in the cases of China and South Africa. Finally, Russia runs the highest risk of having an intelligence system less able to adapt to strategic circumstances, at the same time being the most resilient among the five countries. Likewise, China has the highest risk of a single actor being able to retain information, acting as a gatekeeper. Network Analysis has proved to be a useful approach to promote a comparative research program in the Intelligence Studies field.

  19. 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.

  20. 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.

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

    Science.gov (United States)

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

    2015-08-01

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

  2. 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. PMID:26609303

  3. 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.

  4. 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.

  5. A Swarm Intelligent Algorithm Based Route Maintaining Protocol for Mobile Sink Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaoming Wu

    2015-01-01

    Full Text Available Recent studies have shown that mobile sink can be a solution to solve the problem that energy consumption of sensor nodes is not balanced in wireless sensor networks (WSNs. Caused by the sink mobility, the paths between the sensor nodes and the sink change frequently and have profound influence on the lifetime of WSN. It is necessary to design a protocol that can find efficient routings between the mobile sink and nodes but does not consume too many network resources. In this paper, we propose a swarm intelligent algorithm based route maintaining protocol to resolve this issue. The protocol utilizes the concentric ring mechanism to guide the route researching direction and adopts the optimal routing selection to maintain the data delivery route in mobile sink WSN. Using the immune based artificial bee colony (IABC algorithm to optimize the forwarding path, the routing maintaining protocol could find an alternative routing path quickly and efficiently when the coordinate of sink is changed in WSN. The results of our extensive experiments demonstrate that our proposed route maintaining protocol is able to balance the network traffic load and prolong the network lifetime.

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

    Directory of Open Access Journals (Sweden)

    Kai-Wei Chiang

    2010-10-01

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

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

    Science.gov (United States)

    Szu, Harold H.

    1990-01-01

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

  8. Intelligent Control of Welding Gun Pose for Pipeline Welding Robot Based on Improved Radial Basis Function Network and Expert System

    OpenAIRE

    Jingwen Tian; Meijuan Gao; Yonggang He

    2013-01-01

    Since the control system of the welding gun pose in whole‐position welding is complicated and nonlinear, an intelligent control system of welding gun pose for a pipeline welding robot based on an improved radial basis function neural network (IRBFNN) and expert system (ES) is presented in this paper. The structure of the IRBFNN is constructed and the improved genetic algorithm is adopted to optimize the network structure. This control system makes full use of the characteristics of the IRBFNN...

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

    Science.gov (United States)

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

    2003-01-01

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

  10. Intelligent On/Off Dynamic Link Management for On-Chip Networks

    Directory of Open Access Journals (Sweden)

    Andreas G. Savva

    2012-01-01

    Full Text Available Networks-on-chips (NoCs provide scalable on-chip communication and are expected to be the dominant interconnection architectures in multicore and manycore systems. Power consumption, however, is a major limitation in NoCs today, and researchers have been constantly working on reducing both dynamic and static power. Among the NoC components, links that connect the NoC routers are the most power-hungry components. Several attempts have been made to reduce the link power consumption at both the circuit level and the system level. Most past research efforts have proposed selective on/off link state switching based on system-level information based on link utilization levels. Most of these proposed algorithms focus on a pessimistic and simple static threshold mechanism which determines whether or not a link should be turned on/off. This paper presents an intelligent dynamic power management policy for NoCs with improved predictive abilities based on supervised online learning of the system status (i.e., expected future utilization link levels, where links are turned off and on via the use of a small and scalable neural network. Simulation results with various synthetic traffic models over various network topologies show that the proposed work can reach up to 13% power savings when compared to a trivial threshold computation, at very low (<4% hardware overheads.

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

    Science.gov (United States)

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

    2008-01-01

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

  12. 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.

  13. Multicast protection based on enhanced intelligent p-cycle method in optical mesh networks

    Science.gov (United States)

    Wu, Jingjing; Liu, Yejun; Yu, Cunqian; Wang, Xiaorui; Zhao, Junhong

    2013-01-01

    The increase of multimedia applications results in the growing popularity of multicast demands. At the same time, survivability in an optical network is very important because of its very high transmission rate. Therefore, it is necessary to provide survivability for multicast demands in an optical network. Previous works have proposed multicast protection schemes for single-fiber link failure, in which the preconfigured protection cycle, known as the p-cycle, is an efficient method to overcome the long restoration time and the complicated protection switching procedure in comparison with other schemes. However, most previous schemes are applied only to static multicast protection. Although some schemes are extended to dynamic multicast protection, they do not consider the protection for straddle links. To overcome the shortcoming, this paper improves the existing p-cycle-based dynamic multicast protection and proposes an enhanced intelligent p-cycle (EIpC) scheme, in which all working light-trees of multicast demands can be protected by a p-cycle in the network. For each multicast demand, EIpC can compute a set of high-efficient p-cycles to provide dynamic protection. By combining the existing p-cycles for meeting certain conditions, EIpC can reduce the wavelength usage of p-cycles. Simulation results show that EIpC can obtain performance improvement compared to conventional schemes.

  14. Intelligent Intrusion Detection of Grey Hole and Rushing Attacks in Self-Driving Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Khattab M. Ali Alheeti

    2016-07-01

    Full Text Available Vehicular ad hoc networks (VANETs play a vital role in the success of self-driving and semi self-driving vehicles, where they improve safety and comfort. Such vehicles depend heavily on external communication with the surrounding environment via data control and Cooperative Awareness Messages (CAMs exchanges. VANETs are potentially exposed to a number of attacks, such as grey hole, black hole, wormhole and rushing attacks. This work presents an intelligent Intrusion Detection System (IDS that relies on anomaly detection to protect the external communication system from grey hole and rushing attacks. These attacks aim to disrupt the transmission between vehicles and roadside units. The IDS uses features obtained from a trace file generated in a network simulator and consists of a feed-forward neural network and a support vector machine. Additionally, the paper studies the use of a novel systematic response, employed to protect the vehicle when it encounters malicious behaviour. Our simulations of the proposed detection system show that the proposed schemes possess outstanding detection rates with a reduction in false alarms. This safe mode response system has been evaluated using four performance metrics, namely, received packets, packet delivery ratio, dropped packets and the average end to end delay, under both normal and abnormal conditions.

  15. 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.

  16. Intelligent maritime security system with sensor networks for coastal environmental and homeland security applications

    Science.gov (United States)

    Carapezza, Edward M.; Bucklin, Ann

    2007-10-01

    This paper proposes an innovative command and control system design and the use of low, cost distributed sensor networks for an intelligent maritime security system. This concept utilizes a network of small passive and active multi-phenomenological unattended sensors and shore based optical sensors to detect, classify, and track submerged threat objects approaching high value coastal assets, such as ports, harbors, residential, commercial, and military facilities and areas. The network of unattended, in-water sensors perform the initial detection, classification, and coarse tracking and then queues shore based optical laser radar sensors. These shore-based sensors perform a high resolution sector search to develop a precision track on the submerged threat objects. Potential threat objects include submarines, submerged barges, UUV's, swimmers carrying threat objects such as explosives, chemical, biological, radiological, and nuclear materials. Reliable systems with low false alarm rates (FAR) are proposed. Tens to hundreds of low cost passive sensors are proposed to be deployed conjunctively with several active acoustic and optical sensors in threat and facility dependant patterns to maximize the detection, tracking and classification of submerged threat objects.

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

    Science.gov (United States)

    Alkhatib, Hasan S.

    1991-01-01

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

  18. Application of Swarm Intelligence Based Routingprotocols for Wireless Adhoc Sensor Network

    Directory of Open Access Journals (Sweden)

    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.

  19. An Intelligent Gear Fault Diagnosis Methodology Using a Complex Wavelet Enhanced Convolutional Neural Network.

    Science.gov (United States)

    Sun, Weifang; Yao, Bin; Zeng, Nianyin; Chen, Binqiang; He, Yuchao; Cao, Xincheng; He, Wangpeng

    2017-07-12

    As a typical example of large and complex mechanical systems, rotating machinery is prone to diversified sorts of mechanical faults. Among these faults, one of the prominent causes of malfunction is generated in gear transmission chains. Although they can be collected via vibration signals, the fault signatures are always submerged in overwhelming interfering contents. Therefore, identifying the critical fault's characteristic signal is far from an easy task. In order to improve the recognition accuracy of a fault's characteristic signal, a novel intelligent fault diagnosis method is presented. In this method, a dual-tree complex wavelet transform (DTCWT) is employed to acquire the multiscale signal's features. In addition, a convolutional neural network (CNN) approach is utilized to automatically recognise a fault feature from the multiscale signal features. The experiment results of the recognition for gear faults show the feasibility and effectiveness of the proposed method, especially in the gear's weak fault features.

  20. Development of a Bayesian neural network to perform obstacle avoidance for an intelligent wheelchair.

    Science.gov (United States)

    Nguyen, Anh V; Nguyen, Lien B; Su, Steven; Nguyen, Hung T

    2012-01-01

    This paper presents an extension of a real-time obstacle avoidance algorithm for our laser-based intelligent wheelchair, to provide independent mobility for people with physical, cognitive, and/or perceptual impairments. The laser range finder URG-04LX mounted on the front of the wheelchair collects immediate environment information, and then the raw laser data are directly used to control the wheelchair in real-time without any modification. The central control role is an obstacle avoidance algorithm which is a neural network trained under supervision of Bayesian framework, to optimize its structure and weight values. The experiment results demonstrated that this new approach provides safety, smoothness for autonomous tasks and significantly improves the performance of the system in difficult tasks such as door passing.

  1. The advancement of an obstacle avoidance Bayesian neural network for an intelligent wheelchair.

    Science.gov (United States)

    Nguyen, Anh V; Nguyen, Lien B; Su, Steven; Nguyen, Hung T

    2013-01-01

    In this paper, an advanced obstacle avoidance system is developed for an intelligent wheelchair designed to support people with mobility impairments who also have visual, upper limb, or cognitive impairment. To avoid obstacles, immediate environment information is continuously updated with range data sampled by an on-board laser range finder URG-04LX. Then, the data is transformed to find the relevant information to the navigating process before being presented to a trained obstacle avoidance neural network which is optimized under the supervision of a Bayesian framework to find its structure and weight values. The experiment results showed that this method allows the wheelchair to avoid collisions while simultaneously navigating through an unknown environment in real-time. More importantly, this new approach significantly enhances the performance of the system to pass narrow openings such as door passing.

  2. Assessment of LED Technology in Ornamental Post-Top Luminaires (Host Site: Sacramento, CA)

    Energy Technology Data Exchange (ETDEWEB)

    Tuenge, Jason R.

    2011-12-01

    The DOE Municipal Solid-State Street Lighting Consortium has evaluated four different LED replacements for existing ornamental post-top street lights in Sacramento, California. The project team was composed of the City and its consultant, PNNL (representing the Consortium), and the Sacramento Municipal Utility District. Product selection was finalized in March 2011, yielding one complete luminaire replacement and three lamp-ballast retrofit kits. Computer simulations, field measurements, and laboratory testing were performed to compare the performance and cost-effectiveness of the LED products relative to the existing luminaire with 100 W high-pressure sodium lamp. After it was confirmed the LED products were not equivalent to HPS in terms of initial photopic illumination, the following parameters were scaled proportionally to enable equitable (albeit hypothetical) comparisons: light output, input wattage, and pricing. Four replacement scenarios were considered for each LED product, incorporating new IES guidance for mesopic multipliers and lumen maintenance extrapolation, but life cycle analysis indicated cost effectiveness was also unacceptable. Although LED efficacy and pricing continue to improve, this project serves as a timely and objective notice that LED technology may not be quite ready yet for such applications.

  3. Network Intelligence Based on Network State Information for Connected Vehicles Utilizing Fog Computing

    Directory of Open Access Journals (Sweden)

    Seongjin Park

    2017-01-01

    Full Text Available This paper proposes a method to take advantage of fog computing and SDN in the connected vehicle environment, where communication channels are unstable and the topology changes frequently. A controller knows the current state of the network by maintaining the most recent network topology. Of all the information collected by the controller in the mobile environment, node mobility information is particularly important. Thus, we divide nodes into three classes according to their mobility types and use their related attributes to efficiently manage the mobile connections. Our approach utilizes mobility information to reduce control message overhead by adjusting the period of beacon messages and to support efficient failure recovery. One is to recover the connection failures using only mobility information, and the other is to suggest a real-time scheduling algorithm to recover the services for the vehicles that lost connection in the case of a fog server failure. A real-time scheduling method is first described and then evaluated. The results show that our scheme is effective in the connected vehicle environment. We then demonstrate the reduction of control overhead and the connection recovery by using a network simulator. The simulation results show that control message overhead and failure recovery time are decreased by approximately 55% and 5%, respectively.

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

    Science.gov (United States)

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

    2014-02-01

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

  5. Recent advances on artificial intelligence and learning techniques in cognitive radio networks

    National Research Council Canada - National Science Library

    Abbas, Nadine; Nasser, Youssef; Ahmad, Karim El

    2015-01-01

    ... of the radio spectrum. For efficient real-time process, the cognitive radio is usually combined with artificial intelligence and machine-learning techniques so that an adaptive and intelligent allocation is achieved...

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

    OpenAIRE

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

    2011-01-01

    Fluid intelligence is the ability to think flexibly and to understand abstract relations. People with high fluid intelligence (hi-fluIQ) perform better in analogical reasoning tasks than people with average fluid intelligence (ave-fluIQ). Although previous neuroimaging studies reported involvement of parietal and frontal brain regions in geometric analogical reasoning (which is a prototypical task for fluid intelligence), however, neuroimaging findings on geometric analogical reasoning in hi-...

  7. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

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

    Science.gov (United States)

    Nguyen, Thu L N; Shin, Yoan

    2016-05-18

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

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Thu L. N. Nguyen

    2016-05-01

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

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Michele Zorzi

    2009-05-01

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

  13. Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rajeev Kumar

    2016-01-01

    Full Text Available Currently, wireless sensor networks (WSNs are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i selection of optimal number of subregions and further subregion parts, (ii cluster head selection using ABC algorithm, and (iii efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS. The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.

  14. 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.

  15. Solution-Procesed Small-Molecule OLED Luminaire for Interior Illumination

    Energy Technology Data Exchange (ETDEWEB)

    Parker, Ian [Dupont Displays, Inc., Santa Barbara, CA (United States)

    2012-02-29

    Prototype lighting panels and luminaires were fabricated using DuPont Displays solution-processed small-molecule OLED technology. These lighting panels were based on a spatially-patterned, 3-color design, similar in concept to an OLED display panel, with materials chosen to maximize device efficacy. The majority of the processing steps take place in air (rather than high vacuum). Optimization of device architecture, processing and construction was undertaken, with a final prototype design of 50 cm{sup 2} being fabricated and tested. Performance of these panels reached 35 lm/W at illuminant-A. A unique feature of this technology is the ability to color tune the emission, and color temperatures ranging from 2700 to > 6,500K were attained in the final build. Significant attention was paid to low-cost fabrication techniques.

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

    Science.gov (United States)

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

    2012-11-12

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

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

    Science.gov (United States)

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

    2012-01-01

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

  18. Intelligent Management System of Power Network Information Collection Under Big Data Storage

    Directory of Open Access Journals (Sweden)

    Qin Yingying

    2017-01-01

    Full Text Available With the development of economy and society, big data storage in enterprise management has become a problem that can’t be ignored. How to manage and optimize the allocation of tasks better is an important factor in the sustainable development of an enterprise. Now the enterprise information intelligent management has become a hot spot of management mode and concept in the information age. It presents information to the business managers in a more efficient, lower cost, and global form. The system uses the SG-UAP development tools, which is based on Eclipse development environment, and suits for Windows operating system, with Oracle as database development platform, Tomcat network information service for application server. The system uses SOA service-oriented architecture, provides RESTful style service, and HTTP(S as the communication protocol, and JSON as the data format. The system is divided into two parts, the front-end and the backs-end, achieved functions like user login, registration, password retrieving, enterprise internal personnel information management and internal data display and other functions.

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

    Directory of Open Access Journals (Sweden)

    P. Ganeshkumar

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Pedro M. Ferreira

    2012-11-01

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

  1. Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models

    Directory of Open Access Journals (Sweden)

    Juhwan Kim

    2018-01-01

    Full Text Available Recent developments in artificial intelligence (AI have led to a significant increase in the use of AI technologies. Many experts are researching and developing AI technologies in their respective fields, often submitting papers and patent applications as a result. In particular, owing to the characteristics of the patent system that is used to protect the exclusive rights to registered technology, patent documents contain detailed information on the developed technology. Therefore, in this study, we propose a statistical method for analyzing patent data on AI technology to improve our understanding of sustainable technology in the field of AI. We collect patent documents that are related to AI technology, and then analyze the patent data to identify sustainable AI technology. In our analysis, we develop a statistical method that combines social network analysis and Bayesian modeling. Based on the results of the proposed method, we provide a technological structure that can be applied to understand the sustainability of AI technology. To show how the proposed method can be applied to a practical problem, we apply the technological structure to a case study in order to analyze sustainable AI technology.

  2. Robust and intelligent algorithms for TDOA localization in distributed sensor networks

    Science.gov (United States)

    Fang, Jiaqi; He, Zhiyi; Jian, Cui

    2017-10-01

    Passive source localization utilizing time difference of arrival (TDOA) has widely application in radar, navigation, surveillance, wireless communication, distributed sensor network, etc. This paper presents two robust algorithms named Modified Taylor-seriesmethod (MTS) and Modified Newton (MNT) method. The proposed algorithms are the improvement of the Taylor-series (TS) and Newton (NT) methods for solving the convergent problem which is critical in the iterative methods. The key component of the proposed algorithms is to produce a new modified Hessian matrix intelligently using the Regularization theory which can turn the ill-posed Hessian matrix into a well-conditioned matrix. The regularization parameter which controls the properties of the regularized solution can be automatically determined by the L-curve method. With this procedure, the proposed methods are robust to make the iteration convergence with a bad initial. Simulation results show that the proposed methods improve the convergent probability and have better capability to distinguish the local minimums from the global solutions compared with the TS and NT methods. The proposed methods give superiorperformances of the location accuracy comparing with the closed-form algorithms at large measurement noises.

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

    Science.gov (United States)

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

    2015-11-11

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

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

    Directory of Open Access Journals (Sweden)

    Otto Chris

    2005-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Montri Inthachot

    2016-01-01

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

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

    Science.gov (United States)

    Inthachot, Montri; Boonjing, Veera; Intakosum, Sarun

    2016-01-01

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

  7. 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.

  8. 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.

  9. Intelligent route surveillance

    NARCIS (Netherlands)

    Schoemaker, R.M.; Sandbrink, R.D.J.; Voorthuijsen, G.P. van

    2009-01-01

    Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent

  10. 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

    2018-01-12

    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 R2 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. Published by Elsevier Inc.

  11. Performance enhancements of the CMCC"s national mesh network using the intelligent optical cross-connect switches

    Science.gov (United States)

    Gong, Qian; Xu, Rong; Lin, JinTong L.

    2004-04-01

    In the last five years, the traffic growth rate in China has been extremely fast. By 2005, the number of wired telephone customers is estimated to reach 220 to 260 million, while the number of expected cellular customers will reach 260 to 290 million. To meet these challenges, we will continue evolving with more wavelengths and higher speed. By evolving point-to-point WDM systems to OTN/ASON systems, we can eliminate the throughput bottleneck of network nodes caused by electronics, provide optical-layer bandwidth- management capability, provide scalability (which allows continuous traffic growth and network expansion), and provide reconfigurability (which allows semi-dynamic and dynamic optical networking). We can also simplify and speed up provisioning of high-speed circuits and services and offer fast network protection and restoration on the order of tens or hundreds of milliseconds to guarantee excellent network and service survivability. The CMCC (China Mobile Communication Company) will build its OTN network towards the ASON. The CMCC"s long-haul national network utilizing OXC has clearly becomes an intelligent network. It offers end-to-end point-and-click provisioning, shared mesh restoration with a few tens to a couple of hundred msec restoration times, re-provisioning of connections in the event of double failures and network capacity that is not optimally used. In this paper, first we present the CMCC network situation, The network planning tool will be introduced, Then we compare ring with mesh solution in terms of the cost, network performance, protection and restoration, network re-optimization. At last we derive a desired conclusion.

  12. 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.

  13. 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

  14. Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.

    Science.gov (United States)

    Hirasawa, Toshiaki; Aoyama, Kazuharu; Tanimoto, Tetsuya; Ishihara, Soichiro; Shichijo, Satoki; Ozawa, Tsuyoshi; Ohnishi, Tatsuya; Fujishiro, Mitsuhiro; Matsuo, Keigo; Fujisaki, Junko; Tada, Tomohiro

    2018-01-15

    Image recognition using artificial intelligence with deep learning through convolutional neural networks (CNNs) has dramatically improved and been increasingly applied to medical fields for diagnostic imaging. We developed a CNN that can automatically detect gastric cancer in endoscopic images. A CNN-based diagnostic system was constructed based on Single Shot MultiBox Detector architecture and trained using 13,584 endoscopic images of gastric cancer. To evaluate the diagnostic accuracy, an independent test set of 2296 stomach images collected from 69 consecutive patients with 77 gastric cancer lesions was applied to the constructed CNN. The CNN required 47 s to analyze 2296 test images. The CNN correctly diagnosed 71 of 77 gastric cancer lesions with an overall sensitivity of 92.2%, and 161 non-cancerous lesions were detected as gastric cancer, resulting in a positive predictive value of 30.6%. Seventy of the 71 lesions (98.6%) with a diameter of 6 mm or more as well as all invasive cancers were correctly detected. All missed lesions were superficially depressed and differentiated-type intramucosal cancers that were difficult to distinguish from gastritis even for experienced endoscopists. Nearly half of the false-positive lesions were gastritis with changes in color tone or an irregular mucosal surface. The constructed CNN system for detecting gastric cancer could process numerous stored endoscopic images in a very short time with a clinically relevant diagnostic ability. It may be well applicable to daily clinical practice to reduce the burden of endoscopists.

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

    Directory of Open Access Journals (Sweden)

    Muhammad Asif Zahoor Raja

    2012-01-01

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

  16. 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.

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

    Science.gov (United States)

    Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

    2016-01-01

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

  18. Intelligence networks and the tri border area of South America : the dilemma of efficiency versus oversight

    OpenAIRE

    Wishart, Eric Gregory

    2002-01-01

    Approved for public release; distribution in unlimited. This thesis examines the intelligence communities of Argentina, Brazil, and Paraguay to determine how to better coordinate and share information between themselves and the United States to combat the emerging threat of terrorism within the border region shared by the three Latin American countries. The thesis argues from the standpoint that the primary intelligence effort should be economic and HUMINT due to the currently low threat l...

  19. 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.

  20. 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

    CERN Document Server

    2015-01-01

    This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 – July 2, 2014 in Las Vegas Nevada, USA. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.

  1. 14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

    CERN Document Server

    Studies in Computational Intelligence : Volume 492

    2013-01-01

    This edited book presents scientific results of the 14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013), held in Honolulu, Hawaii, USA on July 1-3, 2013. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 17 outstanding papers from those papers accepted for presentation at the conference.  

  2. Intelligent quotient estimation of mental retarded people from different psychometric instruments using artificial neural networks.

    Science.gov (United States)

    Di Nuovo, Alessandro G; Di Nuovo, Santo; Buono, Serafino

    2012-02-01

    The estimation of a person's intelligence quotient (IQ) by means of psychometric tests is indispensable in the application of psychological assessment to several fields. When complex tests as the Wechsler scales, which are the most commonly used and universally recognized parameter for the diagnosis of degrees of retardation, are not applicable, it is necessary to use other psycho-diagnostic tools more suited for the subject's specific condition. But to ensure a homogeneous diagnosis it is necessary to reach a common metric, thus, the aim of our work is to build models able to estimate accurately and reliably the Wechsler IQ, starting from different psycho-diagnostic tools. Four different psychometric tests (Leiter international performance scale; coloured progressive matrices test; the mental development scale; psycho educational profile), along with the Wechsler scale, were administered to a group of 40 mentally retarded subjects, with various pathologies, and control persons. The obtained database is used to evaluate Wechsler IQ estimation models starting from the scores obtained in the other tests. Five modelling methods, two statistical and three from machine learning, that belong to the family of artificial neural networks (ANNs) are employed to build the estimator. Several error metrics for estimated IQ and for retardation level classification are defined to compare the performance of the various models with univariate and multivariate analyses. Eight empirical studies show that, after ten-fold cross-validation, best average estimation error is of 3.37 IQ points and mental retardation level classification error of 7.5%. Furthermore our experiments prove the superior performance of ANN methods over statistical regression ones, because in all cases considered ANN models show the lowest estimation error (from 0.12 to 0.9 IQ points) and the lowest classification error (from 2.5% to 10%). Since the estimation performance is better than the confidence interval of

  3. Improving Security Incidents Detection for Networked Multilevel Intelligent Control Systems in Railway Transport

    Directory of Open Access Journals (Sweden)

    A. V. Chernov

    2016-06-01

    Full Text Available Security monitoring and incident management systems have become the main research focus in the area of intelligent railway control systems. In this work, we discuss a system architecture of multilevel intelligent control system in Russian Railway transport and security incident classification and the handling of theprocess. We make a detailed explanation of problems and tasks of security information and event management system as an important part of a multilevel intelligent control system. We use a rough sets theory to detect an abnormal activity in the considered system. Our main result consists in the development of simple and fast detection techniques that are based on rough sets theory and allow investigating a new type of incidents.

  4. Intelligent Control of Welding Gun Pose for Pipeline Welding Robot Based on Improved Radial Basis Function Network and Expert System

    Directory of Open Access Journals (Sweden)

    Jingwen Tian

    2013-02-01

    Full Text Available Since the control system of the welding gun pose in whole-position welding is complicated and nonlinear, an intelligent control system of welding gun pose for a pipeline welding robot based on an improved radial basis function neural network (IRBFNN and expert system (ES is presented in this paper. The structure of the IRBFNN is constructed and the improved genetic algorithm is adopted to optimize the network structure. This control system makes full use of the characteristics of the IRBFNN and the ES. The ADXRS300 micro-mechanical gyro is used as the welding gun position sensor in this system. When the welding gun position is obtained, an appropriate pitch angle can be obtained through expert knowledge and the numeric reasoning capacity of the IRBFNN. ARM is used as the controller to drive the welding gun pitch angle step motor in order to adjust the pitch angle of the welding gun in real-time. The experiment results show that the intelligent control system of the welding gun pose using the IRBFNN and expert system is feasible and it enhances the welding quality. This system has wide prospects for application.

  5. APPLICATION OF CLOUD COMPUTING IN PROGRAMMING INTELLIGENT ELECTRIC NETWORKS IN PROSUMERS’ HOUSEHOLDS

    Directory of Open Access Journals (Sweden)

    Marek Horyński

    2016-11-01

    Full Text Available Currently, cloud computing models are provided with increasing a number of new functionalities. The paper describes a laboratory model of intelligent KNX system which makes it possible to test the practical use of cloud computing in components programming for this system. The cloud computing elements were used for this purpose. Innovatory features of services transferred to the cloud computing models consists in the integration of advanced IT techniques and Internet technologies based systems with the users services, in this case with the management of an intelligent building system. The software ETS5 installed on workstation is another important component of the station being discussed.

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

    Science.gov (United States)

    Buzaev, Igor Vyacheslavovich; Plechev, Vladimir Vyacheslavovich; Nikolaeva, Irina Evgenievna; Galimova, Rezida Maratovna

    2016-09-01

    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. 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. 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)]. 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.

  7. Neurobiological correlates of emotional intelligence in voice and face perception networks.

    Science.gov (United States)

    Karle, Kathrin N; Ethofer, Thomas; Jacob, Heike; Brück, Carolin; Erb, Michael; Lotze, Martin; Nizielski, Sophia; Schütz, Astrid; Wildgruber, Dirk; Kreifelts, Benjamin

    2018-01-22

    Facial expressions and voice modulations are among the most important communicational signals to convey emotional information. The ability to correctly interpret this information is highly relevant for successful social interaction and represents an integral component of emotional competencies that have been conceptualized under the term emotional intelligence. Here, we investigated the relationship of emotional intelligence as measured with the Salovey-Caruso-Emotional-Intelligence-Test (MSCEIT) with cerebral voice and face processing using functional and structural magnetic resonance imaging. MSCEIT scores were positively correlated with increased voice-sensitivity and gray matter volume of the insula accompanied by voice-sensitivity enhanced connectivity between the insula and the temporal voice area, indicating generally increased salience of voices. Conversely, in the face processing system, higher MSCEIT scores were associated with decreased face-sensitivity and gray matter volume of the fusiform face area. Taken together, these findings point to an alteration in the balance of cerebral voice and face processing systems in the form of an attenuated face-versus-voice bias as one potential factor underpinning emotional intelligence. © The Author (2018). Published by Oxford University Press.

  8. 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…

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

    Science.gov (United States)

    2006-09-15

    action by U.S. policymakers”.13 Foreknowledge, conceived in a scientific, business, or intelligence sense, obviously does not imply psychic clairvoyance...and induction, abduction and deduction. Briefly, methodology is the logic governing methods. Synthesis builds order and unity out of disorder

  10. Integration of an Intelligent Tutoring System in a Course of Computer Network Design

    Science.gov (United States)

    Verdú, Elena; Regueras, Luisa M.; Gal, Eran; de Castro, Juan P.; Verdú, María J.; Kohen-Vacs, Dan

    2017-01-01

    INTUITEL is a research project aiming to offer a personalized learning environment. The INTUITEL approach includes an Intelligent Tutoring System that gives students recommendations and feedback about what the best learning path is for them according to their profile, learning progress, context and environmental influences. INTUITEL combines…

  11. On Study of Construction of New Generation Intelligent Communication Network for Distribution System

    Science.gov (United States)

    Wu, Dan; Zhang, Xueyan

    2017-09-01

    many new technological means are integrated in the new network of smart electricity distribution including electric power technology, control technology and information technology, and in this area, people carry out profound research to the construction of communication network and power distribution network. This paper analyzes specific structures of the communication network for distribution system, discusses the development trend of it, explores its technical system in depth, and finally proposes some concrete constructive strategies, hoping to be a valuable reference for related research persons.

  12. Design of Randomly Deployed Heterogeneous Wireless Sensor Networks by Algorithms Based on Swarm Intelligence

    OpenAIRE

    Joon-Woo Lee; Won Kim

    2015-01-01

    This paper reports the design of a randomly deployed heterogeneous wireless sensor network (HWSN) with two types of nodes: a powerful node and an ordinary node. Powerful nodes, such as Cluster Heads (CHs), communicate directly to the data sink of the network, and ordinary nodes sense the desired information and transmit the processed data to powerful nodes. The heterogeneity of HWSNs improves the networks lifetime and coverage. This paper focuses on the design of a random network among HWSNs....

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

    Science.gov (United States)

    2011-01-01

    1345– 1361, November 2002. [30] L.F. P. Pollo , J. -Porto, ―A Network-oriented Power Management Architecture,‖ Proc. Integrated Network Management...208, Feb. 2007, doi: 10.1109/TCE.2007.339526. [47] L.F. Pollo and J-Porto, ―A Network-oriented Power Management Architecture,‖ Proc. Integrated

  14. 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

  15. Application of Wireless Sensor and Actuator Networks to Achieve Intelligent Microgrids: A Promising Approach towards a Global Smart Grid Deployment

    Directory of Open Access Journals (Sweden)

    Alvaro Llaria

    2016-02-01

    Full Text Available Smart Grids (SGs constitute the evolution of the traditional electrical grid towards a new paradigm, which should increase the reliability, the security and, at the same time, reduce the costs of energy generation, distribution and consumption. Electrical microgrids (MGs can be considered the first stage of this evolution of the grid, because of the intelligent management techniques that must be applied to assure their correct operation. To accomplish this task, sensors and actuators will be necessary, along with wireless communication technologies to transmit the measured data and the command messages. Wireless Sensor and Actuator Networks (WSANs are therefore a promising solution to achieve an intelligent management of MGs and, by extension, the SG. In this frame, this paper surveys several aspects concerning the application of WSANs to manage MGs and the electrical grid, as well as the communication protocols that could be applied. The main concerns regarding the SG deployment are also presented, including future scenarios where the interoperability of different generation technologies must be assured.

  16. 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.

  17. 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...

  18. 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

    CERN Document Server

    SNPD 2016

    2016-01-01

    This edited book presents scientific results of the 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2016) which was held on May 30 - June 1, 2016 in Shanghai, China. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

  19. 6th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

    CERN Document Server

    2016-01-01

    This edited book presents scientific results of the 16th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2015) which was held on June 1 – 3, 2015 in Takamatsu, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

  20. Future Internet as a Driver for Virtualization, Connectivity and Intelligence of Agri‐Food Supply Chain Networks

    Directory of Open Access Journals (Sweden)

    Cor N. Verdouw

    2014-03-01

    Full Text Available The food and agribusiness is an important sector in European logistics with a share in the EU road transport of about 20%. One of the main logistic challenges in this sector is to deal with the high dynamics and uncertainty in supply and demand. This paper discusses the opportunities of Future Internet (FI technologies to addresses the specific demands on information systems for logistics in the food and agribusiness domain. More specifically, it presents a Future Internet (FI based design for smart agri‐food logistic information systems. This design aims to enable new types of efficient and responsive logistics networks with flexible chain‐encompassing tracking and tracing systems and decision support based on that information. These systems effectively virtualise the logistics flows from farm to fork, support a timely and error‐free exchange of logistics information and provide functionality for intelligent analysis and reporting of exchanged data to enable early warning and advanced forecasting.

  1. Association between structural brain network efficiency and intelligence increases during adolescence

    NARCIS (Netherlands)

    Koenis, Marinka M G; Brouwer, Rachel M; Swagerman, Suzanne C; van Soelen, Inge L C; Boomsma, Dorret I; Hulshoff Pol, Hilleke E

    2017-01-01

    Adolescence represents an important period during which considerable changes in the brain take place, including increases in integrity of white matter bundles, and increasing efficiency of the structural brain network. A more efficient structural brain network has been associated with higher

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

    Science.gov (United States)

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

    2006-01-01

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

  3. 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

    interface for visualizing, configuring and monitoring of the emulated scenarios and a network socket linking the graphic server and network emulation server on-line. Specifically, our focus area is to build a model that gives us ability to look at some of the challenges on implementing inter...... a mechanism for on-line configuration and monitoring of heterogeneous communication technologies implemented at smart energy system testbed of Aal-borg university. It proposes a model with three main components, a network emulator used to emulate the communication scenarios using KauNet, graphical user...

  4. Systematic construction and control of stereo nerve vision network in intelligent manufacturing

    Science.gov (United States)

    Liu, Hua; Wang, Helong; Guo, Chunjie; Ding, Quanxin; Zhou, Liwei

    2017-10-01

    A system method of constructing stereo vision by using neural network is proposed, and the operation and control mechanism in actual operation are proposed. This method makes effective use of the neural network in learning and memory function, by after training with samples. Moreover, the neural network can learn the nonlinear relationship in the stereoscopic vision system and the internal and external orientation elements. These considerations are Worthy of attention, which includes limited constraints, the scientific of critical group, the operating speed and the operability in technical aspects. The results support our theoretical forecast.

  5. Organization of networks with tagged nodes and biased links: a priori distinct communities. The case of Intelligent Design Proponents and Darwinian Evolution Defenders

    CERN Document Server

    Rotundo, G

    2010-01-01

    Among topics of opinion formation it is of interest to observe the characteristics of networks with a priori distinct communities. As an illustration, we report on the citation network(s) unfolded in the recent decades through web available works belonging to selected members of the Neocreationist and Intelligent Design Proponents (IDP) and the Darwinian Evolution Defenders (DED) communities. An adjacency matrix of tagged nodes is first constructed; it is not symmetric. A generalization of considerations pertaining to the case of networks with biased links, directed or undirected, is thus presented. The main characteristic coefficients describing the structure of such partially directed networks with tagged nodes are outlined. The structural features are discussed searching for statistical aspects, equivalence or not of subnetworks through the degree distributions, each network assortativity, the global and local clustering coefficients and the Average Overlap Indices. The various closed and open triangles ma...

  6. Intelligent future wireless networks for energy efficiency: overall analysis and standardization activities

    CSIR Research Space (South Africa)

    Kliks, A

    2013-10-01

    Full Text Available This chapter addresses a number of issues related to standardization and regulatory policies aiming at promoting energy-efficient communications and networking, highlighting the need of synergic approach. It encompasses the analysis of various...

  7. Innovative applications of cars connectivity network – way to intelligent vehicle

    Directory of Open Access Journals (Sweden)

    Milan Kovac

    2012-10-01

    Full Text Available The presented article focuses on characteristic of possibilities to use of ICT tools in automotive traffic. There are specified selected potentialities for a network connected to automotive integration in near future. There is also considerable innovation in the field of Internet-enabled in-car systems. In this contribution we want illustrating affects of Internet networking in automobiles by examples of applications. The goal is to present conceptual model of vehicle connected to external interfaces. Subject of article covered the tendencies in the development of the specific application in automotive sector. Objectives is an increased public perception and customer acceptance of cars network systems which is suitable for multiple application domains – external connectivity, networking, security, diagnosis, integrated safety management etc.

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

    OpenAIRE

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

    2017-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies s...

  9. Development and Improvement of an Intelligent Cable Monitoring System for Underground Distribution Networks Using Distributed Temperature Sensing

    Directory of Open Access Journals (Sweden)

    Jintae Cho

    2014-02-01

    Full Text Available With power systems switching to smart grids, real-time and on-line monitoring technologies for underground distribution power cables have become a priority. Most distribution components have been developed with self-diagnostic sensors to realize self-healing, one of the smart grid functions in a distribution network. Nonetheless, implementing a real-time and on-line monitoring system for underground distribution cables has been difficult because of high cost and low sensitivity. Nowadays, optical fiber composite power cables (OFCPCs are being considered for communication and power delivery to cope with the increasing communication load in a distribution network. Therefore, the application of distributed temperature sensing (DTS technology on OFCPCs used as underground distribution lines is studied for the real-time and on-line monitoring of the underground distribution power cables. Faults can be reduced and operating ampacity of the underground distribution system can be increased. This paper presents the development and improvement of an intelligent cable monitoring system for the underground distribution power system, using DTS technology and OFCPCs as the underground distribution lines in the field.

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

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

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

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

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

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

  12. Region-wide search and pursuit system using networked intelligent cameras

    Science.gov (United States)

    Komiya, Kazumi; Irisawa, Kouji

    2001-11-01

    This paper reports a study on new, region-wide search and pursuit system for missing objects such as stolen cars, wandering people, etc. By using image matching processes on the basis of the object properties such as color and shape, the intelligent camera can search the object. Then the camera transmits the properties to the next camera to pursue the object successively. The experimental results show that the system can judge 2 cars as search object among 40 cars under conditions of changing environment. Based on these data the proposed system can accomplish a fundamental step. Finally, research subjects have been picked up for advancement such as accurate shape extraction processing, camera structure for high speed processing and multimedia attributes such as sound.

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  15. Comparison of Back propagation neural network and Back propagation neural network Based Particle Swarm intelligence in Diagnostic Breast Cancer

    Directory of Open Access Journals (Sweden)

    Farahnaz SADOUGHI

    2014-03-01

    Full Text Available Breast cancer is the most commonly diagnosed cancer and the most common cause of death in women all over the world. Use of computer technology supporting breast cancer diagnosing is now widespread and pervasive across a broad range of medical areas. Early diagnosis of this disease can greatly enhance the chances of long-term survival of breast cancer victims. Artificial Neural Networks (ANN as mainly method play important role in early diagnoses breast cancer. This paper studies Levenberg Marquardet Backpropagation (LMBP neural network and Levenberg Marquardet Backpropagation based Particle Swarm Optimization(LMBP-PSO for the diagnosis of breast cancer. The obtained results show that LMBP and LMBP based PSO system provides higher classification efficiency. But LMBP based PSO needs minimum training and testing time. It helps in developing Medical Decision System (MDS for breast cancer diagnosing. It can also be used as secondary observer in clinical decision making.

  16. A Genetic Algorithm with Location Intelligence Method for Energy Optimization in 5G Wireless Networks

    Directory of Open Access Journals (Sweden)

    Ruchi Sachan

    2016-01-01

    Full Text Available The exponential growth in data traffic due to the modernization of smart devices has resulted in the need for a high-capacity wireless network in the future. To successfully deploy 5G network, it must be capable of handling the growth in the data traffic. The increasing amount of traffic volume puts excessive stress on the important factors of the resource allocation methods such as scalability and throughput. In this paper, we define a network planning as an optimization problem with the decision variables such as transmission power and transmitter (BS location in 5G networks. The decision variables lent themselves to interesting implementation using several heuristic approaches, such as differential evolution (DE algorithm and Real-coded Genetic Algorithm (RGA. The key contribution of this paper is that we modified RGA-based method to find the optimal configuration of BSs not only by just offering an optimal coverage of underutilized BSs but also by optimizing the amounts of power consumption. A comparison is also carried out to evaluate the performance of the conventional approach of DE and standard RGA with our modified RGA approach. The experimental results showed that our modified RGA can find the optimal configuration of 5G/LTE network planning problems, which is better performed than DE and standard RGA.

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

    Science.gov (United States)

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

    2010-05-01

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

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

    Science.gov (United States)

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

    2009-01-01

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

  19. Voltage control in active, intelligent low-voltage distribution networks; Spannungshaltung in aktiven, intelligenten Niederspannungsnetzen

    Energy Technology Data Exchange (ETDEWEB)

    Buelo, Thorsten; Mende, Denis [SMA Solar Technology AG, Niestetal (Germany); Geibel, Dominik [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)] [and others

    2012-07-01

    This paper describes approaches for the voltage control in low-voltage distribution networks with a high share of distributed energy resources (DER). Taken into account are devices such as distribution transformers with on-load tap changer (OLTC), photovoltaic-inverters with reactive power capability and electronic voltage controllers (EVC). After a short description regarding voltage control, the devices and selected system concepts as well as the advantages and disadvantages of the different devices are described. Finally, the system-concepts are compared using the example of a real low voltage network, taking into account the possible increase of hosting capacity of the network, curtailing losses and the amount of reactive energy to be provided. (orig.)

  20. Intelligent Controlling Simulation of Traffic Flow in a Small City Network

    Science.gov (United States)

    Fouladvand, M. Ebrahim; Shaebani, M. Reza; Sadjadi, Zeinab

    2004-11-01

    We propose a two dimensional probabilistic cellular automata for the description of traffic flow in a small city network composed of two intersections. The traffic in the network is controlled by a set of traffic lights which can be operated both in fixed-time and a traffic responsive manner. Vehicular dynamics is simulated and the total delay experienced by the traffic is evaluated within specified time intervals. We investigate both decentralized and centralized traffic responsive schemes and in particular discuss the implementation of the green-wave strategy. Our investigations prove that the network delay strongly depends on the signalisation strategy. We show that in some traffic conditions, the application of the green-wave scheme may destructively lead to the increment of the global delay.

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

    OpenAIRE

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

    2016-01-01

    Data science or “data-driven research” is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healt...

  2. On a new concept of community: social networks, personal communities and collective intelligence

    Directory of Open Access Journals (Sweden)

    Rogério da Costa

    2006-01-01

    Full Text Available This text essentially deals with the transmutation of the concept of "community" into "social networks". This change is due largely to the boom of virtual communities in cyberspace, a fact that has generated a number of studies not only on this new way of weaving a society, but also on the dynamic structure of communication networks. At the core of this transformation, concepts such as social capital, trust and partial sympathy are called upon, to enable us to think about the new forms of association that regulate human activity in our time.

  3. Long-term Testing Results for the 2008 Installation of LED Luminaires at the I-35 West Bridge in Minneapolis

    Energy Technology Data Exchange (ETDEWEB)

    Kinzey, Bruce R.; Davis, Robert G.

    2014-09-30

    This document reports the long-term testing results from an extended GATEWAY project that was first reported in “Demonstration Assessment of Light-Emitting Diode (LED) Roadway Lighting at the I-35W Bridge, in Minneapolis, MN,” August 2009. That original report presented the results of lighting the newly reconstructed I 35W Bridge using LEDs in place of conventional high-pressure sodium (HPS) roadway luminaires, comparing energy use and illuminance levels with a simulated baseline condition. That installation was an early stage implementation of LED lighting and remains one of the oldest installations in continued operation today. This document provides an update of the LED system’s performance since its installation in September 2008.

  4. Intelligent Broadcasting in Mobile Ad Hoc Networks: Three Classes of Adaptive Protocols

    Directory of Open Access Journals (Sweden)

    Colagrosso Michael D

    2007-01-01

    Full Text Available Because adaptability greatly improves the performance of a broadcast protocol, we identify three ways in which machine learning can be applied to broadcasting in a mobile ad hoc network (MANET. We chose broadcasting because it functions as a foundation of MANET communication. Unicast, multicast, and geocast protocols utilize broadcasting as a building block, providing important control and route establishment functionality. Therefore, any improvements to the process of broadcasting can be immediately realized by higher-level MANET functionality and applications. While efficient broadcast protocols have been proposed, no single broadcasting protocol works well in all possible MANET conditions. Furthermore, protocols tend to fail catastrophically in severe network environments. Our three classes of adaptive protocols are pure machine learning, intra-protocol learning, and inter-protocol learning. In the pure machine learning approach, we exhibit a new approach to the design of a broadcast protocol: the decision of whether to rebroadcast a packet is cast as a classification problem. Each mobile node (MN builds a classifier and trains it on data collected from the network environment. Using intra-protocol learning, each MN consults a simple machine model for the optimal value of one of its free parameters. Lastly, in inter-protocol learning, MNs learn to switch between different broadcasting protocols based on network conditions. For each class of learning method, we create a prototypical protocol and examine its performance in simulation.

  5. Intelligent Broadcasting in Mobile Ad Hoc Networks: Three Classes of Adaptive Protocols

    Directory of Open Access Journals (Sweden)

    Michael D. Colagrosso

    2006-11-01

    Full Text Available Because adaptability greatly improves the performance of a broadcast protocol, we identify three ways in which machine learning can be applied to broadcasting in a mobile ad hoc network (MANET. We chose broadcasting because it functions as a foundation of MANET communication. Unicast, multicast, and geocast protocols utilize broadcasting as a building block, providing important control and route establishment functionality. Therefore, any improvements to the process of broadcasting can be immediately realized by higher-level MANET functionality and applications. While efficient broadcast protocols have been proposed, no single broadcasting protocol works well in all possible MANET conditions. Furthermore, protocols tend to fail catastrophically in severe network environments. Our three classes of adaptive protocols are pure machine learning, intra-protocol learning, and inter-protocol learning. In the pure machine learning approach, we exhibit a new approach to the design of a broadcast protocol: the decision of whether to rebroadcast a packet is cast as a classification problem. Each mobile node (MN builds a classifier and trains it on data collected from the network environment. Using intra-protocol learning, each MN consults a simple machine model for the optimal value of one of its free parameters. Lastly, in inter-protocol learning, MNs learn to switch between different broadcasting protocols based on network conditions. For each class of learning method, we create a prototypical protocol and examine its performance in simulation.

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

    Science.gov (United States)

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

    2016-05-01

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

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

    Science.gov (United States)

    Sanchez, Elie

    1991-10-01

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

  8. How Wireless Sensor Networks Can Benefit from Brain Emotional Learning Based Intelligent Controller (BELBIC)

    NARCIS (Netherlands)

    Kalayci, Tahir Emre; Bahrepour, M.; Meratnia, Nirvana; Havinga, Paul J.M.

    2011-01-01

    Wireless sensor networks (WSNs) are composed of small sensing and actuating devices that collaboratively monitor a phenomena, process and reason about sensor measurements, and provide adequate feedback or take actions. One of WSNs tasks is event detection, in which occurrence of events of interest

  9. On the Capacity of a GSM Frequency Hopping network with Intelligent Underlayer-Overlayer

    DEFF Research Database (Denmark)

    Nielsen, Thomas Toftegaard; Wigard, Jeroen; Mogensen, Preben Elgaard

    1997-01-01

    This paper describes a method to increase the capacity of a digital cellular network, like GSM, without having to increase the number of available frequencies or base stations. The idea is to split the frequency spectrum into two bands. One consisting of frequencies that can only be used when...

  10. Design and Implementation of an Intelligent Expansion Module for Wireless Gas Sensor Networks

    Directory of Open Access Journals (Sweden)

    Grigore STAMATESCU

    2015-04-01

    Full Text Available Wireless gas sensor networks (WGSN offer the potential of high spatial and temporal resolution monitoring of target areas in both critical and non-critical scenarios. We describe the design and evaluation of an electronic expansion module, MICARES, suitable for gas sensing applications with wireless sensor networks. The module is intended for use with the MICA family of motes through the 51-pin connector. Proper housing assured, the device is applicable to both indoor and outdoor gas sensing for buildings, commercial and industrial spaces. Challenges lay in sensor selection, analytical and experimental power budgeting and field testing. We present the design goals at the network and node level and the adopted solutions to achieve them. Appropriate adaptive sampling strategies for energy efficiency, along with data resulting from CO2 monitoring are described. Emphasis is put on embedded sensor integration into the electrical design and methods for on-board data acquisition and processing for decision support at the node and network levels.

  11. A motivational health companion in the home as part of an intelligent health monitoring sensor network

    NARCIS (Netherlands)

    Evers, V.; Wildvuur, S.; Kröse, B.

    2010-01-01

    This paper describes our work in progress to develop a personal monitoring system that can monitor the physical and emotional condition of a patient by using contextual information from a sensor network, provide the patient with feedback concerning their health status and motivate the patient to

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

    Energy Technology Data Exchange (ETDEWEB)

    Aman Behal; Sunil Kumar; Goodarz Ahmadi

    2007-08-05

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

  13. HCCI Intelligent Rapid Modeling by Artificial Neural Network and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    AbdoulAhad Validi

    2012-01-01

    Full Text Available A Dynamic model of Homogeneous Charge Compression Ignition (HCCI, based on chemical kinetics principles and artificial intelligence, is developed. The model can rapidly predict the combustion probability, thermochemistry properties, and exact timing of the Start of Combustion (SOC. A realization function is developed on the basis of the Sandia National Laboratory chemical kinetics model, and GRI3.0 methane chemical mechanism. The inlet conditions are optimized by Genetic Algorithm (GA, so that combustion initiates and SOC timing posits in the desired crank angle. The best SOC timing to achieve higher performance and efficiency in HCCI engines is between 5 and 15 degrees crank angle (CAD after top dead center (TDC. To achieve this SOC timing, in the first case, the inlet temperature and equivalence ratio are optimized simultaneously and in the second case, compression ratio is optimized by GA. The model’s results are validated with previous works. The SOC timing can be predicted in less than 0.01 second and the CPU time savings are encouraging. This model can successfully be used for real engine control applications.

  14. Experimental study of the stress level at the workplace using an smart testbed of wireless sensor networks and ambient intelligence techniques

    OpenAIRE

    Silva, Fábio; Olivares, Teresa; Royo, Fernando; Vergara, M. A.; Analide, César

    2013-01-01

    "Natural and artificial computation in engineering and medical applications : 5th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2013, Mallorca, Spain, June 10-14, 2013. Proceedings, Part II", ISBN 978-364238621-3 This paper combines techniques of ambient intelligence and wireless sensor networks with the objective of obtain important conclusions to increase the quality of life of people. In particular, we oriented our study to the stress ...

  15. 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...

  16. A proposition of a manufactronic network approach for intelligent and flexible manufacturing systems

    Directory of Open Access Journals (Sweden)

    Fernando Almeida

    2011-10-01

    Full Text Available The XPRESS project introduces a completely new scalable concept of a manufactronic networked factory, which is composed by a co-ordinated team of specialized autonomous objects (Manufactrons, each knowing how to do a certain process optimally. This knowledge based concept integrated the complete chain: production configuration (decrease of ramp-up time of at least 50%, multi-variant production line (varying types and volumes on a single line and 100% quality monitoring. The manufactronic networked architecture allows continuous process improvement, and will be able to anticipate and to respond to rapidly changing consumer needs, producing high-quality products in adequate quantities while reducing costs. This concept is demonstrated in the automotive, aeronautics and electrical industry but can be transferred to nearly all production processes.

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

    Science.gov (United States)

    2006-01-01

    to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE JAN...19a. NAME OF RESPONSIBLE PERSON a . REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98...Transfer Systems and Computer Networks Losev Gennady M. PhD. Computer and Information Systems and Problem of Information Protection Vorobyov Vladimir I

  18. Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network

    OpenAIRE

    Kale, S. N.; Dudul, S. V.

    2009-01-01

    Electromyography (EMG) signals can be used for clinical/biomedical application and modern human computer interaction. EMG signals acquire noise while traveling through tissue, inherent noise in electronics equipment, ambient noise, and so forth. ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN) can elegantly solve to reduce the noise from EMG signal. After rigorous computer simulations, authors d...

  19. Increasing the capacity of distributed generation in electricity networks by intelligent generator control

    OpenAIRE

    Aristides E. Kiprakis

    2005-01-01

    The rise of environmental awareness as well as the unstable global fossil fuel market has brought about government initiatives to increase electricity generation from renewable energy sources. These resources tend to be geographically and electrically remote from load centres. Consequently many Distributed Generators (DGs) are expected to be connected to the existing Distribution Networks (DNs), which have high impedance and low X/R ratios. Intermittence and unpredictability of the vario...

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

    Science.gov (United States)

    Gertsch, Jürg

    2011-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Giulia Berlusconi

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

  2. Stability of Intelligent Transportation Network Dynamics: A Daily Path Flow Adjustment considering Travel Time Differentiation

    Directory of Open Access Journals (Sweden)

    Ming-Chorng Hwang

    2015-01-01

    Full Text Available A theoretic formulation on how traffic time information distributed by ITS operations influences the trajectory of network flows is presented in this paper. The interactions between users and ITS operator are decomposed into three parts: (i travel time induced path flow dynamics (PFDTT; (ii demand induced path flow dynamics (PFDD; and (iii predicted travel time dynamics for an origin-destination (OD pair (PTTDOD. PFDTT describes the collective results of user’s daily route selection by pairwise comparison of path travel time provided by ITS services. The other two components, PTTDOD and PFDD, are concentrated on the evolutions of system variables which are predicted and observed, respectively, by ITS operators to act as a benchmark in guiding the target system towards an expected status faster. In addition to the delivered modelings, the stability theorem of the equilibrium solution in the sense of Lyapunov stability is also provided. A Lyapunov function is developed and employed to the proof of stability theorem to show the asymptotic behavior of the aimed system. The information of network flow dynamics plays a key role in traffic control policy-making. The evaluation of ITS-based strategies will not be reasonable without a well-established modeling of network flow evolutions.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, N.; Joslyn, C.; Rocha, L.; Smith, S.; Kantor, M. [Los Alamos National Lab., NM (United States); Rasmussen, S. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., NM (United States)

    1998-07-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  6. Multistep Wind Speed Forecasting Using a Novel Model Hybridizing Singular Spectrum Analysis, Modified Intelligent Optimization, and Rolling Elman Neural Network

    Directory of Open Access Journals (Sweden)

    Zhongshan Yang

    2016-01-01

    Full Text Available Wind speed high-accuracy forecasting, an important part of the electrical system monitoring and control, is of the essence to protect the safety of wind power utilization. However, the wind speed signals are always intermittent and intrinsic complexity; therefore, it is difficult to forecast them accurately. Many traditional wind speed forecasting studies have focused on single models, which leads to poor prediction accuracy. In this paper, a new hybrid model is proposed to overcome the shortcoming of single models by combining singular spectrum analysis, modified intelligent optimization, and the rolling Elman neural network. In this model, except for the multiple seasonal patterns used to reduce interferences from the original data, the rolling model is utilized to forecast the multistep wind speed. To verify the forecasting ability of the proposed hybrid model, 10 min and 60 min wind speed data from the province of Shandong, China, were proposed in this paper as the case study. Compared to the other models, the proposed hybrid model forecasts the wind speed with higher accuracy.

  7. A Robust Intelligent Framework for Multiple Response Statistical Optimization Problems Based on Artificial Neural Network and Taguchi Method

    Directory of Open Access Journals (Sweden)

    Ali Salmasnia

    2012-01-01

    Full Text Available An important problem encountered in product or process design is the setting of process variables to meet a required specification of quality characteristics (response variables, called a multiple response optimization (MRO problem. Common optimization approaches often begin with estimating the relationship between the response variable with the process variables. Among these methods, response surface methodology (RSM, due to simplicity, has attracted most attention in recent years. However, in many manufacturing cases, on one hand, the relationship between the response variables with respect to the process variables is far too complex to be efficiently estimated; on the other hand, solving such an optimization problem with accurate techniques is associated with problem. Alternative approach presented in this paper is to use artificial neural network to estimate response functions and meet heuristic algorithms in process optimization. In addition, the proposed approach uses the Taguchi robust parameter design to overcome the common limitation of the existing multiple response approaches, which typically ignore the dispersion effect of the responses. The paper presents a case study to illustrate the effectiveness of the proposed intelligent framework for tackling multiple response optimization problems.

  8. The Global Public Health Intelligence Network and early warning outbreak detection: a Canadian contribution to global public health.

    Science.gov (United States)

    Mykhalovskiy, Eric; Weir, Lorna

    2006-01-01

    The recent SARS epidemic has renewed widespread concerns about the global transmission of infectious diseases. In this commentary, we explore novel approaches to global infectious disease surveillance through a focus on an important Canadian contribution to the area--the Global Public Health Intelligence Network (GPHIN). GPHIN is a cutting-edge initiative that draws on the capacity of the Internet and newly available 24/7 global news coverage of health events to create a unique form of early warning outbreak detection. This commentary outlines the operation and development of GPHIN and compares it to ProMED-mail, another Internet-based approach to global health surveillance. We argue that GPHIN has created an important shift in the relationship of public health and news information. By exiting the pyramid of official reporting, GPHIN has created a new monitoring technique that has disrupted national boundaries of outbreak notification, while creating new possibilities for global outbreak response. By incorporating news within the emerging apparatus of global infectious disease surveillance, GPHIN has effectively responded to the global media's challenge to official country reporting of outbreak and enhanced the effectiveness and credibility of international public health.

  9. 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.

  10. Forming of the regional core transport network taking into account the allocation of alternative energy sources based on artificial intelligence methods

    Directory of Open Access Journals (Sweden)

    Marina ZHURAVSKAYA

    2014-12-01

    Full Text Available In the modern world the alternative energy sources, which considerably depend on a region, play more and more significant role. However, the transition of regions to new energy sources lead to the change of transport and logistic network configuration. The formation of optimal core transport network today is a guarantee of the successful economic development of a region tomorrow. The present article studies the issue of advanced core transport network development in a region based on the experience of European and Asian countries and the opportunity to adapt the best foreign experience to Russian conditions. On the basis of artificial intelligence methods for forest industry complex of Sverdlovskaya Oblast the algorithm of problem solution of an optimal logistic infrastructure allocation is offered and some results of a regional transport network are presented. These methods allowed to solve the set task in the conditions of information uncertainty. There are suggestions on the improvement of transport and logistic network in the territory of Sverdlovskaya Oblast. Traditionally the logistics of mineral fuel plays main role in regions development. Actually it is required to develop logistic strategic plans to be able to provide different possibilities of power-supply, flexible enough to change with the population density, transport infrastructure and demographics of different regions. The problem of logistic centers allocation was studied by many authors. The approach, offered by the authors of this paper is to solve the set of tasks by applying artificial intelligence methods, such as fuzzy set theory and genetic algorithms.

  11. Hybrid intelligence systems and artificial neural network (ANN approach for modeling of surface roughness in drilling

    Directory of Open Access Journals (Sweden)

    Ch. Sanjay

    2014-12-01

    Full Text Available In machining processes, drilling operation is material removal process that has been widely used in manufacturing since industrial revolution. The useful life of cutting tool and its operating conditions largely controls the economics of machining operations. Drilling is most frequently performed material removing process and is used as a preliminary step for many operations, such as reaming, tapping, and boring. Drill wear has a bad effect on the surface finish and dimensional accuracy of the work piece. The surface finish of a machined part is one of the most important quality characteristics in manufacturing industries. The primary objective of this research is the prediction of suitable parameters for surface roughness in drilling. Cutting speed, cutting force, and machining time were given as inputs to the adaptive fuzzy neural network and neuro-fuzzy analysis for estimating the values of surface roughness by using 2, 3, 4, and 5 membership functions. The best structures were selected based on minimum of summation of square with the actual values with the estimated values by artificial neural fuzzy inference system (ANFIS and neuro-fuzzy systems. For artificial neural network (ANN analysis, the number of neurons was selected from 1, 2, 3, … , 20. The learning rate was selected as .5 and .5 smoothing factor was used. The inputs were selected as cutting speed, feed, machining time, and thrust force. The best structures of neural networks were selected based on the criteria as the minimum of summation of square with the actual value of surface roughness. Drilling experiments with 10 mm size were performed at two cutting speeds and feeds. Comparative analysis has been done between the actual values and the estimated values obtained by ANFIS, neuro-fuzzy, and ANN analysis.

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

    Science.gov (United States)

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

    2009-11-01

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

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

    Science.gov (United States)

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

    2016-01-08

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

  14. 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  

  15. Mobile RFID of Wireless Mesh Network for Intelligent Safety Care System

    Directory of Open Access Journals (Sweden)

    Chwen-Fu Horng

    2009-12-01

    Full Text Available This paper presents the Wi-Fi phone with RFID (Radio frequency identification of student entered the school, via Wireless Access Points (APs of school will transmit MAC address with RFID of Wi-Fi phone to Internet Data Center (IDC for server and then the message exchanged by using GSM (or 3G has been transmitted message (or mail to the mobile user of parents (or client user. The wireless access points support broadcasting multiple SSIDs, each of which can have a different set of security and network setting. The RADIUS server is used to authenticate the Wireless Access Point (AP and mobile nodes. In safety case system, we used the several authentication and encryption options for the WLAN. We will discuss the use of Wi-Fi protected Access (WPA, RFID, IP Security (IPSec, and Secure Socket Layer (SSL, and there are high Quality of service (QoS and performance.

  16. Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks.

    Science.gov (United States)

    Kim, D H; MacKinnon, T

    2017-12-18

    To identify the extent to which transfer learning from deep convolutional neural networks (CNNs), pre-trained on non-medical images, can be used for automated fracture detection on plain radiographs. The top layer of the Inception v3 network was re-trained using lateral wrist radiographs to produce a model for the classification of new studies as either "fracture" or "no fracture". The model was trained on a total of 11,112 images, after an eightfold data augmentation technique, from an initial set of 1,389 radiographs (695 "fracture" and 694 "no fracture"). The training data set was split 80:10:10 into training, validation, and test groups, respectively. An additional 100 wrist radiographs, comprising 50 "fracture" and 50 "no fracture" images, were used for final testing and statistical analysis. The area under the receiver operator characteristic curve (AUC) for this test was 0.954. Setting the diagnostic cut-off at a threshold designed to maximise both sensitivity and specificity resulted in values of 0.9 and 0.88, respectively. The AUC scores for this test were comparable to state-of-the-art providing proof of concept for transfer learning from CNNs in fracture detection on plain radiographs. This was achieved using only a moderate sample size. This technique is largely transferable, and therefore, has many potential applications in medical imaging, which may lead to significant improvements in workflow productivity and in clinical risk reduction. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Bosse, Stefan

    2013-05-01

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

  18. Automatic detection of solitary pulmonary nodules using swarm intelligence optimized neural networks on CT images

    Directory of Open Access Journals (Sweden)

    Ezhil E. Nithila

    2017-06-01

    Full Text Available Lung Cancer is one of the most dangerous diseases that cause a large number of deaths. Early detection and analysis will be the only remedy. Computer-Aided Diagnosis (CAD plays a key role in the early detection and diagnosis of lung cancer. This paper develops a CAD system that focus on new heuristic search algorithm to optimize the Back Propagation Neural Network (BPNN in characterizing nodule from non-nodules. The proposed CAD system consists of four main stages: (i image acquisition (ii lesion detection, (iii texture feature extraction and (iv tumor characterization using a classifier. The optimization mechanism employs Particle Swarm Optimization (PSO with new inertia weight for NN in order to investigate the classification rate of these algorithms in reducing the problems of trapping in local minima and the slow convergence rate of current evolutionary learning algorithms. The experiments were conducted on CT images to classify into nodule and non-nodule from the tumor region of interest. The performance of the CAD system was evaluated for the texture characterized images taken from LIDC-IDRI and SPIE-AAPM databases. Due to improved inertia weight used in Particle Swarm (PS the CAD achieves highest classification accuracy of 98% for solid nodules, 99.5% for part solid nodules and 97.2% for non solid nodules respectively. The experimental results suggest that the developed CAD system has great potential and promise in the automatic diagnosis of tumors of lung.

  19. Intelligent Control for USV Based on Improved Elman Neural Network with TSK Fuzzy

    Directory of Open Access Journals (Sweden)

    Shang-Jen Chuang

    2014-01-01

    Full Text Available In recent years, based on the rising of global personal safety demand and human resource cost considerations, development of unmanned vehicles to replace manpower requirement to perform high-risk operations is increasing. In order to acquire useful resources under the marine environment, a large boat as an unmanned surface vehicle (USV was implemented. The USV is equipped with automatic navigation features and a complete substitute artificial manipulation. This USV system for exploring the marine environment has more carrying capacity and that measurement system can also be self-designed through a modular approach in accordance with the needs for various types of environmental conditions. The investigation work becomes more flexible. A catamaran hull is adopted as automatic navigation test with CompactRIO embedded system. Through GPS and direction sensor we not only can know the current location of the boat, but also can calculate the distance with a predetermined position and the angle difference immediately. In this paper, the design of automatic navigation is calculated in accordance with improved Elman neural network (ENN algorithms. Takagi-Sugeno-Kang (TSK fuzzy and improved ENN control are applied to adjust required power and steering, which allows the hull to move straight forward to a predetermined target position. The route will be free from outside influence and realize automatic navigation purpose.

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

    Science.gov (United States)

    Liu, Hongbo; Abraham, Ajith; Badr, Youakim

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

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

    Science.gov (United States)

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

    2009-07-01

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

  2. From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.

    Science.gov (United States)

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

    2016-02-01

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

  3. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  4. 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.

  5. Springer handbook of computational intelligence

    CERN Document Server

    Pedrycz, Witold

    2015-01-01

    This is the first book covering the basics and the state of the art and important applications of the complete growing discipline of computational intelligence. This comprehensive handbook presents a unique synergy of various approaches and new qualities to be gained by using hybrid approaches, incl. inspirations from biology and living organisms and animate systems. The text is organized in 7 main parts foundations, fuzzy sets, rough sets, evolutionary computation, neural networks, swarm intelligence and hybrid computational intelligence systems.

  6. 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...

  7. Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence.

    Science.gov (United States)

    Fukatsu, Hiroshi; Naganawa, Shinji; Yumura, Shinnichiro

    2008-04-01

    This study was aimed to validate the performance of a novel image compression method using a neural network to achieve a lossless compression. The encoding consists of the following blocks: a prediction block; a residual data calculation block; a transformation and quantization block; an organization and modification block; and an entropy encoding block. The predicted image is divided into four macro-blocks using the original image for teaching; and then redivided into sixteen sub-blocks. The predicted image is compared to the original image to create the residual image. The spatial and frequency data of the residual image are compared and transformed. Chest radiography, computed tomography (CT), magnetic resonance imaging, positron emission tomography, radioisotope mammography, ultrasonography, and digital subtraction angiography images were compressed using the AIC lossless compression method; and the compression rates were calculated. The compression rates were around 15:1 for chest radiography and mammography, 12:1 for CT, and around 6:1 for other images. This method thus enables greater lossless compression than the conventional methods. This novel method should improve the efficiency of handling of the increasing volume of medical imaging data.

  8. Design of AN Intelligent Individual Evacuation Model for High Rise Building Fires Based on Neural Network Within the Scope of 3d GIS

    Science.gov (United States)

    Atila, U.; Karas, I. R.; Turan, M. K.; Rahman, A. A.

    2013-09-01

    One of the most dangerous disaster threatening the high rise and complex buildings of today's world including thousands of occupants inside is fire with no doubt. When we consider high population and the complexity of such buildings it is clear to see that performing a rapid and safe evacuation seems hard and human being does not have good memories in case of such disasters like world trade center 9/11. Therefore, it is very important to design knowledge based realtime interactive evacuation methods instead of classical strategies which lack of flexibility. This paper presents a 3D-GIS implementation which simulates the behaviour of an intelligent indoor pedestrian navigation model proposed for a self -evacuation of a person in case of fire. The model is based on Multilayer Perceptron (MLP) which is one of the most preferred artificial neural network architecture in classification and prediction problems. A sample fire scenario following through predefined instructions has been performed on 3D model of the Corporation Complex in Putrajaya (Malaysia) and the intelligent evacuation process has been realized within a proposed 3D-GIS based simulation.

  9. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  10. Cyber threat intelligence exchange: A growing requirement

    CSIR Research Space (South Africa)

    Veerasamy, Namosha

    2017-06-01

    Full Text Available coming into the networks. Open source intelligence (OSINT) is derived from publically available information like books, publications, radio and television. In the context of the cyber threat intelligence, it can be sourced from the Internet from search... engines and other “crawling” technology. Human intelligence (HUMINT) differs somewhat in that SIGINT and OSINT can come from passive forms of intelligence collection like automated software but HUMINT is strongly active. It could consist of human...

  11. Hybrid intelligent engineering systems

    CERN Document Server

    Jain, L C; Adelaide, Australia University of

    1997-01-01

    This book on hybrid intelligent engineering systems is unique, in the sense that it presents the integration of expert systems, neural networks, fuzzy systems, genetic algorithms, and chaos engineering. It shows that these new techniques enhance the capabilities of one another. A number of hybrid systems for solving engineering problems are presented.

  12. 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...

  13. A Multi-Agent-Based Intelligent Sensor and Actuator Network Design for Smart House and Home Automation

    Directory of Open Access Journals (Sweden)

    Fei Hu

    2013-08-01

    Full Text Available The smart-house technology aims to increase home automation and security with reduced energy consumption. A smart house consists of various intelligent sensors and actuators operating on different platforms with conflicting objectives. This paper proposes a multi-agent system (MAS design framework to achieve smart house automation. The novelties of this work include the developments of (1 belief, desire and intention (BDI agent behavior models; (2 a regulation policy-based multi-agent collaboration mechanism; and (3 a set of metrics for MAS performance evaluation. Simulations of case studies are performed using the Java Agent Development Environment (JADE to demonstrate the advantages of the proposed method.

  14. Intelligence Ethics:

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist

    2016-01-01

    Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

  15. Intelligent Elements for ISHM

    Science.gov (United States)

    Schmalzel, John L.; Morris, Jon; Turowski, Mark; Figueroa, Fernando; Oostdyk, Rebecca

    2008-01-01

    There are a number of architecture models for implementing Integrated Systems Health Management (ISHM) capabilities. For example, approaches based on the OSA-CBM and OSA-EAI models, or specific architectures developed in response to local needs. NASA s John C. Stennis Space Center (SSC) has developed one such version of an extensible architecture in support of rocket engine testing that integrates a palette of functions in order to achieve an ISHM capability. Among the functional capabilities that are supported by the framework are: prognostic models, anomaly detection, a data base of supporting health information, root cause analysis, intelligent elements, and integrated awareness. This paper focuses on the role that intelligent elements can play in ISHM architectures. We define an intelligent element as a smart element with sufficient computing capacity to support anomaly detection or other algorithms in support of ISHM functions. A smart element has the capabilities of supporting networked implementations of IEEE 1451.x smart sensor and actuator protocols. The ISHM group at SSC has been actively developing intelligent elements in conjunction with several partners at other Centers, universities, and companies as part of our ISHM approach for better supporting rocket engine testing. We have developed several implementations. Among the key features for these intelligent sensors is support for IEEE 1451.1 and incorporation of a suite of algorithms for determination of sensor health. Regardless of the potential advantages that can be achieved using intelligent sensors, existing large-scale systems are still based on conventional sensors and data acquisition systems. In order to bring the benefits of intelligent sensors to these environments, we have also developed virtual implementations of intelligent sensors.

  16. Artificial neural networks in forecasting tourists’ flow, an intelligent technique to help the economic development of tourism in Albania.

    Directory of Open Access Journals (Sweden)

    Dezdemona Gjylapi

    2014-07-01

    The aim of this paper is to present the neural network usage in the tourists’ number forecasting and to determine the trends of the future tourist inflow, thus helping tourism management agencies in making scientific based financial decisions.

  17. Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

    Directory of Open Access Journals (Sweden)

    Kai Wu

    Full Text Available Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

  18. Optimized intelligent control of a 2-degree of freedom robot for rehabilitation of lower limbs using neural network and genetic algorithm.

    Science.gov (United States)

    Aminiazar, Wahab; Najafi, Farid; Nekoui, Mohammad Ali

    2013-08-14

    There is an increasing trend in using robots for medical purposes. One specific area is rehabilitation. Rehabilitation is one of the non-drug treatments in community health which means the restoration of the abilities to maximize independence. It is a prolonged work and costly labor. On the other hand, by using the flexible and efficient robots in rehabilitation area, this process will be more useful for handicapped patients. In this study, a rule-based intelligent control methodology is proposed to mimic the behavior of a healthy limb in a satisfactory way by a 2-DOF planar robot. Inverse kinematic of the planar robot will be solved by neural networks and control parameters will be optimized by genetic algorithm, as rehabilitation progress. The results of simulations are presented by defining a physiotherapy simple mode on desired trajectory. MATLAB/Simulink is used for simulations. The system is capable of learning the action of the physiotherapist for each patient and imitating this behaviour in the absence of a physiotherapist that can be called robotherapy. In this study, a therapeutic exercise planar 2-DOF robot is designed and controlled for lower-limb rehabilitation. The robot manipulator is controlled by combination of hybrid and adaptive controls. Some safety factors and stability constraints are defined and obtained. The robot is stopped when the safety factors are not satisfied. Kinematics of robot is estimated by an MLP neural network and proper control parameters are achieved using GA optimization.

  19. Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

    Science.gov (United States)

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2013-07-01

    Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Integrating RFID Technology and EPC Network into a B2B Retail Supply Chain: A Step Toward Intelligent Business Processes

    Directory of Open Access Journals (Sweden)

    Samuel Fosso Wamba

    2007-06-01

    Full Text Available This article introduces RFID technology and the EPC Network and investigates their potential for B-to-B eCommerce supply chain management. Based on empirical data gathered from four tightly interrelated firms from three layers of a supply chain, several scenarios integrating RFID and the EPC Network have been tested and evaluated. In the context of warehousing activities in one specific retail supply chain, the results indicate that i the business process approach seems quite appropriate to capture the real potential of RFID and the EPC Network; ii RFID technology and the EPC Network can improve the “shipping” and the “receiving” processes; iii they can automatically trigger some business processes; iv they foster a higher level of information sharing between supply chain members; and v they promote the emergence of new business processes such as “process-to-process,” “process-to-machine,” and “machine-to-machine.” The paper helps to improve our understanding of the real potential of RFID and the EPC Network for business processes.

  1. It's a small world after all: contrasting hierarchical and edge networks in a simulated intelligence analysis task.

    Science.gov (United States)

    Stanton, Neville A; Walker, Guy H; Sorensen, Linda J

    2012-01-01

    This article presents the rationale behind an important enhancement to a socio-technical model of organisations and teams derived from military research. It combines this with empirical results which take advantage of these enhancements. In Part 1, a new theoretical legacy for the model is developed based on Ergonomics theories and insights. This allows team communications data to be plotted into the model and for it to demonstrate discriminate validity between alternative team structures. Part 2 presents multinational data from the Experimental Laboratory for Investigating Collaboration, Information-sharing, and Trust (ELICIT) community. It was surprising to see that teams in both traditional hierarchical command and control and networked 'peer-to-peer' organisations operate in broadly the same area of the model, a region occupied by networks of communication exhibiting 'small world' properties. Small world networks may be of considerable importance for the Ergonomics analysis of team organisation and performance. This article is themed around macro and systems Ergonomics, and examines the effects of command and control structures. Despite some differences in behaviour and measures of agility, when given the freedom to do so, participants organised themselves into a small world network. This network type has important and interesting implications for the Ergonomics design of teams and organisations.

  2. 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...

  3. Artificial Intelligence,

    Science.gov (United States)

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

  4. Multi-Modal Intelligent Traffic Signal Systems (MMITSS) impacts assessment.

    Science.gov (United States)

    2015-08-01

    The study evaluates the potential network-wide impacts of the Multi-Modal Intelligent Transportation Signal System : (MMITSS) based on a field data analysis utilizing data collected from a MMITSS prototype and a simulation analysis. : The Intelligent...

  5. Graph metrics of structural brain networks in individuals with schizophrenia and healthy controls : Group differences, relationships with intelligence, and genetics

    NARCIS (Netherlands)

    Yeo, Ronald A.; Ryman, Sephira G.; Van Den Heuvel, Martijn P.; De Reus, Marcel A.; Jung, Rex E.; Pommy, Jessica; Mayer, Andrew R.; Ehrlich, Stefan; Schulz, S. Charles; Morrow, Eric M.; Manoach, Dara; Ho, Beng Choon; Sponheim, Scott R.; Calhoun, Vince D.

    2016-01-01

    Objectives: One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of

  6. An Intelligent Approach to Educational Data: Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks

    Science.gov (United States)

    Kayri, Murat

    2015-01-01

    The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…

  7. 2nd International Conference on Intelligent Transportation

    CERN Document Server

    2017-01-01

    These proceedings present the latest information on intelligent- transportation technologies and their applications in real-world cases. The Second International Conference on Intelligent Transportation was held in Chengdu, China on November 25–27, 2015, to present the latest research in the field, including intelligent-transportation management, intelligent vehicles, rail transportation systems, traffic transportation networks, as well as road traffic element simulations and their industrial development. The aim of conference was to bring together academics, researchers, engineers and students from across the world to discuss state-of-the-art technologies related to intelligent transportation.

  8. Intelligent Design

    DEFF Research Database (Denmark)

    Hjorth, Poul G.

    2005-01-01

    Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig.......Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig....

  9. Illusory Intelligences?

    Science.gov (United States)

    White, John

    2008-01-01

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

  10. Structure and weights optimisation of a modified Elman network emotion classifier using hybrid computational intelligence algorithms: a comparative study

    Science.gov (United States)

    Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood

    2015-10-01

    Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.

  11. 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.

  12. 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.

  13. Using Artificial Intelligence to Retrieve the Optimal Parameters and Structures of Adaptive Network-Based Fuzzy Inference System for Typhoon Precipitation Forecast Modeling

    Directory of Open Access Journals (Sweden)

    Chien-Lin Huang

    2015-01-01

    Full Text Available This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.

  14. Development of intelligent systems based on Bayesian regularization network and neuro-fuzzy models for mass detection in mammograms: A comparative analysis.

    Science.gov (United States)

    Mahersia, Hela; Boulehmi, Hela; Hamrouni, Kamel

    2016-04-01

    Female breast cancer is the second most common cancer in the world. Several efforts in artificial intelligence have been made to help improving the diagnostic accuracy at earlier stages. However, the identification of breast abnormalities, like masses, on mammographic images is not a trivial task, especially for dense breasts. In this paper we describe our novel mass detection process that includes three successive steps of enhancement, characterization and classification. The proposed enhancement system is based mainly on the analysis of the breast texture. First of all, a filtering step with morphological operators and soft thresholding is achieved. Then, we remove from the filtered breast region, all the details that may interfere with the eventual masses, including pectoral muscle and galactophorous tree. The pixels belonging to this tree will be interpolated and replaced by the average of the neighborhood. In the characterization process, measurement of the Gaussian density in the wavelet domain allows the segmentation of the masses. Finally, a comparative classification mechanism based on the Bayesian regularization back-propagation networks and ANFIS techniques is proposed. The tests were conducted on the MIAS database. The results showed the robustness of the proposed enhancement method. Copyright © 2016. Published by Elsevier Ireland Ltd.

  15. A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks

    Directory of Open Access Journals (Sweden)

    Aamir Shahzad

    2016-03-01

    Full Text Available In Industrial systems, Supervisory control and data acquisition (SCADA system, the pseudo-transport layer of the distributed network protocol (DNP3 performs the functions of the transport layer and network layer of the open systems interconnection (OSI model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design.

  16. France bundles knowledge and expertise in intelligent energy networks; Frankrijk bundelt kennis en expertise in intelligente energienetwerken

    Energy Technology Data Exchange (ETDEWEB)

    Van Kooij, E.

    2012-03-15

    The networks that provides cities, office buildings, houses, cars and mobile phones with energy, is expected in the coming years to be digitized. The French innovation cluster Systematic has recently taken the initiative to set up a knowledge partnership which should connect knowledge and expertise with regard to future smart grids [Dutch] Het netwerk dat onze steden, kantoren, huizen, auto's en mobieltjes van energie voorziet, zal naar verwachting in de komende jaren een digitalisering ondergaan. Het Franse innovatiecluster Systematic heeft onlangs het initiatief genomen een samenwerkingsverband op te richten die kennis en expertise op het gebied van toekomstige intelligente energienetwerken bij elkaar brengt.

  17. Self-organizing intelligent network of smart electrical heating devices as an alternative to traditional ways of heating

    Science.gov (United States)

    Zaslavsky, Aleksander M.; Tkachov, Viktor V.; Protsenko, Stanislav M.; Bublikov, Andrii V.; Suleimenov, Batyrbek; Orshubekov, Nurbek; Gromaszek, Konrad

    2017-08-01

    The paper considers the problem of automated decentralized distribution of the electric energy among unlimited-power electric heaters providing the given temperature distribution within the zones of monitored object heating in the context of maximum use of electric power which limiting level is time-dependent randomly. Principles of collective selforganization automata for solving the problem are analyzed. It has been shown that after all the automata make decision, equilibrium of Nash type is attained when unused power within the electric network is not more than a power of any non-energized electric heater.

  18. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  19. Intelligent playgrounds

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2009-01-01

    This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

  20. Intelligent Decision Technologies : Proceedings of the 4th International Conference on Intelligent Decision Technologies

    CERN Document Server

    Watanabe, Toyohide; Phillips-Wren, Gloria; Howlett, Robert; Jain, Lakhmi

    2012-01-01

    The Intelligent Decision Technologies (IDT) International Conference encourages an interchange of research on intelligent systems and intelligent technologies that enhance or improve decision making. The focus of IDT is interdisciplinary and includes research on all aspects of intelligent decision technologies, from fundamental development to real applications. IDT has the potential to expand their support of decision making in such areas as finance, accounting, marketing, healthcare, medical and diagnostic systems, military decisions, production and operation, networks, traffic management, crisis response, human-machine interfaces, financial and stock market monitoring and prediction, and robotics. Intelligent decision systems implement advances in intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, and genetic algorithms, among others.  Emerging areas of active research include virtual decision environments, social networking, 3D human-machine interfaces, cognitive interfaces,...

  1. 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...

  2. 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.

  3. Unsupervised learning of mixture models based on swarm intelligence and neural networks with optimal completion using incomplete data

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abas

    2012-07-01

    Full Text Available In this paper, a new algorithm is presented for unsupervised learning of finite mixture models (FMMs using data set with missing values. This algorithm overcomes the local optima problem of the Expectation-Maximization (EM algorithm via integrating the EM algorithm with Particle Swarm Optimization (PSO. In addition, the proposed algorithm overcomes the problem of biased estimation due to overlapping clusters in estimating missing values in the input data set by integrating locally-tuned general regression neural networks with Optimal Completion Strategy (OCS. A comparison study shows the superiority of the proposed algorithm over other algorithms commonly used in the literature in unsupervised learning of FMM parameters that result in minimum mis-classification errors when used in clustering incomplete data set that is generated from overlapping clusters and these clusters are largely different in their sizes.

  4. 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

  5. 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.

  6. International Symposium on Intelligent Systems Technologies and Applications

    CERN Document Server

    Thampi, Sabu; Dasgupta, Soura; Srivastava, Praveen; ISTA

    2016-01-01

    This book contains a selection of refereed and revised papers from three special tracks: Ad-hoc and Wireless Sensor Networks, Intelligent Distributed Computing and, Business Intelligence and Big Data Analytics originally presented at the International Symposium on Intelligent Systems Technologies and Applications (ISTA), August 10-13, 2015, Kochi, India.  .

  7. How Intelligent is your Intelligent Robot?

    OpenAIRE

    Winfield, Alan F. T.

    2017-01-01

    How intelligent is robot A compared with robot B? And how intelligent are robots A and B compared with animals (or plants) X and Y? These are both interesting and deeply challenging questions. In this paper we address the question "how intelligent is your intelligent robot?" by proposing that embodied intelligence emerges from the interaction and integration of four different and distinct kinds of intelligence. We then suggest a simple diagrammatic representation on which these kinds of intel...

  8. 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 ...

  9. Intelligent detection of microcalcification from digitized mammograms

    Indian Academy of Sciences (India)

    Breast cancer; digital mammogram; artificial neural networks; microcalcification detection. Abstract. This paper reports the design and implementation of an intelligent system for detection of microcalcification from digital mammograms. ... Suspected areas of microcalcification are detected and marked on the mammogram.

  10. Effect of noise in intelligent cellular decision making.

    Science.gov (United States)

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

    2015-01-01

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

  11. Effect of noise in intelligent cellular decision making.

    Directory of Open Access Journals (Sweden)

    Russell Bates

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

  12. 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 ...

  13. 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

  14. Mechanics issues in intelligent structures

    Science.gov (United States)

    Sirkis, J. S.; Dasgupta, A.

    This paper describes many of the fundamental mechanics issues currently inhibiting the realization of the 'intelligent structures' concept. We view what is commonly referred to as 'intelligent structures' more as sensory and adaptive materials and structures that use distributed networks of structurally integrated actuator and sensor devices to achieve self-monitoring and self-adapting capabilities. Each embedded micro-device has a very localized response on the microscale to an input stimulus, which combines with the localized response of the other micro-devices in the network to produce a metered response in the macroscale structure. All length-scales posses inherent geometric, material, and time dependent non-linearities which must be successfully addressed. The goal of the mechanics research in 'intelligent structures' should be to model the inherent linear and nonlinear interaction mechanics so that accumulating modification to structural response can be predicted and then either accounted for or actively changed in some way.

  15. International Conference on Intelligent Technologies and Engineering System (ICITES 2012)

    CERN Document Server

    Huang, Yi-Cheng; Intelligent Technologies and Engineering Systems

    2013-01-01

    This book concentrates on intelligent technologies as it relates to engineering systems. The book covers the following topics: networking, signal processing, artificial intelligence, control and software engineering, intelligent electronic circuits and systems, communications, and materials and mechanical engineering. The book is a collection of original papers that have been reviewed by technical editors. These papers were presented at the International Conference on Intelligent Technologies and Engineering Systems, held Dec. 13-15, 2012.

  16. Artificial Intelligence A New Synthesis

    CERN Document Server

    Nilsson, Nils J

    1998-01-01

    Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading re

  17. 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....

  18. Speech Intelligibility

    Science.gov (United States)

    Brand, Thomas

    Speech intelligibility (SI) is important for different fields of research, engineering and diagnostics in order to quantify very different phenomena like the quality of recordings, communication and playback devices, the reverberation of auditoria, characteristics of hearing impairment, benefit using hearing aids or combinations of these things.

  19. Multiple Intelligences.

    Science.gov (United States)

    Laughlin, Janet

    1999-01-01

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

  20. Corneal Intelligence

    African Journals Online (AJOL)

    Murdoch3

    Corneal Intelligence. Ian Murdoch. Institute of Ophthalmology, Bath Street, London. In 2002, the ocular hypertension treatment study (OHTS) published their results. This study had taken 1636 ocular hypertensives. 1, 2. (IOP 24-32mmHg) and randomized them to receive therapy or no therapy. The primary outcome of the ...

  1. 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......, 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....... Working through these cases, students will learn to manage and evaluate realistic intelligence accounts....

  2. Spiritual Intelligence, Emotional Intelligence and Auditor's Performance

    OpenAIRE

    Hanafi, Rustam

    2010-01-01

    The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

  3. Integrating artificial intelligence into organizational intelligence

    OpenAIRE

    Leon, Florin; Gabriela M. Atanasiu

    2008-01-01

    Organizational intelligence is the capability of an organization to create knowledge and to use it in order to strategically adapt to its environment. Intelligence of an organization is more than the aggregated intelligence of its members – it is an emergent property of the complex interactions of its subsystems and the way they are aggregated. Processes analyse related to organizational intelligence can be achieved by means of agent-based simulations. Distributed artificial intelligence addr...

  4. An Introduction to Intelligent Networks

    Science.gov (United States)

    1994-02-01

    Branch Exchange POTS Plain Old Telephone Service SO" Service Control Point SM Service Manager SSP Service Switching Point STP Signal Transfer Point RINA...central to the IN concept; specifically: Service Switching Point (SSP); Signal Transfer Point (STP): Service Control Point (SUP); Service Manager (SM... Manager The human interface for operating personnel and users to specify services is provided by the Service Manager . This serves as the central

  5. Team B Intelligence Coups

    Science.gov (United States)

    Mitchell, Gordon R.

    2006-01-01

    The 2003 Iraq prewar intelligence failure was not simply a case of the U.S. intelligence community providing flawed data to policy-makers. It also involved subversion of the competitive intelligence analysis process, where unofficial intelligence boutiques "stovepiped" misleading intelligence assessments directly to policy-makers and…

  6. Intelligent Design and Intelligent Failure

    Science.gov (United States)

    Jerman, Gregory

    2015-01-01

    Good Evening, my name is Greg Jerman and for nearly a quarter century I have been performing failure analysis on NASA's aerospace hardware. During that time I had the distinct privilege of keeping the Space Shuttle flying for two thirds of its history. I have analyzed a wide variety of failed hardware from simple electrical cables to cryogenic fuel tanks to high temperature turbine blades. During this time I have found that for all the time we spend intelligently designing things, we need to be equally intelligent about understanding why things fail. The NASA Flight Director for Apollo 13, Gene Kranz, is best known for the expression "Failure is not an option." However, NASA history is filled with failures both large and small, so it might be more accurate to say failure is inevitable. It is how we react and learn from our failures that makes the difference.

  7. Security-Enhanced Autonomous Network Management for Space Networking Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Intelligent Automation Inc. (IAI) proposes an innovative Security-Enhanced Autonomous Network Management (SEANM) scheme for reliable communication in space...

  8. Soft computing for business intelligence

    CERN Document Server

    Pérez, Rafael; Cobo, Angel; Marx, Jorge; Valdés, Ariel

    2014-01-01

    The book Soft Computing for Business Intelligence is the remarkable output of a program based on the idea of joint trans-disciplinary research as supported by the Eureka Iberoamerica Network and the University of Oldenburg. It contains twenty-seven papers allocated to three sections: Soft Computing, Business Intelligence and Knowledge Discovery, and Knowledge Management and Decision Making. Although the contents touch different domains they are similar in so far as they follow the BI principle “Observation and Analysis” while keeping a practical oriented theoretical eye on sound methodologies, like Fuzzy Logic, Compensatory Fuzzy Logic (CFL), Rough Sets and other softcomputing elements. The book tears down the traditional focus on business, and extends Business Intelligence techniques in an impressive way to a broad range of fields like medicine, environment, wind farming, social collaboration and interaction, car sharing and sustainability.

  9. New trends in computational collective intelligence

    CERN Document Server

    Kim, Sang-Wook; Trawiński, Bogdan

    2015-01-01

    This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

  10. Intelligent computing systems emerging application areas

    CERN Document Server

    Virvou, Maria; Jain, Lakhmi

    2016-01-01

    This book at hand explores emerging scientific and technological areas in which Intelligent Computing Systems provide efficient solutions and, thus, may play a role in the years to come. It demonstrates how Intelligent Computing Systems make use of computational methodologies that mimic nature-inspired processes to address real world problems of high complexity for which exact mathematical solutions, based on physical and statistical modelling, are intractable. Common intelligent computational methodologies are presented including artificial neural networks, evolutionary computation, genetic algorithms, artificial immune systems, fuzzy logic, swarm intelligence, artificial life, virtual worlds and hybrid methodologies based on combinations of the previous. The book will be useful to researchers, practitioners and graduate students dealing with mathematically-intractable problems. It is intended for both the expert/researcher in the field of Intelligent Computing Systems, as well as for the general reader in t...

  11. 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.)

  12. Communications and Intelligent Systems Division Overview

    Science.gov (United States)

    Emerson, Dawn

    2017-01-01

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

  13. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

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

  14. Business Intelligence

    OpenAIRE

    Petersen, Anders

    2001-01-01

    Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

  15. 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.

  16. 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

  17. 16th UK Workshop on Computational Intelligence

    CERN Document Server

    Gegov, Alexander; Jayne, Chrisina; Shen, Qiang

    2017-01-01

    The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, evolving systems and machine learning. The individual chapters are based on peer-reviewed contributions presented at the 16th Annual UK Workshop on Computational Intelligence, held on September 7-9, 2016, in Lancaster, UK. The book puts a special emphasis on novels methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.

  18. 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

  19. 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

  20. Intelligent products : A survey

    NARCIS (Netherlands)

    Meyer, G.G.; Främling, K.; Holmström, J.

    This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

  1. The Advantages of Human Milk Recognize the Spatiotemporal Locations of Toxins and Intelligently Bypass Them by Forming a Hummingbird-Like Hovering Neural Network Circuitry Based on an Organic Biomimetic Choline Acetyltransferase Memristor/Memcapacitor Prosthesis

    Directory of Open Access Journals (Sweden)

    E. T. CHEN

    2016-08-01

    Full Text Available We have demonstrated a unique approach to study human milk’s advantage in promoting and protecting infant early brain cognitive development by recognizing toxins and intelligently bypassing the toxin by forming high frequency oscillation (HFO in the brain circuitry when compared with organic cow milk samples based on an organic memristor/memcapacitor biomimetic Choline Acetyltransferase (CHAT neural network circuitry prosthesis along with a 3D Energy-sensory dynamic mapping method under antibody- free, radiolabeling-free, and reagent-less conditions. We also demonstrated cow milk is unfit for infant cognitive development, and it is actually harmful in terms of mutating infant brain synapse circuitry conformation, current flow direction, and energy output that lead to multiple Pathological High Frequency Oscillation (pHFO formations, and further, it led to sudden infant death syndrome (SIDS based on our prediction.

  2. Intelligent Routines

    CERN Document Server

    Anastassiou, George A

    Intelligent Routines II: Solving Linear Algebra and Differential Geometry with Sage” contains numerous of examples and problems as well as many unsolved problems. This book extensively applies the successful software Sage, which can be found free online http://www.sagemath.org/. Sage is a recent and popular software for mathematical computation, available freely and simple to use. This book is useful to all applied scientists in mathematics, statistics and engineering, as well for late undergraduate and graduate students of above subjects. It is the first such book in solving symbolically with Sage problems in Linear Algebra and Differential Geometry. Plenty of SAGE applications are given at each step of the exposition.

  3. Intelligent Governmentality

    Directory of Open Access Journals (Sweden)

    Willem de Lint

    2008-10-01

    Full Text Available Recently, within liberal democracies, the post-Westphalian consolidation of security and intelligence has ushered in the normalization not only of security in ‘securitization’ but also of intelligence in what is proposed here as ‘intelligencification.’ In outlining the features of intelligencified governance, my aim is to interrogate the view that effects or traces, and productivity rather than negation is as persuasive as commonly thought by the constructivists. After all, counter-intelligence is both about purging and reconstructing the archive for undisclosed values. In practice, what is being normalized is the authorized and legalized use of release and retention protocols of politically actionable information. The intelligencification of governmentality affords a sovereignty shell-game or the instrumentalization of sovereign power by interests that are dependent on, yet often inimical to, the power of state, national, and popular sovereignty. On voit le politique et le social comme dépendant de contingences exclusives. Récemment, au sein des démocraties libérales, la consolidation de la sécurité et des services de renseignements de sécurité qui a suivi les traités de la Westphalie a donné lieu à la normalisation non seulement de la sécurité en «sécurisation» mais aussi des services de renseignements de sécurité en ce qui est proposé ici comme «intelligencification» [terme anglais créé par l’auteur, dérivé du mot anglais «intelligence» dans le sens de renseignements des écurité]. En particulier, ce que l’on normalise dans le but de contourner des contingences exclusives est l’utilisation autorisée et légalisée de protocoles de communication et de rétention d’information qui, politiquement, pourrait mener à des poursuites. En esquissant les traits de la gouvernance «intelligencifiée», mon but est d’interroger le point de vue que les effets ou les traces, et la productivité plutôt que la

  4. Intelligible Pronunciation

    Directory of Open Access Journals (Sweden)

    Luciana Junqueira

    2016-07-01

    Full Text Available It is an accepted fact in the fields of Applied Linguistics and Second Language Acquisition that most people who learn a second language after puberty do not acquire a native-like accent, showing non-native patterns in their pronunciation (DERWING, 2003; GASS and SELINKER, 2008; BROWN, 2007. As a result, in the past few decades scholars have argued for the implementation of more realistic goals for pronunciation and speaking instruction, such as intelligibility and comprehensibility, in the ESL/EFL fields. However, despite the numerous studies discouraging the pursuit of native-like accents and promoting more realistic goals, the number of students who desire to sound like native speakers is still overwhelming (DERWING, 2003; DERWING; MUNRO, 2005; JENKINS, 2005; LEVIS, 2005; WATERS, 2007. Moreover, it is clear that several schools and language institutes, among other educational institutions, value native speakers over non-native professionals. Another very current manifestation in the field is the constant promotion of programs that strive for accent reduction and of pronunciation materials that promise native-like pronunciation (LEVIS, 2005; MUNRO; DERWIN; SATO, 2006. The lack of empirical research and of materials that are applied to teachers’ and students’ needs in the classroom is also a major problem encountered in current pronunciation instruction (DERWING; MUNRO, 2005. Lastly, non-native accents generate social evaluations, which are usually negative. Accordingly, in this work, in order to better understand this debate, I briefly review the history of pronunciation instruction, focusing on the issues of intelligibility, comprehensibility, and identity, and analyze the societal evaluations underlying the complex and social phenomenon of pronunciation. Furthermore, I propose directions I believe could be taken in attempt to improve the present situation for pronunciation teaching and beliefs about native-like/non-native accents.

  5. 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...

  6. Software and Network Engineering

    CERN Document Server

    2012-01-01

    The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.   The purpose of the first ACIS International Symposium on Software and Network Engineering held on Decembe...

  7. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  8. Intelligent nesting system

    Directory of Open Access Journals (Sweden)

    Đuričić Zoran

    2003-01-01

    Full Text Available The economy of the process for the manufacture of parts from sheet metal plates depends on successful solution of the process of cutting various parts from sheet metal plates. Essentially, the problem is to arrange contours within a defined space so that they take up minimal surface. When taken in this way, the considered problem assumes a more general nature; it refers to the utilization of a flat surface, and it can represent a general principle of arranging 2D contours on a certain surface. The paper presents a conceptual solution and a prototypal intelligent nesting system for optimal cutting. The problem of nesting can generally be divided into two intellectual phases: recognition and classification of shapes, and arrangement of recognized shapes on a given surface. In solving these problems, methods of artificial intelligence are applied. In the paper, trained neural network is used for recognition of shapes; on the basis of raster record of a part's drawing, it recognizes the part's shape and which class it belongs to. By means of the expert system, based on rules defined on the basis of acquisition of knowledge from manufacturing sections, as well as on the basis of certain mathematical algorithms, parts are arranged on the arrangement surface. Both systems can also work independently, having been built on the modular principle. The system uses various product models as elements of integration for the entire system. .

  9. 2nd International Symposium on Intelligent Systems Technologies and Applications

    CERN Document Server

    Mitra, Sushmita; Thampi, Sabu; El-Alfy, El-Sayed

    2016-01-01

    This book constitutes the thoroughly refereed proceedings of the second International Symposium on Intelligent Systems Technologies and Applications (ISTA’16), held on September 21–24, 2016 in Jaipur, India. The 80 revised papers presented were carefully reviewed and selected from 210 initial submissions and are organized in topical sections on image processing and artificial vision, computer networks and distributed systems, intelligent tools and techniques and applications using intelligent techniques.

  10. 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 ...

  11. Bayesian Networks and Influence Diagrams

    DEFF Research Database (Denmark)

    Kjærulff, Uffe Bro; Madsen, Anders Læsø

     Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification...

  12. An Intelligent Weather Station.

    Science.gov (United States)

    Mestre, Gonçalo; Ruano, Antonio; Duarte, Helder; Silva, Sergio; Khosravani, Hamid; Pesteh, Shabnam; Ferreira, Pedro M; Horta, Ricardo

    2015-12-10

    Accurate measurements of global solar radiation, atmospheric temperature and relative humidity, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight, self-powered and portable sensor was developed, using a nearest-neighbors (NEN) algorithm and artificial neural network (ANN) models as the time-series predictor mechanisms. The hardware and software design of the implemented prototype are described, as well as the forecasting performance related to the three atmospheric variables, using both approaches, over a prediction horizon of 48-steps-ahead.

  13. An Intelligent Weather Station

    Science.gov (United States)

    Mestre, Gonçalo; Ruano, Antonio; Duarte, Helder; Silva, Sergio; Khosravani, Hamid; Pesteh, Shabnam; Ferreira, Pedro M.; Horta, Ricardo

    2015-01-01

    Accurate measurements of global solar radiation, atmospheric temperature and relative humidity, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight, self-powered and portable sensor was developed, using a nearest-neighbors (NEN) algorithm and artificial neural network (ANN) models as the time-series predictor mechanisms. The hardware and software design of the implemented prototype are described, as well as the forecasting performance related to the three atmospheric variables, using both approaches, over a prediction horizon of 48-steps-ahead. PMID:26690433

  14. Intelligence Community Reorganization: Potential Effects on DOD Intelligence Agencies

    National Research Council Canada - National Science Library

    Best, Jr, Richard A

    2004-01-01

    Although the Central Intelligence Agency (CIA) is the best known member of the Intelligence Community, the bulk of the nation's intelligence effort is undertaken by the intelligence agencies of the Department of Defense (DoD...

  15. 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. .

  16. 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.…

  17. Intelligence Policy and the Science of Intelligence

    Science.gov (United States)

    Baginski, Maureen

    Intelligence policy must protect the security of intelligence sources, and the privacy of individuals. We have moved away from a world in which the most important information was secret, and was very hard to collect. Today there is a lot of valuable information that is available open source, and provides key context for intelligence analysis. At the same time, a scientific focus is needed to define the missing elements, so that they can be collected. Moving away from the “vacuum cleaner” approach will improve intelligence operations and, at the same time, solve many of the most difficult issues of privacy of citizens and security of sources.

  18. Educational Programs for Intelligence Professionals.

    Science.gov (United States)

    Miller, Jerry P.

    1994-01-01

    Discusses the need for education programs for competitive intelligence professionals. Highlights include definitions of intelligence functions, focusing on business intelligence; information utilization by decision makers; information sources; competencies for intelligence professionals; and the development of formal education programs. (38…

  19. A New Dimension of Business Intelligence: Location-based Intelligence

    OpenAIRE

    Zeljko Panian

    2012-01-01

    Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

  20. Speech Intelligibility Evaluation for Mobile Phones

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Cubick, Jens; Dau, Torsten

    2015-01-01

    In the development process of modern telecommunication systems, such as mobile phones, it is common practice to use computer models to objectively evaluate the transmission quality of the system, instead of time-consuming perceptual listening tests. Such models have typically focused on the quality...... of the transmitted speech, while little or no attention has been provided to speech intelligibility. The present study investigated to what extent three state-of-the art speech intelligibility models could predict the intelligibility of noisy speech transmitted through mobile phones. Sentences from the Danish...... Dantale II speech material were mixed with three different kinds of background noise, transmitted through three different mobile phones, and recorded at the receiver via a local network simulator. The speech intelligibility of the transmitted sentences was assessed by six normal-hearing listeners...

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

    Science.gov (United States)

    Booth, Richard G

    2016-01-01

    The increased adoption and use of technology within healthcare and society has influenced the nursing informatics specialty in a multitude of fashions. Namely, the nursing informatics specialty currently faces a range of important decisions related to its knowledge base, established values and future directions - all of which are in need of development and future-proofing. In light of the increased use of automation, artificial intelligence and big data in healthcare, the specialty must also reconceptualize the roles of both nurses and informaticians to ensure that the nursing profession is ready to operate within future digitalized healthcare ecosystems. To explore these goals, the author of this manuscript outlines an examination of technological advancements currently taking place within healthcare, and also proposes implications for the nursing role and the nursing informatics specialty. Finally, recommendations and insights towards how the roles of nurses and informaticians might evolve or be shaped in the growing post-nursing informatics era are presented. Copyright © 2016 Longwoods Publishing.

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

    Science.gov (United States)

    Theisen, Bernard L.

    2010-01-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of four unmanned systems student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned ground vehicle. Teams from around the world focus on developing a suite of dual-use technologies to equip their system of the future with intelligent driving capabilities. Over the past 17 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 70 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

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

    Science.gov (United States)

    Theisen, Bernard L.; Nguyen, Dmitri

    2006-10-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 14 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 50 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

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

    Science.gov (United States)

    Theisen, Bernard L.

    2007-09-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 15 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 50 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

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

    Science.gov (United States)

    Theisen, Bernard L.

    2009-01-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 16 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from nearly 70 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

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

    Science.gov (United States)

    Theisen, Bernard L.

    2005-10-01

    The Intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 13 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 50 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

  7. Computational intelligence techniques in bioinformatics.

    Science.gov (United States)

    Hassanien, Aboul Ella; Al-Shammari, Eiman Tamah; Ghali, Neveen I

    2013-12-01

    Computational intelligence (CI) is a well-established paradigm with current systems having many of the characteristics of biological computers and capable of performing a variety of tasks that are difficult to do using conventional techniques. It is a methodology involving adaptive mechanisms and/or an ability to learn that facilitate intelligent behavior in complex and changing environments, such that the system is perceived to possess one or more attributes of reason, such as generalization, discovery, association and abstraction. The objective of this article is to present to the CI and bioinformatics research communities some of the state-of-the-art in CI applications to bioinformatics and motivate research in new trend-setting directions. In this article, we present an overview of the CI techniques in bioinformatics. We will show how CI techniques including neural networks, restricted Boltzmann machine, deep belief network, fuzzy logic, rough sets, evolutionary algorithms (EA), genetic algorithms (GA), swarm intelligence, artificial immune systems and support vector machines, could be successfully employed to tackle various problems such as gene expression clustering and classification, protein sequence classification, gene selection, DNA fragment assembly, multiple sequence alignment, and protein function prediction and its structure. We discuss some representative methods to provide inspiring examples to illustrate how CI can be utilized to address these problems and how bioinformatics data can be characterized by CI. Challenges to be addressed and future directions of research are also presented and an extensive bibliography is included. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. 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...

  9. The National Artificial Intelligence Research And Development Strategic Plan

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential...

  10. 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.

  11. R and E: Communications and Intelligent Systems Division (LC)

    Science.gov (United States)

    Emerson, Dawn C.; Miranda, Felix A.

    2015-01-01

    This presentation is intended for the Ohio Federal Research Network's Centers of Excellence. The presentation provides an overview of the Communications and Intelligent Systems Division including current research and engineering work as well as future technology needs.

  12. Intelligent Extruder

    Energy Technology Data Exchange (ETDEWEB)

    AlperEker; Mark Giammattia; Paul Houpt; Aditya Kumar; Oscar Montero; Minesh Shah; Norberto Silvi; Timothy Cribbs

    2003-04-24

    ''Intelligent Extruder'' described in this report is a software system and associated support services for monitoring and control of compounding extruders to improve material quality, reduce waste and energy use, with minimal addition of new sensors or changes to the factory floor system components. Emphasis is on process improvements to the mixing, melting and de-volatilization of base resins, fillers, pigments, fire retardants and other additives in the :finishing'' stage of high value added engineering polymer materials. While GE Plastics materials were used for experimental studies throughout the program, the concepts and principles are broadly applicable to other manufacturers materials. The project involved a joint collaboration among GE Global Research, GE Industrial Systems and Coperion Werner & Pleiderer, USA, a major manufacturer of compounding equipment. Scope of the program included development of a algorithms for monitoring process material viscosity without rheological sensors or generating waste streams, a novel detection scheme for rapid detection of process upsets and an adaptive feedback control system to compensate for process upsets where at line adjustments are feasible. Software algorithms were implemented and tested on a laboratory scale extruder (50 lb/hr) at GE Global Research and data from a production scale system (2000 lb/hr) at GE Plastics was used to validate the monitoring and detection software. Although not evaluated experimentally, a new concept for extruder process monitoring through estimation of high frequency drive torque without strain gauges is developed and demonstrated in simulation. A plan to commercialize the software system is outlined, but commercialization has not been completed.

  13. Airborne Network Optimization with Dynamic Network Update

    Science.gov (United States)

    2015-03-26

    Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University...require small amounts of network bandwidth to perform routing. This thesis advocates the use of Kalman filters to predict network congestion in...airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The

  14. Fuzzy Logic-based Intelligent Scheme for Enhancing QoS of Vertical Handover Decision in Vehicular Ad-hoc Networks

    Science.gov (United States)

    Azzali, F.; Ghazali, O.; Omar, M. H.

    2017-08-01

    The design of next generation networks in various technologies under the “Anywhere, Anytime” paradigm offers seamless connectivity across different coverage. A conventional algorithm such as RSSThreshold algorithm, that only uses the received strength signal (RSS) as a metric, will decrease handover performance regarding handover latency, delay, packet loss, and handover failure probability. Moreover, the RSS-based algorithm is only suitable for horizontal handover decision to examine the quality of service (QoS) compared to the vertical handover decision in advanced technologies. In the next generation network, vertical handover can be started based on the user’s convenience or choice rather than connectivity reasons. This study proposes a vertical handover decision algorithm that uses a Fuzzy Logic (FL) algorithm, to increase QoS performance in heterogeneous vehicular ad-hoc networks (VANET). The study uses network simulator 2.29 (NS 2.29) along with the mobility traffic network and generator to implement simulation scenarios and topologies. This helps the simulation to achieve a realistic VANET mobility scenario. The required analysis on the performance of QoS in the vertical handover can thus be conducted. The proposed Fuzzy Logic algorithm shows improvement over the conventional algorithm (RSSThreshold) in the average percentage of handover QoS whereby it achieves 20%, 21% and 13% improvement on handover latency, delay, and packet loss respectively. This is achieved through triggering a process in layer two and three that enhances the handover performance.

  15. Intelligent Computer Graphics 2012

    CERN Document Server

    Miaoulis, Georgios

    2013-01-01

    In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area.   The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009), “Intelligent Computer Graphics 2010” (2010) and “Intelligent Computer Graphics 2011” (2011).   Usually, this kind of volume contains, every year, selected extended papers from the corresponding 3IA Conference of the year. However, the current volume is made from directly reviewed and selected papers, submitted for publication in the volume “Intelligent Computer Gr...

  16. Review of Manufacturing Intelligence

    OpenAIRE

    Stokey, Richard

    1990-01-01

    "Manufacturing Intelligence (Addison Wesley, Reading, Massachusetts, 1988, 352 pages, $43.25, ISBN 0-201-13576-0) by Paul Kenneth Wright and David Alan Bourne develops principles for the design of intelligent machine tools.

  17. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best. Jr, Richard A

    2002-01-01

    ... of Central Intelligence (DCI). Priority continues to be placed on intelligence support to military operations and on involvement in efforts to combat narcotics trafficking and, especially since September 11, 2001, international terrorism...

  18. International Conference on Frontiers of Intelligent Computing : Theory and Applications

    CERN Document Server

    Udgata, Siba; Biswal, Bhabendra

    2014-01-01

    This volume contains the papers presented at the Second International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA-2013) held during 14-16 November 2013 organized by Bhubaneswar Engineering College (BEC), Bhubaneswar, Odisha, India. It contains 63 papers focusing on application of intelligent techniques which includes evolutionary computation techniques like genetic algorithm, particle swarm optimization techniques, teaching-learning based optimization etc  for various engineering applications such as data mining, Fuzzy systems, Machine Intelligence and ANN, Web technologies and Multimedia applications and Intelligent computing and Networking etc.

  19. USE OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN QUALITY IMPROVING PROCESS

    Directory of Open Access Journals (Sweden)

    KALİTE İYİLEŞTİRME SÜRECİNDE YAPAY ZEKÃ KAYA

    2005-01-01

    Full Text Available Today, changing of competition conditions and customer preferences caused to happen many differences in the viewpoint of firms' quality studies. At the same time, improvements in computer technologies accelerated use of artificial intelligence. Artificial intelligence technologies are being used to solve many industry problems. In this paper, we investigated the use of artificial intelligence techniques to solve quality problems. The artificial intelligence techniques, which are used in quality improving process in the recent years, are artificial neural networks, expert systems, genetic algorithms and fuzzy logic.

  20. Advances in Collective Intelligence 2011

    CERN Document Server

    Baumöl, Ulrike; Krämer, Bernd

    2012-01-01

    Collective intelligence has become an attractive subject of interest for both academia and industry. More and more conferences and workshops discuss the impact of the users‘ motivation to participate in the value creation process, the enabling role of leading-edge information and communication technologies and the need for better algorithms to deal with the growing amount of shared data. There are many interesting and challenging topics that need to be researched and discussed with respect to knowledge creation, creativity and innovation processes carried forward in the emerging communities of practice. COLLIN is on the path to become the flagship conference in the areas of collective intelligence and ICT-enabled social networking. We were delighted to again receive contributions from different parts of the world including Australia, Europe, Asia, and the United States. Encouraged by the positive response, we plan COLLIN 2012 to be held next year end of August at FernUniverstität in Hagen. In order to guar...

  1. Computational intelligence in optimization

    CERN Document Server

    Tenne, Yoel

    2010-01-01

    This volume presents a collection of recent studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world problems. Topics covered include: Intelligent agent-based algorithms, Hybrid intelligent systems, Cognitive and evolutionary robotics, Knowledge-Based Engineering, fuzzy sets and systems, Bioinformatics and Bioengineering, Computational finance and Computational economics, Data mining, Machine learning, and Expert systems. ""Computational Intelligence in Optimization"" is a comprehensive reference for researchers, prac

  2. Competitive Intelligence HF Czechforge

    OpenAIRE

    Nejtek, Petr

    2012-01-01

    This diploma thesis focuses on options of Competitive Intelligence solutions in small and medium enterprises. Applied part is conducted in a medium sized manufacturing company. Theoretical part of this thesis introduces areas of Competitive Intelligence and Business Intelligence, basic technological overview and illustrates Competitive Intelligence cycle description. In Czech republic, majority of companies are in a form of a small or medium enterprise, therefore theoretical definition is pro...

  3. Construct of emotional intelligence

    Directory of Open Access Journals (Sweden)

    Sonja Pečjak in Andreja Avsec

    2003-04-01

    Full Text Available The article highlights the construct of emotional intelligence, that has appeared about then years ago. We present the popular and scientific comprehension of emotional intelligence, briefly describe the development of the concept and than in detail we propose the existing comprehension of emotional intelligence: through the models of Goleman (1995 and Bar-On (1997 we present the comprehension of emotional intelligence as a non-cognitive (personality traits.

  4. Orchestrating Multiple Intelligences

    Science.gov (United States)

    Moran, Seana; Kornhaber, Mindy; Gardner, Howard

    2006-01-01

    Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

  5. Collective Intelligence in Crises

    DEFF Research Database (Denmark)

    Büscher, Monika; Liegl, Michael; Thomas, Vanessa

    2014-01-01

    . By examining these dynamics with the concept of social collective intelligence, important opportunities and challenges can be examined. In this chapter we focus on socio-technical aspects of social collective intelligence in crises to discuss positive and negative frictions and avenues for innovation....... Of particular interest are ways of bridging between collective intelligence in crises and official emergency response efforts....

  6. Designing with computational intelligence

    CERN Document Server

    Lopes, Heitor; Mourelle, Luiza

    2017-01-01

    This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

  7. Study of intelligent building system based on the internet of things

    Science.gov (United States)

    Wan, Liyong; Xu, Renbo

    2017-03-01

    In accordance with the problem such as isolated subsystems, weak system linkage and expansibility of the bus type buildings management system, this paper based on the modern intelligent buildings has studied some related technologies of the intelligent buildings and internet of things, and designed system architecture of the intelligent buildings based on the Internet of Things. Meanwhile, this paper has also analyzed wireless networking modes, wireless communication protocol and wireless routing protocol of the intelligent buildings based on the Internet of Things.

  8. Intelligent urban heating

    Energy Technology Data Exchange (ETDEWEB)

    Dyrelund, A.

    2011-05-15

    In smart cities District heating is a precondition for large scale and cost effective integration of CHP and renewable energy for heating in urban areas. In particular, district heating systems combined with CHP, heat pumps, electric boilers and large thermal storages is important for efficient integration of fluctuating wind energy. In order to develop an intelligent and cost effective urban heating system it is important to integrate and optimize the total urban heating energy system including building envelope, heating installations, district heating networks, heat storages and renewable energy sources. Two examples: 1) the variable long term production cost is a basic parameter for the optimal building envelope. 2) efficient low temperature heating installations increases the efficiency of the district heating distribution network and all the low temperature heat sources. Besides, in districts with a cooling load, it is important to include the district cooling in the optimized energy system, both for production and end-use. In EU countries, the Renewable energy directive encourage all local authorities to plan for urban heating and cooling in order to provide the buildings with renewable energy for heating hot tap water and cooling via this infrastructure, whenever it is cost effective compared to individual solutions. Ramboll has in association with Aalborg University prepared an updated study of Heat Plan Denmark in 2010. The study demonstrates how the Danish Heating sector has reduced the fossil fuel consumption to 40% from 1980 to 2010 and how the sector can be independent of fossil fuels before 2030 in a cost effective way. The study concludes that it is necessary to optimize investments both at the supply and the demand side. It is estimated that an optimal combination could be 25 % additional heat demand reduction, further reduction of the return temperature in the building installations, expansion of district heating from 50 to 65 %, local heating up

  9. 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.

  10. A Conceptual Framework for Representing Human Behavior Characteristics in a System of Systems Agent-based Survivability Simulation-Intelligent Networks

    Science.gov (United States)

    2014-10-17

    Integration of Knowledge intensive Multi-Agent Systems (KIMAS’05) (Waltham, USA), April. Younis, O., Kant , L., Chang, K, & Young, K. (2009...Cognitive MANET Design for Mission-Critical Networks. IEEE Communications Magazine. Younis, O., Kant , L., Mcauley, A., Manousakis, K., Shallcross, D

  11. The Missing Piece in Threat Intelligence

    Directory of Open Access Journals (Sweden)

    Frank Denis

    2016-03-01

    Full Text Available Common systems for sharing intelligence on security threats have not been designed to efficiently process feedback from infrastructure providers. In order to fill this gap, we introduce DIP, a new description language to expose changes being made on a network that are relevant to security research and prevention.

  12. The Missing Piece in Threat Intelligence

    OpenAIRE

    Frank Denis

    2016-01-01

    Common systems for sharing intelligence on security threats have not been designed to efficiently process feedback from infrastructure providers. In order to fill this gap, we introduce DIP, a new description language to expose changes being made on a network that are relevant to security research and prevention.

  13. Portable AI Lab for Teaching Artificial Intelligence.

    Science.gov (United States)

    Rosner, Michael; Baj, Fabio.

    1993-01-01

    Describes the Portable AI Lab, a computing environment containing artificial intelligence (AI) tools, examples, and documentation for use with university AI courses. Two modules of the lab are highlighted: the automated theorem proving module and the natural language processing module, which includes augmented transition networks. (23 references)…

  14. Providing an efficient intelligent transportation system through ...

    Indian Academy of Sciences (India)

    Syst. 11(4): 917–930. Hou Z 2009 An automated road sign inventory system based on computer vision, Thesis. Kellmeyer D and Zwahlen H 1994 Detection of highway warning signs in natural video images using color image processing and neural networks, IEEE World Congress on Computational Intelligence, Orlando,.

  15. 7th International Symposium on Intelligent Distributed Computing

    CERN Document Server

    Jung, Jason; Badica, Costin

    2014-01-01

    This book represents the combined peer-reviewed proceedings of the Seventh International Symposium on Intelligent Distributed Computing - IDC-2013, of the Second Workshop on Agents for Clouds - A4C-2013, of the Fifth International Workshop on Multi-Agent Systems Technology and Semantics - MASTS-2013, and of the International Workshop on Intelligent Robots - iR-2013. All the events were held in Prague, Czech Republic during September 4-6, 2013. The 41 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, bio-informatics, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, intelligent robotics, knowledge management, linked data, mobile agents, ontologies, pervasive computing, self-organizing systems, peer-to-peer computing, social networks and trust, and swarm intelligence.  .

  16. Intelligence Quotient and Intelligence Grade of Artificial Intelligence

    OpenAIRE

    LIU, Feng; Shi, Yong; Liu, Ying

    2017-01-01

    Although artificial intelligence is currently one of the most interesting areas in scientific research, the potential threats posed by emerging AI systems remain a source of persistent controversy. To address the issue of AI threat, this study proposes a standard intelligence model that unifies AI and human characteristics in terms of four aspects of knowledge, i.e., input, output, mastery, and creation. Using this model, we observe three challenges, namely, expanding of the von Neumann archi...

  17. Paradigms of Intelligent Systems

    Directory of Open Access Journals (Sweden)

    2007-01-01

    Full Text Available This paper approaches the subject of paradigms for the categories of intelligent systems. First we can look at the term paradigm in its scientific meaning and then we make acquaintance with the main categories of intelligent systems (expert systems, intelligent systems based on genetic algorithms, artificial neuronal systems, fuzzy systems, hybrid intelligent systems. We will see that every system has one or more paradigms, but hybrid intelligent systems combine paradigms because they are made of different technologies. This research has been made under the guidance of Dr. Ioan AND ONE, Professor and Director of Research Laboratory.

  18. Social intelligence, human intelligence and niche construction.

    Science.gov (United States)

    Sterelny, Kim

    2007-04-29

    This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

  19. Throwing Down the Visual Intelligence Gauntlet

    KAUST Repository

    Tan, Cheston

    2013-01-01

    In recent years, scientific and technological advances have produced artificial systems that have matched or surpassed human capabilities in narrow domains such as face detection and optical character recognition. However, the problem of producing truly intelligent machines still remains far from being solved. In this chapter, we first describe some of these recent advances, and then review one approach to moving beyond these limited successes – the neuromorphic approach of studying and reverse-engineering the networks of neurons in the human brain (specifically, the visual system). Finally, we discuss several possible future directions in the quest for visual intelligence.

  20. Application of artificial intelligence in process control

    CERN Document Server

    Krijgsman, A

    1993-01-01

    This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.

  1. Artificial intelligence for analyzing orthopedic trauma radiographs.

    Science.gov (United States)

    Olczak, Jakub; Fahlberg, Niklas; Maki, Atsuto; Razavian, Ali Sharif; Jilert, Anthony; Stark, André; Sköldenberg, Olof; Gordon, Max

    2017-12-01

    Background and purpose - Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never been applied in an orthopedic setting, and in this study we sought to determine the feasibility of using deep learning for skeletal radiographs. Methods - We extracted 256,000 wrist, hand, and ankle radiographs from Danderyd's Hospital and identified 4 classes: fracture, laterality, body part, and exam view. We then selected 5 openly available deep learning networks that were adapted for these images. The most accurate network was benchmarked against a gold standard for fractures. We furthermore compared the network's performance with 2 senior orthopedic surgeons who reviewed images at the same resolution as the network. Results - All networks exhibited an accuracy of at least 90% when identifying laterality, body part, and exam view. The final accuracy for fractures was estimated at 83% for the best performing network. The network performed similarly to senior orthopedic surgeons when presented with images at the same resolution as the network. The 2 reviewer Cohen's kappa under these conditions was 0.76. Interpretation - This study supports the use for orthopedic radiographs of artificial intelligence, which can perform at a human level. While current implementation lacks important features that surgeons require, e.g. risk of dislocation, classifications, measurements, and combining multiple exam views, these problems have technical solutions that are waiting to be implemented for orthopedics.

  2. Intelligence analysis – the royal discipline of Competitive Intelligence

    National Research Council Canada - National Science Library

    Bartes, František

    ... cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed...

  3. Intelligent Fish Freshness Assessment

    Directory of Open Access Journals (Sweden)

    Hamid Gholam Hosseini

    2008-01-01

    Full Text Available Fish species identification and automated fish freshness assessment play important roles in fishery industry applications. This paper describes a method based on support vector machines (SVMs to improve the performance of fish identification systems. The result is used for the assessment of fish freshness using artificial neural network (ANN. Identification of the fish species involves processing of the images of fish. The most efficient features were extracted and combined with the down-sampled version of the images to create a 1D input vector. Max-Win algorithm applied to the SVM-based classifiers has enhanced the reliability of sorting to 96.46%. The realisation of Cyranose 320 Electronic nose (E-nose, in order to evaluate the fish freshness in real-time, is experimented. Intelligent processing of the sensor patterns involves the use of a dedicated ANN for each species under study. The best estimation of freshness was provided by the most sensitive sensors. Data was collected from four selected species of fishes over a period of ten days. It was concluded that the performance can be increased using individual trained ANN for each specie. The proposed system has been successful in identifying the number of days after catching the fish with an accuracy of up to 91%.

  4. 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 GPS....... This paper presents an on-line map matching algorithm with an extensive number of weighting parameters that allow better determination of a vehicle's road network position. The algorithm uses certainty value to express its belief in the correctness of its results. The algorithm was designed and implemented...

  5. Intelligence analysis – the royal discipline of Competitive Intelligence

    OpenAIRE

    František Bartes

    2011-01-01

    The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in busines...

  6. On what intelligence is.

    Science.gov (United States)

    Howard, R W

    1993-02-01

    Despite much controversy over the exact definition of intelligence, most researchers agree that it is a concept labelled by a word, or even several related concepts labelled by a word. The present study applies recent theorizing about the nature of concepts in general to clarify the notion (or notions) of intelligence. This theorizing defines a concept as a person's unique and individual information about a category and a category as a set of things in the world. An example of a concept/category pair is 'dog', with the category being the set of all dogs and an individual's concept of dog being his or her personal knowledge of dogs. This knowledge can be used to place things in or out of the category. Different individuals may have somewhat different knowledge about the same category and a single word may label several different concept/category pairs. A concept of intelligence thus consists of information about a general category labelled by the word 'intelligence'. This study analyses three major concept/category pairs of 'intelligence': (1) Spearman's g; (2) intelligence as a property of behaviour; and (3) intelligence as a set of abilities. Each concept contains different information, refers to a different category, and should be used in different ways. Several recurrent issues, such as whether the word 'intelligence' refers to a thing and what things are intelligent (e.g. animals, computers), can be resolved by considering each issue in relation to these concept/category pairs. For instance, the word 'intelligence' refers to a thing only if one uses the g concept. Similarly, only humans are intelligent according to the g concept but animals and computers may be considered intelligent if the other concepts are applied. Recent theorizing on the nature of concepts can be used to clarify other important psychological notions.

  7. Intelligence and chess

    OpenAIRE

    Gobet, F.; Campitelli, G

    2002-01-01

    The goal of this paper is to critically evaluate the evidence supporting the hypothesis that innate talent (for example a higher level of intelligence) may account for aspects of chess skill. We start by giving some standard definitions of intelligence, and then present empirical data on chessplayers’ intelligence, both with children and adults. In the second part of this paper, we discuss Geschwind and Galaburda’s (1985) influential theory of the neurobiology of talent in music, mathematics,...

  8. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  9. Projective simulation for artificial intelligence

    Science.gov (United States)

    Briegel, Hans J.; de Las Cuevas, Gemma

    2012-05-01

    We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

  10. The search for intelligence

    Science.gov (United States)

    Coffey, E. J.

    1980-12-01

    Implications of current understandings of the nature of human intelligence for the possibility of extraterrestrial intelligence are discussed. The perceptual theory of intelligence as the manipulation of perceptual images rather than language is introduced, and conditions leading to the ascendancy of man over other hominids with similar conceptual abilities are discussed, including the liberation of the hands from a locomotive function and the evolution of neoteny. It is argued that the specificity of the environmental, behavioral and physiological conditions which lead to the emergence of technologically oriented, and communicative intelligent creatures suggests that any SETI would most likely be fruitless.

  11. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

    This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

  12. Intelligent Optics Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Intelligent Optics Laboratory supports sophisticated investigations on adaptive and nonlinear optics; advancedimaging and image processing; ground-to-ground and...

  13. Artificial Intelligence Education

    National Research Council Canada - National Science Library

    Michael Wollowski; Todd Neller; James Boerkoel

    2017-01-01

    .... The article Ethical Considerations in Artificial Intelligence Courses by Emanuelle Burton, Judy Goldsmith, Sven Koenig, Benjamin Kuipers, Nicholas Mattei, and Toby Walsh is concerned with providing...

  14. Successful intelligence: A model for testing intelligence beyond IQ tests

    National Research Council Canada - National Science Library

    Sternberg, Robert J

    2015-01-01

    .... In contrast, the augmented theory of successful intelligence asserts that intelligence involves creative skills in producing new ideas, analytical skills in evaluating whether the ideas are good ones...

  15. Routledge companion to intelligence studies

    CERN Document Server

    Dover, Robert; Hillebrand, Claudia

    2013-01-01

    The Routledge Companion to Intelligence Studies provides a broad overview of the growing field of intelligence studies. The recent growth of interest in intelligence and security studies has led to an increased demand for popular depictions of intelligence and reference works to explain the architecture and underpinnings of intelligence activity. Divided into five comprehensive sections, this Companion provides a strong survey of the cutting-edge research in the field of intelligence studies: Part I: The evolution of intelligence studies; Part II: Abstract approaches to intelligence; Part III: Historical approaches to intelligence; Part IV: Systems of intelligence; Part V: Contemporary challenges. With a broad focus on the origins, practices and nature of intelligence, the book not only addresses classical issues, but also examines topics of recent interest in security studies. The overarching aim is to reveal the rich tapestry of intelligence studies in both a sophisticated and accessible way. This Companion...

  16. 75 FR 76423 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

    Science.gov (United States)

    2010-12-08

    ... of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of... a closed meeting of the Defense Intelligence Agency National Defense Intelligence College Board of...

  17. 76 FR 28960 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

    Science.gov (United States)

    2011-05-19

    ... of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of... a closed meeting of the Defense Intelligence Agency National Defense Intelligence College Board of...

  18. 77 FR 32952 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

    Science.gov (United States)

    2012-06-04

    ... of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: Department of Defense, Defense Intelligence Agency, National Intelligence... a closed meeting of the Defense Intelligence Agency National Intelligence University Board of...

  19. National Intelligence: A Consumer’s Guide

    Science.gov (United States)

    2009-01-01

    Intelligence Analysis 14 The Intelligence Cycle 17 Prioritizing Intelligence Issues...Office of Intelligence and Counterintelligence 47 Department of Homeland Security Office of Intelligence & Analysis 48...Research Treasury Office of Intelligence and Analysis DHS Office of Intelligence & Analysis SERVICES Marine Corps Intelligence Coast Guard

  20. Artifical intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Warwick, K.; Ekwue, A.; Aggarwal, R. [eds.

    1997-12-31

    Research in artificial intelligence has developed many techniques and methodologies that can be either adapted or used directly to solve complex power system problems. A variety of such problems are covered in this book including reactive power control, alarm analysis, fault diagnosis, protection systems and load forecasting. Methods such as knowledge-based (expert) systems, fuzzy logic, neural networks and genetic algorithms are all first introduced and then investigated in terms of their applicability in the power systems field. The book, therefore, serves as both an introduction to the use of artificial intelligence techniques for those from a power systems background and as an overview of the power systems implementation area for those from an artificial intelligence computing or control background. It is structured so that it is suitable for various levels of reader, covering basic principles as well as applications and case studies. The most popular methods and the most fruitful application fields are considered in more detail. (UK)

  1. 2015 Chinese Intelligent Systems Conference

    CERN Document Server

    Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

    2016-01-01

    This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

  2. Smart and Intelligent Sensors

    Science.gov (United States)

    Lansaw, John; Schmalzel, John; Figueroa, Jorge

    2009-01-01

    John C. Stennis Space Center (SSC) provides rocket engine propulsion testing for NASA's space programs. Since the development of the Space Shuttle, every Space Shuttle Main Engine (SSME) has undergone acceptance testing at SSC before going to Kennedy Space Center (KSC) for integration into the Space Shuttle. The SSME is a large cryogenic rocket engine that uses Liquid Hydrogen (LH2) as the fuel. As NASA moves to the new ARES V launch system, the main engines on the new vehicle, as well as the upper stage engine, are currently base lined to be cryogenic rocket engines that will also use LH2. The main rocket engines for the ARES V will be larger than the SSME, while the upper stage engine will be approximately half that size. As a result, significant quantities of hydrogen will be required during the development, testing, and operation of these rocket engines.Better approaches are needed to simplify sensor integration and help reduce life-cycle costs. 1.Smarter sensors. Sensor integration should be a matter of "plug-and-play" making sensors easier to add to a system. Sensors that implement new standards can help address this problem; for example, IEEE STD 1451.4 defines transducer electronic data sheet (TEDS) templates for commonly used sensors such as bridge elements and thermocouples. When a 1451.4 compliant smart sensor is connected to a system that can read the TEDS memory, all information needed to configure the data acquisition system can be uploaded. This reduces the amount of labor required and helps minimize configuration errors. 2.Intelligent sensors. Data received from a sensor be scaled, linearized; and converted to engineering units. Methods to reduce sensor processing overhead at the application node are needed. Smart sensors using low-cost microprocessors with integral data acquisition and communication support offer the means to add these capabilities. Once a processor is embedded, other features can be added; for example, intelligent sensors can make

  3. Artificial Neural Networks and Instructional Technology.

    Science.gov (United States)

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  4. Spiritual Intelligence: The Tenth Intelligence that Integrates All Other Intelligences.

    Science.gov (United States)

    Sisk, Dorothy

    2002-01-01

    This article discusses seven ways to develop spiritual intelligence, including: think about goals and identify values; access inner processes and use visualization to see goals fulfilled; integrate personal and universal vision; take responsibility for goals; develop a sense of community; focus on love and compassion; and take advantages of…

  5. Artificial intelligence and intelligent tutoring systems

    Energy Technology Data Exchange (ETDEWEB)

    Livergood, N.D.

    1989-01-01

    As a species we have evolved by increasing our mental and physical powers through the deliberate development and use of instruments that amplify our inherent capabilities. Whereas hereditarily given instincts predetermine the actions of lower animal forms, human existence begins with freedom. As humans we can choose what actions we will perform. We have invented a technology called education to prepare ourselves for life. At present, our educational structures and procedures are failing to prepare us efficiently for the demands of modern life. One of the most important new technologies, in relation to human development, is the digital computer. This dissertation proposes that artificial intelligence maintain a highly critical technological awareness. Artificial intelligence, because of its origin as a politically sponsored field of investigation, must strive for constant awareness of its place within the larger political-economic world and its possible misuse by factions intent on manipulation and control. Computerized models of the human mind could be used in developing progressively more sophisticated brainwashing systems. Intelligent tutoring systems comprise an important new technology within the field of artificial intelligence. This dissertation explores specification and design procedures, functions and issues in developing intelligent tutoring systems.

  6. Smart grids, smart network companies

    NARCIS (Netherlands)

    Arends, M.; Hendriks, P.H.J.

    2014-01-01

    The introduction of intelligent technology to turn electricity networks into smart grids is an important vehicle to meet the many challenges modern society poses. However, technology alone will not make energy supply more intelligent and may for the medium and long range even involve risks of

  7. Landau Theory of Adaptive Integration in Computational Intelligence

    CERN Document Server

    Plewczynski, Dariusz

    2010-01-01

    Computational Intelligence (CI) is a sub-branch of Artificial Intelligence paradigm focusing on the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments. There are several paradigms of CI [like artificial neural networks, evolutionary computations, swarm intelligence, artificial immune systems, fuzzy systems and many others], each of these has its origins in biological systems [biological neural systems, natural Darwinian evolution, social behavior, immune system, interactions of organisms with their environment]. Most of those paradigms evolved into separate machine learning (ML) techniques, where probabilistic methods are used complementary with CI techniques in order to effectively combine elements of learning, adaptation, evolution and Fuzzy logic to create heuristic algorithms that are, in some sense, intelligent. The current trend is to develop consensus techniques, since no single machine learning algorithms is superior to others in all possible...

  8. 8th Asian Conference on Intelligent Information and Database Systems

    CERN Document Server

    Madeyski, Lech; Nguyen, Ngoc

    2016-01-01

    The objective of this book is to contribute to the development of the intelligent information and database systems with the essentials of current knowledge, experience and know-how. The book contains a selection of 40 chapters based on original research presented as posters during the 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016) held on 14–16 March 2016 in Da Nang, Vietnam. The papers to some extent reflect the achievements of scientific teams from 17 countries in five continents. The volume is divided into six parts: (a) Computational Intelligence in Data Mining and Machine Learning, (b) Ontologies, Social Networks and Recommendation Systems, (c) Web Services, Cloud Computing, Security and Intelligent Internet Systems, (d) Knowledge Management and Language Processing, (e) Image, Video, Motion Analysis and Recognition, and (f) Advanced Computing Applications and Technologies. The book is an excellent resource for researchers, those working in artificial intelligence, mu...

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

    Directory of Open Access Journals (Sweden)

    Shan Li

    2014-01-01

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

  10. International Conference on Intelligent and Interactive Systems and Applications

    CERN Document Server

    Patnaik, Srikanta; Yu, Zhengtao

    2017-01-01

    This book provides the latest research findings and developments in the field of interactive intelligent systems, addressing diverse areas such as autonomous systems, Internet and cloud computing, pattern recognition and vision systems, mobile computing and intelligent networking, and e-enabled systems. It gathers selected papers from the International Conference on Intelligent and Interactive Systems and Applications (IISA2016) held on June 25–26, 2016 in Shanghai, China. Interactive intelligent systems are among the most important multi-disciplinary research and development domains of artificial intelligence, human–computer interaction, machine learning and new Internet-based technologies. Accordingly, these systems embrace a considerable number of application areas such as autonomous systems, expert systems, mobile systems, recommender systems, knowledge-based and semantic web-based systems, virtual communication environments, and decision support systems, to name a few. To date, research on interactiv...

  11. Applying Multiple Intelligences

    Science.gov (United States)

    Christodoulou, Joanna A.

    2009-01-01

    The ideas of multiple intelligences introduced by Howard Gardner of Harvard University more than 25 years ago have taken form in many ways, both in schools and in other sometimes-surprising settings. The silver anniversary of Gardner's learning theory provides an opportunity to reflect on the ways multiple intelligences theory has taken form and…

  12. Next generation Emotional Intelligence

    Science.gov (United States)

    J. Saveland

    2012-01-01

    Emotional Intelligence has been a hot topic in leadership training since Dan Goleman published his book on the subject in 1995. Emotional intelligence competencies are typically focused on recognition and regulation of emotions in one's self and social situations, yielding four categories: self-awareness, self-management, social awareness and relationship...

  13. Can Ai Be Intelligent?

    Directory of Open Access Journals (Sweden)

    Trzęsicki Kazimierz

    2016-12-01

    Full Text Available The aim of this paper is an attempt to give an answer to the question what does it mean that a computational system is intelligent. We base on some theses that though debatable are commonly accepted. Intelligence is conceived as the ability of tractable solving of some problems that in general are not solvable by deterministic Turing Machine.

  14. Systems Intelligence Inventory

    Science.gov (United States)

    Törmänen, Juha; Hämäläinen, Raimo P.; Saarinen, Esa

    2016-01-01

    Purpose: Systems intelligence (SI) (Saarinen and Hämäläinen, 2004) is a construct defined as a person's ability to act intelligently within complex systems involving interaction and feedback. SI relates to our ability to act in systems and reason about systems to adaptively carry out productive actions within and with respect to systems such as…

  15. Towards Intelligent Supply Chains

    DEFF Research Database (Denmark)

    Siurdyban, Artur; Møller, Charles

    2012-01-01

    of deploying inapt operations leading to deterioration of profits. To address this problem, we propose a unified business process design framework based on the paradigm of intelligence. Intelligence allows humans and human-designed systems cope with environmental volatility, and we argue that its principles...

  16. Multiple Intelligences in Action.

    Science.gov (United States)

    Campbell, Bruce

    1992-01-01

    Describes the investigation of the effects of a four-step model program used with third through fifth grade students to implement Gardener's concepts of seven human intelligences--linguistic, logical/mathematical, visual/spatial, musical, kinesthetic, intrapersonal, and interpersonal intelligence--into daily learning. (BB)

  17. A Multiple Intelligence Approach.

    Science.gov (United States)

    Nuzzi, Ronald

    1997-01-01

    Describes multiple intelligence instruction (MII), based on the theory that humans possess seven intelligences: visual, musical, logical-mathematical, intrapersonal, interpersonal, linguistic, and bodily-kinesthetic. Argues that current methods of assessment are deficit-based and, therefore, not helpful in assessing MII students. Describes an…

  18. Cyber Intelligence Threat Prioritization

    Science.gov (United States)

    2014-10-01

    platform that allows anyone to make their organization more visible to threat actors. Online Presence Extracurricular Activities Motive Risk...PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL. CARNEGIE MELLON UNIVERSITY DOES NOT MAKE ANY WARRANTY OF ANY KIND...Project Sponsor • National Intelligence Manager for Cyber, Office of the Director of National Intelligence (ODNI) Purpose • Study how

  19. The Reproduction of Intelligence

    Science.gov (United States)

    Meisenberg, Gerhard

    2010-01-01

    Although a negative relationship between fertility and education has been described consistently in most countries of the world, less is known about the relationship between intelligence and reproductive outcomes. Also the paths through which intelligence influences reproductive outcomes are uncertain. The present study uses the NLSY79 to analyze…

  20. The Physics of Intelligence

    Science.gov (United States)

    Escultura, E. E.

    2012-01-01

    This paper explores the physics of intelligence and provides an overview of what happens in the brain when a person is engaged in mental activity that we classify under thought or intelligence. It traces the formation of a concept starting with reception of visible or detectable signals from the real world by and external to the sense organs,…